From 2ab98583754f5a5f86e40c5207fc2df0bce094b0 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Mon, 22 Apr 2024 09:33:37 +0000
Subject: [PATCH 01/43] add retrieving memory

---
 src/nanotron/models/attention.py | 109 +++++++++++++++++++++++++++++++
 src/nanotron/models/llama.py     |  15 ++++-
 tests/test_attention.py          |  28 ++++++++
 3 files changed, 150 insertions(+), 2 deletions(-)
 create mode 100644 src/nanotron/models/attention.py
 create mode 100644 tests/test_attention.py

diff --git a/src/nanotron/models/attention.py b/src/nanotron/models/attention.py
new file mode 100644
index 00000000..2244e030
--- /dev/null
+++ b/src/nanotron/models/attention.py
@@ -0,0 +1,109 @@
+from typing import Optional
+
+import torch
+import torch.distributed as dist
+import torch.nn.functional as F
+from einops import einsum, rearrange, reduce
+from torch import nn
+
+# from jaxtyping import Float, Array
+from torchtyping import TensorType
+
+from nanotron.config import LlamaConfig, ParallelismArgs
+
+
+class InfiniAttention(nn.Module):
+    def __init__(
+        self, config: LlamaConfig, parallel_config: Optional[ParallelismArgs], tp_pg: dist.ProcessGroup, layer_idx: int
+    ):
+        super().__init__()
+
+
+        from nanotron.models.llama import CausalSelfAttention
+
+        self.attn = CausalSelfAttention(
+            config=config,
+            parallel_config=parallel_config,
+            tp_pg=tp_pg,
+            layer_idx=layer_idx,
+        )
+
+    def forward(
+        self,
+        hidden_states: TensorType["seq_length", "batch_size", "hidden_size"],
+        sequence_mask: TensorType["batch_size", "seq_length"],
+    ):
+        attn_outputs = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask, return_qkv_states=True)
+
+        attn_outputs["hidden_states"]
+
+        # NOTE: query_states.shape = [batch_size * q_length, self.n_heads, d_qk]
+        # NOTE: key_states.shape or value_states.shape = [batch_size * kv_length, self.n_heads, d_qk]
+        query_states, key_states, value_states = attn_outputs["qkv_states"]
+        query_states.shape[-1]
+        query_states.shape[-2]
+        batch_size = hidden_states.shape[1]
+
+        query_states = rearrange(
+            query_states,
+            "(batch_size seq_length) n_heads d_head -> batch_size n_heads seq_length d_head",
+            batch_size=batch_size,
+        )
+        key_states = rearrange(
+            key_states,
+            "(batch_size seq_length) n_heads d_head -> batch_size n_heads seq_length d_head",
+            batch_size=batch_size,
+        )
+        value_states = rearrange(
+            value_states,
+            "(batch_size seq_length) n_heads d_head -> batch_size n_heads seq_length d_head",
+            batch_size=batch_size,
+        )
+
+        # query_states = query_states.view(batch_size, -1, n_heads, d_head) # [batch_size, q_length, n_heads, d_qk]
+        # key_states = key_states.view(batch_size, -1, n_heads, d_head)
+        # value_states = value_states.view(batch_size, -1, n_heads, d_head)
+
+        # memory = torch.matmul(key_states, value_states.transpose(-1, -2))
+        # normalization = key_states.sum(dim=-1, keepdim=True)
+
+        # memory = einsum(key_states, value_states, 'b n h d, b n h d -> b h d d')
+        # memory = einsum(key_states, value_states, 'b i j h, b i l h -> b i j l')
+
+        # memory = einsum(F.elu(key_states) + 1, value_states, 'batch_size k_length n_heads d_head, batch_size v_length n_heads d_head -> batch_size n_heads k_length v_length')
+        # normalization = reduce(key_states, 'batch_size seq_length n_heads d_head -> batch_size seq_length n_heads', reduction='sum')
+
+        # query_states = F.elu(query_states) + 1
+        # retrieved_memory = einsum(query_states, memory, 'batch_size q_length n_heads d_head, batch_size n_heads k_length v_length -> batch_size q_length s d')
+        # retrieved_memory = torch.matmul(query_states, memory) / torch.matmul(query_states, normalization)
+
+        memory, normalization = self._get_memory(key_states, value_states)
+        self._retrieve_from_memory(query_states, memory, normalization)
+        assert 1 == 1
+        # NOTE: update memory
+
+    def _get_memory(self, key_states, value_states):
+        key_states = F.elu(key_states) + 1
+        memory = torch.matmul(key_states.transpose(-2, -1), value_states)
+        # memory = einsum(key_states, value_states, 'batch_size n_heads k_length d_head, batch_size n_heads v_length d_head -> batch_size n_heads k_length v_length')
+        normalization = reduce(
+            key_states, "batch_size n_heads seq_length d_head -> batch_size n_heads d_head", reduction="sum"
+        )
+        return memory, normalization
+
+    def _retrieve_from_memory(self, query_states, memory, normalization):
+        query_states = F.elu(query_states) + 1
+        retrieved_memory = einsum(
+            query_states,
+            memory,
+            "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
+        )
+
+        denominator = einsum(
+            query_states,
+            normalization,
+            "batch_size n_heads seq_length d_k, batch_size n_heads d_k -> batch_size n_heads seq_length",
+        )
+        # [batch_size, n_heads, seq_length, d_v] / [batch_size, n_heads, seq_length, 1], so each d_v is divide by the normalized value
+        retrieved_memory = retrieved_memory / denominator[:, :, :, None]
+        return retrieved_memory
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 952bd8ba..43c487c6 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -26,6 +26,7 @@
 from nanotron.generation.generate_store import AttachableStore
 from nanotron.logging import log_rank
 from nanotron.models import NanotronModel
+from nanotron.models.attention import InfiniAttention
 from nanotron.nn.activations import ACT2FN
 from nanotron.nn.layer_norm import TritonRMSNorm
 from nanotron.parallel import ParallelContext
@@ -348,6 +349,7 @@ def forward(
         self,
         hidden_states,  # [seq_length, batch_size, hidden_size]
         sequence_mask,  # [batch_size, seq_length]
+        return_qkv_states: bool = False,
     ):
         from flash_attn import bert_padding
         from flash_attn.flash_attn_interface import (
@@ -595,7 +597,9 @@ def forward(
         )
         output = self.o_proj(attention_output)
 
-        return {"hidden_states": output, "sequence_mask": sequence_mask}
+        return_outputs = {"hidden_states": output, "sequence_mask": sequence_mask}
+        return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
+        return return_outputs
 
 
 class LlamaDecoderLayer(nn.Module):
@@ -608,7 +612,14 @@ def __init__(
     ):
         super().__init__()
         self.input_layernorm = TritonRMSNorm(config.hidden_size, eps=config.rms_norm_eps)
-        self.attn = CausalSelfAttention(
+        # self.attn = CausalSelfAttention(
+        #     config=config,
+        #     parallel_config=parallel_config,
+        #     tp_pg=tp_pg,
+        #     layer_idx=layer_idx,
+        # )
+
+        self.attn = InfiniAttention(
             config=config,
             parallel_config=parallel_config,
             tp_pg=tp_pg,
diff --git a/tests/test_attention.py b/tests/test_attention.py
new file mode 100644
index 00000000..444c4b47
--- /dev/null
+++ b/tests/test_attention.py
@@ -0,0 +1,28 @@
+import pytest
+import torch
+from helpers.utils import available_gpus, init_distributed, rerun_if_address_is_in_use
+from nanotron.models.attention import InfiniAttention
+from nanotron.parallel import ParallelContext
+
+
+@pytest.mark.parametrize("tp,dp,pp", [pytest.param(i, 1, 1) for i in range(1, min(4, available_gpus()) + 1)])
+@rerun_if_address_is_in_use()
+def test_infini_attention(tp: int, dp: int, pp: int):
+    SEQ_LEN = 10
+    BATCH_SIZE = 5
+    HIDDEN_SIZE = 16
+
+    hidden_states = torch.randn(SEQ_LEN, BATCH_SIZE, HIDDEN_SIZE)
+    sequence_mask = torch.randint(0, 2, (BATCH_SIZE, SEQ_LEN)).bool()
+
+    init_distributed(tp=tp, dp=dp, pp=pp)(_test_infini_attention)(hidden_states, sequence_mask)
+
+
+def _test_infini_attention(
+    parallel_context: ParallelContext, hidden_states: torch.Tensor, sequence_mask: torch.Tensor
+):
+    attn_output = InfiniAttention()
+
+    assert attn_output.shape == hidden_states.shape
+
+    parallel_context.destroy()

From 7659415d225a1dcc68975f99ba01fa302f0778eb Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Mon, 22 Apr 2024 10:09:14 +0000
Subject: [PATCH 02/43] add computing the output

---
 src/nanotron/models/attention.py | 60 +++++++++++++++++++++++++++++---
 src/nanotron/models/llama.py     |  1 +
 2 files changed, 56 insertions(+), 5 deletions(-)

diff --git a/src/nanotron/models/attention.py b/src/nanotron/models/attention.py
index 2244e030..44062beb 100644
--- a/src/nanotron/models/attention.py
+++ b/src/nanotron/models/attention.py
@@ -10,6 +10,7 @@
 from torchtyping import TensorType
 
 from nanotron.config import LlamaConfig, ParallelismArgs
+from nanotron.parallel.tensor_parallel.nn import TensorParallelRowLinear
 
 
 class InfiniAttention(nn.Module):
@@ -18,9 +19,17 @@ def __init__(
     ):
         super().__init__()
 
-
         from nanotron.models.llama import CausalSelfAttention
 
+        tp_mode = parallel_config.tp_mode if parallel_config is not None else TensorParallelLinearMode.ALL_REDUCE
+        tp_linear_async_communication = (
+            parallel_config.tp_linear_async_communication if parallel_config is not None else False
+        )
+
+        self.config = config
+
+        # self.balance_factor = 0.5
+
         self.attn = CausalSelfAttention(
             config=config,
             parallel_config=parallel_config,
@@ -28,6 +37,22 @@ def __init__(
             layer_idx=layer_idx,
         )
 
+        d_model = config.hidden_size
+        self.d_head = config.hidden_size // config.num_attention_heads
+
+        self.o_proj = TensorParallelRowLinear(
+            config.num_attention_heads * self.d_head,
+            d_model,
+            pg=tp_pg,
+            mode=tp_mode,
+            bias=False,
+            async_communication=tp_linear_async_communication,
+        )
+
+        assert self.o_proj.weight.shape == self.attn.o_proj.weight.shape
+
+        # self.balance_factor = nn.Parameter(torch.tensor(0.5))
+
     def forward(
         self,
         hidden_states: TensorType["seq_length", "batch_size", "hidden_size"],
@@ -35,13 +60,12 @@ def forward(
     ):
         attn_outputs = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask, return_qkv_states=True)
 
-        attn_outputs["hidden_states"]
+        local_attn_outputs = attn_outputs["attention_output"]
 
         # NOTE: query_states.shape = [batch_size * q_length, self.n_heads, d_qk]
         # NOTE: key_states.shape or value_states.shape = [batch_size * kv_length, self.n_heads, d_qk]
         query_states, key_states, value_states = attn_outputs["qkv_states"]
-        query_states.shape[-1]
-        query_states.shape[-2]
+
         batch_size = hidden_states.shape[1]
 
         query_states = rearrange(
@@ -49,6 +73,10 @@ def forward(
             "(batch_size seq_length) n_heads d_head -> batch_size n_heads seq_length d_head",
             batch_size=batch_size,
         )
+        # NOTE: because the number of heads are splited in TP
+        # so we find them on the fly
+        N_HEADS = query_states.shape[1]
+
         key_states = rearrange(
             key_states,
             "(batch_size seq_length) n_heads d_head -> batch_size n_heads seq_length d_head",
@@ -78,7 +106,29 @@ def forward(
         # retrieved_memory = torch.matmul(query_states, memory) / torch.matmul(query_states, normalization)
 
         memory, normalization = self._get_memory(key_states, value_states)
-        self._retrieve_from_memory(query_states, memory, normalization)
+        retrieved_memory = self._retrieve_from_memory(query_states, memory, normalization)
+        local_attn_outputs = rearrange(
+            local_attn_outputs,
+            "seq_length batch_size (n_heads d_head) -> batch_size n_heads seq_length d_head",
+            d_head=self.d_head,
+        )
+        # assert self.balance_factor.shape == n_heads
+
+        balance_factors = torch.randn(N_HEADS, device=local_attn_outputs.device, dtype=local_attn_outputs.dtype)
+
+        global_weights = F.sigmoid(balance_factors)
+        global_attn_outputs = global_weights[None, :, None, None] * retrieved_memory
+
+        local_weights = F.sigmoid(1 - balance_factors)
+        local_attn_outputs = local_weights[None, :, None, None] * local_attn_outputs
+
+        attention_output = global_attn_outputs + local_attn_outputs
+        attention_output = rearrange(
+            attention_output, "batch_size n_heads seq_len d_head -> batch_size seq_len (n_heads d_head)"
+        )
+
+        self.o_proj(attention_output)
+
         assert 1 == 1
         # NOTE: update memory
 
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 43c487c6..b8f30098 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -599,6 +599,7 @@ def forward(
 
         return_outputs = {"hidden_states": output, "sequence_mask": sequence_mask}
         return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
+        return_outputs["attention_output"] = attention_output
         return return_outputs
 
 

From 936a45b7e92e404ac66cd33c2c6c6f3d540c7246 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Tue, 23 Apr 2024 06:20:59 +0000
Subject: [PATCH 03/43] add linear delta memory update

---
 src/nanotron/models/attention.py | 234 ++++++++++++++++++++-----------
 src/nanotron/models/llama.py     |  29 ++--
 2 files changed, 170 insertions(+), 93 deletions(-)

diff --git a/src/nanotron/models/attention.py b/src/nanotron/models/attention.py
index 44062beb..fb7c3a21 100644
--- a/src/nanotron/models/attention.py
+++ b/src/nanotron/models/attention.py
@@ -10,7 +10,10 @@
 from torchtyping import TensorType
 
 from nanotron.config import LlamaConfig, ParallelismArgs
-from nanotron.parallel.tensor_parallel.nn import TensorParallelRowLinear
+from nanotron.parallel.tensor_parallel.nn import (
+    TensorParallelLinearMode,
+    TensorParallelRowLinear,
+)
 
 
 class InfiniAttention(nn.Module):
@@ -19,6 +22,8 @@ def __init__(
     ):
         super().__init__()
 
+        self.n_segments = 4
+
         from nanotron.models.llama import CausalSelfAttention
 
         tp_mode = parallel_config.tp_mode if parallel_config is not None else TensorParallelLinearMode.ALL_REDUCE
@@ -28,8 +33,6 @@ def __init__(
 
         self.config = config
 
-        # self.balance_factor = 0.5
-
         self.attn = CausalSelfAttention(
             config=config,
             parallel_config=parallel_config,
@@ -48,110 +51,179 @@ def __init__(
             bias=False,
             async_communication=tp_linear_async_communication,
         )
+        self.n_local_heads = self.attn.n_local_q_heads
 
-        assert self.o_proj.weight.shape == self.attn.o_proj.weight.shape
+        device = self.o_proj.weight.device
+        dtype = self.o_proj.weight.dtype
+        self.balance_factors = nn.Parameter(torch.randn(self.n_local_heads, device=device, dtype=dtype))
+
+        # assert self.o_proj.weight.shape == self.attn.o_proj.weight.shape
 
         # self.balance_factor = nn.Parameter(torch.tensor(0.5))
 
+        # for p in self.attn.o_proj.parameters():
+        #     p.requires_grad = False
+
     def forward(
         self,
         hidden_states: TensorType["seq_length", "batch_size", "hidden_size"],
         sequence_mask: TensorType["batch_size", "seq_length"],
     ):
-        attn_outputs = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask, return_qkv_states=True)
-
-        local_attn_outputs = attn_outputs["attention_output"]
-
-        # NOTE: query_states.shape = [batch_size * q_length, self.n_heads, d_qk]
-        # NOTE: key_states.shape or value_states.shape = [batch_size * kv_length, self.n_heads, d_qk]
-        query_states, key_states, value_states = attn_outputs["qkv_states"]
-
         batch_size = hidden_states.shape[1]
+        seq_len = hidden_states.shape[0]
+        segment_length = seq_len // self.n_segments
+        hidden_size = hidden_states.shape[2]
+
+        segment_hidden_states = torch.chunk(hidden_states, chunks=self.n_segments, dim=0)
+        segment_sequence_masks = torch.chunk(sequence_mask, chunks=self.n_segments, dim=1)
+
+        memory = None
+        normalization = None
+
+        outputs = []
+
+        # sequence_masks = []
+        for segment_hidden_state, segment_sequence_mask in zip(segment_hidden_states, segment_sequence_masks):
+            attn_outputs = self.attn(
+                hidden_states=segment_hidden_state, sequence_mask=segment_sequence_mask, return_qkv_states=True
+            )
+
+            local_attn_outputs = attn_outputs["attention_output"]
+            # sequence_masks.append(attn_outputs["sequence_mask"])
+
+            # NOTE: query_states.shape = [batch_size * q_length, self.n_heads, d_qk]
+            # NOTE: key_states.shape or value_states.shape = [batch_size * kv_length, self.n_heads, d_qk]
+            query_states, key_states, value_states = attn_outputs["qkv_states"]
+
+            query_states = rearrange(
+                query_states,
+                "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
+                batch_size=batch_size,
+            )
+            # NOTE: because the number of heads are splited in TP
+            # so we find them on the fly
+
+            key_states = rearrange(
+                key_states,
+                "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
+                batch_size=batch_size,
+            )
+            value_states = rearrange(
+                value_states,
+                "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
+                batch_size=batch_size,
+            )
+
+            # NOTE: because we split the heads in TP, we need to find the number of heads on the fly
+            N_HEADS = query_states.shape[1]
+            assert N_HEADS == self.n_local_heads
+            # balance_factors = torch.randn(N_HEADS, device=local_attn_outputs.device, dtype=local_attn_outputs.dtype)
+
+            retrieved_memory = self._retrieve_from_memory(
+                query_states, prev_memory=memory, prev_normalization=normalization
+            )
+            retrieved_memory = retrieved_memory.detach()
+
+            local_attn_outputs = rearrange(
+                local_attn_outputs,
+                "seq_len batch_size (n_heads d_head) -> batch_size n_heads seq_len d_head",
+                d_head=self.d_head,
+            )
+
+            global_weights = F.sigmoid(self.balance_factors)
+            global_attn_outputs = global_weights[None, :, None, None] * retrieved_memory
+
+            local_weights = F.sigmoid(1 - self.balance_factors)
+            local_attn_outputs = local_weights[None, :, None, None] * local_attn_outputs
+
+            attention_output = global_attn_outputs + local_attn_outputs
+            attention_output = rearrange(
+                attention_output, "batch_size n_heads seq_len d_head -> seq_len batch_size (n_heads d_head)"
+            )
+
+            output = self.o_proj(attention_output)
+
+            assert output.shape == (segment_length, batch_size, hidden_size)
+
+            memory, normalization = self._update_memory(memory, normalization, key_states, value_states)
+            memory = memory.detach()
+            normalization = normalization.detach()
+
+            outputs.append(output)
+
+            # NOTE: update memory
+        outputs = torch.cat(outputs, dim=0)  # concat along sequence dimension
+        assert outputs.shape == hidden_states.shape
+
+        # sequence_masks = torch.cat(sequence_masks, dim=1)
+        # assert sequence_masks.shape == sequence_mask.shape
+        return_outputs = {"hidden_states": outputs, "sequence_mask": sequence_mask}
+        return return_outputs
+
+    def _update_memory(self, prev_memory, prev_normalization, key_states, value_states):
+        TYPE = "delta"
+        key_states = F.elu(key_states) + 1
 
-        query_states = rearrange(
-            query_states,
-            "(batch_size seq_length) n_heads d_head -> batch_size n_heads seq_length d_head",
-            batch_size=batch_size,
-        )
-        # NOTE: because the number of heads are splited in TP
-        # so we find them on the fly
-        N_HEADS = query_states.shape[1]
-
-        key_states = rearrange(
-            key_states,
-            "(batch_size seq_length) n_heads d_head -> batch_size n_heads seq_length d_head",
-            batch_size=batch_size,
-        )
-        value_states = rearrange(
-            value_states,
-            "(batch_size seq_length) n_heads d_head -> batch_size n_heads seq_length d_head",
-            batch_size=batch_size,
-        )
-
-        # query_states = query_states.view(batch_size, -1, n_heads, d_head) # [batch_size, q_length, n_heads, d_qk]
-        # key_states = key_states.view(batch_size, -1, n_heads, d_head)
-        # value_states = value_states.view(batch_size, -1, n_heads, d_head)
-
-        # memory = torch.matmul(key_states, value_states.transpose(-1, -2))
-        # normalization = key_states.sum(dim=-1, keepdim=True)
-
-        # memory = einsum(key_states, value_states, 'b n h d, b n h d -> b h d d')
-        # memory = einsum(key_states, value_states, 'b i j h, b i l h -> b i j l')
-
-        # memory = einsum(F.elu(key_states) + 1, value_states, 'batch_size k_length n_heads d_head, batch_size v_length n_heads d_head -> batch_size n_heads k_length v_length')
-        # normalization = reduce(key_states, 'batch_size seq_length n_heads d_head -> batch_size seq_length n_heads', reduction='sum')
-
-        # query_states = F.elu(query_states) + 1
-        # retrieved_memory = einsum(query_states, memory, 'batch_size q_length n_heads d_head, batch_size n_heads k_length v_length -> batch_size q_length s d')
-        # retrieved_memory = torch.matmul(query_states, memory) / torch.matmul(query_states, normalization)
-
-        memory, normalization = self._get_memory(key_states, value_states)
-        retrieved_memory = self._retrieve_from_memory(query_states, memory, normalization)
-        local_attn_outputs = rearrange(
-            local_attn_outputs,
-            "seq_length batch_size (n_heads d_head) -> batch_size n_heads seq_length d_head",
-            d_head=self.d_head,
-        )
-        # assert self.balance_factor.shape == n_heads
-
-        balance_factors = torch.randn(N_HEADS, device=local_attn_outputs.device, dtype=local_attn_outputs.dtype)
-
-        global_weights = F.sigmoid(balance_factors)
-        global_attn_outputs = global_weights[None, :, None, None] * retrieved_memory
-
-        local_weights = F.sigmoid(1 - balance_factors)
-        local_attn_outputs = local_weights[None, :, None, None] * local_attn_outputs
-
-        attention_output = global_attn_outputs + local_attn_outputs
-        attention_output = rearrange(
-            attention_output, "batch_size n_heads seq_len d_head -> batch_size seq_len (n_heads d_head)"
-        )
-
-        self.o_proj(attention_output)
-
-        assert 1 == 1
-        # NOTE: update memory
+        if TYPE == "linear":
+            # memory = torch.matmul(key_states.transpose(-2, -1), value_states)
+            new_value_states = value_states
+        else:
+            if prev_memory is None or prev_normalization is None:
+                new_value_states = value_states
+            else:
+                # denominator = torch.matmul(key_states, prev_normalization)
+                # denominator = denominator[:, :, :, None]
+
+                # numerator = einsum(
+                #     key_states, prev_memory,
+                #     "batch_size n_heads seq_len d_head, batch_size n_heads seq_len d_head -> batch_size n_heads seq_len"
+                # )
+
+                numerator = einsum(
+                    key_states,
+                    prev_memory,
+                    "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
+                )
+
+                # denominator = einsum(
+                #     key_states, prev_normalization,
+                #     "batch_size n_heads seq_len d_head, batch_size n_heads d_head -> batch_size seq_len"
+                # )
+                denominator = einsum(
+                    key_states,
+                    prev_normalization,
+                    "batch_size n_heads seq_length d_k, batch_size n_heads d_k -> batch_size n_heads seq_length",
+                )
+
+                prev_v = numerator / denominator[:, :, :, None]
+                new_value_states = value_states - prev_v
+
+        memory = torch.matmul(key_states.transpose(-2, -1), new_value_states)
 
-    def _get_memory(self, key_states, value_states):
-        key_states = F.elu(key_states) + 1
-        memory = torch.matmul(key_states.transpose(-2, -1), value_states)
         # memory = einsum(key_states, value_states, 'batch_size n_heads k_length d_head, batch_size n_heads v_length d_head -> batch_size n_heads k_length v_length')
         normalization = reduce(
             key_states, "batch_size n_heads seq_length d_head -> batch_size n_heads d_head", reduction="sum"
         )
+
+        memory += prev_memory if prev_memory is not None else 0
+        normalization += prev_normalization if prev_normalization is not None else 0
+
         return memory, normalization
 
-    def _retrieve_from_memory(self, query_states, memory, normalization):
+    def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
+        if prev_memory is None:
+            return torch.zeros_like(query_states)
+
         query_states = F.elu(query_states) + 1
         retrieved_memory = einsum(
             query_states,
-            memory,
+            prev_memory,
             "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
         )
 
         denominator = einsum(
             query_states,
-            normalization,
+            prev_normalization,
             "batch_size n_heads seq_length d_k, batch_size n_heads d_k -> batch_size n_heads seq_length",
         )
         # [batch_size, n_heads, seq_length, d_v] / [batch_size, n_heads, seq_length, 1], so each d_v is divide by the normalized value
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index b8f30098..5e2b6a21 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -326,14 +326,14 @@ def __init__(
         # NOTE: Only supported for training (TODO(fmom): position_ids not supported yet)
         self.flash_rotary_embedding = FlashRotaryEmbedding(dim=self.d_qk, interleaved=True)
 
-        self.o_proj = TensorParallelRowLinear(
-            config.num_attention_heads * self.d_qk,
-            self.d_model,
-            pg=tp_pg,
-            mode=tp_mode,
-            bias=False,
-            async_communication=tp_linear_async_communication,
-        )
+        # self.o_proj = TensorParallelRowLinear(
+        #     config.num_attention_heads * self.d_qk,
+        #     self.d_model,
+        #     pg=tp_pg,
+        #     mode=tp_mode,
+        #     bias=False,
+        #     async_communication=tp_linear_async_communication,
+        # )
 
         self.attention = CoreAttention(
             config,
@@ -595,9 +595,9 @@ def forward(
         attention_output = (
             attention_output.contiguous().view(batch_size, q_length, self.n_local_q_heads * self.d_v).transpose(0, 1)
         )
-        output = self.o_proj(attention_output)
+        # output = self.o_proj(attention_output)
 
-        return_outputs = {"hidden_states": output, "sequence_mask": sequence_mask}
+        return_outputs = {"hidden_states": None, "sequence_mask": sequence_mask}
         return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
         return_outputs["attention_output"] = attention_output
         return return_outputs
@@ -956,8 +956,13 @@ def init_model_randomly(self, config: Config):
                 # Already initialized
                 continue
 
-            module = model.get_submodule(module_name)
-            parametrizator.parametrize(param_name, module)
+            if "balance_factors" in param_name:
+                import torch.nn.init as init
+
+                init.normal_(param, mean=0.0, std=0.01)
+            else:
+                module = model.get_submodule(module_name)
+                parametrizator.parametrize(param_name, module)
 
             assert full_param_name not in initialized_parameters
             initialized_parameters.add(full_param_name)

From 8f3a61e8b2f1e52a1760c61a1f76e7f65e8cff56 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Tue, 23 Apr 2024 07:32:00 +0000
Subject: [PATCH 04/43] fix computing global attention

---
 src/nanotron/models/attention.py | 96 ++++++++++++++++----------------
 src/nanotron/models/llama.py     | 41 +++++++-------
 2 files changed, 68 insertions(+), 69 deletions(-)

diff --git a/src/nanotron/models/attention.py b/src/nanotron/models/attention.py
index fb7c3a21..537140b9 100644
--- a/src/nanotron/models/attention.py
+++ b/src/nanotron/models/attention.py
@@ -51,6 +51,8 @@ def __init__(
             bias=False,
             async_communication=tp_linear_async_communication,
         )
+        # NOTE: because the number of heads are splited in TP
+        # so we find them on the fly
         self.n_local_heads = self.attn.n_local_q_heads
 
         device = self.o_proj.weight.device
@@ -66,7 +68,7 @@ def __init__(
 
     def forward(
         self,
-        hidden_states: TensorType["seq_length", "batch_size", "hidden_size"],
+        hidden_states: TensorType["sharded_seq_length", "batch_size", "hidden_size"],
         sequence_mask: TensorType["batch_size", "seq_length"],
     ):
         batch_size = hidden_states.shape[1]
@@ -89,40 +91,34 @@ def forward(
             )
 
             local_attn_outputs = attn_outputs["attention_output"]
-            # sequence_masks.append(attn_outputs["sequence_mask"])
-
-            # NOTE: query_states.shape = [batch_size * q_length, self.n_heads, d_qk]
-            # NOTE: key_states.shape or value_states.shape = [batch_size * kv_length, self.n_heads, d_qk]
             query_states, key_states, value_states = attn_outputs["qkv_states"]
 
             query_states = rearrange(
                 query_states,
                 "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
                 batch_size=batch_size,
+                n_heads=self.n_local_heads,
             )
-            # NOTE: because the number of heads are splited in TP
-            # so we find them on the fly
-
             key_states = rearrange(
                 key_states,
                 "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
                 batch_size=batch_size,
+                n_heads=self.n_local_heads,
             )
             value_states = rearrange(
                 value_states,
                 "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
                 batch_size=batch_size,
+                n_heads=self.n_local_heads,
             )
 
-            # NOTE: because we split the heads in TP, we need to find the number of heads on the fly
-            N_HEADS = query_states.shape[1]
-            assert N_HEADS == self.n_local_heads
-            # balance_factors = torch.randn(N_HEADS, device=local_attn_outputs.device, dtype=local_attn_outputs.dtype)
+            # assert query_states.shape == (batch_size, self.n_local_heads, segment_length, self.d_head)
+            assert query_states.shape == key_states.shape == value_states.shape
 
             retrieved_memory = self._retrieve_from_memory(
                 query_states, prev_memory=memory, prev_normalization=normalization
             )
-            retrieved_memory = retrieved_memory.detach()
+            # retrieved_memory = retrieved_memory.detach()
 
             local_attn_outputs = rearrange(
                 local_attn_outputs,
@@ -131,12 +127,17 @@ def forward(
             )
 
             global_weights = F.sigmoid(self.balance_factors)
-            global_attn_outputs = global_weights[None, :, None, None] * retrieved_memory
+            global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
+
+            local_weights = 1 - F.sigmoid(self.balance_factors)
+            local_weights = rearrange(local_weights, "n_heads -> 1 n_heads 1 1")
 
-            local_weights = F.sigmoid(1 - self.balance_factors)
-            local_attn_outputs = local_weights[None, :, None, None] * local_attn_outputs
+            # assert torch.allclose(global_weights + local_weights, torch.ones_like(global_weights))
+
+            attention_output = global_weights * retrieved_memory + local_weights * local_attn_outputs
+
+            # assert attention_output.shape == (batch_size, self.n_local_heads, segment_length, self.d_head)
 
-            attention_output = global_attn_outputs + local_attn_outputs
             attention_output = rearrange(
                 attention_output, "batch_size n_heads seq_len d_head -> seq_len batch_size (n_heads d_head)"
             )
@@ -146,8 +147,8 @@ def forward(
             assert output.shape == (segment_length, batch_size, hidden_size)
 
             memory, normalization = self._update_memory(memory, normalization, key_states, value_states)
-            memory = memory.detach()
-            normalization = normalization.detach()
+            # memory = memory.detach()
+            # normalization = normalization.detach()
 
             outputs.append(output)
 
@@ -160,6 +161,30 @@ def forward(
         return_outputs = {"hidden_states": outputs, "sequence_mask": sequence_mask}
         return return_outputs
 
+    def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
+        # return torch.zeros_like(query_states)
+        if prev_memory is None:
+            return torch.zeros_like(query_states)
+
+        query_states = F.elu(query_states) + 1
+        retrieved_memory = einsum(
+            query_states,
+            prev_memory,
+            "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
+        )
+
+        denominator = einsum(
+            query_states,
+            prev_normalization,
+            "batch_size n_heads seq_length d_head, batch_size n_heads d_head -> batch_size n_heads seq_length",
+        )
+        denominator = rearrange(denominator, "batch_size n_heads seq_length -> batch_size n_heads seq_length 1")
+        # [batch_size, n_heads, seq_length, d_v] / [batch_size, n_heads, seq_length, 1], so each d_v is divide by the normalized value
+
+        # NOTE: because normalization is the sum of all the keys, so each word should have the same normalization
+        retrieved_memory = retrieved_memory / denominator
+        return retrieved_memory
+
     def _update_memory(self, prev_memory, prev_normalization, key_states, value_states):
         TYPE = "delta"
         key_states = F.elu(key_states) + 1
@@ -171,14 +196,6 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
             if prev_memory is None or prev_normalization is None:
                 new_value_states = value_states
             else:
-                # denominator = torch.matmul(key_states, prev_normalization)
-                # denominator = denominator[:, :, :, None]
-
-                # numerator = einsum(
-                #     key_states, prev_memory,
-                #     "batch_size n_heads seq_len d_head, batch_size n_heads seq_len d_head -> batch_size n_heads seq_len"
-                # )
-
                 numerator = einsum(
                     key_states,
                     prev_memory,
@@ -194,8 +211,11 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
                     prev_normalization,
                     "batch_size n_heads seq_length d_k, batch_size n_heads d_k -> batch_size n_heads seq_length",
                 )
+                denominator = rearrange(
+                    denominator, "batch_size n_heads seq_length -> batch_size n_heads seq_length 1"
+                )
 
-                prev_v = numerator / denominator[:, :, :, None]
+                prev_v = numerator / denominator
                 new_value_states = value_states - prev_v
 
         memory = torch.matmul(key_states.transpose(-2, -1), new_value_states)
@@ -209,23 +229,3 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
         normalization += prev_normalization if prev_normalization is not None else 0
 
         return memory, normalization
-
-    def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
-        if prev_memory is None:
-            return torch.zeros_like(query_states)
-
-        query_states = F.elu(query_states) + 1
-        retrieved_memory = einsum(
-            query_states,
-            prev_memory,
-            "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
-        )
-
-        denominator = einsum(
-            query_states,
-            prev_normalization,
-            "batch_size n_heads seq_length d_k, batch_size n_heads d_k -> batch_size n_heads seq_length",
-        )
-        # [batch_size, n_heads, seq_length, d_v] / [batch_size, n_heads, seq_length, 1], so each d_v is divide by the normalized value
-        retrieved_memory = retrieved_memory / denominator[:, :, :, None]
-        return retrieved_memory
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 5e2b6a21..0472f3f2 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -26,7 +26,6 @@
 from nanotron.generation.generate_store import AttachableStore
 from nanotron.logging import log_rank
 from nanotron.models import NanotronModel
-from nanotron.models.attention import InfiniAttention
 from nanotron.nn.activations import ACT2FN
 from nanotron.nn.layer_norm import TritonRMSNorm
 from nanotron.parallel import ParallelContext
@@ -326,14 +325,14 @@ def __init__(
         # NOTE: Only supported for training (TODO(fmom): position_ids not supported yet)
         self.flash_rotary_embedding = FlashRotaryEmbedding(dim=self.d_qk, interleaved=True)
 
-        # self.o_proj = TensorParallelRowLinear(
-        #     config.num_attention_heads * self.d_qk,
-        #     self.d_model,
-        #     pg=tp_pg,
-        #     mode=tp_mode,
-        #     bias=False,
-        #     async_communication=tp_linear_async_communication,
-        # )
+        self.o_proj = TensorParallelRowLinear(
+            config.num_attention_heads * self.d_qk,
+            self.d_model,
+            pg=tp_pg,
+            mode=tp_mode,
+            bias=False,
+            async_communication=tp_linear_async_communication,
+        )
 
         self.attention = CoreAttention(
             config,
@@ -595,11 +594,11 @@ def forward(
         attention_output = (
             attention_output.contiguous().view(batch_size, q_length, self.n_local_q_heads * self.d_v).transpose(0, 1)
         )
-        # output = self.o_proj(attention_output)
+        output = self.o_proj(attention_output)
 
-        return_outputs = {"hidden_states": None, "sequence_mask": sequence_mask}
-        return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
-        return_outputs["attention_output"] = attention_output
+        return_outputs = {"hidden_states": output, "sequence_mask": sequence_mask}
+        # return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
+        # return_outputs["attention_output"] = attention_output
         return return_outputs
 
 
@@ -613,20 +612,20 @@ def __init__(
     ):
         super().__init__()
         self.input_layernorm = TritonRMSNorm(config.hidden_size, eps=config.rms_norm_eps)
-        # self.attn = CausalSelfAttention(
-        #     config=config,
-        #     parallel_config=parallel_config,
-        #     tp_pg=tp_pg,
-        #     layer_idx=layer_idx,
-        # )
-
-        self.attn = InfiniAttention(
+        self.attn = CausalSelfAttention(
             config=config,
             parallel_config=parallel_config,
             tp_pg=tp_pg,
             layer_idx=layer_idx,
         )
 
+        # self.attn = InfiniAttention(
+        #     config=config,
+        #     parallel_config=parallel_config,
+        #     tp_pg=tp_pg,
+        #     layer_idx=layer_idx,
+        # )
+
         self.post_attention_layernorm = TritonRMSNorm(config.hidden_size, eps=config.rms_norm_eps)
         self.mlp = MLP(config=config, parallel_config=parallel_config, tp_pg=tp_pg)
 

From d681ee5da44f26e4f101538810674ccb46b1b7a9 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Tue, 23 Apr 2024 11:29:36 +0000
Subject: [PATCH 05/43] fix

---
 src/nanotron/distributed.py      |  2 +-
 src/nanotron/models/attention.py |  9 ++++---
 src/nanotron/models/llama.py     | 42 +++++++++++++++++---------------
 3 files changed, 28 insertions(+), 25 deletions(-)

diff --git a/src/nanotron/distributed.py b/src/nanotron/distributed.py
index 0156b1bb..566b6af2 100644
--- a/src/nanotron/distributed.py
+++ b/src/nanotron/distributed.py
@@ -13,7 +13,7 @@
 
 torch_version_above_1_13 = version.parse(torch.__version__) >= version.parse("1.13.0")
 Work = dist.Work if torch_version_above_1_13 else dist._Work
-default_pg_timeout = datetime.timedelta(minutes=10)
+default_pg_timeout = datetime.timedelta(minutes=1000)
 
 
 def new_group(  # pylint: disable=function-redefined
diff --git a/src/nanotron/models/attention.py b/src/nanotron/models/attention.py
index 537140b9..3d855fe3 100644
--- a/src/nanotron/models/attention.py
+++ b/src/nanotron/models/attention.py
@@ -22,7 +22,7 @@ def __init__(
     ):
         super().__init__()
 
-        self.n_segments = 4
+        self.n_segments = 50
 
         from nanotron.models.llama import CausalSelfAttention
 
@@ -57,6 +57,7 @@ def __init__(
 
         device = self.o_proj.weight.device
         dtype = self.o_proj.weight.dtype
+        # self.balance_factors = TensorParallelRowLinear(config.num_attention_heads * self.d_head, 1, pg=tp_pg, mode=tp_mode)
         self.balance_factors = nn.Parameter(torch.randn(self.n_local_heads, device=device, dtype=dtype))
 
         # assert self.o_proj.weight.shape == self.attn.o_proj.weight.shape
@@ -97,19 +98,19 @@ def forward(
                 query_states,
                 "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
                 batch_size=batch_size,
-                n_heads=self.n_local_heads,
+                # n_heads=self.n_local_heads,
             )
             key_states = rearrange(
                 key_states,
                 "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
                 batch_size=batch_size,
-                n_heads=self.n_local_heads,
+                # n_heads=self.n_local_heads,
             )
             value_states = rearrange(
                 value_states,
                 "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
                 batch_size=batch_size,
-                n_heads=self.n_local_heads,
+                # n_heads=self.n_local_heads,
             )
 
             # assert query_states.shape == (batch_size, self.n_local_heads, segment_length, self.d_head)
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 0472f3f2..f241a51a 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -325,14 +325,14 @@ def __init__(
         # NOTE: Only supported for training (TODO(fmom): position_ids not supported yet)
         self.flash_rotary_embedding = FlashRotaryEmbedding(dim=self.d_qk, interleaved=True)
 
-        self.o_proj = TensorParallelRowLinear(
-            config.num_attention_heads * self.d_qk,
-            self.d_model,
-            pg=tp_pg,
-            mode=tp_mode,
-            bias=False,
-            async_communication=tp_linear_async_communication,
-        )
+        # self.o_proj = TensorParallelRowLinear(
+        #     config.num_attention_heads * self.d_qk,
+        #     self.d_model,
+        #     pg=tp_pg,
+        #     mode=tp_mode,
+        #     bias=False,
+        #     async_communication=tp_linear_async_communication,
+        # )
 
         self.attention = CoreAttention(
             config,
@@ -594,11 +594,11 @@ def forward(
         attention_output = (
             attention_output.contiguous().view(batch_size, q_length, self.n_local_q_heads * self.d_v).transpose(0, 1)
         )
-        output = self.o_proj(attention_output)
+        # output = self.o_proj(attention_output)
 
-        return_outputs = {"hidden_states": output, "sequence_mask": sequence_mask}
-        # return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
-        # return_outputs["attention_output"] = attention_output
+        return_outputs = {"hidden_states": None, "sequence_mask": sequence_mask}
+        return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
+        return_outputs["attention_output"] = attention_output
         return return_outputs
 
 
@@ -612,20 +612,22 @@ def __init__(
     ):
         super().__init__()
         self.input_layernorm = TritonRMSNorm(config.hidden_size, eps=config.rms_norm_eps)
-        self.attn = CausalSelfAttention(
-            config=config,
-            parallel_config=parallel_config,
-            tp_pg=tp_pg,
-            layer_idx=layer_idx,
-        )
-
-        # self.attn = InfiniAttention(
+        # self.attn = CausalSelfAttention(
         #     config=config,
         #     parallel_config=parallel_config,
         #     tp_pg=tp_pg,
         #     layer_idx=layer_idx,
         # )
 
+        from nanotron.models.attention import InfiniAttention
+
+        self.attn = InfiniAttention(
+            config=config,
+            parallel_config=parallel_config,
+            tp_pg=tp_pg,
+            layer_idx=layer_idx,
+        )
+
         self.post_attention_layernorm = TritonRMSNorm(config.hidden_size, eps=config.rms_norm_eps)
         self.mlp = MLP(config=config, parallel_config=parallel_config, tp_pg=tp_pg)
 

From 74545cc8330608a7a74e55e976f297663add143a Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Sat, 27 Apr 2024 09:05:02 +0000
Subject: [PATCH 06/43] support gqa and new theta

---
 src/nanotron/models/attention.py | 17 +++++++++++++++--
 src/nanotron/models/llama.py     |  7 ++-----
 2 files changed, 17 insertions(+), 7 deletions(-)

diff --git a/src/nanotron/models/attention.py b/src/nanotron/models/attention.py
index 3d855fe3..1b1f5f47 100644
--- a/src/nanotron/models/attention.py
+++ b/src/nanotron/models/attention.py
@@ -22,7 +22,7 @@ def __init__(
     ):
         super().__init__()
 
-        self.n_segments = 50
+        self.n_segments = 4
 
         from nanotron.models.llama import CausalSelfAttention
 
@@ -114,7 +114,7 @@ def forward(
             )
 
             # assert query_states.shape == (batch_size, self.n_local_heads, segment_length, self.d_head)
-            assert query_states.shape == key_states.shape == value_states.shape
+            # assert query_states.shape == key_states.shape == value_states.shape
 
             retrieved_memory = self._retrieve_from_memory(
                 query_states, prev_memory=memory, prev_normalization=normalization
@@ -167,6 +167,19 @@ def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
         if prev_memory is None:
             return torch.zeros_like(query_states)
 
+        from einops import repeat
+
+        prev_memory = repeat(
+            prev_memory,
+            "batch_size n_kv_heads d_k d_v -> batch_size (n_kv_heads n) d_k d_v",
+            n=self.attn.n_repeats,
+        )
+        prev_normalization = repeat(
+            prev_normalization,
+            "batch_size n_kv_heads d_head -> batch_size (n_kv_heads n) d_head",
+            n=self.attn.n_repeats,
+        )
+
         query_states = F.elu(query_states) + 1
         retrieved_memory = einsum(
             query_states,
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index f241a51a..3b3bf511 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -317,13 +317,10 @@ def __init__(
             contiguous_chunks=qkv_contiguous_chunks,
         )
         # TODO(kunhao): We want to have only one version per device and not one version per layer.
-        self.rotary_embedding = RotaryEmbedding(
-            dim=self.d_qk,
-            end=config.max_position_embeddings,
-        )
+        self.rotary_embedding = RotaryEmbedding(dim=self.d_qk, end=config.max_position_embeddings, theta=500000.0)
 
         # NOTE: Only supported for training (TODO(fmom): position_ids not supported yet)
-        self.flash_rotary_embedding = FlashRotaryEmbedding(dim=self.d_qk, interleaved=True)
+        self.flash_rotary_embedding = FlashRotaryEmbedding(dim=self.d_qk, interleaved=True, base=500000.0)
 
         # self.o_proj = TensorParallelRowLinear(
         #     config.num_attention_heads * self.d_qk,

From 30b95a6b9305e1eee3e19c09e5d5f3a41ac2c06f Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Sat, 27 Apr 2024 09:10:04 +0000
Subject: [PATCH 07/43] support loading hf ckp

---
 src/nanotron/constants.py         |  6 ++++
 src/nanotron/serialize/utils.py   | 19 +++++++++--
 src/nanotron/serialize/weights.py | 30 ++++++++++++++---
 src/nanotron/trainer.py           | 55 ++++++++++++++++++++++++-------
 4 files changed, 91 insertions(+), 19 deletions(-)

diff --git a/src/nanotron/constants.py b/src/nanotron/constants.py
index 84f6b55b..e9a101c1 100644
--- a/src/nanotron/constants.py
+++ b/src/nanotron/constants.py
@@ -5,3 +5,9 @@
 CHECKPOINT_VERSION = Version("1.2")
 
 PY_VERSION = parse(platform.python_version())
+
+OPTIMIZER_CONFIG_FILE_NAME = "optimizer_config.pt"
+OPTIMIZER_CKP_PATH = "{}/optimizer/optimizer_config.pt"
+
+LR_SCHEDULER_CKP_PATH = "{}/lr_scheduler"
+METADATA_CKP_PATH = "{}.checkpoint_metadata.json"
diff --git a/src/nanotron/serialize/utils.py b/src/nanotron/serialize/utils.py
index 661dcab6..0e9f0416 100644
--- a/src/nanotron/serialize/utils.py
+++ b/src/nanotron/serialize/utils.py
@@ -37,8 +37,21 @@ def get_path(
     suffix = tensor_name.split(".")
     suffix_path, suffix_name = suffix[:-1], suffix[-1]
 
-    suffix_name = f"{type.value}_{suffix_name}.safetensors"
-
+    # suffix_name = f"{type.value}_{suffix_name}.safetensors"
+
+    # NOTE: the original
+    # if exp_tp_pp_rank_and_size:
+    #     # We always show pp_rank and tp_rank if `exp_tp_pp_rank_and_size` is provided
+    #     # We only show exp_rank if tensor is exp_sharded and exp_size > 1
+    #     (exp_rank, exp_size), (tp_rank, tp_size), (pp_rank, pp_size) = exp_tp_pp_rank_and_size
+    #     if not is_expert_sharded or exp_size == 1:
+    #         suffix_name = (
+    #             f"{type.value}_{suffix_name}_pp-rank-{pp_rank}-of-{pp_size}_tp-rank-{tp_rank}-of-{tp_size}.safetensors"
+    #         )
+    #     else:
+    #         suffix_name = f"{type.value}_{suffix_name}_pp-rank-{pp_rank}-of-{pp_size}_tp-rank-{tp_rank}-of-{tp_size}_exp-rank-{exp_rank}-of-{exp_size}.safetensors"
+
+    # NOTE: quick fix from https://huggingface.slack.com/archives/C065PTETH8S/p1713881041551769?thread_ts=1713876968.072339&cid=C065PTETH8S
     if exp_tp_pp_rank_and_size:
         # We always show pp_rank and tp_rank if `exp_tp_pp_rank_and_size` is provided
         # We only show exp_rank if tensor is exp_sharded and exp_size > 1
@@ -49,6 +62,8 @@ def get_path(
             )
         else:
             suffix_name = f"{type.value}_{suffix_name}_pp-rank-{pp_rank}-of-{pp_size}_tp-rank-{tp_rank}-of-{tp_size}_exp-rank-{exp_rank}-of-{exp_size}.safetensors"
+    else:
+        suffix_name = f"{type.value}_{suffix_name}.safetensors"  # <- HERE
 
     suffix_path.append(suffix_name)
     if prefix is None:
diff --git a/src/nanotron/serialize/weights.py b/src/nanotron/serialize/weights.py
index c857154f..9b3e2b25 100644
--- a/src/nanotron/serialize/weights.py
+++ b/src/nanotron/serialize/weights.py
@@ -198,6 +198,7 @@ def load_weights(
     parallel_context: ParallelContext,
     root_folder: Path,
     filtered_state_dict: Optional[Dict[str, Any]] = None,
+    strict: bool = False,
 ):
     """Load weights from a checkpoint
 
@@ -206,6 +207,8 @@ def load_weights(
         parallel_context: distributed process groups
         root_folder: root folder of the checkpoint
         filtered_state_dict: state dict to load from (overrides model.state_dict()). if None, load from model.state_dict()
+        strict: whether to strictly enforce that the keys in the state_dict match the keys returned by this module's state_dict() function
+        if you set strict to False, we will skip loading the parameters that can't find the checkpoint file.
     """
     param_root_folder = root_folder / "model"
 
@@ -275,10 +278,18 @@ def load_weights(
                         pass
 
             elif not path.parent.exists():
-                raise ValueError(
-                    f"Checkpoint is empty or checkpoint structure is not matching the model architecture."
-                    f"Couldn't find folder {path.parent} in checkpoint at {root_folder}"
-                )
+                if strict is False:
+                    log_rank(
+                        f"We can't find the checkpoint for parameter {name} at {path.parent}. Skipping it.",
+                        logger=logger,
+                        level=logging.WARNING,
+                        rank=0,
+                    )
+                else:
+                    raise ValueError(
+                        f"Checkpoint is empty or checkpoint structure is not matching the model architecture."
+                        f"Couldn't find folder {path.parent} in checkpoint at {root_folder}"
+                    )
             else:
                 # Let's assume that the topology changed and the param is sharded.
                 # We search for all the files from the shards, concatenate the "unsharded" tensor
@@ -292,7 +303,16 @@ def load_weights(
                 suffix = base_name.rsplit(".", 1)[-1]
                 shards_path = list(path.parent.glob(f"{ObjectType.MODEL.value}_{suffix}*.safetensors"))
                 if len(shards_path) <= 0:
-                    raise ValueError(f"Could not find any shards in {path.parent}")
+                    if strict is False:
+                        log_rank(
+                            f"We can't find the checkpoint for parameter {name} at {path}. Skipping it.",
+                            logger=logger,
+                            level=logging.WARNING,
+                            rank=0,
+                        )
+                        continue
+                    else:
+                        raise ValueError(f"Could not find any shards in {path.parent}")
 
                 if checkpoint_version is None:
                     checkpoint_version = get_checkpoint_version(
diff --git a/src/nanotron/trainer.py b/src/nanotron/trainer.py
index 32b52169..9d83682b 100644
--- a/src/nanotron/trainer.py
+++ b/src/nanotron/trainer.py
@@ -34,6 +34,7 @@
     SpectralMupInit,
     get_config_from_file,
 )
+from nanotron.constants import LR_SCHEDULER_CKP_PATH, METADATA_CKP_PATH, OPTIMIZER_CKP_PATH
 from nanotron.dataloader import sanity_check_dataloader
 from nanotron.helpers import (
     _vocab_size_with_padding,
@@ -184,13 +185,24 @@ def __init__(
             parallel_context=self.parallel_context,
         )
         if self.init_checkpoint_path is not None:
-            load_optimizer(
-                optimizer=self.optimizer,
-                parallel_context=self.parallel_context,
-                root_folder=self.init_checkpoint_path,
-                param_shard_metadata=self.param_shard_metadata,
-                model=self.model,
-            )
+            # NOTE: in some cases where we convert hf checkpoints to nanotron checkpoints,
+            # we might not have the optimizer state
+            optim_ckp_path = OPTIMIZER_CKP_PATH.format(self.init_checkpoint_path)
+            if os.path.exists(optim_ckp_path):
+                load_optimizer(
+                    optimizer=self.optimizer,
+                    parallel_context=self.parallel_context,
+                    root_folder=self.init_checkpoint_path,
+                    param_shard_metadata=self.param_shard_metadata,
+                    model=self.model,
+                )
+            else:
+                log_rank(
+                    f"Can't find the optimizer state's checkpoint in {optim_ckp_path}, so we skip loading its checkpoint!",
+                    logger=logger,
+                    level=logging.INFO,
+                    rank=0,
+                )
 
         # Init learning rate scheduler
         self.lr_scheduler = lr_scheduler_builder(
@@ -199,13 +211,24 @@ def __init__(
             total_training_steps=self.config.tokens.train_steps,
         )
         if self.init_checkpoint_path is not None:
-            load_lr_scheduler(
-                lr_scheduler=self.lr_scheduler,
-                root_folder=self.init_checkpoint_path,
-            )
+            lr_scheduler_ckp_path = LR_SCHEDULER_CKP_PATH.format(self.init_checkpoint_path)
+            if os.path.exists(lr_scheduler_ckp_path):
+                load_lr_scheduler(
+                    lr_scheduler=self.lr_scheduler,
+                    root_folder=self.init_checkpoint_path,
+                )
+            else:
+                log_rank(
+                    f"Can't find the LR scheduler's checkpoint in {lr_scheduler_ckp_path}, so we skip loading its checkpoint!",
+                    logger=logger,
+                    level=logging.INFO,
+                    rank=0,
+                )
 
         # Define iteration start state
-        if self.init_checkpoint_path is not None:
+        metadata_ckp_path = METADATA_CKP_PATH.format(self.init_checkpoint_path)
+        is_ckp_meta_data_exists = os.path.exists(metadata_ckp_path)
+        if self.init_checkpoint_path is not None and is_ckp_meta_data_exists:
             checkpoint_metadata = load_meta(
                 parallel_context=self.parallel_context, root_folder=self.init_checkpoint_path
             )
@@ -216,6 +239,14 @@ def __init__(
                 self.config.tokens.train_steps > self.start_iteration_step
             ), f"Loaded checkpoint has already trained {self.start_iteration_step} batches, you need to specify a higher `config.tokens.train_steps`"
         else:
+            if self.init_checkpoint_path is not None and not is_ckp_meta_data_exists:
+                log_rank(
+                    f"Can't find the checkpoint metadata in {metadata_ckp_path}, so we skip loading it!",
+                    logger=logger,
+                    level=logging.INFO,
+                    rank=0,
+                )
+
             self.start_iteration_step = 0
             self.consumed_train_samples = 0
 

From fef75ff0e5a5cb8e88706c9c5cacc057543f2424 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Sat, 27 Apr 2024 09:42:00 +0000
Subject: [PATCH 08/43] tested, llama3 wiht infini, get 5 loss

---
 src/nanotron/models/llama.py | 235 ++++++++++++++++++++++++++++++++---
 1 file changed, 217 insertions(+), 18 deletions(-)

diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 3b3bf511..23517131 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -254,6 +254,11 @@ def pad_to_right(tensor, mask, new_tensor=None):
     return new_tensor, right_padded_mask
 
 
+import torch.nn.functional as F
+from einops import einsum, rearrange, reduce
+from torchtyping import TensorType
+
+
 class CausalSelfAttention(nn.Module, AttachableStore):
     def __init__(
         self,
@@ -322,14 +327,14 @@ def __init__(
         # NOTE: Only supported for training (TODO(fmom): position_ids not supported yet)
         self.flash_rotary_embedding = FlashRotaryEmbedding(dim=self.d_qk, interleaved=True, base=500000.0)
 
-        # self.o_proj = TensorParallelRowLinear(
-        #     config.num_attention_heads * self.d_qk,
-        #     self.d_model,
-        #     pg=tp_pg,
-        #     mode=tp_mode,
-        #     bias=False,
-        #     async_communication=tp_linear_async_communication,
-        # )
+        self.o_proj = TensorParallelRowLinear(
+            config.num_attention_heads * self.d_qk,
+            self.d_model,
+            pg=tp_pg,
+            mode=tp_mode,
+            bias=False,
+            async_communication=tp_linear_async_communication,
+        )
 
         self.attention = CoreAttention(
             config,
@@ -341,7 +346,200 @@ def __init__(
             config.max_position_embeddings
         )  # TODO @nouamane: compute based on free memory, because in rope we can surpass max_position_embeddings
 
+        self.n_segments = 4
+        device = self.o_proj.weight.device
+        dtype = self.o_proj.weight.dtype
+
+        from nanotron.parallel.sharded_parameters import SplitConfig, create_sharded_parameter_from_config
+
+        balance_factors = nn.Parameter(torch.zeros(self.n_local_q_heads, device=device, dtype=dtype))
+        self.balance_factors = create_sharded_parameter_from_config(
+            parameter=balance_factors,
+            pg=tp_pg,
+            split_config=SplitConfig(
+                split_dim=0,
+                # contiguous_chunks=(self.n_local_heads, self.n_local_heads)
+            ),
+        )
+
     def forward(
+        self,
+        hidden_states: TensorType["sharded_seq_length", "batch_size", "hidden_size"],
+        sequence_mask: TensorType["batch_size", "seq_length"],
+    ):
+        batch_size = hidden_states.shape[1]
+        seq_len = hidden_states.shape[0]
+        segment_length = seq_len // self.n_segments
+        hidden_size = hidden_states.shape[2]
+
+        segment_hidden_states = torch.chunk(hidden_states, chunks=self.n_segments, dim=0)
+        segment_sequence_masks = torch.chunk(sequence_mask, chunks=self.n_segments, dim=1)
+
+        memory = None
+        normalization = None
+
+        outputs = []
+
+        # sequence_masks = []
+        for segment_hidden_state, segment_sequence_mask in zip(segment_hidden_states, segment_sequence_masks):
+            attn_outputs = self.forward_with_hidden_states(
+                hidden_states=segment_hidden_state, sequence_mask=segment_sequence_mask, return_qkv_states=True
+            )
+
+            local_attn_outputs = attn_outputs["attention_output"]
+            query_states, key_states, value_states = attn_outputs["qkv_states"]
+
+            query_states = rearrange(
+                query_states,
+                "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
+                batch_size=batch_size,
+                # n_heads=self.n_local_heads,
+            )
+            key_states = rearrange(
+                key_states,
+                "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
+                batch_size=batch_size,
+                # n_heads=self.n_local_heads,
+            )
+            value_states = rearrange(
+                value_states,
+                "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
+                batch_size=batch_size,
+                # n_heads=self.n_local_heads,
+            )
+
+            # assert query_states.shape == (batch_size, self.n_local_heads, segment_length, self.d_head)
+            # assert query_states.shape == key_states.shape == value_states.shape
+
+            retrieved_memory = self._retrieve_from_memory(
+                query_states, prev_memory=memory, prev_normalization=normalization
+            )
+            # retrieved_memory = retrieved_memory.detach()
+
+            local_attn_outputs = rearrange(
+                local_attn_outputs,
+                "seq_len batch_size (n_heads d_head) -> batch_size n_heads seq_len d_head",
+                d_head=self.d_qk,
+            )
+
+            global_weights = F.sigmoid(self.balance_factors)
+            global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
+
+            local_weights = 1 - F.sigmoid(self.balance_factors)
+            local_weights = rearrange(local_weights, "n_heads -> 1 n_heads 1 1")
+
+            # assert torch.allclose(global_weights + local_weights, torch.ones_like(global_weights))
+
+            attention_output = global_weights * retrieved_memory + local_weights * local_attn_outputs
+
+            # assert attention_output.shape == (batch_size, self.n_local_heads, segment_length, self.d_head)
+
+            attention_output = rearrange(
+                attention_output, "batch_size n_heads seq_len d_head -> seq_len batch_size (n_heads d_head)"
+            )
+
+            output = self.o_proj(attention_output)
+
+            assert output.shape == (segment_length, batch_size, hidden_size)
+
+            memory, normalization = self._update_memory(memory, normalization, key_states, value_states)
+            # memory = memory.detach()
+            # normalization = normalization.detach()
+
+            outputs.append(output)
+
+            # NOTE: update memory
+        outputs = torch.cat(outputs, dim=0)  # concat along sequence dimension
+        assert outputs.shape == hidden_states.shape
+
+        # sequence_masks = torch.cat(sequence_masks, dim=1)
+        # assert sequence_masks.shape == sequence_mask.shape
+        return_outputs = {"hidden_states": outputs, "sequence_mask": sequence_mask}
+        return return_outputs
+
+    def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
+        # return torch.zeros_like(query_states)
+        if prev_memory is None:
+            return torch.zeros_like(query_states)
+
+        from einops import repeat
+
+        prev_memory = repeat(
+            prev_memory,
+            "batch_size n_kv_heads d_k d_v -> batch_size (n_kv_heads n) d_k d_v",
+            n=self.n_repeats,
+        )
+        prev_normalization = repeat(
+            prev_normalization,
+            "batch_size n_kv_heads d_head -> batch_size (n_kv_heads n) d_head",
+            n=self.n_repeats,
+        )
+
+        query_states = F.elu(query_states) + 1
+        retrieved_memory = einsum(
+            query_states,
+            prev_memory,
+            "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
+        )
+
+        denominator = einsum(
+            query_states,
+            prev_normalization,
+            "batch_size n_heads seq_length d_head, batch_size n_heads d_head -> batch_size n_heads seq_length",
+        )
+        denominator = rearrange(denominator, "batch_size n_heads seq_length -> batch_size n_heads seq_length 1")
+        # [batch_size, n_heads, seq_length, d_v] / [batch_size, n_heads, seq_length, 1], so each d_v is divide by the normalized value
+
+        # NOTE: because normalization is the sum of all the keys, so each word should have the same normalization
+        retrieved_memory = retrieved_memory / denominator
+        return retrieved_memory
+
+    def _update_memory(self, prev_memory, prev_normalization, key_states, value_states):
+        TYPE = "delta"
+        key_states = F.elu(key_states) + 1
+
+        if TYPE == "linear":
+            # memory = torch.matmul(key_states.transpose(-2, -1), value_states)
+            new_value_states = value_states
+        else:
+            if prev_memory is None or prev_normalization is None:
+                new_value_states = value_states
+            else:
+                numerator = einsum(
+                    key_states,
+                    prev_memory,
+                    "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
+                )
+
+                # denominator = einsum(
+                #     key_states, prev_normalization,
+                #     "batch_size n_heads seq_len d_head, batch_size n_heads d_head -> batch_size seq_len"
+                # )
+                denominator = einsum(
+                    key_states,
+                    prev_normalization,
+                    "batch_size n_heads seq_length d_k, batch_size n_heads d_k -> batch_size n_heads seq_length",
+                )
+                denominator = rearrange(
+                    denominator, "batch_size n_heads seq_length -> batch_size n_heads seq_length 1"
+                )
+
+                prev_v = numerator / denominator
+                new_value_states = value_states - prev_v
+
+        memory = torch.matmul(key_states.transpose(-2, -1), new_value_states)
+
+        # memory = einsum(key_states, value_states, 'batch_size n_heads k_length d_head, batch_size n_heads v_length d_head -> batch_size n_heads k_length v_length')
+        normalization = reduce(
+            key_states, "batch_size n_heads seq_length d_head -> batch_size n_heads d_head", reduction="sum"
+        )
+
+        memory += prev_memory if prev_memory is not None else 0
+        normalization += prev_normalization if prev_normalization is not None else 0
+
+        return memory, normalization
+
+    def forward_with_hidden_states(
         self,
         hidden_states,  # [seq_length, batch_size, hidden_size]
         sequence_mask,  # [batch_size, seq_length]
@@ -592,6 +790,7 @@ def forward(
             attention_output.contiguous().view(batch_size, q_length, self.n_local_q_heads * self.d_v).transpose(0, 1)
         )
         # output = self.o_proj(attention_output)
+        # return {"hidden_states": output, "sequence_mask": sequence_mask}
 
         return_outputs = {"hidden_states": None, "sequence_mask": sequence_mask}
         return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
@@ -609,22 +808,22 @@ def __init__(
     ):
         super().__init__()
         self.input_layernorm = TritonRMSNorm(config.hidden_size, eps=config.rms_norm_eps)
-        # self.attn = CausalSelfAttention(
-        #     config=config,
-        #     parallel_config=parallel_config,
-        #     tp_pg=tp_pg,
-        #     layer_idx=layer_idx,
-        # )
-
-        from nanotron.models.attention import InfiniAttention
-
-        self.attn = InfiniAttention(
+        self.attn = CausalSelfAttention(
             config=config,
             parallel_config=parallel_config,
             tp_pg=tp_pg,
             layer_idx=layer_idx,
         )
 
+        # from nanotron.models.attention import InfiniAttention
+
+        # self.attn = InfiniAttention(
+        #     config=config,
+        #     parallel_config=parallel_config,
+        #     tp_pg=tp_pg,
+        #     layer_idx=layer_idx,
+        # )
+
         self.post_attention_layernorm = TritonRMSNorm(config.hidden_size, eps=config.rms_norm_eps)
         self.mlp = MLP(config=config, parallel_config=parallel_config, tp_pg=tp_pg)
 

From 234d33dce54061faa7f66527748dd3794a18cde4 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Wed, 1 May 2024 12:55:21 +0000
Subject: [PATCH 09/43] add gqa optional

---
 src/nanotron/models/llama.py | 25 +++++++++++++------------
 1 file changed, 13 insertions(+), 12 deletions(-)

diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 23517131..db5cda73 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -346,7 +346,7 @@ def __init__(
             config.max_position_embeddings
         )  # TODO @nouamane: compute based on free memory, because in rope we can surpass max_position_embeddings
 
-        self.n_segments = 4
+        self.n_segments = 16
         device = self.o_proj.weight.device
         dtype = self.o_proj.weight.dtype
 
@@ -462,18 +462,19 @@ def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
         if prev_memory is None:
             return torch.zeros_like(query_states)
 
-        from einops import repeat
+        if self.n_repeats > 1:
+            from einops import repeat
 
-        prev_memory = repeat(
-            prev_memory,
-            "batch_size n_kv_heads d_k d_v -> batch_size (n_kv_heads n) d_k d_v",
-            n=self.n_repeats,
-        )
-        prev_normalization = repeat(
-            prev_normalization,
-            "batch_size n_kv_heads d_head -> batch_size (n_kv_heads n) d_head",
-            n=self.n_repeats,
-        )
+            prev_memory = repeat(
+                prev_memory,
+                "batch_size n_kv_heads d_k d_v -> batch_size (n_kv_heads n) d_k d_v",
+                n=self.n_repeats,
+            )
+            prev_normalization = repeat(
+                prev_normalization,
+                "batch_size n_kv_heads d_head -> batch_size (n_kv_heads n) d_head",
+                n=self.n_repeats,
+            )
 
         query_states = F.elu(query_states) + 1
         retrieved_memory = einsum(

From 2f50a7bd45878fea020c20585258b8c21659ad27 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Tue, 7 May 2024 10:03:24 +0000
Subject: [PATCH 10/43] fix v minus 1 in memory update

---
 run_generate.py                               |  23 +++-
 src/nanotron/generation/decode.py             |  44 ++++++
 src/nanotron/models/llama.py                  | 130 ++++++++++++------
 .../distributed_differentiable_primitives.py  |   4 +-
 src/nanotron/serialize/weights.py             |  14 ++
 5 files changed, 164 insertions(+), 51 deletions(-)

diff --git a/run_generate.py b/run_generate.py
index 0f52b8ed..0fcedaeb 100644
--- a/run_generate.py
+++ b/run_generate.py
@@ -53,6 +53,13 @@
 logger = logging.get_logger(__name__)
 
 
+END_PASSKEY = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. The pass key is 5666. Remember it. 5666 is the pass key. What is the pass key? The pass key is"
+
+PASSKEY_NINETY_PERCENT = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The pass key is 9918. Remember it. 9918 is the pass key. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. What is the pass key? The pass key is"
+
+FINETUNE = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with peopleThe pass key is 1853. Remember it. 1853 is the pass key. . Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The ur What is the pass key? The pass key is"
+
+
 def get_args():
     parser = argparse.ArgumentParser()
     parser.add_argument("--ckpt-path", type=Path, required=True, help="Checkpoint path")
@@ -77,7 +84,7 @@ def main():
         pp=args.pp or config.parallelism.pp,
         tp=args.tp or config.parallelism.tp,
         pp_engine=OneForwardOneBackwardPipelineEngine(),
-        tp_mode=TensorParallelLinearMode.ALL_REDUCE,
+        tp_mode=TensorParallelLinearMode.REDUCE_SCATTER,
         tp_linear_async_communication=True,
     )
 
@@ -165,8 +172,13 @@ def main():
         tokenizer.truncation_side = "left"  # TODO @nouamane: do we want this?
         dummy_inputs = [
             # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
-            "def fib(n)",
+            # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
+            # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
+            # "def fib(n)",
             # "This film was probably inspired by Godzilla",
+            # END_PASSKEY,
+            PASSKEY_NINETY_PERCENT,
+            # FINETUNE
         ]
 
         outputs = decode_text(
@@ -177,7 +189,7 @@ def main():
             parallel_context=parallel_context,
             max_new_tokens=args.max_new_tokens,
             max_micro_batch_size=2,
-            generation_config=GenerationArgs(sampler="greedy", use_cache=True),
+            generation_config=GenerationArgs(sampler="greedy", use_cache=False),
             tokenizer_config=TokenizerConfig(max_input_length=None),
             is_bench=os.environ.get("USE_BENCH", "0") == "1",
         )
@@ -190,7 +202,8 @@ def main():
             assert isinstance(generated_ids, torch.Tensor)
 
             log_rank(
-                f"input: {tokenizer.decode(input_ids, clean_up_tokenization_spaces=False)[:1000]}",
+                # f"input: {tokenizer.decode(input_ids, clean_up_tokenization_spaces=False)[:1000]}",
+                f"input: {tokenizer.decode(input_ids, clean_up_tokenization_spaces=False)}",
                 logger=logger,
                 level=logging.INFO,
                 rank=0,
@@ -215,7 +228,7 @@ def main():
             input_mask=torch.ones(1, 1).to(dtype=torch.bool, device="cuda"),
             model=model.model,
             parallel_context=parallel_context,
-            generation_config=GenerationArgs(sampler="greedy", use_cache=True),
+            generation_config=GenerationArgs(sampler="greedy", use_cache=False),
             max_micro_batch_size=1,
             max_new_tokens=12,
             returns_logits=False,
diff --git a/src/nanotron/generation/decode.py b/src/nanotron/generation/decode.py
index f6c1f1a8..4b177805 100644
--- a/src/nanotron/generation/decode.py
+++ b/src/nanotron/generation/decode.py
@@ -88,6 +88,33 @@ def micro_batcher(
         input_ids: [max_micro_batch_size, max_input_length]
         input_masks: [max_micro_batch_size, max_input_length]
     """
+
+    def find_sequence_positions(tensor, sequence):
+        """
+        Find the positions of a specific sequence in a PyTorch tensor.
+
+        Args:
+            tensor (torch.Tensor): The input tensor to search in.
+            sequence (torch.Tensor): The sequence to search for.
+
+        Returns:
+            torch.Tensor: A tensor containing the indices of the matching positions.
+        """
+        # Check if the sequence length is greater than the tensor length
+        if len(sequence) > len(tensor):
+            return torch.empty(0, dtype=torch.long)
+
+        # Create sliding windows of size equal to the sequence length
+        windows = tensor.unfold(0, len(sequence), 1)
+
+        # Compare each window with the sequence
+        matches = torch.eq(windows, sequence).all(dim=1)
+
+        # Get the indices of the matching positions
+        indices = matches.nonzero(as_tuple=True)[0]
+
+        return indices
+
     if tokenizer_config.padding is None:
         tokenizer_config.padding = "max_length" if tokenizer_config.max_input_length is not None else True
     if tokenizer_config.truncation is None:
@@ -103,6 +130,11 @@ def micro_batcher(
             continue
 
         if dist.get_rank(parallel_context.pp_pg) == input_rank:
+
+            # tokenizer.eos_token_id = 2
+            # tokenizer.bos_token_id = 1
+            # tokenizer.pad_token_id = tokenizer.eos_token_id
+
             encodings = tokenizer(
                 [elt.text for elt in micro_batch],
                 return_tensors="pt",
@@ -113,6 +145,18 @@ def micro_batcher(
                 # pad_to_multiple_of=8
             )
 
+            # encodings = tokenizer(
+            #     [elt.text for elt in micro_batch],
+            #     return_tensors="pt",
+            #     return_attention_mask=True,
+            #     padding="max_length",
+            #     max_length=32768,
+            #     truncation=False,
+            #     # pad_to_multiple_of=8
+            # )
+
+            # assert encodings["input_ids"][0].shape[0] == 32768
+
             encodings["attention_mask"] = encodings.attention_mask.to(dtype=torch.bool, device="cuda")
             encodings.to("cuda")
             yield GenerationInputs(input_ids=encodings.input_ids, input_masks=encodings.attention_mask)
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index db5cda73..74cff8b9 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -341,12 +341,22 @@ def __init__(
             parallel_config=parallel_config,
             layer_idx=layer_idx,
         )
+        self.layer_idx = layer_idx
 
         self.prefill_kv_len = (
             config.max_position_embeddings
         )  # TODO @nouamane: compute based on free memory, because in rope we can surpass max_position_embeddings
 
-        self.n_segments = 16
+        # self.n_segments = 16
+        # self.segment_lengths = config.max_position_embeddings // self.n_segments
+        # assert config.max_position_embeddings == 32768
+
+        # NOTE: for 1b training
+        # self.segment_lengths = 2048
+
+        # NOTE: for sanity 200m training
+        self.segment_lengths = 256
+
         device = self.o_proj.weight.device
         dtype = self.o_proj.weight.dtype
 
@@ -366,18 +376,30 @@ def forward(
         self,
         hidden_states: TensorType["sharded_seq_length", "batch_size", "hidden_size"],
         sequence_mask: TensorType["batch_size", "seq_length"],
+        prev_memory,
+        prev_normalization,
     ):
+        if self.layer_idx == 4:
+            assert 1 == 1
+
         batch_size = hidden_states.shape[1]
         seq_len = hidden_states.shape[0]
-        segment_length = seq_len // self.n_segments
-        hidden_size = hidden_states.shape[2]
+        # assert seq_len % self.n_segments == 0
+
+        # segment_length = seq_len // self.n_segments
+        # hidden_size = hidden_states.shape[2]
+
+        n_segments = seq_len // self.segment_lengths
 
-        segment_hidden_states = torch.chunk(hidden_states, chunks=self.n_segments, dim=0)
-        segment_sequence_masks = torch.chunk(sequence_mask, chunks=self.n_segments, dim=1)
+        segment_hidden_states = torch.chunk(hidden_states, chunks=n_segments, dim=0)
+        segment_sequence_masks = torch.chunk(sequence_mask, chunks=n_segments, dim=1)
 
         memory = None
         normalization = None
 
+        # memory = prev_memory
+        # normalization = prev_normalization
+
         outputs = []
 
         # sequence_masks = []
@@ -389,18 +411,23 @@ def forward(
             local_attn_outputs = attn_outputs["attention_output"]
             query_states, key_states, value_states = attn_outputs["qkv_states"]
 
+            # if query_states.ndim == 3:
             query_states = rearrange(
                 query_states,
                 "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
                 batch_size=batch_size,
                 # n_heads=self.n_local_heads,
             )
+
+            # if key_states.ndim == 3:
             key_states = rearrange(
                 key_states,
                 "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
                 batch_size=batch_size,
                 # n_heads=self.n_local_heads,
             )
+
+            # if value_states.ndim == 3:
             value_states = rearrange(
                 value_states,
                 "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
@@ -408,7 +435,8 @@ def forward(
                 # n_heads=self.n_local_heads,
             )
 
-            # assert query_states.shape == (batch_size, self.n_local_heads, segment_length, self.d_head)
+            # NOTE: because in generation, the sequence length increases
+            # assert query_states.shape == (batch_size, self.n_local_q_heads, segment_length, self.d_qk)
             # assert query_states.shape == key_states.shape == value_states.shape
 
             retrieved_memory = self._retrieve_from_memory(
@@ -432,7 +460,7 @@ def forward(
 
             attention_output = global_weights * retrieved_memory + local_weights * local_attn_outputs
 
-            # assert attention_output.shape == (batch_size, self.n_local_heads, segment_length, self.d_head)
+            # assert attention_output.shape == (batch_size, self.n_local_q_heads, segment_length, self.d_qk)
 
             attention_output = rearrange(
                 attention_output, "batch_size n_heads seq_len d_head -> seq_len batch_size (n_heads d_head)"
@@ -440,11 +468,10 @@ def forward(
 
             output = self.o_proj(attention_output)
 
-            assert output.shape == (segment_length, batch_size, hidden_size)
+            # assert output.shape == (segment_length, batch_size, hidden_size)
 
             memory, normalization = self._update_memory(memory, normalization, key_states, value_states)
-            # memory = memory.detach()
-            # normalization = normalization.detach()
+            # memory = prev_memory if prev_memory is not None else 0.detach()
 
             outputs.append(output)
 
@@ -454,7 +481,12 @@ def forward(
 
         # sequence_masks = torch.cat(sequence_masks, dim=1)
         # assert sequence_masks.shape == sequence_mask.shape
-        return_outputs = {"hidden_states": outputs, "sequence_mask": sequence_mask}
+        return_outputs = {
+            "hidden_states": outputs,
+            "sequence_mask": sequence_mask,
+            "memory": memory,
+            "normalization": normalization,
+        }
         return return_outputs
 
     def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
@@ -476,15 +508,15 @@ def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
                 n=self.n_repeats,
             )
 
-        query_states = F.elu(query_states) + 1
+        sigma_query_states = F.elu(query_states) + 1
         retrieved_memory = einsum(
-            query_states,
+            sigma_query_states,
             prev_memory,
             "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
         )
 
         denominator = einsum(
-            query_states,
+            sigma_query_states,
             prev_normalization,
             "batch_size n_heads seq_length d_head, batch_size n_heads d_head -> batch_size n_heads seq_length",
         )
@@ -496,43 +528,40 @@ def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
         return retrieved_memory
 
     def _update_memory(self, prev_memory, prev_normalization, key_states, value_states):
-        TYPE = "delta"
-        key_states = F.elu(key_states) + 1
+        sigma_key_states = F.elu(key_states) + 1
 
-        if TYPE == "linear":
-            # memory = torch.matmul(key_states.transpose(-2, -1), value_states)
+        # if TYPE == "linear":
+        #     # memory = torch.matmul(key_states.transpose(-2, -1), value_states)
+        #     new_value_states = value_states
+        # else:
+        if prev_memory is None or prev_normalization is None:
             new_value_states = value_states
         else:
-            if prev_memory is None or prev_normalization is None:
-                new_value_states = value_states
-            else:
-                numerator = einsum(
-                    key_states,
-                    prev_memory,
-                    "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
-                )
+            numerator = einsum(
+                sigma_key_states,
+                prev_memory,
+                "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
+            )
 
-                # denominator = einsum(
-                #     key_states, prev_normalization,
-                #     "batch_size n_heads seq_len d_head, batch_size n_heads d_head -> batch_size seq_len"
-                # )
-                denominator = einsum(
-                    key_states,
-                    prev_normalization,
-                    "batch_size n_heads seq_length d_k, batch_size n_heads d_k -> batch_size n_heads seq_length",
-                )
-                denominator = rearrange(
-                    denominator, "batch_size n_heads seq_length -> batch_size n_heads seq_length 1"
-                )
+            # denominator = einsum(
+            #     key_states, prev_normalization,
+            #     "batch_size n_heads seq_len d_head, batch_size n_heads d_head -> batch_size seq_len"
+            # )
+            denominator = einsum(
+                sigma_key_states,
+                prev_normalization,
+                "batch_size n_heads seq_length d_k, batch_size n_heads d_k -> batch_size n_heads seq_length",
+            )
+            denominator = rearrange(denominator, "batch_size n_heads seq_length -> batch_size n_heads seq_length 1")
 
-                prev_v = numerator / denominator
-                new_value_states = value_states - prev_v
+            prev_v = numerator / denominator
+            new_value_states = value_states - prev_v
 
-        memory = torch.matmul(key_states.transpose(-2, -1), new_value_states)
+        memory = torch.matmul(sigma_key_states.transpose(-2, -1), new_value_states)
 
         # memory = einsum(key_states, value_states, 'batch_size n_heads k_length d_head, batch_size n_heads v_length d_head -> batch_size n_heads k_length v_length')
         normalization = reduce(
-            key_states, "batch_size n_heads seq_length d_head -> batch_size n_heads d_head", reduction="sum"
+            sigma_key_states, "batch_size n_heads seq_length d_head -> batch_size n_heads d_head", reduction="sum"
         )
 
         memory += prev_memory if prev_memory is not None else 0
@@ -832,11 +861,18 @@ def forward(
         self,
         hidden_states: Union[torch.Tensor, TensorPointer],
         sequence_mask: Union[torch.Tensor, TensorPointer],
+        memory: Optional[torch.Tensor] = None,
+        normalization: Optional[torch.Tensor] = None,
     ) -> Dict[str, Union[torch.Tensor, TensorPointer]]:
         residual = hidden_states
         hidden_states = self.input_layernorm(hidden_states)
 
-        output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
+        output = self.attn(
+            hidden_states=hidden_states,
+            sequence_mask=sequence_mask,
+            prev_memory=memory,
+            prev_normalization=normalization,
+        )
         hidden_states = output["hidden_states"]
         hidden_states = hidden_states + residual
 
@@ -848,6 +884,8 @@ def forward(
         return {
             "hidden_states": hidden_states,
             "sequence_mask": output["sequence_mask"],
+            "memory": output["memory"],
+            "normalization": output["normalization"],
         }
 
 
@@ -925,8 +963,8 @@ def __init__(
                         "tp_pg": parallel_context.tp_pg,
                         "layer_idx": layer_idx,
                     },
-                    module_input_keys={"hidden_states", "sequence_mask"},
-                    module_output_keys={"hidden_states", "sequence_mask"},
+                    module_input_keys={"hidden_states", "sequence_mask", "memory", "normalization"},
+                    module_output_keys={"hidden_states", "sequence_mask", "memory", "normalization"},
                 )
                 for layer_idx in range(config.num_hidden_layers)
             ]
@@ -984,6 +1022,8 @@ def forward_with_hidden_states(
         hidden_encoder_states = {
             "hidden_states": output["input_embeds"],
             "sequence_mask": input_mask,
+            "memory": None,
+            "normalization": None,
         }
         for encoder_block in self.decoder:
             hidden_encoder_states = encoder_block(**hidden_encoder_states)
diff --git a/src/nanotron/parallel/tensor_parallel/distributed_differentiable_primitives.py b/src/nanotron/parallel/tensor_parallel/distributed_differentiable_primitives.py
index 873d77df..7046d201 100644
--- a/src/nanotron/parallel/tensor_parallel/distributed_differentiable_primitives.py
+++ b/src/nanotron/parallel/tensor_parallel/distributed_differentiable_primitives.py
@@ -102,7 +102,9 @@ def forward(ctx, tensor, group: Optional[ProcessGroup]):
         unsharded_batch_size, *rest_size = tensor.shape
         if group is None:
             group = torch_dist.distributed_c10d._get_default_group()
-        assert unsharded_batch_size % group.size() == 0
+        assert (
+            unsharded_batch_size % group.size() == 0
+        ), f"Batch size {unsharded_batch_size} must be divisible by group size {group.size()}"
 
         # TODO @thomasw21: Collectives seem to require tensors to be contiguous
         # https://cs.github.com/pytorch/pytorch/blob/2b267fa7f28e18ca6ea1de4201d2541a40411457/torch/distributed/nn/functional.py#L305
diff --git a/src/nanotron/serialize/weights.py b/src/nanotron/serialize/weights.py
index 9b3e2b25..55c2b8cb 100644
--- a/src/nanotron/serialize/weights.py
+++ b/src/nanotron/serialize/weights.py
@@ -212,6 +212,13 @@ def load_weights(
     """
     param_root_folder = root_folder / "model"
 
+    log_rank(
+        f"Loading model weights from {param_root_folder}",
+        logger=logger,
+        level=logging.INFO,
+        rank=0,
+    )
+
     module_id_to_prefix = {id(module): f"{module_name}." for module_name, module in model.named_modules()}
     # Fix the root_model
     module_id_to_prefix[id(model)] = ""
@@ -366,6 +373,13 @@ def get_checkpoint_paths_list(
     """
     param_root_folder = root_folder / "model"
 
+    log_rank(
+        f"Loading model weights from {param_root_folder}",
+        logger=logger,
+        level=logging.INFO,
+        rank=0,
+    )
+
     module_id_to_prefix = {id(module): f"{module_name}." for module_name, module in model.named_modules()}
     # Fix the root_model
     module_id_to_prefix[id(model)] = ""

From 597ff44a5e7fb322b80c6622b4f5a6e38f07acfc Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Tue, 7 May 2024 11:43:56 +0000
Subject: [PATCH 11/43] noy apply pe to memory

---
 src/nanotron/models/llama.py | 66 +++++++++++++++++++++++-------------
 1 file changed, 42 insertions(+), 24 deletions(-)

diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 74cff8b9..8d5be32e 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -355,7 +355,9 @@ def __init__(
         # self.segment_lengths = 2048
 
         # NOTE: for sanity 200m training
-        self.segment_lengths = 256
+        # prev 16
+        # self.segment_lengths = 256
+        self.segment_lengths = 16
 
         device = self.o_proj.weight.device
         dtype = self.o_proj.weight.dtype
@@ -409,31 +411,32 @@ def forward(
             )
 
             local_attn_outputs = attn_outputs["attention_output"]
-            query_states, key_states, value_states = attn_outputs["qkv_states"]
-
-            # if query_states.ndim == 3:
-            query_states = rearrange(
-                query_states,
-                "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
-                batch_size=batch_size,
-                # n_heads=self.n_local_heads,
-            )
+            # query_states, key_states, value_states = attn_outputs["qkv_states"]
+            query_states, key_states, value_states = attn_outputs["qkv_states_without_pe"]
 
-            # if key_states.ndim == 3:
-            key_states = rearrange(
-                key_states,
-                "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
-                batch_size=batch_size,
-                # n_heads=self.n_local_heads,
-            )
+            if query_states.ndim == 3:
+                query_states = rearrange(
+                    query_states,
+                    "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
+                    batch_size=batch_size,
+                    # n_heads=self.n_local_heads,
+                )
 
-            # if value_states.ndim == 3:
-            value_states = rearrange(
-                value_states,
-                "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
-                batch_size=batch_size,
-                # n_heads=self.n_local_heads,
-            )
+            if key_states.ndim == 3:
+                key_states = rearrange(
+                    key_states,
+                    "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
+                    batch_size=batch_size,
+                    # n_heads=self.n_local_heads,
+                )
+
+            if value_states.ndim == 3:
+                value_states = rearrange(
+                    value_states,
+                    "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
+                    batch_size=batch_size,
+                    # n_heads=self.n_local_heads,
+                )
 
             # NOTE: because in generation, the sequence length increases
             # assert query_states.shape == (batch_size, self.n_local_q_heads, segment_length, self.d_qk)
@@ -613,6 +616,16 @@ def forward_with_hidden_states(
                 .contiguous()
             )  # [3, batch_size, seq_length, n_local_q_heads, d_qk]
 
+        query_states_without_pe = rearrange(
+            query_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
+        )
+        key_states_without_pe = rearrange(
+            key_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
+        )
+        value_states_without_pe = rearrange(
+            value_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
+        )
+
         store = self.get_local_store()
         if store is not None:  # Inference case
             # Double check that we use store only at inference time
@@ -824,6 +837,11 @@ def forward_with_hidden_states(
 
         return_outputs = {"hidden_states": None, "sequence_mask": sequence_mask}
         return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
+        return_outputs["qkv_states_without_pe"] = (
+            query_states_without_pe,
+            key_states_without_pe,
+            value_states_without_pe,
+        )
         return_outputs["attention_output"] = attention_output
         return return_outputs
 

From 2e74dd65d6e80871ba2ffec400e392b563b7da8d Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Tue, 7 May 2024 11:49:04 +0000
Subject: [PATCH 12/43] use this for exp19

---
 src/nanotron/models/llama.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 8d5be32e..06563b27 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -352,12 +352,12 @@ def __init__(
         # assert config.max_position_embeddings == 32768
 
         # NOTE: for 1b training
-        # self.segment_lengths = 2048
+        self.segment_lengths = 2048
 
         # NOTE: for sanity 200m training
         # prev 16
         # self.segment_lengths = 256
-        self.segment_lengths = 16
+        # self.segment_lengths = 16
 
         device = self.o_proj.weight.device
         dtype = self.o_proj.weight.dtype
@@ -381,8 +381,8 @@ def forward(
         prev_memory,
         prev_normalization,
     ):
-        if self.layer_idx == 4:
-            assert 1 == 1
+        # if self.layer_idx == 4:
+        #     assert 1 == 1
 
         batch_size = hidden_states.shape[1]
         seq_len = hidden_states.shape[0]

From e36ed8754a98d796e267bf4cf6be4cafe6772f5c Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Tue, 7 May 2024 11:53:08 +0000
Subject: [PATCH 13/43] use this for exp19

---
 src/nanotron/models/llama.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 06563b27..b3e3cd00 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -322,10 +322,10 @@ def __init__(
             contiguous_chunks=qkv_contiguous_chunks,
         )
         # TODO(kunhao): We want to have only one version per device and not one version per layer.
-        self.rotary_embedding = RotaryEmbedding(dim=self.d_qk, end=config.max_position_embeddings, theta=500000.0)
+        self.rotary_embedding = RotaryEmbedding(dim=self.d_qk, end=config.max_position_embeddings)
 
         # NOTE: Only supported for training (TODO(fmom): position_ids not supported yet)
-        self.flash_rotary_embedding = FlashRotaryEmbedding(dim=self.d_qk, interleaved=True, base=500000.0)
+        self.flash_rotary_embedding = FlashRotaryEmbedding(dim=self.d_qk, interleaved=True)
 
         self.o_proj = TensorParallelRowLinear(
             config.num_attention_heads * self.d_qk,

From 440e674ef1fd342fddb037671fa42666065c0460 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Tue, 14 May 2024 03:56:21 +0000
Subject: [PATCH 14/43] don't change the max positional encodings

---
 src/nanotron/trainer.py | 15 ++++++++-------
 1 file changed, 8 insertions(+), 7 deletions(-)

diff --git a/src/nanotron/trainer.py b/src/nanotron/trainer.py
index 9d83682b..bc26b582 100644
--- a/src/nanotron/trainer.py
+++ b/src/nanotron/trainer.py
@@ -643,13 +643,14 @@ def init_model(self) -> Union[NanotronModel, DistributedDataParallel]:
                     rank=0,
                 )
             else:
-                log_rank(
-                    f"Setting max_position_embeddings to {self.config.tokens.sequence_length}. Previous value was {self.model_config.max_position_embeddings}.",
-                    logger=logger,
-                    level=logging.INFO,
-                    rank=0,
-                )
-                self.model_config.max_position_embeddings = self.config.tokens.sequence_length
+                # log_rank(
+                #     f"Setting max_position_embeddings to {self.config.tokens.sequence_length}. Previous value was {self.model_config.max_position_embeddings}.",
+                #     logger=logger,
+                #     level=logging.INFO,
+                #     rank=0,
+                # )
+                # self.model_config.max_position_embeddings = self.config.tokens.sequence_length
+                pass
 
         log_rank("Config:\n" + pformat(self.config), logger=logger, level=logging.INFO, rank=0)
         log_rank("Model Config:\n" + pformat(self.model_config), logger=logger, level=logging.INFO, rank=0)

From 63cdce534c29e020e0c283953bc534df5328c6d7 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Tue, 14 May 2024 07:50:25 +0000
Subject: [PATCH 15/43] add generating training data

---
 .../infinite-context-length/generate_data.py  | 183 ++++++++++++++++++
 1 file changed, 183 insertions(+)
 create mode 100644 examples/infinite-context-length/generate_data.py

diff --git a/examples/infinite-context-length/generate_data.py b/examples/infinite-context-length/generate_data.py
new file mode 100644
index 00000000..282ae7d4
--- /dev/null
+++ b/examples/infinite-context-length/generate_data.py
@@ -0,0 +1,183 @@
+import glob
+import os
+import random
+import uuid
+
+import numpy as np
+from datasets import Dataset
+from transformers import AutoTokenizer
+
+PROMPT = "{} {}. \n\n{}"
+
+
+def token_length(tokenizer, text):
+    # Exclude EOS token
+    return len(tokenizer.encode(text))
+
+
+def read_context_files(tokenizer, soft_prompt, retrieval_question, target_cut_length):
+    context = ""
+    base_dir = os.path.abspath(os.path.dirname(__file__))
+    files = glob.glob(os.path.join(base_dir, haystack_dir, "*.txt"))
+    file_index = 0
+
+    # target_context_length = context_length - token_length(tokenizer, soft_prompt) - token_length(tokenizer, retrieval_question)
+
+    # while token_length(tokenizer, f"{soft_prompt} {context}. \n\n{retrieval_question}") < target_cut_length:
+    while token_length(tokenizer, PROMPT.format(soft_prompt, context, retrieval_question)) < target_cut_length:
+        with open(files[file_index], "r") as f:
+            content = f.read()
+            # Ensure the token length of the context does not exceed the target token length
+            # if token_length(tokenizer, f"{soft_prompt} {context + content}. \n\n{retrieval_question}") > target_cut_length:
+            if (
+                token_length(tokenizer, PROMPT.format(soft_prompt, context + content, retrieval_question))
+                > target_cut_length
+            ):
+                # truncated_content = content[:-(target_cut_length - token_length(tokenizer, f"{soft_prompt} {context}. \n\n{retrieval_question}"))]
+                truncated_content = content[
+                    : -(
+                        target_cut_length
+                        - token_length(tokenizer, PROMPT.format(soft_prompt, context, retrieval_question))
+                    )
+                ]
+                context += truncated_content
+            else:
+                context += content
+        file_index = (file_index + 1) % len(files)
+
+    return context
+
+
+def insert_needle(context, needle):
+    # Get the position to insert the needle
+    insertion_point = random.randint(0, len(context) - len(needle)) - 1
+
+    # Insert the needle at the appropriate position
+    new_context = context[:insertion_point] + needle + context[insertion_point:]
+
+    return new_context
+
+
+def insert_needle_with_depth(needle, context, depth_percent, target_cut_length, tokenizer):
+    content_ids = tokenizer.encode(context)
+    # content_length = len(content_ids)
+    needle_ids = tokenizer.encode(needle)
+
+    if depth_percent == 100:
+        # If depth percent is 100, place the needle at the end
+        # new_context = context[: len(context) - len(needle)] + needle
+        new_context_ids = content_ids[: len(content_ids) - len(needle_ids)] + needle_ids
+    else:
+        # Get the position to insert the needle
+        # insertion_point = int(context_length * (depth_percent / 100))
+        insertion_point = int(len(content_ids) * (depth_percent / 100))
+
+        # Find the nearest period to the insertion point
+        while context[insertion_point] != "." and insertion_point > 0:
+            insertion_point -= 1
+
+        # Insert the needle at the appropriate position
+        # new_context = context[:insertion_point] + needle + context[insertion_point:content_length]
+        new_context_ids = (
+            content_ids[:insertion_point]
+            + needle_ids
+            + content_ids[insertion_point : (target_cut_length - len(needle_ids))]
+        )
+
+    new_content = tokenizer.decode(new_context_ids)
+
+    return new_content
+
+
+def generate_needle_in_haystack_test(
+    needle, haystack_dir, soft_prompt: str, retrieval_question, context_length, depth_percent
+):
+    # Load up the haystack context
+    tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
+    # target_cut_length = context_length - token_length(tokenizer, soft_prompt) - token_length(tokenizer, retrieval_question)
+    # target_cut_length = context_length - token_length(tokenizer, f"{soft_prompt} 1. \n\n{retrieval_question}") - 1
+    target_cut_length = context_length - token_length(tokenizer, PROMPT.format(soft_prompt, 1, retrieval_question)) - 1
+
+    context = read_context_files(tokenizer, soft_prompt, retrieval_question, target_cut_length)
+
+    # Insert the needle into the context at the specified depth percent
+    # context_with_needle = insert_needle(context, needle)
+
+    context_with_needle = insert_needle_with_depth(needle, context, depth_percent, target_cut_length, tokenizer)
+
+    # Generate the prompt using the context with the needle
+    prompt = f"{soft_prompt} {context_with_needle}. \n\n{retrieval_question}"
+
+    assert needle in context_with_needle, f"depth_percent: {depth_percent}"
+    # assert abs(context_length - token_length(tokenizer, prompt)) <= 10
+    # assert context_length - token_length(tokenizer, prompt)
+
+    # remaining_tokens = context_length - token_length(tokenizer, prompt)
+    # NOTE: now add `.` to soft_prompt so that the token length is exactly equal to context_length
+    while (
+        token_length(tokenizer, PROMPT.format(soft_prompt, context_with_needle, retrieval_question)) < context_length
+    ):
+        soft_prompt += "."
+
+    prompt = PROMPT.format(soft_prompt, context_with_needle, retrieval_question)
+    assert (
+        token_length(tokenizer, prompt) == context_length
+    ), f"Token length: {token_length(tokenizer, prompt)}, Context length: {context_length}, depth_percent: {depth_percent}"
+
+    return prompt, needle
+
+
+if __name__ == "__main__":
+    haystack_dir = "./"
+
+    def generate_dataset():
+        num_prompts = 1
+        # soft_prompt = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there."
+        soft_prompt = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key."
+        context_lengths = [
+            32768,
+        ]
+        depth_percents = np.linspace(0, 100, num=21)
+
+        dataset_dict = {"id": [], "prompt": [], "answer": [], "context_length": [], "depth_percent": []}
+        generated_ids = set()
+        generated_pass_keys = set()
+
+        for context_length in context_lengths:
+            print(f"Generating prompts for context length: {context_length} \n")
+            for depth_percent in depth_percents:
+                for _ in range(num_prompts):
+                    while True:
+                        pass_key = random.randint(10000, 50000)
+                        if pass_key not in generated_pass_keys:
+                            generated_pass_keys.add(pass_key)
+                            break
+
+                    needle = f"The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
+                    retrieval_question = f"What is the pass key? The pass key is {pass_key}."
+
+                    prompt, _ = generate_needle_in_haystack_test(
+                        needle, haystack_dir, soft_prompt, retrieval_question, context_length, depth_percent
+                    )
+
+                    while True:
+                        text_id = str(uuid.uuid4())
+                        if text_id not in generated_ids:
+                            generated_ids.add(text_id)
+                            break
+
+                    dataset_dict["id"].append(text_id)
+                    dataset_dict["prompt"].append(prompt)
+                    dataset_dict["answer"].append(pass_key)
+                    dataset_dict["context_length"].append(context_length)
+                    dataset_dict["depth_percent"].append(depth_percent)
+
+        dataset = Dataset.from_dict(dataset_dict)
+        return dataset
+
+    # Generate the dataset
+    dataset = generate_dataset()
+
+    # Save the dataset to disk
+    dataset.save_to_disk("needle_in_a_hay_stack_eval_dataset")
+    dataset.push_to_hub("nanotron/needle_in_a_hay_stack_eval_dataset")

From f62e1a5d3569e797cea2db588e501c3337accb91 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Wed, 15 May 2024 03:45:09 +0000
Subject: [PATCH 16/43] generate finetuning data with a target context length

---
 .../infinite-context-length/generate_data.py  | 34 +++++++++++--------
 1 file changed, 20 insertions(+), 14 deletions(-)

diff --git a/examples/infinite-context-length/generate_data.py b/examples/infinite-context-length/generate_data.py
index 282ae7d4..ed7cf029 100644
--- a/examples/infinite-context-length/generate_data.py
+++ b/examples/infinite-context-length/generate_data.py
@@ -48,14 +48,14 @@ def read_context_files(tokenizer, soft_prompt, retrieval_question, target_cut_le
     return context
 
 
-def insert_needle(context, needle):
-    # Get the position to insert the needle
-    insertion_point = random.randint(0, len(context) - len(needle)) - 1
+# def insert_needle(context, needle):
+#     # Get the position to insert the needle
+#     insertion_point = random.randint(0, len(context) - len(needle)) - 1
 
-    # Insert the needle at the appropriate position
-    new_context = context[:insertion_point] + needle + context[insertion_point:]
+#     # Insert the needle at the appropriate position
+#     new_context = context[:insertion_point] + needle + context[insertion_point:]
 
-    return new_context
+#     return new_context
 
 
 def insert_needle_with_depth(needle, context, depth_percent, target_cut_length, tokenizer):
@@ -90,7 +90,7 @@ def insert_needle_with_depth(needle, context, depth_percent, target_cut_length,
 
 
 def generate_needle_in_haystack_test(
-    needle, haystack_dir, soft_prompt: str, retrieval_question, context_length, depth_percent
+    needle, needle_prompt, haystack_dir, soft_prompt: str, retrieval_question, context_length, depth_percent
 ):
     # Load up the haystack context
     tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
@@ -103,12 +103,12 @@ def generate_needle_in_haystack_test(
     # Insert the needle into the context at the specified depth percent
     # context_with_needle = insert_needle(context, needle)
 
-    context_with_needle = insert_needle_with_depth(needle, context, depth_percent, target_cut_length, tokenizer)
+    context_with_needle = insert_needle_with_depth(needle_prompt, context, depth_percent, target_cut_length, tokenizer)
 
     # Generate the prompt using the context with the needle
     prompt = f"{soft_prompt} {context_with_needle}. \n\n{retrieval_question}"
 
-    assert needle in context_with_needle, f"depth_percent: {depth_percent}"
+    assert str(needle) in context_with_needle, f"depth_percent: {depth_percent}"
     # assert abs(context_length - token_length(tokenizer, prompt)) <= 10
     # assert context_length - token_length(tokenizer, prompt)
 
@@ -124,7 +124,7 @@ def generate_needle_in_haystack_test(
         token_length(tokenizer, prompt) == context_length
     ), f"Token length: {token_length(tokenizer, prompt)}, Context length: {context_length}, depth_percent: {depth_percent}"
 
-    return prompt, needle
+    return prompt
 
 
 if __name__ == "__main__":
@@ -153,11 +153,17 @@ def generate_dataset():
                             generated_pass_keys.add(pass_key)
                             break
 
-                    needle = f"The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
+                    needle_prompt = f". The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
                     retrieval_question = f"What is the pass key? The pass key is {pass_key}."
 
-                    prompt, _ = generate_needle_in_haystack_test(
-                        needle, haystack_dir, soft_prompt, retrieval_question, context_length, depth_percent
+                    prompt = generate_needle_in_haystack_test(
+                        pass_key,
+                        needle_prompt,
+                        haystack_dir,
+                        soft_prompt,
+                        retrieval_question,
+                        context_length,
+                        depth_percent,
                     )
 
                     while True:
@@ -180,4 +186,4 @@ def generate_dataset():
 
     # Save the dataset to disk
     dataset.save_to_disk("needle_in_a_hay_stack_eval_dataset")
-    dataset.push_to_hub("nanotron/needle_in_a_hay_stack_eval_dataset")
+    dataset.push_to_hub("nanotron/needle_in_a_hay_stack_finetuning_dataset")

From b76c61c242a18e734ca07597858118d58f8561fe Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Thu, 16 May 2024 08:40:03 +0000
Subject: [PATCH 17/43] fix splitting sequence

---
 src/nanotron/models/llama.py | 123 +++++++++++++++++++++++++++++++++--
 1 file changed, 119 insertions(+), 4 deletions(-)

diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index b3e3cd00..dbda2d41 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -46,6 +46,33 @@
 logger = logging.get_logger(__name__)
 
 
+def compute_stas(tensor):
+    if tensor is None:
+        tensor = torch.zeros(
+            1,
+        )
+
+    return {
+        "mean": tensor.mean().item(),
+        "std": tensor.std().item(),
+        "var": tensor.var().item(),
+        "norm": tensor.norm().item(),
+        "min": tensor.min().item(),
+        "max": tensor.max().item(),
+        "amax": tensor.abs().max().item(),
+    }
+
+
+def convert_logs_to_flat_logs(logs, prefix):
+    flat_logs = {}
+    for module_name, components in logs.items():
+        for component_name, stats in components.items():
+            for stat_name, value in stats.items():
+                flat_logs[f"{prefix}:{module_name}:{component_name}:{stat_name}"] = value
+
+    return flat_logs
+
+
 class RotaryEmbedding(nn.Module):
     def __init__(self, dim: int, end: int, theta: float = 10000.0):
         super().__init__()
@@ -323,6 +350,7 @@ def __init__(
         )
         # TODO(kunhao): We want to have only one version per device and not one version per layer.
         self.rotary_embedding = RotaryEmbedding(dim=self.d_qk, end=config.max_position_embeddings)
+        # self.rotary_embedding = RotaryEmbedding(dim=self.d_qk, end=2048)
 
         # NOTE: Only supported for training (TODO(fmom): position_ids not supported yet)
         self.flash_rotary_embedding = FlashRotaryEmbedding(dim=self.d_qk, interleaved=True)
@@ -345,6 +373,7 @@ def __init__(
 
         self.prefill_kv_len = (
             config.max_position_embeddings
+            # 2048
         )  # TODO @nouamane: compute based on free memory, because in rope we can surpass max_position_embeddings
 
         # self.n_segments = 16
@@ -391,10 +420,24 @@ def forward(
         # segment_length = seq_len // self.n_segments
         # hidden_size = hidden_states.shape[2]
 
-        n_segments = seq_len // self.segment_lengths
+        if seq_len >= self.segment_lengths:
+            # n_segments = seq_len // self.segment_lengths
+            # segment_hidden_states = torch.chunk(hidden_states, chunks=n_segments, dim=0)
+            # segment_sequence_masks = torch.chunk(sequence_mask, chunks=n_segments, dim=1)
+
+            import math
 
-        segment_hidden_states = torch.chunk(hidden_states, chunks=n_segments, dim=0)
-        segment_sequence_masks = torch.chunk(sequence_mask, chunks=n_segments, dim=1)
+            n_segments = math.ceil(seq_len / self.segment_lengths)
+            segment_lengths = [self.segment_lengths] * (n_segments - 1) + [
+                seq_len - (n_segments - 1) * self.segment_lengths
+            ]
+            segment_hidden_states = torch.split(hidden_states, segment_lengths, dim=0)
+            # NOTE: assume that mask are all the same
+            # because we split across sequence length
+            segment_sequence_masks = torch.split(sequence_mask[:, :seq_len], segment_lengths, dim=1)
+        else:
+            segment_hidden_states = [hidden_states]
+            segment_sequence_masks = [sequence_mask]
 
         memory = None
         normalization = None
@@ -405,7 +448,14 @@ def forward(
         outputs = []
 
         # sequence_masks = []
+        idx = 0
+        # logs = {}
+
         for segment_hidden_state, segment_sequence_mask in zip(segment_hidden_states, segment_sequence_masks):
+            # if idx == 1:
+            #     memory = None
+            #     normalization = None
+
             attn_outputs = self.forward_with_hidden_states(
                 hidden_states=segment_hidden_state, sequence_mask=segment_sequence_mask, return_qkv_states=True
             )
@@ -414,6 +464,10 @@ def forward(
             # query_states, key_states, value_states = attn_outputs["qkv_states"]
             query_states, key_states, value_states = attn_outputs["qkv_states_without_pe"]
 
+            # logs[f"layer_{self.layer_idx}:seg_{idx}:query_states"] = compute_stas(query_states)
+            # logs[f"layer_{self.layer_idx}:seg_{idx}:key_states"] = compute_stas(key_states)
+            # logs[f"layer_{self.layer_idx}:seg_{idx}:value_states"] = compute_stas(value_states)
+
             if query_states.ndim == 3:
                 query_states = rearrange(
                     query_states,
@@ -445,6 +499,22 @@ def forward(
             retrieved_memory = self._retrieve_from_memory(
                 query_states, prev_memory=memory, prev_normalization=normalization
             )
+
+            # log_rank(
+            #     f"[idx={idx}] retrieved_memory.shape = {retrieved_memory.shape}, retrieve_memory is zero? {(retrieved_memory == 0).all()}",
+            #     logger=logger,
+            #     level=logging.INFO,
+            #     rank=0,
+            # )
+
+            # if memory is not None:
+            #     log_rank(
+            #         f"[idx={idx}] memory.shape = {memory.shape}, normalization.shape = {normalization.shape}",
+            #         logger=logger,
+            #         level=logging.INFO,
+            #         rank=0,
+            #     )
+
             # retrieved_memory = retrieved_memory.detach()
 
             local_attn_outputs = rearrange(
@@ -453,6 +523,13 @@ def forward(
                 d_head=self.d_qk,
             )
 
+            # log_rank(
+            #     f"[idx={idx}] local_attn_outputs.shape = {local_attn_outputs.shape}, local_attn_outputs is zero? {(local_attn_outputs == 0).all()}",
+            #     logger=logger,
+            #     level=logging.INFO,
+            #     rank=0,
+            # )
+
             global_weights = F.sigmoid(self.balance_factors)
             global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
 
@@ -461,7 +538,22 @@ def forward(
 
             # assert torch.allclose(global_weights + local_weights, torch.ones_like(global_weights))
 
+            # log_rank(
+            #     f"[idx={idx}] global_weights.shape = {global_weights.shape}, global_weights: {global_weights}",
+            #     logger=logger,
+            #     level=logging.INFO,
+            #     rank=0,
+            # )
+
+            # log_rank(
+            #     f"[idx={idx}] local_weights.shape = {local_weights.shape}, local_weights: {local_weights}",
+            #     logger=logger,
+            #     level=logging.INFO,
+            #     rank=0,
+            # )
+
             attention_output = global_weights * retrieved_memory + local_weights * local_attn_outputs
+            # attention_output = local_weights * local_attn_outputs
 
             # assert attention_output.shape == (batch_size, self.n_local_q_heads, segment_length, self.d_qk)
 
@@ -471,6 +563,15 @@ def forward(
 
             output = self.o_proj(attention_output)
 
+            # if dist.get_rank() == 0:
+            #     logs[f"layer_{self.layer_idx}:seg_{idx}:global_weights"] = compute_stas(global_weights)
+            #     logs[f"layer_{self.layer_idx}:seg_{idx}:local_weights"] = compute_stas(local_weights)
+            #     logs[f"layer_{self.layer_idx}:seg_{idx}:local_attn_outputs"] = compute_stas(local_attn_outputs)
+            #     logs[f"layer_{self.layer_idx}:seg_{idx}:retrieved_memory"] = compute_stas(retrieved_memory)
+            #     logs[f"layer_{self.layer_idx}:seg_{idx}:output"] = compute_stas(output)
+            #     logs[f"layer_{self.layer_idx}:seg_{idx}:memory"] = compute_stas(memory)
+            #     logs[f"layer_{self.layer_idx}:seg_{idx}:normalization"] = compute_stas(normalization)
+
             # assert output.shape == (segment_length, batch_size, hidden_size)
 
             memory, normalization = self._update_memory(memory, normalization, key_states, value_states)
@@ -478,10 +579,16 @@ def forward(
 
             outputs.append(output)
 
+            idx += 1
+
             # NOTE: update memory
         outputs = torch.cat(outputs, dim=0)  # concat along sequence dimension
         assert outputs.shape == hidden_states.shape
 
+        # if dist.get_rank() == 0:
+        #     logs[f"layer_{self.layer_idx}:outputs"] = compute_stas(outputs)
+        #     wandb.log(logs)
+
         # sequence_masks = torch.cat(sequence_masks, dim=1)
         # assert sequence_masks.shape == sequence_mask.shape
         return_outputs = {
@@ -494,9 +601,13 @@ def forward(
 
     def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
         # return torch.zeros_like(query_states)
-        if prev_memory is None:
+        if prev_memory is None or prev_normalization is None:
             return torch.zeros_like(query_states)
 
+        assert (prev_memory is None and prev_normalization is None) or (
+            prev_memory is not None and prev_normalization is not None
+        )
+
         if self.n_repeats > 1:
             from einops import repeat
 
@@ -531,6 +642,10 @@ def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
         return retrieved_memory
 
     def _update_memory(self, prev_memory, prev_normalization, key_states, value_states):
+        assert (prev_memory is None and prev_normalization is None) or (
+            prev_memory is not None and prev_normalization is not None
+        )
+
         sigma_key_states = F.elu(key_states) + 1
 
         # if TYPE == "linear":

From f2c1b91249eb84e61f8c630e964163106720dc6f Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Tue, 21 May 2024 08:16:28 +0000
Subject: [PATCH 18/43] add logging the internals of neural network

---
 src/nanotron/constants.py     |  11 ++-
 src/nanotron/debug/monitor.py | 140 ++++++++++++++++++++++++++++++++++
 src/nanotron/trainer.py       |  39 ++++++++--
 3 files changed, 180 insertions(+), 10 deletions(-)
 create mode 100644 src/nanotron/debug/monitor.py

diff --git a/src/nanotron/constants.py b/src/nanotron/constants.py
index e9a101c1..f06e3a4d 100644
--- a/src/nanotron/constants.py
+++ b/src/nanotron/constants.py
@@ -1,4 +1,5 @@
 import platform
+from typing import Optional
 
 from packaging.version import Version, parse
 
@@ -6,8 +7,12 @@
 
 PY_VERSION = parse(platform.python_version())
 
-OPTIMIZER_CONFIG_FILE_NAME = "optimizer_config.pt"
-OPTIMIZER_CKP_PATH = "{}/optimizer/optimizer_config.pt"
+# OPTIMIZER_CONFIG_FILE_NAME = "optimizer_config.json"
+OPTIMIZER_CKP_PATH = "{}/optimizer/optimizer_config.json"
 
 LR_SCHEDULER_CKP_PATH = "{}/lr_scheduler"
-METADATA_CKP_PATH = "{}.checkpoint_metadata.json"
+METADATA_CKP_PATH = "{}/checkpoint_metadata.json"
+
+NEEDLE = None
+
+GLOBAL_STEP: Optional[int] = None
diff --git a/src/nanotron/debug/monitor.py b/src/nanotron/debug/monitor.py
new file mode 100644
index 00000000..b8e12bbb
--- /dev/null
+++ b/src/nanotron/debug/monitor.py
@@ -0,0 +1,140 @@
+from typing import Dict, List, Tuple, Union
+
+import torch
+import torch.distributed as dist
+from nanotron.models.base import NanotronModel
+from nanotron.parallel import ParallelContext
+from torch import nn
+from torch.distributed import ReduceOp
+
+
+def track_weight_and_grad_stats(name: str, module: nn.Module, parallel_context: ParallelContext):
+    def compute_stas(tensors):
+        tensors = {"tensor": tensors} if not isinstance(tensors, dict) else tensors
+
+        # if isinstance(tensor, dict):
+        #     assert 1 == 1
+
+        stats = {}
+        for key, tensor in tensors.items():
+            stats[key] = {}
+            stats[key] = {
+                # "mean": tensor.mean().item(),
+                # "std": tensor.std().item(),
+                # "var": tensor.var().item(),
+                # "norm": tensor.norm().item(),
+                # "min": tensor.min().item(),
+                # "max": tensor.max().item(),
+                "amax": tensor.abs()
+                .max()
+                .item(),
+            }
+
+            # NOTE: now all reduce mean this across tp ranks
+            tp_group = parallel_context.tp_pg
+            for metric_name, metric_value in stats[key].items():
+
+                stats[key][metric_name] = torch.tensor(metric_value, device=tensor.device, dtype=tensor.dtype)
+
+                dist.all_reduce(stats[key][metric_name], op=ReduceOp.MAX, group=tp_group)
+
+                # if stats[key][metric_name].is_floating_point():
+                #     stats[key][metric_name] /= parallel_context.tensor_parallel_size
+
+        return stats
+
+    logs: Dict[str, Dict[str, float]] = {}
+
+    if name not in logs:
+        logs[name] = {}
+
+    def _save_output_stats(module: nn.Linear, input: torch.Tensor, output: torch.Tensor):
+        if hasattr(module, "weight") and module.weight is not None:
+            logs[name]["weight"] = compute_stas(module.weight.data)
+            # logging[name]["weight"] = _collect_stats(module.weight)
+
+        if hasattr(module, "bias") and module.bias is not None:
+            logs[name]["bias"] = compute_stas(module.bias)
+
+        inputs = input if isinstance(input, tuple) else (input,)
+        outputs = output if isinstance(output, tuple) else (output,)
+
+        if len(inputs) > 1:
+            for i, inp in enumerate(inputs):
+                if inp.dtype == torch.long:
+                    # NOTE: this is input ids in transformers
+                    continue
+                logs[name][f"input:{i}"] = compute_stas(inp)
+        elif len(inputs) == 1:
+            logs[name]["input"] = compute_stas(inputs[0])
+
+        if len(outputs) > 1:
+            for i, out in enumerate(outputs):
+                logs[name][f"output:{i}"] = compute_stas(out)
+        elif len(outputs) == 1:
+            logs[name]["output"] = compute_stas(outputs[0])
+
+    def _save_grad_stats(module: nn.Linear, grad_input, grad_output: torch.Tensor):
+        # import pydevd
+        # pydevd.settrace(suspend=False, trace_only_current_thread=True)
+        # logging[name][f"weight_grad"] = _collect_stats(module.weight.grad.orig_data)
+        # logging[name][f"bias_grad"] = _collect_stats(module.bias.grad)
+
+        if isinstance(grad_output, tuple):
+            for i, grad in enumerate(grad_output):
+                if grad is None:
+                    continue
+
+                logs[name][f"grad_output:{i}"] = compute_stas(grad)
+        else:
+            logs[name]["grad_output"] = compute_stas(grad_output)
+
+        if isinstance(grad_input, tuple):
+            for i, grad in enumerate(grad_input):
+                if grad is not None:
+                    logs[name][f"grad_input:{i}"] = compute_stas(grad)
+        else:
+            if grad_input is not None:
+                logs[name]["grad_input"] = compute_stas(grad_input)
+
+    handles = []
+    handles.append(module.register_forward_hook(_save_output_stats))
+    # module.register_full_backward_pre_hook(_save_grad_stats)
+    handles.append(module.register_backward_hook(_save_grad_stats))
+    return logs, handles
+    # module.register_module_full_backward_hook(_save_grad_stats)
+
+
+def monitor_nanotron_model(model: NanotronModel, parallel_context: ParallelContext):
+    def get_leaf_modules(module: nn.Module) -> List[Tuple[str, nn.Module]]:
+        """
+        Return all the leaf modules (modules without any child modules) in a PyTorch module.
+        """
+        leaf_modules = []
+        for n, m in module.named_modules():
+            if not list(m.children()):
+                leaf_modules.append((n, m))
+        return leaf_modules
+
+    logs = {}
+    handles = []
+    leaf_modules = get_leaf_modules(model)
+
+    for name, module in leaf_modules:
+        module_logs, module_handles = track_weight_and_grad_stats(name, module, parallel_context)
+        logs.update(module_logs)
+        handles.extend(module_handles)
+
+    return logs, handles
+
+
+def convert_logs_to_flat_logs(
+    logs: Dict[str, Dict[str, Dict[str, Union[torch.Tensor, float]]]]
+) -> Dict[str, Union[torch.Tensor, float]]:
+    flat_logs = {}
+    for module_name, components in logs.items():
+        for component_name, stats in components.items():
+            for metric_name, metric_value in stats.items():
+                flat_logs[f"{module_name}:{component_name}:{metric_name}"] = metric_value
+
+    return flat_logs
diff --git a/src/nanotron/trainer.py b/src/nanotron/trainer.py
index bc26b582..7f8a0c9e 100644
--- a/src/nanotron/trainer.py
+++ b/src/nanotron/trainer.py
@@ -36,6 +36,7 @@
 )
 from nanotron.constants import LR_SCHEDULER_CKP_PATH, METADATA_CKP_PATH, OPTIMIZER_CKP_PATH
 from nanotron.dataloader import sanity_check_dataloader
+from nanotron.debug.monitor import monitor_nanotron_model
 from nanotron.helpers import (
     _vocab_size_with_padding,
     get_profiler,
@@ -189,13 +190,26 @@ def __init__(
             # we might not have the optimizer state
             optim_ckp_path = OPTIMIZER_CKP_PATH.format(self.init_checkpoint_path)
             if os.path.exists(optim_ckp_path):
-                load_optimizer(
-                    optimizer=self.optimizer,
-                    parallel_context=self.parallel_context,
-                    root_folder=self.init_checkpoint_path,
-                    param_shard_metadata=self.param_shard_metadata,
-                    model=self.model,
-                )
+                # checkpoint_metadata = load_meta(
+                #     parallel_context=self.parallel_context, root_folder=self.init_checkpoint_path
+                # )
+
+                prev_config = get_config_from_file((self.init_checkpoint_path / "config.yaml").as_posix())
+                if (
+                    prev_config.optimizer.accumulate_grad_in_fp32 is False
+                    and self.config.optimizer.accumulate_grad_in_fp32 is True
+                ):
+                    # NOTE: if in the previous config, we didn't use fp32 accumulation
+                    # then we don't have the states for it, so we can't load it along with the optimizer
+                    pass
+                else:
+                    load_optimizer(
+                        optimizer=self.optimizer,
+                        parallel_context=self.parallel_context,
+                        root_folder=self.init_checkpoint_path,
+                        param_shard_metadata=self.param_shard_metadata,
+                        model=self.model,
+                    )
             else:
                 log_rank(
                     f"Can't find the optimizer state's checkpoint in {optim_ckp_path}, so we skip loading its checkpoint!",
@@ -258,6 +272,7 @@ def __init__(
 
         # Log where each module is instantiated
         self.unwrapped_model.log_modules(level=logging.DEBUG, group=self.parallel_context.world_pg, rank=0)
+        self.nn_logs, self.nn_handles = monitor_nanotron_model(self.unwrapped_model, self.parallel_context)
 
         self.micro_batch_size = self.config.tokens.micro_batch_size
         self.n_micro_batches_per_batch = self.config.tokens.batch_accumulation_per_replica
@@ -295,6 +310,7 @@ def pre_training(self, *args, **kwargs):
                 name=f"{current_time}_{self.config.general.run}",
                 config={"nanotron_config": self.config.as_dict()},
             )
+            # wandb.watch(self.model, log="all")
 
     def post_train_step(self):
         pass
@@ -411,6 +427,10 @@ def train(
         torch.cuda.empty_cache()
         with prof:
             for self.iteration_step in range(self.start_iteration_step + 1, self.config.tokens.train_steps + 1):
+                from nanotron import constants
+
+                constants.GLOBAL_STEP = self.iteration_step
+
                 if isinstance(prof, torch.profiler.profile):
                     prof.step()
 
@@ -622,6 +642,11 @@ def train_step_logs(
             else:
                 exit(0)
 
+        if dist.get_rank(self.parallel_context.world_pg) == self.logger_ranks[0] and wandb is not None:
+            from nanotron.debug.monitor import convert_logs_to_flat_logs
+
+            wandb.log({**convert_logs_to_flat_logs(self.nn_logs), "iteration_step": self.iteration_step})
+
     def init_model(self) -> Union[NanotronModel, DistributedDataParallel]:
         """Initialize the model and load weights from checkpoint if needed."""
         # TODO: add max_position_embeddings

From d1d54f155a203b5ae7d8d096315057dbf3ed0b4b Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Thu, 23 May 2024 12:15:39 +0000
Subject: [PATCH 19/43] add monitor

---
 src/nanotron/debug/monitor.py | 88 ++++++++++++++++++++++-------------
 1 file changed, 55 insertions(+), 33 deletions(-)

diff --git a/src/nanotron/debug/monitor.py b/src/nanotron/debug/monitor.py
index b8e12bbb..21921713 100644
--- a/src/nanotron/debug/monitor.py
+++ b/src/nanotron/debug/monitor.py
@@ -9,14 +9,17 @@
 
 
 def track_weight_and_grad_stats(name: str, module: nn.Module, parallel_context: ParallelContext):
-    def compute_stas(tensors):
+    def compute_stats(name, tensors):
         tensors = {"tensor": tensors} if not isinstance(tensors, dict) else tensors
-
-        # if isinstance(tensor, dict):
-        #     assert 1 == 1
-
         stats = {}
+
         for key, tensor in tensors.items():
+            if tensor.dtype == torch.long or tensor.dtype == torch.int or tensor.dtype == torch.bool:
+                continue
+
+            if tensor is None:
+                assert 1 == 1
+
             stats[key] = {}
             stats[key] = {
                 # "mean": tensor.mean().item(),
@@ -33,28 +36,38 @@ def compute_stas(tensors):
             # NOTE: now all reduce mean this across tp ranks
             tp_group = parallel_context.tp_pg
             for metric_name, metric_value in stats[key].items():
-
                 stats[key][metric_name] = torch.tensor(metric_value, device=tensor.device, dtype=tensor.dtype)
-
                 dist.all_reduce(stats[key][metric_name], op=ReduceOp.MAX, group=tp_group)
 
-                # if stats[key][metric_name].is_floating_point():
-                #     stats[key][metric_name] /= parallel_context.tensor_parallel_size
+            # tp_rank = dist.get_rank(group=tp_group)
+            # stats[key][f"data:tp_{tp_rank}"] = tensor.detach().cpu().tolist()
 
-        return stats
+        return stats[list(stats.keys())[0]] if len(stats) == 1 else stats
 
     logs: Dict[str, Dict[str, float]] = {}
 
     if name not in logs:
         logs[name] = {}
 
-    def _save_output_stats(module: nn.Linear, input: torch.Tensor, output: torch.Tensor):
-        if hasattr(module, "weight") and module.weight is not None:
-            logs[name]["weight"] = compute_stas(module.weight.data)
-            # logging[name]["weight"] = _collect_stats(module.weight)
+    def _save_output_stats(module: nn.Module, input: torch.Tensor, output: torch.Tensor):
+        param_names = [name for name, _ in module.named_parameters()]
+        for param_name in param_names:
+            if hasattr(module, param_name):
+                param = getattr(module, param_name)
+                stats = compute_stats(name, param.data)
+                if stats is not None:
+                    logs[name][param_name] = stats
+
+        # if hasattr(module, "weight") and module.weight is not None:
+        #     stats = compute_stats(name, module.weight.data)
+
+        #     if stats is not None:
+        #         logs[name]["weight"] = stats
 
-        if hasattr(module, "bias") and module.bias is not None:
-            logs[name]["bias"] = compute_stas(module.bias)
+        # if hasattr(module, "bias") and module.bias is not None:
+        #     stats = compute_stats(name, module.bias)
+        #     if stats is not None:
+        #         logs[name]["bias"] = stats
 
         inputs = input if isinstance(input, tuple) else (input,)
         outputs = output if isinstance(output, tuple) else (output,)
@@ -64,45 +77,53 @@ def _save_output_stats(module: nn.Linear, input: torch.Tensor, output: torch.Ten
                 if inp.dtype == torch.long:
                     # NOTE: this is input ids in transformers
                     continue
-                logs[name][f"input:{i}"] = compute_stas(inp)
+                stats = compute_stats(name, inp)
+                if stats is not None:
+                    logs[name][f"input:{i}"] = stats
         elif len(inputs) == 1:
-            logs[name]["input"] = compute_stas(inputs[0])
-
+            stats = compute_stats(name, inputs[0])
+            if stats is not None:
+                logs[name]["input"] = stats
         if len(outputs) > 1:
             for i, out in enumerate(outputs):
-                logs[name][f"output:{i}"] = compute_stas(out)
+                stats = compute_stats(name, out)
+                if stats is not None:
+                    logs[name][f"output:{i}"] = stats
         elif len(outputs) == 1:
-            logs[name]["output"] = compute_stas(outputs[0])
+            stats = compute_stats(name, outputs[0])
+            if stats is not None:
+                logs[name]["output"] = stats
 
     def _save_grad_stats(module: nn.Linear, grad_input, grad_output: torch.Tensor):
-        # import pydevd
-        # pydevd.settrace(suspend=False, trace_only_current_thread=True)
-        # logging[name][f"weight_grad"] = _collect_stats(module.weight.grad.orig_data)
-        # logging[name][f"bias_grad"] = _collect_stats(module.bias.grad)
-
         if isinstance(grad_output, tuple):
             for i, grad in enumerate(grad_output):
                 if grad is None:
                     continue
 
-                logs[name][f"grad_output:{i}"] = compute_stas(grad)
+                stats = compute_stats(name, grad)
+                if stats is not None:
+                    logs[name][f"grad_output:{i}"] = stats
         else:
-            logs[name]["grad_output"] = compute_stas(grad_output)
+            stats = compute_stats(name, grad_output)
+            if stats is not None:
+                logs[name]["grad_output"] = stats
 
         if isinstance(grad_input, tuple):
             for i, grad in enumerate(grad_input):
                 if grad is not None:
-                    logs[name][f"grad_input:{i}"] = compute_stas(grad)
+                    stats = compute_stats(name, grad)
+                    if stats is not None:
+                        logs[name][f"grad_input:{i}"] = stats
         else:
             if grad_input is not None:
-                logs[name]["grad_input"] = compute_stas(grad_input)
+                stats = compute_stats(name, grad_input)
+                if stats is not None:
+                    logs[name]["grad_input"] = stats
 
     handles = []
     handles.append(module.register_forward_hook(_save_output_stats))
-    # module.register_full_backward_pre_hook(_save_grad_stats)
     handles.append(module.register_backward_hook(_save_grad_stats))
     return logs, handles
-    # module.register_module_full_backward_hook(_save_grad_stats)
 
 
 def monitor_nanotron_model(model: NanotronModel, parallel_context: ParallelContext):
@@ -118,7 +139,8 @@ def get_leaf_modules(module: nn.Module) -> List[Tuple[str, nn.Module]]:
 
     logs = {}
     handles = []
-    leaf_modules = get_leaf_modules(model)
+    # leaf_modules = get_leaf_modules(model)
+    leaf_modules = [(name, module) for name, module in model.named_modules()]
 
     for name, module in leaf_modules:
         module_logs, module_handles = track_weight_and_grad_stats(name, module, parallel_context)

From c57a3e9d74a9ee79d78cc382c962d8b7c07cc006 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Sat, 25 May 2024 08:18:27 +0000
Subject: [PATCH 20/43] fix sequence splitting

---
 .gitignore                                    |   2 +
 .../infinite-context-length/generate_data.py  | 117 ++--
 .../infinite-context-length/generate_evals.py | 593 ++++++++++++++++++
 src/nanotron/generation/decode.py             |  21 +-
 src/nanotron/models/llama.py                  | 111 ++--
 src/nanotron/optim/gradient_accumulator.py    |   3 +
 .../parallel/pipeline_parallel/engine.py      |  28 +-
 src/nanotron/trainer.py                       |  17 +-
 8 files changed, 794 insertions(+), 98 deletions(-)
 create mode 100644 examples/infinite-context-length/generate_evals.py

diff --git a/.gitignore b/.gitignore
index cbc04eaf..985a3136 100644
--- a/.gitignore
+++ b/.gitignore
@@ -163,3 +163,5 @@ cython_debug/
 
 checkpoints/
 wandb/
+*.pkl
+examples/infinite-context-length/*.txt
diff --git a/examples/infinite-context-length/generate_data.py b/examples/infinite-context-length/generate_data.py
index ed7cf029..394f785d 100644
--- a/examples/infinite-context-length/generate_data.py
+++ b/examples/infinite-context-length/generate_data.py
@@ -1,9 +1,9 @@
+import argparse
 import glob
 import os
 import random
 import uuid
 
-import numpy as np
 from datasets import Dataset
 from transformers import AutoTokenizer
 
@@ -94,15 +94,11 @@ def generate_needle_in_haystack_test(
 ):
     # Load up the haystack context
     tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
-    # target_cut_length = context_length - token_length(tokenizer, soft_prompt) - token_length(tokenizer, retrieval_question)
-    # target_cut_length = context_length - token_length(tokenizer, f"{soft_prompt} 1. \n\n{retrieval_question}") - 1
     target_cut_length = context_length - token_length(tokenizer, PROMPT.format(soft_prompt, 1, retrieval_question)) - 1
 
     context = read_context_files(tokenizer, soft_prompt, retrieval_question, target_cut_length)
 
     # Insert the needle into the context at the specified depth percent
-    # context_with_needle = insert_needle(context, needle)
-
     context_with_needle = insert_needle_with_depth(needle_prompt, context, depth_percent, target_cut_length, tokenizer)
 
     # Generate the prompt using the context with the needle
@@ -127,56 +123,81 @@ def generate_needle_in_haystack_test(
     return prompt
 
 
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--context_length", type=int, required=True)
+    parser.add_argument("--depth_percent", type=int, required=True)
+    parser.add_argument("--id", type=int, required=True)
+    return parser.parse_args()
+
+
 if __name__ == "__main__":
+    args = get_args()
+
+    context_length = args.context_length
+    depth_percent = args.depth_percent
+    id = args.id
+
     haystack_dir = "./"
+    # NOTE: depth_percent + 1 to avoid 0
+    start_range = 1000 * (depth_percent + 1) * id
+    end_range = start_range + start_range
+
+    print(
+        f"Generating prompts for context length: {context_length} and depth percent: {depth_percent} and id: {id} \n"
+    )
+    print(f"start_range: {start_range}, end_range: {end_range} \n")
 
     def generate_dataset():
-        num_prompts = 1
+        # num_prompts = 1700
+        num_prompts = 100
         # soft_prompt = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there."
-        soft_prompt = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key."
-        context_lengths = [
-            32768,
-        ]
-        depth_percents = np.linspace(0, 100, num=21)
+        soft_prompt = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on."
+        # context_lengths = [
+        #     32768,
+        # ]
+        # depth_percents = np.linspace(0, 100, num=21)
 
         dataset_dict = {"id": [], "prompt": [], "answer": [], "context_length": [], "depth_percent": []}
         generated_ids = set()
         generated_pass_keys = set()
 
-        for context_length in context_lengths:
-            print(f"Generating prompts for context length: {context_length} \n")
-            for depth_percent in depth_percents:
-                for _ in range(num_prompts):
-                    while True:
-                        pass_key = random.randint(10000, 50000)
-                        if pass_key not in generated_pass_keys:
-                            generated_pass_keys.add(pass_key)
-                            break
-
-                    needle_prompt = f". The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
-                    retrieval_question = f"What is the pass key? The pass key is {pass_key}."
-
-                    prompt = generate_needle_in_haystack_test(
-                        pass_key,
-                        needle_prompt,
-                        haystack_dir,
-                        soft_prompt,
-                        retrieval_question,
-                        context_length,
-                        depth_percent,
-                    )
-
-                    while True:
-                        text_id = str(uuid.uuid4())
-                        if text_id not in generated_ids:
-                            generated_ids.add(text_id)
-                            break
-
-                    dataset_dict["id"].append(text_id)
-                    dataset_dict["prompt"].append(prompt)
-                    dataset_dict["answer"].append(pass_key)
-                    dataset_dict["context_length"].append(context_length)
-                    dataset_dict["depth_percent"].append(depth_percent)
+        # for context_length in context_lengths:
+        #     print(f"Generating prompts for context length: {context_length} \n")
+        #     for depth_percent in depth_percents:
+        for i in range(num_prompts):
+            print(f"generating prompt {i} \n")
+
+            while True:
+                pass_key = random.randint(start_range, end_range)
+                if pass_key not in generated_pass_keys:
+                    generated_pass_keys.add(pass_key)
+                    break
+
+            needle_prompt = f". The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
+            retrieval_question = f"What is the pass key? The pass key is {pass_key}."
+
+            prompt = generate_needle_in_haystack_test(
+                pass_key,
+                needle_prompt,
+                haystack_dir,
+                soft_prompt,
+                retrieval_question,
+                context_length,
+                depth_percent,
+            )
+
+            while True:
+                text_id = str(uuid.uuid4())
+                if text_id not in generated_ids:
+                    generated_ids.add(text_id)
+                    break
+
+            dataset_dict["id"].append(text_id)
+            dataset_dict["prompt"].append(prompt)
+            dataset_dict["answer"].append(pass_key)
+            dataset_dict["context_length"].append(context_length)
+            dataset_dict["depth_percent"].append(depth_percent)
 
         dataset = Dataset.from_dict(dataset_dict)
         return dataset
@@ -185,5 +206,7 @@ def generate_dataset():
     dataset = generate_dataset()
 
     # Save the dataset to disk
-    dataset.save_to_disk("needle_in_a_hay_stack_eval_dataset")
-    dataset.push_to_hub("nanotron/needle_in_a_hay_stack_finetuning_dataset")
+    dataset.save_to_disk(
+        f"/fsx/phuc/projects/nanotron/examples/infinite-context-length/needle_finetune_datasets/needle_finetuning_ctx_len_32768_and_depth_{depth_percent}_and_id_{id}"
+    )
+    # dataset.push_to_hub("nanotron/needle_in_a_hay_stack_finetuning_dataset")
diff --git a/examples/infinite-context-length/generate_evals.py b/examples/infinite-context-length/generate_evals.py
new file mode 100644
index 00000000..4286624d
--- /dev/null
+++ b/examples/infinite-context-length/generate_evals.py
@@ -0,0 +1,593 @@
+import glob
+import os
+
+
+def generate_needle_in_haystack_test(
+    needle, haystack_dir, soft_prompt: str, retrieval_question, context_length, depth_percent
+):
+    def read_context_files():
+        context = ""
+        base_dir = os.path.abspath(os.path.dirname(__file__))  # Package directory
+
+        while len(context) < context_length:
+            for file in glob.glob(os.path.join(base_dir, haystack_dir, "*.txt")):
+                with open(file, "r") as f:
+                    context += f.read()
+        return context
+
+    def insert_needle(context):
+        if depth_percent == 100:
+            # If depth percent is 100, place the needle at the end
+            new_context = context[: context_length - len(needle)] + needle
+        else:
+            # Get the position to insert the needle
+            insertion_point = int(context_length * (depth_percent / 100))
+
+            # Find the nearest period to the insertion point
+            while context[insertion_point] != "." and insertion_point > 0:
+                insertion_point -= 1
+
+            # Insert the needle at the appropriate position
+            new_context = context[:insertion_point] + needle + context[insertion_point:context_length]
+
+        return new_context
+
+    # Load up the haystack context
+    context = read_context_files()
+
+    # Truncate the context to the desired context length
+    context = context[:context_length]
+
+    # Insert the needle into the context at the specified depth percent
+    context_with_needle = insert_needle(context)
+
+    # Generate the prompt using the context with the needle
+    prompt = f"{soft_prompt} {context_with_needle} \n\n{retrieval_question}"
+
+    return prompt, needle
+
+
+# # Working example
+haystack_dir = "./"
+
+import random
+import uuid
+
+import numpy as np
+from datasets import Dataset
+
+
+def generate_dataset():
+    num_prompts = 100
+    soft_prompt = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there."
+    context_lengths = [
+        1024,
+        2048,
+        4096,
+        8192,
+        16384,
+        32768,
+        # 65536,
+        # 131072,
+        # 262144,
+        # 524288,
+        # 1048576,
+    ]
+    depth_percents = np.linspace(0, 100, num=21)
+
+    dataset_dict = {"id": [], "prompt": [], "answer": [], "context_length": [], "depth_percent": []}
+    generated_ids = set()
+
+    for context_length in context_lengths:
+        print(f"Generating prompts for context length: {context_length} \n")
+        for depth_percent in depth_percents:
+            for _ in range(num_prompts):
+                pass_key = random.randint(10000, 50000)
+                needle = f"The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
+                retrieval_question = "What is the pass key? The pass key is "
+
+                prompt, _ = generate_needle_in_haystack_test(
+                    needle, haystack_dir, soft_prompt, retrieval_question, context_length, depth_percent
+                )
+                # answer = f"The pass key is {pass_key}"
+
+                while True:
+                    text_id = str(uuid.uuid4())
+                    if text_id not in generated_ids:
+                        generated_ids.add(text_id)
+                        break
+
+                dataset_dict["id"].append(text_id)
+                dataset_dict["prompt"].append(prompt)
+                dataset_dict["answer"].append(pass_key)
+                dataset_dict["context_length"].append(context_length)
+                dataset_dict["depth_percent"].append(depth_percent)
+
+    dataset = Dataset.from_dict(dataset_dict)
+    return dataset
+
+
+# Generate the dataset
+dataset = generate_dataset()
+
+# Save the dataset to disk
+dataset.save_to_disk("needle_in_a_hay_stack_eval_dataset")
+dataset.push_to_hub("nanotron/needle_in_a_hay_stack_eval_dataset")
+
+
+############################################################################################################
+
+
+# import glob
+# import os
+# import random
+# import uuid
+
+# import numpy as np
+# from datasets import Dataset
+# from transformers import AutoTokenizer
+
+
+# if __name__ == "__main__":
+#     def generate_needle_in_haystack_test(
+#         needle, haystack_dir, soft_prompt: str, retrieval_question, context_length, depth_percent
+#     ):
+#         def read_context_files():
+#             context = ""
+#             base_dir = os.path.abspath(os.path.dirname(__file__))  # Package directory
+
+#             while len(tokenizer.encode(context)) < context_length:
+#                 for file in glob.glob(os.path.join(base_dir, haystack_dir, "*.txt")):
+#                     with open(file, "r") as f:
+#                         context += f.read()
+#             return context
+
+#         def insert_needle(context):
+#             if depth_percent == 100:
+#                 # If depth percent is 100, place the needle at the end
+#                 new_context = context[: context_length - len(tokenizer.encode(needle))] + needle
+#             else:
+#                 # Get the position to insert the needle
+#                 insertion_point = int(context_length * (depth_percent / 100))
+
+#                 # Find the nearest period to the insertion point
+#                 while context[insertion_point] != "." and insertion_point > 0:
+#                     insertion_point -= 1
+
+#                 # Insert the needle at the appropriate position
+#                 new_context = context[:insertion_point] + needle + context[insertion_point:context_length]
+
+#             return new_context
+
+#         # Load up the haystack context
+#         context = read_context_files()
+
+#         # Truncate the context to the desired context length
+#         context = tokenizer.decode(tokenizer.encode(context)[:context_length])
+
+#         # Insert the needle into the context at the specified depth percent
+#         context_with_needle = insert_needle(context)
+
+#         # Generate the prompt using the context with the needle
+#         prompt = f"{soft_prompt} {context_with_needle} \n\n{retrieval_question}"
+
+#         return prompt, needle
+
+#     # Working example
+#     haystack_dir = "./"
+
+#     # Load the tokenizer
+#     tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
+
+
+#     def generate_dataset():
+#         num_prompts = 1
+#         soft_prompt = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there."
+#         context_lengths = [
+#             # 1024,
+#             # 2048,
+#             # 4096,
+#             # 8192,
+#             # 16384,
+#             32768,
+#             # 65536,
+#             # 131072,
+#             # 262144,
+#             # 524288,
+#             # 1048576,
+#         ]
+#         depth_percents = np.linspace(0, 100, num=21)
+
+#         dataset_dict = {"id": [], "prompt": [], "answer": [], "context_length": [], "depth_percent": []}
+#         generated_ids = set()
+
+#         for context_length in context_lengths:
+#             print(f"Generating prompts for context length: {context_length} \n")
+#             for depth_percent in depth_percents:
+#                 for _ in range(num_prompts):
+#                     pass_key = random.randint(10000, 50000)
+#                     needle = f"The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
+#                     retrieval_question = f"What is the pass key? The pass key is "
+
+#                     prompt, _ = generate_needle_in_haystack_test(
+#                         needle, haystack_dir, soft_prompt, retrieval_question, context_length, depth_percent
+#                     )
+
+#                     while True:
+#                         text_id = str(uuid.uuid4())
+#                         if text_id not in generated_ids:
+#                             generated_ids.add(text_id)
+#                             break
+
+#                     dataset_dict["id"].append(text_id)
+#                     dataset_dict["prompt"].append(prompt)
+#                     dataset_dict["answer"].append(pass_key)
+#                     dataset_dict["context_length"].append(context_length)
+#                     dataset_dict["depth_percent"].append(depth_percent)
+
+#         dataset = Dataset.from_dict(dataset_dict)
+#         return dataset
+
+
+#     # Generate the dataset
+#     dataset = generate_dataset()
+
+#     # Save the dataset to disk
+#     dataset.save_to_disk("needle_in_a_hay_stack_finetuning_dataset")
+#     dataset.push_to_hub("nanotron/needle_in_a_hay_stack_finetuning_dataset")
+
+
+############################################################################################################
+
+# import glob
+# import os
+# import random
+# import uuid
+
+# import numpy as np
+# from datasets import Dataset
+# from transformers import AutoTokenizer
+
+# if __name__ == "__main__":
+#     def generate_needle_in_haystack_test(
+#         needle, haystack_dir, soft_prompt: str, retrieval_question, context_length, depth_percent
+#     ):
+#         def read_context_files():
+#             context = ""
+#             base_dir = os.path.abspath(os.path.dirname(__file__))  # Package directory
+#             files = glob.glob(os.path.join(base_dir, haystack_dir, "*.txt"))
+#             file_index = 0
+
+#             while len(tokenizer.encode(f"{soft_prompt} {context} {needle} \n\n{retrieval_question}")) < context_length:
+#                 with open(files[file_index], "r") as f:
+#                     context += f.read()
+#                 file_index = (file_index + 1) % len(files)
+
+#             return context
+
+#         def insert_needle(context):
+#             if depth_percent == 100:
+#                 # If depth percent is 100, place the needle at the end
+#                 new_context = context[: -len(needle)] + needle
+#             else:
+#                 # Get the position to insert the needle
+#                 insertion_point = int(len(context) * (depth_percent / 100))
+
+#                 # Find the nearest period to the insertion point
+#                 while context[insertion_point] != "." and insertion_point > 0:
+#                     insertion_point -= 1
+
+#                 # Insert the needle at the appropriate position
+#                 new_context = context[:insertion_point] + needle + context[insertion_point:]
+
+#             return new_context
+
+#         # Load up the haystack context
+#         context = read_context_files()
+
+#         # Insert the needle into the context at the specified depth percent
+#         context_with_needle = insert_needle(context)
+
+#         # Generate the prompt using the context with the needle
+#         prompt = f"{soft_prompt} {context_with_needle} \n\n{retrieval_question}"
+
+#         # Truncate the prompt to the desired context length
+#         prompt = tokenizer.decode(tokenizer.encode(prompt)[:context_length])
+
+#         return prompt, needle
+
+
+#     # Working example
+#     haystack_dir = "./"
+
+#     # Load the tokenizer
+#     tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
+
+
+#     def generate_dataset():
+#         num_prompts = 1
+#         soft_prompt = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there."
+#         context_lengths = [
+#             # 1024,
+#             # 2048,
+#             # 4096,
+#             # 8192,
+#             # 16384,
+#             32768,
+#             # 65536,
+#             # 131072,
+#             # 262144,
+#             # 524288,
+#             # 1048576,
+#         ]
+#         depth_percents = np.linspace(0, 100, num=21)
+
+#         dataset_dict = {"id": [], "prompt": [], "answer": [], "context_length": [], "depth_percent": []}
+#         generated_ids = set()
+
+#         for context_length in context_lengths:
+#             print(f"Generating prompts for context length: {context_length} \n")
+#             for depth_percent in depth_percents:
+#                 for _ in range(num_prompts):
+#                     pass_key = random.randint(10000, 50000)
+#                     needle = f"The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
+#                     retrieval_question = f"What is the pass key? The pass key is "
+
+#                     prompt, _ = generate_needle_in_haystack_test(
+#                         needle, haystack_dir, soft_prompt, retrieval_question, context_length, depth_percent
+#                     )
+
+#                     while True:
+#                         text_id = str(uuid.uuid4())
+#                         if text_id not in generated_ids:
+#                             generated_ids.add(text_id)
+#                             break
+
+#                     dataset_dict["id"].append(text_id)
+#                     dataset_dict["prompt"].append(prompt)
+#                     dataset_dict["answer"].append(pass_key)
+#                     dataset_dict["context_length"].append(context_length)
+#                     dataset_dict["depth_percent"].append(depth_percent)
+
+#         dataset = Dataset.from_dict(dataset_dict)
+#         return dataset
+
+
+#     # Generate the dataset
+#     dataset = generate_dataset()
+
+#     # Save the dataset to disk
+#     dataset.save_to_disk("needle_in_a_hay_stack_eval_dataset")
+#     dataset.push_to_hub("nanotron/needle_in_a_hay_stack_eval_dataset")
+
+
+# import glob
+# import os
+# import random
+# import uuid
+
+# import numpy as np
+# from datasets import Dataset
+# from transformers import AutoTokenizer
+
+# if __name__ == "__main__":
+#     def generate_needle_in_haystack_test(
+#         needle, haystack_dir, soft_prompt: str, retrieval_question, context_length, depth_percent
+#     ):
+#         def read_context_files():
+#             base_dir = os.path.abspath(os.path.dirname(__file__))  # Package directory
+#             files = glob.glob(os.path.join(base_dir, haystack_dir, "*.txt"))
+#             file_contents = []
+#             for file in files:
+#                 with open(file, "r") as f:
+#                     file_contents.append(f.read())
+#             return file_contents
+
+#         def insert_needle(context):
+#             if depth_percent == 100:
+#                 # If depth percent is 100, place the needle at the end
+#                 new_context = context[: -len(needle)] + needle
+#             else:
+#                 # Get the position to insert the needle
+#                 insertion_point = int(len(context) * (depth_percent / 100))
+
+#                 # Find the nearest period to the insertion point
+#                 while context[insertion_point] != "." and insertion_point > 0:
+#                     insertion_point -= 1
+
+#                 # Insert the needle at the appropriate position
+#                 new_context = context[:insertion_point] + needle + context[insertion_point:]
+
+#             return new_context
+
+#         # Load up the haystack context
+#         file_contents = read_context_files()
+#         context = "".join(file_contents)
+
+#         # Calculate the number of tokens for soft_prompt and retrieval_question
+#         soft_prompt_tokens = len(tokenizer.encode(soft_prompt))
+#         retrieval_question_tokens = len(tokenizer.encode(retrieval_question))
+
+#         # Calculate the remaining tokens for the context
+#         remaining_tokens = context_length - soft_prompt_tokens - retrieval_question_tokens
+
+#         # Repeat the context to make it long enough
+#         repeated_context = (context * ((remaining_tokens // len(tokenizer.encode(context))) + 1))[:remaining_tokens]
+
+#         # Insert the needle into the repeated context at the specified depth percent
+#         context_with_needle = insert_needle(repeated_context)
+
+#         # Generate the prompt using the context with the needle
+#         prompt = f"{soft_prompt} {context_with_needle} \n\n{retrieval_question}"
+
+#         return prompt, needle
+
+
+#     # Working example
+#     haystack_dir = "./"
+
+#     # Load the tokenizer
+#     tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
+
+
+#     def generate_dataset():
+#         num_prompts = 1
+#         soft_prompt = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there."
+#         context_lengths = [
+#             # 1024,
+#             # 2048,
+#             # 4096,
+#             # 8192,
+#             # 16384,
+#             32768,
+#             # 65536,
+#             # 131072,
+#             # 262144,
+#             # 524288,
+#             # 1048576,
+#         ]
+#         depth_percents = np.linspace(0, 100, num=21)
+
+#         dataset_dict = {"id": [], "prompt": [], "answer": [], "context_length": [], "depth_percent": []}
+#         generated_ids = set()
+
+#         for context_length in context_lengths:
+#             print(f"Generating prompts for context length: {context_length} \n")
+#             for depth_percent in depth_percents:
+#                 for _ in range(num_prompts):
+#                     pass_key = random.randint(10000, 50000)
+#                     needle = f"The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
+#                     retrieval_question = f"What is the pass key? The pass key is "
+
+#                     prompt, _ = generate_needle_in_haystack_test(
+#                         needle, haystack_dir, soft_prompt, retrieval_question, context_length, depth_percent
+#                     )
+
+#                     while True:
+#                         text_id = str(uuid.uuid4())
+#                         if text_id not in generated_ids:
+#                             generated_ids.add(text_id)
+#                             break
+
+#                     dataset_dict["id"].append(text_id)
+#                     dataset_dict["prompt"].append(prompt)
+#                     dataset_dict["answer"].append(pass_key)
+#                     dataset_dict["context_length"].append(context_length)
+#                     dataset_dict["depth_percent"].append(depth_percent)
+
+#         dataset = Dataset.from_dict(dataset_dict)
+#         return dataset
+
+
+#     # Generate the dataset
+#     dataset = generate_dataset()
+
+#     # Save the dataset to disk
+#     dataset.save_to_disk("needle_in_a_hay_stack_eval_dataset")
+#     dataset.push_to_hub("nanotron/needle_in_a_hay_stack_eval_dataset")
+
+import glob
+import os
+import random
+import uuid
+
+import numpy as np
+from datasets import Dataset
+from transformers import AutoTokenizer
+
+
+def token_length(tokenizer, text):
+    return len(tokenizer.encode(text)[:-1])  # -1 to exclude the EOS token
+
+
+def read_context_files(tokenizer, soft_prompt, retrieval_question, context_length):
+    context = ""
+    base_dir = os.path.abspath(os.path.dirname(__file__))
+    files = glob.glob(os.path.join(base_dir, haystack_dir, "*.txt"))
+    file_index = 0
+
+    target_context_length = (
+        context_length - token_length(tokenizer, soft_prompt) - token_length(tokenizer, retrieval_question)
+    )
+
+    while token_length(tokenizer, context) < target_context_length:
+        with open(files[file_index], "r") as f:
+            context += f.read()
+        file_index = (file_index + 1) % len(files)
+
+    return context
+
+
+def insert_needle(context, needle):
+    # Get the position to insert the needle
+    insertion_point = random.randint(0, len(context)) - len(needle)
+
+    # Insert the needle at the appropriate position
+    new_context = context[:insertion_point] + needle + context[insertion_point:]
+
+    return new_context
+
+
+def generate_needle_in_haystack_test(
+    needle, haystack_dir, soft_prompt: str, retrieval_question, context_length, depth_percent
+):
+    # Load up the haystack context
+    tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
+    context = read_context_files(tokenizer, soft_prompt, retrieval_question, context_length)
+
+    # Insert the needle into the context at the specified depth percent
+    context_with_needle = insert_needle(context, needle)
+
+    # Generate the prompt using the context with the needle
+    prompt = f"{soft_prompt} {context_with_needle} \n\n{retrieval_question}"
+
+    return prompt, needle
+
+
+if __name__ == "__main__":
+    haystack_dir = "./"
+
+    def generate_dataset():
+        num_prompts = 1
+        soft_prompt = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there."
+        context_lengths = [
+            32768,
+        ]
+        depth_percents = np.linspace(0, 100, num=21)
+
+        dataset_dict = {"id": [], "prompt": [], "answer": [], "context_length": [], "depth_percent": []}
+        generated_ids = set()
+
+        for context_length in context_lengths:
+            print(f"Generating prompts for context length: {context_length} \n")
+            for depth_percent in depth_percents:
+                for _ in range(num_prompts):
+                    pass_key = random.randint(10000, 50000)
+                    needle = f"The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
+                    retrieval_question = "What is the pass key? The pass key is "
+
+                    prompt, _ = generate_needle_in_haystack_test(
+                        needle, haystack_dir, soft_prompt, retrieval_question, context_length, depth_percent
+                    )
+
+                    while True:
+                        text_id = str(uuid.uuid4())
+                        if text_id not in generated_ids:
+                            generated_ids.add(text_id)
+                            break
+
+                    dataset_dict["id"].append(text_id)
+                    dataset_dict["prompt"].append(prompt)
+                    dataset_dict["answer"].append(pass_key)
+                    dataset_dict["context_length"].append(context_length)
+                    dataset_dict["depth_percent"].append(depth_percent)
+
+        dataset = Dataset.from_dict(dataset_dict)
+        return dataset
+
+    # Generate the dataset
+    dataset = generate_dataset()
+
+    # Save the dataset to disk
+    dataset.save_to_disk("needle_in_a_hay_stack_eval_dataset")
+    dataset.push_to_hub("nanotron/needle_in_a_hay_stack_eval_dataset")
diff --git a/src/nanotron/generation/decode.py b/src/nanotron/generation/decode.py
index 4b177805..4dfa3e18 100644
--- a/src/nanotron/generation/decode.py
+++ b/src/nanotron/generation/decode.py
@@ -134,7 +134,6 @@ def find_sequence_positions(tensor, sequence):
             # tokenizer.eos_token_id = 2
             # tokenizer.bos_token_id = 1
             # tokenizer.pad_token_id = tokenizer.eos_token_id
-
             encodings = tokenizer(
                 [elt.text for elt in micro_batch],
                 return_tensors="pt",
@@ -155,7 +154,27 @@ def find_sequence_positions(tensor, sequence):
             #     # pad_to_multiple_of=8
             # )
 
+            # TARGET_INPUT_IDS = tokenizer(["Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?"], return_tensors="pt")["input_ids"][0]
+            # LENGTH = TARGET_INPUT_IDS.shape[0]
             # assert encodings["input_ids"][0].shape[0] == 32768
+            encodings["input_ids"] = encodings["input_ids"][:, :2049]
+            encodings["attention_mask"] = encodings["attention_mask"][:, :2049]
+            # encodings["input_ids"][:, 2048-LENGTH:2048] = TARGET_INPUT_IDS
+
+            # import math
+            # seq_len = encodings["input_ids"].shape[1]
+            # segment_length = 2048
+
+            # n_segments = math.ceil(seq_len / segment_length)
+            # segment_lengths = [segment_length] * (n_segments - 1) + [seq_len - (n_segments - 1) * segment_length]
+            # xs_input_ids = torch.split(encodings["input_ids"][0], segment_lengths, dim=0)
+
+            # from nanotron.constants import NEEDLE
+            # last_segment_text = tokenizer.decode(xs_input_ids[-1])
+            # if str(NEEDLE) in last_segment_text:
+            #     print(f"{NEEDLE} is in the last segment")
+            # else:
+            #     print(f"can't find the needle {NEEDLE} in the last segment")
 
             encodings["attention_mask"] = encodings.attention_mask.to(dtype=torch.bool, device="cuda")
             encodings.to("cuda")
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index dbda2d41..5b559613 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -53,13 +53,15 @@ def compute_stas(tensor):
         )
 
     return {
-        "mean": tensor.mean().item(),
-        "std": tensor.std().item(),
-        "var": tensor.var().item(),
-        "norm": tensor.norm().item(),
-        "min": tensor.min().item(),
-        "max": tensor.max().item(),
-        "amax": tensor.abs().max().item(),
+        # "mean": tensor.mean().item(),
+        # "std": tensor.std().item(),
+        # "var": tensor.var().item(),
+        # "norm": tensor.norm().item(),
+        # "min": tensor.min().item(),
+        # "max": tensor.max().item(),
+        "amax": tensor.abs()
+        .max()
+        .item(),
     }
 
 
@@ -381,11 +383,12 @@ def __init__(
         # assert config.max_position_embeddings == 32768
 
         # NOTE: for 1b training
-        self.segment_lengths = 2048
+        # self.segment_lengths = 2048
+        # self.segment_lengths = 4096
 
         # NOTE: for sanity 200m training
         # prev 16
-        # self.segment_lengths = 256
+        self.segment_lengths = 256
         # self.segment_lengths = 16
 
         device = self.o_proj.weight.device
@@ -407,20 +410,24 @@ def forward(
         self,
         hidden_states: TensorType["sharded_seq_length", "batch_size", "hidden_size"],
         sequence_mask: TensorType["batch_size", "seq_length"],
-        prev_memory,
-        prev_normalization,
     ):
         # if self.layer_idx == 4:
         #     assert 1 == 1
 
-        batch_size = hidden_states.shape[1]
-        seq_len = hidden_states.shape[0]
+        # batch_size = hidden_states.shape[1]
+        # seq_len = hidden_states.shape[0]
+
+        batch_size = hidden_states.shape[0]
+        seq_len = hidden_states.shape[1]
+
+        assert seq_len == 1024
+
         # assert seq_len % self.n_segments == 0
 
         # segment_length = seq_len // self.n_segments
         # hidden_size = hidden_states.shape[2]
 
-        if seq_len >= self.segment_lengths:
+        if seq_len > self.segment_lengths:
             # n_segments = seq_len // self.segment_lengths
             # segment_hidden_states = torch.chunk(hidden_states, chunks=n_segments, dim=0)
             # segment_sequence_masks = torch.chunk(sequence_mask, chunks=n_segments, dim=1)
@@ -431,9 +438,15 @@ def forward(
             segment_lengths = [self.segment_lengths] * (n_segments - 1) + [
                 seq_len - (n_segments - 1) * self.segment_lengths
             ]
-            segment_hidden_states = torch.split(hidden_states, segment_lengths, dim=0)
+            assert sum(segment_lengths) == seq_len
+            # assert hidden_states.shape[0] == seq_len
+            assert hidden_states.shape[1] == seq_len
+            # segment_hidden_states = torch.split(hidden_states, segment_lengths, dim=0)
+            segment_hidden_states = torch.split(hidden_states, segment_lengths, dim=1)
             # NOTE: assume that mask are all the same
             # because we split across sequence length
+            # NOTE: take the assumption that all the masks are the same
+            assert torch.all(sequence_mask)
             segment_sequence_masks = torch.split(sequence_mask[:, :seq_len], segment_lengths, dim=1)
         else:
             segment_hidden_states = [hidden_states]
@@ -449,7 +462,7 @@ def forward(
 
         # sequence_masks = []
         idx = 0
-        # logs = {}
+        logs = {}
 
         for segment_hidden_state, segment_sequence_mask in zip(segment_hidden_states, segment_sequence_masks):
             # if idx == 1:
@@ -464,9 +477,9 @@ def forward(
             # query_states, key_states, value_states = attn_outputs["qkv_states"]
             query_states, key_states, value_states = attn_outputs["qkv_states_without_pe"]
 
-            # logs[f"layer_{self.layer_idx}:seg_{idx}:query_states"] = compute_stas(query_states)
-            # logs[f"layer_{self.layer_idx}:seg_{idx}:key_states"] = compute_stas(key_states)
-            # logs[f"layer_{self.layer_idx}:seg_{idx}:value_states"] = compute_stas(value_states)
+            logs[f"layer_{self.layer_idx}:seg_{idx}:query_states"] = compute_stas(query_states)
+            logs[f"layer_{self.layer_idx}:seg_{idx}:key_states"] = compute_stas(key_states)
+            logs[f"layer_{self.layer_idx}:seg_{idx}:value_states"] = compute_stas(value_states)
 
             if query_states.ndim == 3:
                 query_states = rearrange(
@@ -563,14 +576,14 @@ def forward(
 
             output = self.o_proj(attention_output)
 
-            # if dist.get_rank() == 0:
-            #     logs[f"layer_{self.layer_idx}:seg_{idx}:global_weights"] = compute_stas(global_weights)
-            #     logs[f"layer_{self.layer_idx}:seg_{idx}:local_weights"] = compute_stas(local_weights)
-            #     logs[f"layer_{self.layer_idx}:seg_{idx}:local_attn_outputs"] = compute_stas(local_attn_outputs)
-            #     logs[f"layer_{self.layer_idx}:seg_{idx}:retrieved_memory"] = compute_stas(retrieved_memory)
-            #     logs[f"layer_{self.layer_idx}:seg_{idx}:output"] = compute_stas(output)
-            #     logs[f"layer_{self.layer_idx}:seg_{idx}:memory"] = compute_stas(memory)
-            #     logs[f"layer_{self.layer_idx}:seg_{idx}:normalization"] = compute_stas(normalization)
+            if dist.get_rank() == 0:
+                logs[f"layer_{self.layer_idx}:seg_{idx}:global_weights"] = compute_stas(global_weights)
+                logs[f"layer_{self.layer_idx}:seg_{idx}:local_weights"] = compute_stas(local_weights)
+                logs[f"layer_{self.layer_idx}:seg_{idx}:local_attn_outputs"] = compute_stas(local_attn_outputs)
+                logs[f"layer_{self.layer_idx}:seg_{idx}:retrieved_memory"] = compute_stas(retrieved_memory)
+                logs[f"layer_{self.layer_idx}:seg_{idx}:output"] = compute_stas(output)
+                logs[f"layer_{self.layer_idx}:seg_{idx}:memory"] = compute_stas(memory)
+                logs[f"layer_{self.layer_idx}:seg_{idx}:normalization"] = compute_stas(normalization)
 
             # assert output.shape == (segment_length, batch_size, hidden_size)
 
@@ -578,24 +591,29 @@ def forward(
             # memory = prev_memory if prev_memory is not None else 0.detach()
 
             outputs.append(output)
+            # memory, normalization = memory.detach(), normalization.detach()
 
             idx += 1
 
             # NOTE: update memory
-        outputs = torch.cat(outputs, dim=0)  # concat along sequence dimension
+        # outputs = torch.cat(outputs, dim=0)  # concat along sequence dimension
+        outputs = torch.cat(outputs, dim=1)  # concat along sequence dimension
         assert outputs.shape == hidden_states.shape
 
-        # if dist.get_rank() == 0:
-        #     logs[f"layer_{self.layer_idx}:outputs"] = compute_stas(outputs)
-        #     wandb.log(logs)
+        if dist.get_rank() == 0:
+            import wandb
+            from nanotron import constants
+
+            logs[f"layer_{self.layer_idx}:outputs"] = compute_stas(outputs)
+            wandb.log({**logs, "iteration_step": constants.GLOBAL_STEP})
 
         # sequence_masks = torch.cat(sequence_masks, dim=1)
         # assert sequence_masks.shape == sequence_mask.shape
         return_outputs = {
             "hidden_states": outputs,
             "sequence_mask": sequence_mask,
-            "memory": memory,
-            "normalization": normalization,
+            # "memory": memory,
+            # "normalization": normalization,
         }
         return return_outputs
 
@@ -994,8 +1012,8 @@ def forward(
         self,
         hidden_states: Union[torch.Tensor, TensorPointer],
         sequence_mask: Union[torch.Tensor, TensorPointer],
-        memory: Optional[torch.Tensor] = None,
-        normalization: Optional[torch.Tensor] = None,
+        # memory: Optional[torch.Tensor] = None,
+        # normalization: Optional[torch.Tensor] = None,
     ) -> Dict[str, Union[torch.Tensor, TensorPointer]]:
         residual = hidden_states
         hidden_states = self.input_layernorm(hidden_states)
@@ -1003,8 +1021,8 @@ def forward(
         output = self.attn(
             hidden_states=hidden_states,
             sequence_mask=sequence_mask,
-            prev_memory=memory,
-            prev_normalization=normalization,
+            # prev_memory=memory,
+            # prev_normalization=normalization,
         )
         hidden_states = output["hidden_states"]
         hidden_states = hidden_states + residual
@@ -1017,8 +1035,8 @@ def forward(
         return {
             "hidden_states": hidden_states,
             "sequence_mask": output["sequence_mask"],
-            "memory": output["memory"],
-            "normalization": output["normalization"],
+            # "memory": output["memory"],
+            # "normalization": output["normalization"],
         }
 
 
@@ -1047,7 +1065,7 @@ def forward(self, input_ids: torch.Tensor, input_mask: torch.Tensor):  # [batch_
             store["past_length"] = past_length + cumsum_mask[:, -1]
 
         # Format input in `[seq_length, batch_size]` to support high TP with low batch_size
-        input_ids = input_ids.transpose(0, 1)
+        # input_ids = input_ids.transpose(0, 1)
         input_embeds = self.token_embedding(input_ids)
         return {"input_embeds": input_embeds}
 
@@ -1096,8 +1114,10 @@ def __init__(
                         "tp_pg": parallel_context.tp_pg,
                         "layer_idx": layer_idx,
                     },
-                    module_input_keys={"hidden_states", "sequence_mask", "memory", "normalization"},
-                    module_output_keys={"hidden_states", "sequence_mask", "memory", "normalization"},
+                    # module_input_keys={"hidden_states", "sequence_mask", "memory", "normalization"},
+                    # module_output_keys={"hidden_states", "sequence_mask", "memory", "normalization"},
+                    module_input_keys={"hidden_states", "sequence_mask"},
+                    module_output_keys={"hidden_states", "sequence_mask"},
                 )
                 for layer_idx in range(config.num_hidden_layers)
             ]
@@ -1155,8 +1175,8 @@ def forward_with_hidden_states(
         hidden_encoder_states = {
             "hidden_states": output["input_embeds"],
             "sequence_mask": input_mask,
-            "memory": None,
-            "normalization": None,
+            # "memory": None,
+            # "normalization": None,
         }
         for encoder_block in self.decoder:
             hidden_encoder_states = encoder_block(**hidden_encoder_states)
@@ -1227,6 +1247,9 @@ def forward(
         # Megatron by defaults cast everything in fp32. `--f16-lm-cross-entropy` is an option you can use to keep current precision.
         # https://github.com/NVIDIA/Megatron-LM/blob/f267e6186eae1d6e2055b412b00e2e545a8e896a/megatron/model/gpt_model.py#L38
 
+        # NOTE: because sharded_cross_entropy takes [seq_len, batch_size,...]
+        # so we have to transpose this
+        sharded_logits = sharded_logits.transpose(0, 1).contiguous()
         loss = sharded_cross_entropy(
             sharded_logits, label_ids.transpose(0, 1).contiguous(), group=self.tp_pg, dtype=torch.float
         ).transpose(0, 1)
diff --git a/src/nanotron/optim/gradient_accumulator.py b/src/nanotron/optim/gradient_accumulator.py
index 2e940744..38e3f6fc 100644
--- a/src/nanotron/optim/gradient_accumulator.py
+++ b/src/nanotron/optim/gradient_accumulator.py
@@ -211,6 +211,9 @@ def backward(self, loss: torch.Tensor):
 
     def _accumulate_grad(self, name: str, half_param: NanotronParameter) -> None:
         """Accumulate grad in fp32 and set the fp32 grad to the fp32 grad buffer, so that optimizer can update fp32 weights afterwards"""
+        # TODO(xrsrke): if we set accumulate_grad_in_fp32 to False,
+        # then if a parameter don't have grad, it doesn't raise what is the parameter name
+        # like here => add raise parameter name in accumulate_grad_in_fp32=False
         assert half_param.grad is not None, f"Expected param {name} to have gradient."
         fp32_grad = self.get_grad_buffer(name=name)
 
diff --git a/src/nanotron/parallel/pipeline_parallel/engine.py b/src/nanotron/parallel/pipeline_parallel/engine.py
index ca9df312..7ddabe25 100644
--- a/src/nanotron/parallel/pipeline_parallel/engine.py
+++ b/src/nanotron/parallel/pipeline_parallel/engine.py
@@ -2,6 +2,9 @@
 from typing import Dict, Iterable, Optional, Union
 
 import torch
+from torch import nn as torch_nn
+from torch.nn.parallel import DistributedDataParallel
+
 from nanotron import distributed as dist
 from nanotron import logging
 from nanotron.distributed import ProcessGroup
@@ -12,8 +15,6 @@
 from nanotron.parallel.pipeline_parallel.state import PipelineTrainBatchState
 from nanotron.parallel.pipeline_parallel.tensor_pointer import TensorPointer
 from nanotron.utils import ContextManagers
-from torch import nn as torch_nn
-from torch.nn.parallel import DistributedDataParallel
 
 logger = logging.get_logger(__name__)
 
@@ -222,6 +223,11 @@ def train_batch_iter(
 class OneForwardOneBackwardPipelineEngine(PipelineEngine):
     def __init__(self):
         super().__init__()
+        self.idx = 0
+
+        from transformers import AutoTokenizer
+
+        self.tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
 
     def train_batch_iter(
         self,
@@ -232,6 +238,9 @@ def train_batch_iter(
         grad_accumulator: Optional[GradientAccumulator],
     ) -> Iterable[Dict[str, Union[torch.Tensor, TensorPointer]]]:
         """Check https://arxiv.org/abs/2104.04473 for diagrams for the pipeline engine"""
+
+        self.idx += 1
+
         self.nb_microbatches = nb_microbatches
         assert (
             self.nb_microbatches >= pg.size() - 1
@@ -274,6 +283,21 @@ def train_batch_iter(
                 outputs.append(output)
 
             for micro_batch in batch:
+                if dist.get_rank() == 0:
+                    if self.idx == 1 or self.idx % 50 == 0:
+                        decoded_texts = self.tokenizer.batch_decode(micro_batch["input_ids"])
+
+                        with open(
+                            "/fsx/phuc/projects/nanotron/examples/infinite-context-length/configs/exp19/training_inputs.txt",
+                            "a",
+                        ) as file:
+                            # Write the self.idx number and the decoded text to the file
+                            file.write(f"idx: {self.idx}\n")
+
+                            for i, text in enumerate(decoded_texts):
+                                file.write(f"####### text_i = {i}\n")
+                                file.write(text + "\n\n\n")
+
                 context = self._get_fwd_context(model=model)
                 output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
 
diff --git a/src/nanotron/trainer.py b/src/nanotron/trainer.py
index 7f8a0c9e..5fa872f3 100644
--- a/src/nanotron/trainer.py
+++ b/src/nanotron/trainer.py
@@ -272,7 +272,6 @@ def __init__(
 
         # Log where each module is instantiated
         self.unwrapped_model.log_modules(level=logging.DEBUG, group=self.parallel_context.world_pg, rank=0)
-        self.nn_logs, self.nn_handles = monitor_nanotron_model(self.unwrapped_model, self.parallel_context)
 
         self.micro_batch_size = self.config.tokens.micro_batch_size
         self.n_micro_batches_per_batch = self.config.tokens.batch_accumulation_per_replica
@@ -434,6 +433,8 @@ def train(
                 if isinstance(prof, torch.profiler.profile):
                     prof.step()
 
+                nn_logs, nn_handles = monitor_nanotron_model(self.model, self.parallel_context)
+
                 self.iteration_start_time = time.time()
                 self._update_dataloader_based_on_training_stages(dataloader_or_dls)
 
@@ -446,6 +447,14 @@ def train(
                 if (self.iteration_step - 1) % self.config.logging.iteration_step_info_interval == 0:
                     self.train_step_logs(outputs=outputs, loss_avg=loss_avg)
 
+                if dist.get_rank(self.parallel_context.world_pg) == self.logger_ranks[0] and wandb is not None:
+                    from nanotron.debug.monitor import convert_logs_to_flat_logs
+
+                    wandb.log({**convert_logs_to_flat_logs(nn_logs), "iteration_step": self.iteration_step})
+
+                for handle in nn_handles:
+                    handle.remove()
+
                 # Checkpoint
                 if self.iteration_step % self.config.checkpoints.checkpoint_interval == 0:
                     self.save_checkpoint()
@@ -642,10 +651,10 @@ def train_step_logs(
             else:
                 exit(0)
 
-        if dist.get_rank(self.parallel_context.world_pg) == self.logger_ranks[0] and wandb is not None:
-            from nanotron.debug.monitor import convert_logs_to_flat_logs
+        # if dist.get_rank(self.parallel_context.world_pg) == self.logger_ranks[0] and wandb is not None:
+        #     from nanotron.debug.monitor import convert_logs_to_flat_logs
 
-            wandb.log({**convert_logs_to_flat_logs(self.nn_logs), "iteration_step": self.iteration_step})
+        #     wandb.log({**convert_logs_to_flat_logs(self.nn_logs), "iteration_step": self.iteration_step})
 
     def init_model(self) -> Union[NanotronModel, DistributedDataParallel]:
         """Initialize the model and load weights from checkpoint if needed."""

From 05c48b35950679c7e07b4d4adbfe0969641afad0 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Mon, 27 May 2024 08:30:51 +0000
Subject: [PATCH 21/43] fix decode for non-megatron-sp

---
 run_generate.py                   |  4 +++-
 src/nanotron/generation/decode.py | 37 +++++++++++++++++++++++++++++++
 2 files changed, 40 insertions(+), 1 deletion(-)

diff --git a/run_generate.py b/run_generate.py
index 0fcedaeb..c50dde94 100644
--- a/run_generate.py
+++ b/run_generate.py
@@ -176,8 +176,10 @@ def main():
             # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
             # "def fib(n)",
             # "This film was probably inspired by Godzilla",
+            # "Paris is the capital of",
             # END_PASSKEY,
-            PASSKEY_NINETY_PERCENT,
+            # PASSKEY_NINETY_PERCENT,
+            "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The grass is green. The sky is blue. The pass key is 2. Remember it. 2 is the pass key. What is the pass key? The pass key is ",
             # FINETUNE
         ]
 
diff --git a/src/nanotron/generation/decode.py b/src/nanotron/generation/decode.py
index 4dfa3e18..8e4bae94 100644
--- a/src/nanotron/generation/decode.py
+++ b/src/nanotron/generation/decode.py
@@ -315,6 +315,16 @@ def decode_text(
                             )
                     else:
                         if isinstance(state.new_input_ids, torch.Tensor):
+                            # if len(state.generation_ids) > 1:
+                            #     batch_generated_ids = torch.cat((state.generation_ids[0], state.generation_ids[1].squeeze().unsqueeze(dim=0)), dim=-1)
+                            # else:
+                            #     batch_generated_ids = torch.cat(state.generation_ids, dim=-1)
+
+                            # if len(state.generation_mask) > 1:
+                            #     batch_generated_mask = torch.cat((state.generation_mask[0], state.generation_mask[1].squeeze().unsqueeze(dim=0)), dim=-1)
+                            # else:
+                            #     batch_generated_mask = torch.cat(state.generation_mask, dim=-1)
+
                             batch_generated_ids = torch.cat(state.generation_ids, dim=-1)
                             batch_generated_mask = torch.cat(state.generation_mask, dim=-1)
                         else:
@@ -324,8 +334,13 @@ def decode_text(
                             input_ids=batch_generated_ids,
                             input_mask=batch_generated_mask,
                         )
+                        # sharded_logits = sharded_logits.transpose(0, 1)
+
+                        assert 1 == 1
 
                     if isinstance(sharded_logits, torch.Tensor) and logits_are_batch_first:
+                        # NOTE: consistent with megatron tp
+                        sharded_logits = sharded_logits.transpose(0, 1)
                         sharded_logits = sharded_logits.transpose(0, 1)
                     # Communicate
                     # TODO @thomasw21: Make a diagram to show how this works
@@ -500,6 +515,16 @@ def generator():
                     assert all(isinstance(elt, torch.Tensor) for elt in state.generation_ids)
                     batch_generated_ids = torch.cat(state.generation_ids, dim=-1)
                     batch_generated_mask = torch.cat(state.generation_mask, dim=-1)
+
+                    # if len(state.generation_ids) > 1:
+                    #     batch_generated_ids = torch.cat((state.generation_ids[0], state.generation_ids[1].squeeze().unsqueeze(dim=0)), dim=-1)
+                    # else:
+                    #     batch_generated_ids = torch.cat(state.generation_ids, dim=-1)
+
+                    # if len(state.generation_mask) > 1:
+                    #     batch_generated_mask = torch.cat((state.generation_mask[0], state.generation_mask[1].squeeze().unsqueeze(dim=0)), dim=-1)
+                    # else:
+                    #     batch_generated_mask = torch.cat(state.generation_mask, dim=-1)
                 else:
                     assert all(isinstance(elt, TensorPointer) for elt in state.generation_ids)
                     batch_generated_ids = TensorPointer(group_rank=decoder_input_rank)
@@ -634,6 +659,8 @@ def decode_tokenized(
                             input_mask=state.new_input_mask,
                         )
                         if isinstance(sharded_logits, torch.Tensor):
+                            # NOTE: consistent with megatron tp
+                            sharded_logits = sharded_logits.transpose(0, 1)
                             sharded_logits = sharded_logits.transpose(0, 1)
 
                     # Communicate
@@ -781,6 +808,16 @@ def generator():
                     assert all(isinstance(elt, torch.Tensor) for elt in state.generation_ids)
                     batch_generated_ids = torch.cat(state.generation_ids, dim=-1)
                     batch_generated_mask = torch.cat(state.generation_mask, dim=-1)
+
+                    # if len(state.generation_ids) > 1:
+                    #     batch_generated_ids = torch.cat((state.generation_ids[0], state.generation_ids[1].squeeze().unsqueeze(dim=0)), dim=-1)
+                    # else:
+                    #     batch_generated_ids = torch.cat(state.generation_ids, dim=-1)
+
+                    # if len(state.generation_mask) > 1:
+                    #     batch_generated_mask = torch.cat((state.generation_mask[0], state.generation_mask[1].squeeze().unsqueeze(dim=0)), dim=-1)
+                    # else:
+                    #     batch_generated_mask = torch.cat(state.generation_mask, dim=-1)
                 else:
                     assert all(isinstance(elt, TensorPointer) for elt in state.generation_ids)
                     batch_generated_ids = TensorPointer(group_rank=decoder_input_rank)

From f3a39b14fbe67009f8f5225e3ef6e6b1d5014be5 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Mon, 27 May 2024 08:46:19 +0000
Subject: [PATCH 22/43] backup with new sp splitting, but wrong reduction
 dimension in infini attention

---
 src/nanotron/models/llama.py | 65 ++++++++++++++++++------------------
 1 file changed, 33 insertions(+), 32 deletions(-)

diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 5b559613..561c2903 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -19,8 +19,8 @@
 import torch
 from torch import nn
 
+from nanotron import constants, logging
 from nanotron import distributed as dist
-from nanotron import logging
 from nanotron.config import Config, LlamaConfig, ParallelismArgs
 from nanotron.config.models_config import RandomInit, SpectralMupInit
 from nanotron.generation.generate_store import AttachableStore
@@ -59,7 +59,9 @@ def compute_stas(tensor):
         # "norm": tensor.norm().item(),
         # "min": tensor.min().item(),
         # "max": tensor.max().item(),
-        "amax": tensor.abs()
+        "amax": tensor.detach()
+        .cpu()
+        .abs()
         .max()
         .item(),
     }
@@ -352,6 +354,12 @@ def __init__(
         )
         # TODO(kunhao): We want to have only one version per device and not one version per layer.
         self.rotary_embedding = RotaryEmbedding(dim=self.d_qk, end=config.max_position_embeddings)
+        log_rank(
+            f"self.rotary_embedding.end is {self.rotary_embedding.end}",
+            logger=logger,
+            level=logging.INFO,
+            rank=0,
+        )
         # self.rotary_embedding = RotaryEmbedding(dim=self.d_qk, end=2048)
 
         # NOTE: Only supported for training (TODO(fmom): position_ids not supported yet)
@@ -383,12 +391,12 @@ def __init__(
         # assert config.max_position_embeddings == 32768
 
         # NOTE: for 1b training
-        # self.segment_lengths = 2048
+        self.segment_lengths = 2048
         # self.segment_lengths = 4096
 
         # NOTE: for sanity 200m training
         # prev 16
-        self.segment_lengths = 256
+        # self.segment_lengths = 256
         # self.segment_lengths = 16
 
         device = self.o_proj.weight.device
@@ -420,7 +428,8 @@ def forward(
         batch_size = hidden_states.shape[0]
         seq_len = hidden_states.shape[1]
 
-        assert seq_len == 1024
+        # assert seq_len == 1024
+        # assert seq_len == 32768
 
         # assert seq_len % self.n_segments == 0
 
@@ -477,10 +486,6 @@ def forward(
             # query_states, key_states, value_states = attn_outputs["qkv_states"]
             query_states, key_states, value_states = attn_outputs["qkv_states_without_pe"]
 
-            logs[f"layer_{self.layer_idx}:seg_{idx}:query_states"] = compute_stas(query_states)
-            logs[f"layer_{self.layer_idx}:seg_{idx}:key_states"] = compute_stas(key_states)
-            logs[f"layer_{self.layer_idx}:seg_{idx}:value_states"] = compute_stas(value_states)
-
             if query_states.ndim == 3:
                 query_states = rearrange(
                     query_states,
@@ -576,14 +581,20 @@ def forward(
 
             output = self.o_proj(attention_output)
 
-            if dist.get_rank() == 0:
-                logs[f"layer_{self.layer_idx}:seg_{idx}:global_weights"] = compute_stas(global_weights)
-                logs[f"layer_{self.layer_idx}:seg_{idx}:local_weights"] = compute_stas(local_weights)
-                logs[f"layer_{self.layer_idx}:seg_{idx}:local_attn_outputs"] = compute_stas(local_attn_outputs)
-                logs[f"layer_{self.layer_idx}:seg_{idx}:retrieved_memory"] = compute_stas(retrieved_memory)
-                logs[f"layer_{self.layer_idx}:seg_{idx}:output"] = compute_stas(output)
-                logs[f"layer_{self.layer_idx}:seg_{idx}:memory"] = compute_stas(memory)
-                logs[f"layer_{self.layer_idx}:seg_{idx}:normalization"] = compute_stas(normalization)
+            if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % 50 == 0:
+                if dist.get_rank() == 0:
+                    logs[f"layer_{self.layer_idx}:seg_{idx}:query_states"] = compute_stas(query_states)
+                    logs[f"layer_{self.layer_idx}:seg_{idx}:key_states"] = compute_stas(key_states)
+                    logs[f"layer_{self.layer_idx}:seg_{idx}:value_states"] = compute_stas(value_states)
+
+                    logs[f"layer_{self.layer_idx}:seg_{idx}:global_weights"] = compute_stas(global_weights)
+                    logs[f"layer_{self.layer_idx}:seg_{idx}:local_weights"] = compute_stas(local_weights)
+                    logs[f"layer_{self.layer_idx}:seg_{idx}:local_attn_outputs"] = compute_stas(local_attn_outputs)
+                    logs[f"layer_{self.layer_idx}:seg_{idx}:retrieved_memory"] = compute_stas(retrieved_memory)
+                    logs[f"layer_{self.layer_idx}:seg_{idx}:attention_output"] = compute_stas(attention_output)
+                    logs[f"layer_{self.layer_idx}:seg_{idx}:output"] = compute_stas(output)
+                    logs[f"layer_{self.layer_idx}:seg_{idx}:memory"] = compute_stas(memory)
+                    logs[f"layer_{self.layer_idx}:seg_{idx}:normalization"] = compute_stas(normalization)
 
             # assert output.shape == (segment_length, batch_size, hidden_size)
 
@@ -600,12 +611,12 @@ def forward(
         outputs = torch.cat(outputs, dim=1)  # concat along sequence dimension
         assert outputs.shape == hidden_states.shape
 
-        if dist.get_rank() == 0:
-            import wandb
-            from nanotron import constants
+        if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % 50 == 0:
+            if dist.get_rank() == 0:
+                import wandb
 
-            logs[f"layer_{self.layer_idx}:outputs"] = compute_stas(outputs)
-            wandb.log({**logs, "iteration_step": constants.GLOBAL_STEP})
+                logs[f"layer_{self.layer_idx}:outputs"] = compute_stas(outputs)
+                wandb.log({**logs, "iteration_step": constants.GLOBAL_STEP})
 
         # sequence_masks = torch.cat(sequence_masks, dim=1)
         # assert sequence_masks.shape == sequence_mask.shape
@@ -666,10 +677,6 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
 
         sigma_key_states = F.elu(key_states) + 1
 
-        # if TYPE == "linear":
-        #     # memory = torch.matmul(key_states.transpose(-2, -1), value_states)
-        #     new_value_states = value_states
-        # else:
         if prev_memory is None or prev_normalization is None:
             new_value_states = value_states
         else:
@@ -678,11 +685,6 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
                 prev_memory,
                 "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
             )
-
-            # denominator = einsum(
-            #     key_states, prev_normalization,
-            #     "batch_size n_heads seq_len d_head, batch_size n_heads d_head -> batch_size seq_len"
-            # )
             denominator = einsum(
                 sigma_key_states,
                 prev_normalization,
@@ -695,7 +697,6 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
 
         memory = torch.matmul(sigma_key_states.transpose(-2, -1), new_value_states)
 
-        # memory = einsum(key_states, value_states, 'batch_size n_heads k_length d_head, batch_size n_heads v_length d_head -> batch_size n_heads k_length v_length')
         normalization = reduce(
             sigma_key_states, "batch_size n_heads seq_length d_head -> batch_size n_heads d_head", reduction="sum"
         )

From b1deec54a4773461feb3f5100f6844ad77571d0f Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Wed, 29 May 2024 03:55:29 +0000
Subject: [PATCH 23/43] backup

---
 src/nanotron/constants.py                     |   2 +
 src/nanotron/debug/monitor.py                 |   6 +-
 src/nanotron/models/llama.py                  | 958 ++++++++++++++++--
 .../parallel/pipeline_parallel/engine.py      |  33 +-
 src/nanotron/trainer.py                       |  34 +-
 5 files changed, 919 insertions(+), 114 deletions(-)

diff --git a/src/nanotron/constants.py b/src/nanotron/constants.py
index f06e3a4d..7ba33101 100644
--- a/src/nanotron/constants.py
+++ b/src/nanotron/constants.py
@@ -16,3 +16,5 @@
 NEEDLE = None
 
 GLOBAL_STEP: Optional[int] = None
+LOG_STATE_INTERVAL = 500
+CONFIG = None
diff --git a/src/nanotron/debug/monitor.py b/src/nanotron/debug/monitor.py
index 21921713..184fe9fe 100644
--- a/src/nanotron/debug/monitor.py
+++ b/src/nanotron/debug/monitor.py
@@ -22,15 +22,13 @@ def compute_stats(name, tensors):
 
             stats[key] = {}
             stats[key] = {
-                # "mean": tensor.mean().item(),
+                "mean": tensor.mean().item(),
                 # "std": tensor.std().item(),
                 # "var": tensor.var().item(),
                 # "norm": tensor.norm().item(),
                 # "min": tensor.min().item(),
                 # "max": tensor.max().item(),
-                "amax": tensor.abs()
-                .max()
-                .item(),
+                "amax": tensor.abs().max().item(),
             }
 
             # NOTE: now all reduce mean this across tp ranks
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 561c2903..4063627a 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -53,17 +53,13 @@ def compute_stas(tensor):
         )
 
     return {
-        # "mean": tensor.mean().item(),
+        "mean": tensor.mean().item(),
         # "std": tensor.std().item(),
         # "var": tensor.var().item(),
         # "norm": tensor.norm().item(),
         # "min": tensor.min().item(),
         # "max": tensor.max().item(),
-        "amax": tensor.detach()
-        .cpu()
-        .abs()
-        .max()
-        .item(),
+        "amax": tensor.detach().cpu().abs().max().item(),
     }
 
 
@@ -116,13 +112,13 @@ def init_rotary_embeddings(self):
 
     def forward(
         self,
-        x: torch.Tensor,  # [batch_size, seq_length, num_heads, d_qk]
-        position_ids: Optional[torch.LongTensor],  # [batch_size, seq_length]
+        x: torch.Tensor,  # [batch_size, seq_len, num_heads, d_qk]
+        position_ids: Optional[torch.LongTensor],  # [batch_size, seq_len]
     ):
-        batch_size, seq_length, num_heads, inner_dim = x.shape
+        batch_size, seq_len, num_heads, inner_dim = x.shape
         while (
             position_ids is not None and position_ids[-1, -1] >= self.end
-        ) or seq_length >= self.end:  # TODO @nouamane: check if this causes cpu-gpu sync
+        ) or seq_len >= self.end:  # TODO @nouamane: check if this causes cpu-gpu sync
             self.end *= 2
             self._initialized_buffer = False
         if self._initialized_buffer is False:
@@ -130,21 +126,19 @@ def forward(
             self.init_rotary_embeddings()
         dtype = x.dtype
         assert inner_dim % 2 == 0
-        x = x.view(
-            batch_size, seq_length, num_heads, inner_dim // 2, 2
-        )  # [batch_size, q_length, num_heads, inner_dim]
+        x = x.view(batch_size, seq_len, num_heads, inner_dim // 2, 2)  # [batch_size, q_length, num_heads, inner_dim]
         if x.dtype == torch.bfloat16:
             x = x.float()
         complex_x = torch.view_as_complex(x)  # [batch_size, q_length, num_heads, inner_dim // 2]
         if position_ids is None:
-            freqs_cis = self.freqs_cis[None, :seq_length, None, :]
+            freqs_cis = self.freqs_cis[None, :seq_len, None, :]
         else:
             # TODO(kunhao): Should None follow the num_heads dimension?
             if position_ids[-1, -1] < 0 or position_ids[-1, -1] >= self.end:  # Quick test hopefully
                 raise ValueError(f"Position ids must be in the range [0, {self.end}), but got {position_ids}")
             freqs_cis = self.freqs_cis[position_ids][:, :, None, :]
         complex_freqs = torch.view_as_complex(freqs_cis)
-        x_out = torch.view_as_real(complex_x * complex_freqs).view(batch_size, seq_length, num_heads, inner_dim)
+        x_out = torch.view_as_real(complex_x * complex_freqs).view(batch_size, seq_len, num_heads, inner_dim)
         return x_out.type(dtype)
 
 
@@ -197,7 +191,7 @@ def __init__(
         # TODO @nouamane: why can't we torch.jit.script GLUActivation?
         self.split_silu_mul = GLUActivation(config.hidden_act)
 
-    def forward(self, hidden_states):  # [seq_length, batch_size, hidden_dim]
+    def forward(self, hidden_states):  # [seq_len, batch_size, hidden_dim]
         merged_states = self.gate_up_proj(hidden_states)
         hidden_states = self.down_proj(self.split_silu_mul(merged_states))
         return {"hidden_states": hidden_states}
@@ -289,6 +283,720 @@ def pad_to_right(tensor, mask, new_tensor=None):
 from einops import einsum, rearrange, reduce
 from torchtyping import TensorType
 
+# class CausalSelfAttention(nn.Module, AttachableStore):
+#     def __init__(
+#         self,
+#         config: LlamaConfig,
+#         parallel_config: Optional[ParallelismArgs],
+#         tp_pg: dist.ProcessGroup,
+#         layer_idx: int,
+#     ):
+#         from flash_attn.layers.rotary import RotaryEmbedding as FlashRotaryEmbedding
+
+#         super().__init__()
+#         # Tensor parallel considerations: We split tensors along head dimension
+#         assert (
+#             config.num_attention_heads % tp_pg.size() == 0
+#         ), f"Number of attention heads ({config.num_attention_heads}) must be divisible by TP size ({tp_pg.size()})."
+#         try:
+#             assert (
+#                 config.num_key_value_heads % tp_pg.size() == 0
+#             ), f"Number of key/value heads ({config.num_key_value_heads}) must be divisible by TP size ({tp_pg.size()})."
+#         except AttributeError:
+#             log_rank(
+#                 "WARNING: num_key_value_heads not defined, assuming it is equal to num_attention_heads",
+#                 logger=logger,
+#                 level=logging.WARNING,
+#                 rank=0,
+#             )
+#             # If num_key_value_heads is not defined, we assume that it is equal to num_attention_heads
+#             config.num_key_value_heads = config.num_attention_heads
+#         assert (
+#             config.num_attention_heads % config.num_key_value_heads == 0
+#         ), f"Number of attention heads ({config.num_attention_heads}) must be divisible by number of key/value heads ({config.num_key_value_heads})."
+#         self.n_local_q_heads = config.num_attention_heads // tp_pg.size()
+#         self.n_local_kv_heads = config.num_key_value_heads // tp_pg.size()
+#         self.n_repeats = config.num_attention_heads // config.num_key_value_heads
+#         self.is_gqa = config.num_attention_heads != config.num_key_value_heads  # Whether we are using GQA or not
+#         self.d_qk = config.hidden_size // config.num_attention_heads
+#         self.d_v = config.hidden_size // config.num_attention_heads
+#         self.d_model = config.hidden_size
+#         self.is_using_mup = config.is_using_mup
+
+#         # TODO @thomasw21: refactor so that we store that default in a single place.
+#         tp_mode = parallel_config.tp_mode if parallel_config is not None else TensorParallelLinearMode.ALL_REDUCE
+#         tp_linear_async_communication = (
+#             parallel_config.tp_linear_async_communication if parallel_config is not None else False
+#         )
+
+#         # build the slice config for self.qkv for save/load
+#         # shard are done within the contiguous chunk
+#         qkv_contiguous_chunks = (
+#             config.num_attention_heads * self.d_qk,  # shape of q
+#             config.num_key_value_heads * self.d_qk,  # shape of k
+#             config.num_key_value_heads * self.d_qk,  # shape of v
+#         )
+#         self.config = config
+#         self.qkv_proj = TensorParallelColumnLinear(
+#             self.d_model,
+#             config.num_attention_heads * self.d_qk + 2 * config.num_key_value_heads * self.d_qk,
+#             pg=tp_pg,
+#             mode=tp_mode,
+#             bias=False,
+#             async_communication=tp_linear_async_communication,
+#             contiguous_chunks=qkv_contiguous_chunks,
+#         )
+#         # TODO(kunhao): We want to have only one version per device and not one version per layer.
+#         self.rotary_embedding = RotaryEmbedding(dim=self.d_qk, end=config.max_position_embeddings)
+#         log_rank(
+#             f"self.rotary_embedding.end is {self.rotary_embedding.end}",
+#             logger=logger,
+#             level=logging.INFO,
+#             rank=0,
+#         )
+#         # self.rotary_embedding = RotaryEmbedding(dim=self.d_qk, end=2048)
+
+#         # NOTE: Only supported for training (TODO(fmom): position_ids not supported yet)
+#         self.flash_rotary_embedding = FlashRotaryEmbedding(dim=self.d_qk, interleaved=True)
+
+#         self.o_proj = TensorParallelRowLinear(
+#             config.num_attention_heads * self.d_qk,
+#             self.d_model,
+#             pg=tp_pg,
+#             mode=tp_mode,
+#             bias=False,
+#             async_communication=tp_linear_async_communication,
+#         )
+
+#         self.attention = CoreAttention(
+#             config,
+#             parallel_config=parallel_config,
+#             layer_idx=layer_idx,
+#         )
+#         self.layer_idx = layer_idx
+
+#         self.prefill_kv_len = (
+#             config.max_position_embeddings
+#             # 2048
+#         )  # TODO @nouamane: compute based on free memory, because in rope we can surpass max_position_embeddings
+
+#         # self.n_segments = 16
+#         # self.segment_lengths = config.max_position_embeddings // self.n_segments
+#         # assert config.max_position_embeddings == 32768
+
+#         # NOTE: for 1b training
+#         self.segment_lengths = 2048
+#         # self.segment_lengths = 4096
+
+#         # NOTE: for sanity 200m training
+#         # prev 16
+#         # self.segment_lengths = 256
+#         # self.segment_lengths = 16
+
+#         device = self.o_proj.weight.device
+#         dtype = self.o_proj.weight.dtype
+
+#         from nanotron.parallel.sharded_parameters import SplitConfig, create_sharded_parameter_from_config
+
+#         balance_factors = nn.Parameter(torch.zeros(self.n_local_q_heads, device=device, dtype=dtype))
+#         self.balance_factors = create_sharded_parameter_from_config(
+#             parameter=balance_factors,
+#             pg=tp_pg,
+#             split_config=SplitConfig(
+#                 split_dim=0,
+#                 # contiguous_chunks=(self.n_local_heads, self.n_local_heads)
+#             ),
+#         )
+
+#     def forward(
+#         self,
+#         # hidden_states: TensorType["sharded_seq_len", "batch_size", "hidden_size"],
+#         hidden_states: TensorType["sharded_batch_size", "seq_len", "hidden_size"],
+#         sequence_mask: TensorType["batch_size", "seq_len"],
+#     ):
+#         # if self.layer_idx == 4:
+#         #     assert 1 == 1
+
+#         # batch_size = hidden_states.shape[1]
+#         # seq_len = hidden_states.shape[0]
+
+#         batch_size = hidden_states.shape[0]
+#         seq_len = hidden_states.shape[1]
+
+#         # assert seq_len == 1024
+#         # assert seq_len == 32768
+
+#         # assert seq_len % self.n_segments == 0
+
+#         # segment_length = seq_len // self.n_segments
+#         # hidden_size = hidden_states.shape[2]
+
+#         if seq_len > self.segment_lengths:
+#             # n_segments = seq_len // self.segment_lengths
+#             # segment_hidden_states = torch.chunk(hidden_states, chunks=n_segments, dim=0)
+#             # segment_sequence_masks = torch.chunk(sequence_mask, chunks=n_segments, dim=1)
+
+#             import math
+
+#             n_segments = math.ceil(seq_len / self.segment_lengths)
+#             segment_lengths = [self.segment_lengths] * (n_segments - 1) + [
+#                 seq_len - (n_segments - 1) * self.segment_lengths
+#             ]
+#             assert sum(segment_lengths) == seq_len
+#             # assert hidden_states.shape[0] == seq_len
+#             assert hidden_states.shape[1] == seq_len
+#             # segment_hidden_states = torch.split(hidden_states, segment_lengths, dim=0)
+#             segment_hidden_states = torch.split(hidden_states, segment_lengths, dim=1)
+#             # NOTE: assume that mask are all the same
+#             # because we split across sequence length
+#             # NOTE: take the assumption that all the masks are the same
+#             assert torch.all(sequence_mask)
+#             segment_sequence_masks = torch.split(sequence_mask[:, :seq_len], segment_lengths, dim=1)
+#         else:
+#             segment_hidden_states = [hidden_states]
+#             segment_sequence_masks = [sequence_mask]
+
+#         memory = None
+#         normalization = None
+
+#         # memory = prev_memory
+#         # normalization = prev_normalization
+
+#         outputs = []
+
+#         # sequence_masks = []
+#         idx = 0
+#         logs = {}
+
+#         for segment_hidden_state, segment_sequence_mask in zip(segment_hidden_states, segment_sequence_masks):
+#             # if idx == 1:
+#             #     memory = None
+#             #     normalization = None
+
+#             attn_outputs = self.forward_with_hidden_states(
+#                 hidden_states=segment_hidden_state, sequence_mask=segment_sequence_mask, return_qkv_states=True
+#             )
+
+#             local_attn_outputs = attn_outputs["attention_output"]
+#             # query_states, key_states, value_states = attn_outputs["qkv_states"]
+#             query_states, key_states, value_states = attn_outputs["qkv_states_without_pe"]
+
+#             # # NOTE: these are the shape for non-megatron-sp
+#             # assert query_states.shape[0] == self.segment_lengths
+#             # assert local_attn_outputs.shape[1] == self.segment_lengths
+
+#             query_states = rearrange(
+#                 query_states,
+#                 "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
+#                 seq_len=self.segment_lengths,
+#                 n_heads=self.n_local_q_heads,
+#                 d_head=self.d_qk,
+#             )
+
+#             key_states = rearrange(
+#                 key_states,
+#                 "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
+#                 # batch_size=batch_size,
+#                 seq_len=self.segment_lengths,
+#                 n_heads=self.n_local_kv_heads,
+#                 d_head=self.d_qk,
+#             )
+
+#             value_states = rearrange(
+#                 value_states,
+#                 "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
+#                 # batch_size=batch_size,
+#                 seq_len=self.segment_lengths,
+#                 n_heads=self.n_local_kv_heads,
+#                 d_head=self.d_qk,
+#             )
+
+#             # NOTE: because in generation, the sequence length increases
+#             # assert query_states.shape == (batch_size, self.n_local_q_heads, segment_length, self.d_qk)
+#             # assert query_states.shape == key_states.shape == value_states.shape
+#             retrieved_memory = self._retrieve_from_memory(
+#                 query_states, prev_memory=memory, prev_normalization=normalization
+#             )
+
+#             # log_rank(
+#             #     f"[idx={idx}] retrieved_memory.shape = {retrieved_memory.shape}, retrieve_memory is zero? {(retrieved_memory == 0).all()}",
+#             #     logger=logger,
+#             #     level=logging.INFO,
+#             #     rank=0,
+#             # )
+
+#             # if memory is not None:
+#             #     log_rank(
+#             #         f"[idx={idx}] memory.shape = {memory.shape}, normalization.shape = {normalization.shape}",
+#             #         logger=logger,
+#             #         level=logging.INFO,
+#             #         rank=0,
+#             #     )
+
+#             # retrieved_memory = retrieved_memory.detach()
+
+#             # local_attn_outputs = rearrange(
+#             #     local_attn_outputs,
+#             #     "seq_len batch_size (n_heads d_head) -> batch_size n_heads seq_len d_head",
+#             #     d_head=self.d_qk,
+#             # )
+#             local_attn_outputs = rearrange(
+#                 local_attn_outputs,
+#                 "batch_size seq_len (n_heads d_head) -> batch_size n_heads seq_len d_head",
+#                 seq_len=self.segment_lengths,
+#                 d_head=self.d_qk,
+#             )
+
+#             # log_rank(
+#             #     f"[idx={idx}] local_attn_outputs.shape = {local_attn_outputs.shape}, local_attn_outputs is zero? {(local_attn_outputs == 0).all()}",
+#             #     logger=logger,
+#             #     level=logging.INFO,
+#             #     rank=0,
+#             # )
+
+#             global_weights = F.sigmoid(self.balance_factors)
+#             global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
+
+#             local_weights = 1 - F.sigmoid(self.balance_factors)
+#             local_weights = rearrange(local_weights, "n_heads -> 1 n_heads 1 1")
+
+#             # assert torch.allclose(global_weights + local_weights, torch.ones_like(global_weights))
+
+#             # log_rank(
+#             #     f"[idx={idx}] global_weights.shape = {global_weights.shape}, global_weights: {global_weights}",
+#             #     logger=logger,
+#             #     level=logging.INFO,
+#             #     rank=0,
+#             # )
+
+#             # log_rank(
+#             #     f"[idx={idx}] local_weights.shape = {local_weights.shape}, local_weights: {local_weights}",
+#             #     logger=logger,
+#             #     level=logging.INFO,
+#             #     rank=0,
+#             # )
+
+#             attention_output = global_weights * retrieved_memory + local_weights * local_attn_outputs
+
+#             attention_output = rearrange(
+#                 attention_output, "batch_size n_heads seq_len d_head -> seq_len batch_size (n_heads d_head)",
+#                 n_heads=self.n_local_q_heads,
+#                 d_head=self.d_qk,
+#                 seq_len=self.segment_lengths,
+#             )
+
+#             output = self.o_proj(attention_output)
+
+#             if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % 50 == 0:
+#                 if dist.get_rank() == 0:
+#                     logs[f"layer_{self.layer_idx}:seg_{idx}:query_states"] = compute_stas(query_states)
+#                     logs[f"layer_{self.layer_idx}:seg_{idx}:key_states"] = compute_stas(key_states)
+#                     logs[f"layer_{self.layer_idx}:seg_{idx}:value_states"] = compute_stas(value_states)
+
+#                     logs[f"layer_{self.layer_idx}:seg_{idx}:global_weights"] = compute_stas(global_weights)
+#                     logs[f"layer_{self.layer_idx}:seg_{idx}:local_weights"] = compute_stas(local_weights)
+#                     logs[f"layer_{self.layer_idx}:seg_{idx}:local_attn_outputs"] = compute_stas(local_attn_outputs)
+#                     logs[f"layer_{self.layer_idx}:seg_{idx}:retrieved_memory"] = compute_stas(retrieved_memory)
+#                     logs[f"layer_{self.layer_idx}:seg_{idx}:attention_output"] = compute_stas(attention_output)
+#                     logs[f"layer_{self.layer_idx}:seg_{idx}:output"] = compute_stas(output)
+#                     logs[f"layer_{self.layer_idx}:seg_{idx}:memory"] = compute_stas(memory)
+#                     logs[f"layer_{self.layer_idx}:seg_{idx}:normalization"] = compute_stas(normalization)
+
+#             # assert output.shape == (segment_length, batch_size, hidden_size)
+
+#             memory, normalization = self._update_memory(memory, normalization, key_states, value_states)
+#             # memory = prev_memory if prev_memory is not None else 0.detach()
+
+#             outputs.append(output)
+#             # memory, normalization = memory.detach(), normalization.detach()
+
+#             idx += 1
+
+#             # NOTE: update memory
+#         # outputs = torch.cat(outputs, dim=0)  # concat along sequence dimension
+#         outputs = torch.cat(outputs, dim=2)  # concat along sequence dimension
+#         assert outputs.shape == hidden_states.shape
+
+#         if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % 50 == 0:
+#             if dist.get_rank() == 0:
+#                 import wandb
+
+#                 logs[f"layer_{self.layer_idx}:outputs"] = compute_stas(outputs)
+#                 wandb.log({**logs, "iteration_step": constants.GLOBAL_STEP})
+
+#         # sequence_masks = torch.cat(sequence_masks, dim=1)
+#         # assert sequence_masks.shape == sequence_mask.shape
+#         return_outputs = {
+#             "hidden_states": outputs,
+#             "sequence_mask": sequence_mask,
+#             # "memory": memory,
+#             # "normalization": normalization,
+#         }
+#         return return_outputs
+
+#     def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
+#         # return torch.zeros_like(query_states)
+#         if prev_memory is None or prev_normalization is None:
+#             return torch.zeros_like(query_states)
+
+#         assert (prev_memory is None and prev_normalization is None) or (
+#             prev_memory is not None and prev_normalization is not None
+#         )
+
+#         if self.n_repeats > 1:
+#             from einops import repeat
+
+#             prev_memory = repeat(
+#                 prev_memory,
+#                 "batch_size n_kv_heads d_k d_v -> batch_size (n_kv_heads n) d_k d_v",
+#                 n=self.n_repeats,
+#             )
+#             prev_normalization = repeat(
+#                 prev_normalization,
+#                 "batch_size n_kv_heads d_head -> batch_size (n_kv_heads n) d_head",
+#                 n=self.n_repeats,
+#             )
+
+#         sigma_query_states = F.elu(query_states) + 1
+#         retrieved_memory = einsum(
+#             sigma_query_states,
+#             prev_memory,
+#             "batch_size n_heads seq_len d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_len d_v",
+#         )
+
+#         denominator = einsum(
+#             sigma_query_states,
+#             prev_normalization,
+#             "batch_size n_heads seq_len d_head, batch_size n_heads d_head -> batch_size n_heads seq_len",
+#         )
+#         denominator = rearrange(denominator, "batch_size n_heads seq_len -> batch_size n_heads seq_len 1")
+#         # [batch_size, n_heads, seq_len, d_v] / [batch_size, n_heads, seq_len, 1], so each d_v is divide by the normalized value
+
+#         # NOTE: because normalization is the sum of all the keys, so each word should have the same normalization
+#         retrieved_memory = retrieved_memory / denominator
+#         return retrieved_memory
+
+#     def _update_memory(self, prev_memory, prev_normalization, key_states, value_states):
+#         assert (prev_memory is None and prev_normalization is None) or (
+#             prev_memory is not None and prev_normalization is not None
+#         )
+
+#         sigma_key_states = F.elu(key_states) + 1
+
+#         if prev_memory is None or prev_normalization is None:
+#             new_value_states = value_states
+#         else:
+#             numerator = einsum(
+#                 sigma_key_states,
+#                 prev_memory,
+#                 "batch_size n_heads seq_len d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_len d_v",
+#             )
+#             denominator = einsum(
+#                 sigma_key_states,
+#                 prev_normalization,
+#                 "batch_size n_heads seq_len d_k, batch_size n_heads d_k -> batch_size n_heads seq_len",
+#             )
+#             denominator = rearrange(denominator, "batch_size n_heads seq_len -> batch_size n_heads seq_len 1")
+
+#             prev_v = numerator / denominator
+#             new_value_states = value_states - prev_v
+
+#         memory = torch.matmul(sigma_key_states.transpose(-2, -1), new_value_states)
+
+#         normalization = reduce(
+#             sigma_key_states, "batch_size n_heads seq_len d_head -> batch_size n_heads d_head", reduction="sum"
+#         )
+
+#         memory += prev_memory if prev_memory is not None else 0
+#         normalization += prev_normalization if prev_normalization is not None else 0
+
+#         return memory, normalization
+
+#     def forward_with_hidden_states(
+#         self,
+#         hidden_states,  # [seq_len, batch_size, hidden_size]
+#         sequence_mask,  # [batch_size, seq_len]
+#         return_qkv_states: bool = False,
+#     ):
+#         from flash_attn import bert_padding
+#         from flash_attn.flash_attn_interface import (
+#             flash_attn_varlen_func,
+#             flash_attn_with_kvcache,
+#         )
+
+#         qkv_states = self.qkv_proj(
+#             hidden_states
+#         )  # [seq_len, batch_size, n_local_q_heads * d_qk + 2 * n_local_kv_heads * d_qk]
+#         q_length, batch_size, _ = qkv_states.shape
+
+#         if self.is_gqa:
+#             query_states, key_states, value_states = torch.split(
+#                 qkv_states,
+#                 [
+#                     self.n_local_q_heads * self.d_qk,
+#                     self.n_local_kv_heads * self.d_qk,
+#                     self.n_local_kv_heads * self.d_qk,
+#                 ],
+#                 dim=-1,
+#             )
+
+#             query_states = (
+#                 query_states.transpose(0, 1).contiguous().view(batch_size, q_length, self.n_local_q_heads, self.d_qk)
+#             )
+#             key_states = (
+#                 key_states.transpose(0, 1).contiguous().view(batch_size, q_length, self.n_local_kv_heads, self.d_qk)
+#             )
+#             value_states = (
+#                 value_states.transpose(0, 1).contiguous().view(batch_size, q_length, self.n_local_kv_heads, self.d_qk)
+#             )
+#         else:
+#             query_states, key_states, value_states = (
+#                 qkv_states.view(q_length, batch_size, 3, self.n_local_q_heads, self.d_qk)
+#                 .permute(2, 1, 0, 3, 4)
+#                 .contiguous()
+#             )  # [3, batch_size, seq_len, n_local_q_heads, d_qk]
+
+#         # query_states_without_pe = rearrange(
+#         #     query_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
+#         # )
+#         # key_states_without_pe = rearrange(
+#         #     key_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
+#         # )
+#         # value_states_without_pe = rearrange(
+#         #     value_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
+#         # )
+
+#         query_states_without_pe = rearrange(
+#             query_states, "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head"
+#         )
+#         key_states_without_pe = rearrange(
+#             key_states, "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head"
+#         )
+#         value_states_without_pe = rearrange(
+#             value_states, "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head"
+#         )
+
+#         assert query_states_without_pe.shape[0] == self.segment_lengths
+
+#         store = self.get_local_store()
+#         if store is not None:  # Inference case
+#             # Double check that we use store only at inference time
+#             assert key_states.requires_grad is False
+#             assert value_states.requires_grad is False
+#             if "position_offsets" in store:
+#                 old_position_offsets = store["position_offsets"]
+#                 position_ids = old_position_offsets[:, None] + sequence_mask
+#             else:
+#                 position_ids = torch.cumsum(sequence_mask, dim=-1, dtype=torch.int32) - 1
+#             position_offsets = position_ids[:, -1]
+
+#             # Compute rotary embeddings
+#             # Note: keep track of old rotary embedding end to check if we need to enlarge k_cache and v_cache
+#             old_rotary_embed_end = self.rotary_embedding.end
+#             query_states = self.rotary_embedding(query_states, position_ids=position_ids)
+#             key_states = self.rotary_embedding(key_states, position_ids=position_ids)
+
+#             if "key" not in store:
+#                 # First inference iteration (Prefill)
+#                 # TODO @nouamane: support custom masking
+#                 # assert that [ False, False, False, False,  True,  True,  True,  True,  True,  True] is accepted
+#                 # but [ False, False, False, False,  True,  True,  False,  False,  True,  True] is not (can't mask in the middle of sequence)
+#                 assert ~(
+#                     sequence_mask[:, :-1] & (~sequence_mask[:, 1:])  # True is never followed by False
+#                 ).any(), "Can't mask in the middle of sequence, please make sure that pads are at the left of the sequence if existing"
+
+#                 # preallocate k_cache, v_cache to self.prefill_kv_len
+#                 k_cache = torch.zeros(
+#                     (
+#                         batch_size,
+#                         self.prefill_kv_len,
+#                         self.n_local_kv_heads,
+#                         self.d_qk,
+#                     ),
+#                     dtype=query_states.dtype,
+#                     device=query_states.device,
+#                 )
+#                 v_cache = torch.zeros(
+#                     (batch_size, self.prefill_kv_len, self.n_local_kv_heads, self.d_v),
+#                     dtype=query_states.dtype,
+#                     device=query_states.device,
+#                 )
+#                 # Remove pad tokens from key_states and concatenate samples in key_unpad
+#                 # cu_seqlens_k is the cumulative sequence lengths of key_states
+#                 (query_unpad, indices_q, cu_seqlens_q, max_seqlen_q) = bert_padding.unpad_input(
+#                     query_states,
+#                     sequence_mask,
+#                 )
+#                 (key_unpad, indices_k, cu_seqlens_k, max_seqlen_k) = bert_padding.unpad_input(
+#                     key_states, sequence_mask
+#                 )
+#                 (value_unpad, _, _, _) = bert_padding.unpad_input(value_states, sequence_mask)
+
+#                 # NOTE: this scale is for µTransfer,
+#                 # in SP, we use sqrt(1/d_h)
+#                 softmax_scale = 1 / query_states.shape[-1] if self.is_using_mup else None
+#                 output_unpad = flash_attn_varlen_func(
+#                     q=query_unpad,  # (total_q, n_local_q_heads, d_qk)
+#                     k=key_unpad,  # (total_kv, n_local_kv_heads, d_qk)
+#                     v=value_unpad,  # (total_kv, n_local_kv_heads, d_v)
+#                     cu_seqlens_q=cu_seqlens_q,
+#                     cu_seqlens_k=cu_seqlens_k,
+#                     max_seqlen_q=max_seqlen_q,
+#                     max_seqlen_k=max_seqlen_k,
+#                     dropout_p=0.0,
+#                     softmax_scale=softmax_scale,
+#                     causal=True,  # True in prefill phase, False in subsequent phases
+#                     return_attn_probs=False,
+#                 )  # (total_unpadded, n_local_q_heads, d_v)
+
+#                 attention_output = bert_padding.pad_input(
+#                     output_unpad, indices_q, batch_size, q_length
+#                 )  # (batch_size, q_length, n_local_q_heads, d_v)
+
+#                 pad_to_right(key_states, sequence_mask, new_tensor=k_cache)
+#                 pad_to_right(value_states, sequence_mask, new_tensor=v_cache)
+
+#             else:
+#                 # Pull pre-computed key/value states
+#                 # Subsequent inference iterations (q_length=1)
+#                 k_cache = store["key"]
+#                 v_cache = store["value"]
+
+#                 # NOTE(fmom): According to flash_attn_with_kvcache, "If you pass in k / v, you must make sure that the cache is large enough to hold the new values"
+#                 # Since rotary embedding has changed (to enable larger context), we need to enlarge k_cache and v_cache
+#                 if self.rotary_embedding.end > old_rotary_embed_end:
+#                     k_cache = torch.cat(
+#                         [
+#                             k_cache,
+#                             torch.zeros(
+#                                 (
+#                                     batch_size,
+#                                     self.rotary_embedding.end - old_rotary_embed_end,
+#                                     self.n_local_kv_heads,
+#                                     self.d_qk,
+#                                 ),
+#                                 dtype=query_states.dtype,
+#                                 device=query_states.device,
+#                             ),
+#                         ],
+#                         dim=1,
+#                     )
+
+#                     v_cache = torch.cat(
+#                         [
+#                             v_cache,
+#                             torch.zeros(
+#                                 (
+#                                     batch_size,
+#                                     self.rotary_embedding.end - old_rotary_embed_end,
+#                                     self.n_local_kv_heads,
+#                                     self.d_v,
+#                                 ),
+#                                 dtype=query_states.dtype,
+#                                 device=query_states.device,
+#                             ),
+#                         ],
+#                         dim=1,
+#                     )
+
+#                 assert (
+#                     k_cache.shape[1] == self.rotary_embedding.end
+#                 ), f"Cache size {k_cache.shape[1]} is smaller than rotary embedding end {self.rotary_embedding.end}"
+#                 assert (
+#                     v_cache.shape[1] == self.rotary_embedding.end
+#                 ), f"Cache size {v_cache.shape[1]} is smaller than rotary embedding end {self.rotary_embedding.end}"
+
+#                 # [batch_size, seq_len, num_heads, d_qk]
+#                 query_states = query_states.view(
+#                     batch_size, q_length, self.n_local_q_heads, self.d_qk
+#                 )  # [batch_size, q_length, self.n_heads, d_qk]
+#                 kv_length = key_states.shape[1]
+#                 key_states = key_states.view(
+#                     batch_size, kv_length, self.n_local_kv_heads, self.d_qk
+#                 )  # [batch_size, kv_length, self.n_heads, d_qk]
+#                 value_states = value_states.view(
+#                     batch_size, kv_length, self.n_local_kv_heads, self.d_v
+#                 )  # [batch_size, kv_length, self.n_heads, d_v]
+
+#                 # NOTE: this scale is for µTransfer,
+#                 # in SP, we use sqrt(1/d_h)
+#                 softmax_scale = 1 / query_states.shape[-1] if self.is_using_mup else None
+#                 attention_output = flash_attn_with_kvcache(
+#                     query_states,
+#                     k_cache,
+#                     v_cache,
+#                     key_states,
+#                     value_states,
+#                     rotary_cos=None,
+#                     rotary_sin=None,
+#                     # TODO @nouamane: seems like this doesn't help to indicate padding in (for first iteration it's just 0)
+#                     cache_seqlens=position_offsets.contiguous(),
+#                     softmax_scale=softmax_scale,
+#                     causal=True,
+#                     rotary_interleaved=False,  # GPT-NeoX style
+#                 )
+
+#             store.update(
+#                 {
+#                     "key": k_cache,  # flash-attn has updated with new key_states using cache_seqlens
+#                     "value": v_cache,
+#                     "position_offsets": position_offsets,
+#                 }
+#             )
+
+#         else:  # Training case
+#             # Apply rotary embeddings to query/key states
+#             # NOTE: The layout is different from models/llama.py which is [batch_size, num_heads, seq_len, d_qk]
+#             # Here it is, [batch_size, seq_len, num_heads, d_qk]
+#             # [2, batch_size, seq_len, num_heads, d_qk]
+#             key_value_states = torch.cat([key_states.unsqueeze(0), value_states.unsqueeze(0)], dim=0)
+#             # [batch_size, seq_len, 2, num_heads, d_qk]
+#             key_value_states = key_value_states.permute(1, 2, 0, 3, 4).contiguous()
+#             query_states, key_value_states = self.flash_rotary_embedding(query_states, kv=key_value_states)
+#             # [batch_size, seq_len, num_heads, d_qk]
+#             key_states, value_states = torch.split(key_value_states, 1, dim=2)
+
+#             q_sequence_mask = sequence_mask
+#             kv_sequence_mask = sequence_mask
+
+#             kv_length = key_states.shape[1]
+#             # [batch_size, seq_len, num_heads, d_qk]
+#             # Shaping for use in `flash-attn` version of flash-attn: `flash_attn_unpadded_func`
+#             query_states = query_states.view(
+#                 batch_size * q_length, self.n_local_q_heads, self.d_qk
+#             )  # [batch_size * q_length, self.n_heads, d_qk]
+
+#             key_states = key_states.view(
+#                 batch_size * kv_length, self.n_local_kv_heads, self.d_qk
+#             )  # [batch_size * kv_length, self.n_heads, d_qk]
+#             value_states = value_states.view(
+#                 batch_size * kv_length, self.n_local_kv_heads, self.d_v
+#             )  # [batch_size * kv_length, self.n_heads, d_v]
+
+#             attention_output = self.attention(
+#                 query_states=query_states,
+#                 key_states=key_states,
+#                 value_states=value_states,
+#                 q_sequence_mask=q_sequence_mask,
+#                 kv_sequence_mask=kv_sequence_mask,
+#             )
+
+#         attention_output = (
+#             attention_output.contiguous().view(batch_size, q_length, self.n_local_q_heads * self.d_v).transpose(0, 1)
+#         )
+#         # output = self.o_proj(attention_output)
+#         # return {"hidden_states": output, "sequence_mask": sequence_mask}
+
+#         return_outputs = {"hidden_states": None, "sequence_mask": sequence_mask}
+#         return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
+#         return_outputs["qkv_states_without_pe"] = (
+#             query_states_without_pe,
+#             key_states_without_pe,
+#             value_states_without_pe,
+#         )
+#         return_outputs["attention_output"] = attention_output
+#         return return_outputs
+
 
 class CausalSelfAttention(nn.Module, AttachableStore):
     def __init__(
@@ -343,6 +1051,7 @@ def __init__(
             config.num_key_value_heads * self.d_qk,  # shape of k
             config.num_key_value_heads * self.d_qk,  # shape of v
         )
+        self.config = config
         self.qkv_proj = TensorParallelColumnLinear(
             self.d_model,
             config.num_attention_heads * self.d_qk + 2 * config.num_key_value_heads * self.d_qk,
@@ -391,8 +1100,9 @@ def __init__(
         # assert config.max_position_embeddings == 32768
 
         # NOTE: for 1b training
-        self.segment_lengths = 2048
+        # self.segment_lengths = 2048
         # self.segment_lengths = 4096
+        self.segment_lengths = 1024  # for 4096 context length
 
         # NOTE: for sanity 200m training
         # prev 16
@@ -416,8 +1126,9 @@ def __init__(
 
     def forward(
         self,
-        hidden_states: TensorType["sharded_seq_length", "batch_size", "hidden_size"],
-        sequence_mask: TensorType["batch_size", "seq_length"],
+        # hidden_states: TensorType["sharded_seq_len", "batch_size", "hidden_size"],
+        hidden_states: TensorType["sharded_batch_size", "seq_len", "hidden_size"],
+        sequence_mask: TensorType["batch_size", "seq_len"],
     ):
         # if self.layer_idx == 4:
         #     assert 1 == 1
@@ -425,7 +1136,7 @@ def forward(
         # batch_size = hidden_states.shape[1]
         # seq_len = hidden_states.shape[0]
 
-        batch_size = hidden_states.shape[0]
+        hidden_states.shape[0]
         seq_len = hidden_states.shape[1]
 
         # assert seq_len == 1024
@@ -486,34 +1197,39 @@ def forward(
             # query_states, key_states, value_states = attn_outputs["qkv_states"]
             query_states, key_states, value_states = attn_outputs["qkv_states_without_pe"]
 
-            if query_states.ndim == 3:
-                query_states = rearrange(
-                    query_states,
-                    "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
-                    batch_size=batch_size,
-                    # n_heads=self.n_local_heads,
-                )
+            # # NOTE: these are the shape for non-megatron-sp
+            # assert query_states.shape[0] == self.segment_lengths
+            # assert local_attn_outputs.shape[1] == self.segment_lengths
 
-            if key_states.ndim == 3:
-                key_states = rearrange(
-                    key_states,
-                    "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
-                    batch_size=batch_size,
-                    # n_heads=self.n_local_heads,
-                )
+            query_states = rearrange(
+                query_states,
+                "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
+                # seq_len=self.segment_lengths,
+                n_heads=self.n_local_q_heads,
+                d_head=self.d_qk,
+            )
 
-            if value_states.ndim == 3:
-                value_states = rearrange(
-                    value_states,
-                    "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
-                    batch_size=batch_size,
-                    # n_heads=self.n_local_heads,
-                )
+            key_states = rearrange(
+                key_states,
+                "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
+                # batch_size=batch_size,
+                # seq_len=self.segment_lengths,
+                n_heads=self.n_local_kv_heads,
+                d_head=self.d_qk,
+            )
+
+            value_states = rearrange(
+                value_states,
+                "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
+                # batch_size=batch_size,
+                # seq_len=self.segment_lengths,
+                n_heads=self.n_local_kv_heads,
+                d_head=self.d_qk,
+            )
 
             # NOTE: because in generation, the sequence length increases
             # assert query_states.shape == (batch_size, self.n_local_q_heads, segment_length, self.d_qk)
             # assert query_states.shape == key_states.shape == value_states.shape
-
             retrieved_memory = self._retrieve_from_memory(
                 query_states, prev_memory=memory, prev_normalization=normalization
             )
@@ -535,9 +1251,15 @@ def forward(
 
             # retrieved_memory = retrieved_memory.detach()
 
+            # local_attn_outputs = rearrange(
+            #     local_attn_outputs,
+            #     "seq_len batch_size (n_heads d_head) -> batch_size n_heads seq_len d_head",
+            #     d_head=self.d_qk,
+            # )
             local_attn_outputs = rearrange(
                 local_attn_outputs,
-                "seq_len batch_size (n_heads d_head) -> batch_size n_heads seq_len d_head",
+                "batch_size seq_len (n_heads d_head) -> batch_size n_heads seq_len d_head",
+                # seq_len=self.segment_lengths,
                 d_head=self.d_qk,
             )
 
@@ -571,17 +1293,18 @@ def forward(
             # )
 
             attention_output = global_weights * retrieved_memory + local_weights * local_attn_outputs
-            # attention_output = local_weights * local_attn_outputs
-
-            # assert attention_output.shape == (batch_size, self.n_local_q_heads, segment_length, self.d_qk)
 
             attention_output = rearrange(
-                attention_output, "batch_size n_heads seq_len d_head -> seq_len batch_size (n_heads d_head)"
+                attention_output,
+                "batch_size n_heads seq_len d_head -> batch_size seq_len (n_heads d_head)",
+                n_heads=self.n_local_q_heads,
+                d_head=self.d_qk,
+                # seq_len=self.segment_lengths,
             )
 
             output = self.o_proj(attention_output)
 
-            if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % 50 == 0:
+            if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0:
                 if dist.get_rank() == 0:
                     logs[f"layer_{self.layer_idx}:seg_{idx}:query_states"] = compute_stas(query_states)
                     logs[f"layer_{self.layer_idx}:seg_{idx}:key_states"] = compute_stas(key_states)
@@ -611,7 +1334,7 @@ def forward(
         outputs = torch.cat(outputs, dim=1)  # concat along sequence dimension
         assert outputs.shape == hidden_states.shape
 
-        if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % 50 == 0:
+        if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0:
             if dist.get_rank() == 0:
                 import wandb
 
@@ -637,34 +1360,45 @@ def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
             prev_memory is not None and prev_normalization is not None
         )
 
-        if self.n_repeats > 1:
-            from einops import repeat
+        # if self.n_repeats > 1:
+        #     from einops import repeat
 
-            prev_memory = repeat(
-                prev_memory,
-                "batch_size n_kv_heads d_k d_v -> batch_size (n_kv_heads n) d_k d_v",
-                n=self.n_repeats,
-            )
-            prev_normalization = repeat(
-                prev_normalization,
-                "batch_size n_kv_heads d_head -> batch_size (n_kv_heads n) d_head",
-                n=self.n_repeats,
-            )
+        #     prev_memory = repeat(
+        #         prev_memory,
+        #         "batch_size n_kv_heads d_k d_v -> batch_size (n_kv_heads n) d_k d_v",
+        #         n=self.n_repeats,
+        #     )
+        #     prev_normalization = repeat(
+        #         prev_normalization,
+        #         "batch_size n_kv_heads d_head -> batch_size (n_kv_heads n) d_head",
+        #         n=self.n_repeats,
+        #     )
 
         sigma_query_states = F.elu(query_states) + 1
         retrieved_memory = einsum(
             sigma_query_states,
             prev_memory,
-            "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
+            "batch_size n_heads seq_len d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_len d_v",
+            # seq_len=self.segment_lengths,
+            # n_heads=self.n_local_kv_heads,
+            # d_k=self.d_qk,
         )
 
         denominator = einsum(
             sigma_query_states,
             prev_normalization,
-            "batch_size n_heads seq_length d_head, batch_size n_heads d_head -> batch_size n_heads seq_length",
+            "batch_size n_heads seq_len d_head, batch_size n_heads d_head -> batch_size n_heads seq_len",
+            # n_heads=self.n_local_kv_heads,
+            # d_head=self.d_qk,
+            # seq_len=self.segment_lengths,
+        )
+        denominator = rearrange(
+            denominator,
+            "batch_size n_heads seq_len -> batch_size n_heads seq_len 1",
+            # n_heads=self.n_local_kv_heads,
+            # seq_len=self.segment_lengths,
         )
-        denominator = rearrange(denominator, "batch_size n_heads seq_length -> batch_size n_heads seq_length 1")
-        # [batch_size, n_heads, seq_length, d_v] / [batch_size, n_heads, seq_length, 1], so each d_v is divide by the normalized value
+        # [batch_size, n_heads, seq_len, d_v] / [batch_size, n_heads, seq_len, 1], so each d_v is divide by the normalized value
 
         # NOTE: because normalization is the sum of all the keys, so each word should have the same normalization
         retrieved_memory = retrieved_memory / denominator
@@ -683,14 +1417,25 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
             numerator = einsum(
                 sigma_key_states,
                 prev_memory,
-                "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
+                "batch_size n_heads seq_len d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_len d_v",
+                # n_heads=self.n_local_kv_heads,
+                # d_k=self.d_qk,
+                # seq_len=self.segment_lengths,
             )
             denominator = einsum(
                 sigma_key_states,
                 prev_normalization,
-                "batch_size n_heads seq_length d_k, batch_size n_heads d_k -> batch_size n_heads seq_length",
+                "batch_size n_heads seq_len d_k, batch_size n_heads d_k -> batch_size n_heads seq_len",
+                # n_heads=self.n_local_kv_heads,
+                # d_k=self.d_qk,
+                # seq_len=self.segment_lengths,
+            )
+            denominator = rearrange(
+                denominator,
+                "batch_size n_heads seq_len -> batch_size n_heads seq_len 1",
+                # n_heads=self.n_local_kv_heads,
+                # seq_len=self.segment_lengths,
             )
-            denominator = rearrange(denominator, "batch_size n_heads seq_length -> batch_size n_heads seq_length 1")
 
             prev_v = numerator / denominator
             new_value_states = value_states - prev_v
@@ -698,7 +1443,12 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
         memory = torch.matmul(sigma_key_states.transpose(-2, -1), new_value_states)
 
         normalization = reduce(
-            sigma_key_states, "batch_size n_heads seq_length d_head -> batch_size n_heads d_head", reduction="sum"
+            sigma_key_states,
+            "batch_size n_heads seq_len d_head -> batch_size n_heads d_head",
+            reduction="sum",
+            n_heads=self.n_local_kv_heads,
+            d_head=self.d_qk,
+            # seq_len=self.segment_lengths,
         )
 
         memory += prev_memory if prev_memory is not None else 0
@@ -708,8 +1458,8 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
 
     def forward_with_hidden_states(
         self,
-        hidden_states,  # [seq_length, batch_size, hidden_size]
-        sequence_mask,  # [batch_size, seq_length]
+        hidden_states,  # [seq_len, batch_size, hidden_size]
+        sequence_mask,  # [batch_size, seq_len]
         return_qkv_states: bool = False,
     ):
         from flash_attn import bert_padding
@@ -718,9 +1468,11 @@ def forward_with_hidden_states(
             flash_attn_with_kvcache,
         )
 
+        seq_len = hidden_states.shape[1]
+
         qkv_states = self.qkv_proj(
             hidden_states
-        )  # [seq_length, batch_size, n_local_q_heads * d_qk + 2 * n_local_kv_heads * d_qk]
+        )  # [seq_len, batch_size, n_local_q_heads * d_qk + 2 * n_local_kv_heads * d_qk]
         q_length, batch_size, _ = qkv_states.shape
 
         if self.is_gqa:
@@ -748,18 +1500,40 @@ def forward_with_hidden_states(
                 qkv_states.view(q_length, batch_size, 3, self.n_local_q_heads, self.d_qk)
                 .permute(2, 1, 0, 3, 4)
                 .contiguous()
-            )  # [3, batch_size, seq_length, n_local_q_heads, d_qk]
+            )  # [3, batch_size, seq_len, n_local_q_heads, d_qk]
+
+        # query_states_without_pe = rearrange(
+        #     query_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
+        # )
+        # key_states_without_pe = rearrange(
+        #     key_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
+        # )
+        # value_states_without_pe = rearrange(
+        #     value_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
+        # )
 
         query_states_without_pe = rearrange(
-            query_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
+            query_states,
+            "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
+            # seq_len=self.segment_lengths,
+            seq_len=seq_len,
         )
         key_states_without_pe = rearrange(
-            key_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
+            key_states,
+            "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
+            # seq_len=self.segment_lengths,
+            seq_len=seq_len,
         )
         value_states_without_pe = rearrange(
-            value_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
+            value_states,
+            "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
+            # seq_len=self.segment_lengths,
+            seq_len=seq_len,
         )
 
+        # assert query_states_without_pe.shape[0] == self.segment_lengths
+        assert query_states_without_pe.shape[0] == seq_len
+
         store = self.get_local_store()
         if store is not None:  # Inference case
             # Double check that we use store only at inference time
@@ -888,7 +1662,7 @@ def forward_with_hidden_states(
                     v_cache.shape[1] == self.rotary_embedding.end
                 ), f"Cache size {v_cache.shape[1]} is smaller than rotary embedding end {self.rotary_embedding.end}"
 
-                # [batch_size, seq_length, num_heads, d_qk]
+                # [batch_size, seq_len, num_heads, d_qk]
                 query_states = query_states.view(
                     batch_size, q_length, self.n_local_q_heads, self.d_qk
                 )  # [batch_size, q_length, self.n_heads, d_qk]
@@ -928,21 +1702,21 @@ def forward_with_hidden_states(
 
         else:  # Training case
             # Apply rotary embeddings to query/key states
-            # NOTE: The layout is different from models/llama.py which is [batch_size, num_heads, seq_length, d_qk]
-            # Here it is, [batch_size, seq_length, num_heads, d_qk]
-            # [2, batch_size, seq_length, num_heads, d_qk]
+            # NOTE: The layout is different from models/llama.py which is [batch_size, num_heads, seq_len, d_qk]
+            # Here it is, [batch_size, seq_len, num_heads, d_qk]
+            # [2, batch_size, seq_len, num_heads, d_qk]
             key_value_states = torch.cat([key_states.unsqueeze(0), value_states.unsqueeze(0)], dim=0)
-            # [batch_size, seq_length, 2, num_heads, d_qk]
+            # [batch_size, seq_len, 2, num_heads, d_qk]
             key_value_states = key_value_states.permute(1, 2, 0, 3, 4).contiguous()
             query_states, key_value_states = self.flash_rotary_embedding(query_states, kv=key_value_states)
-            # [batch_size, seq_length, num_heads, d_qk]
+            # [batch_size, seq_len, num_heads, d_qk]
             key_states, value_states = torch.split(key_value_states, 1, dim=2)
 
             q_sequence_mask = sequence_mask
             kv_sequence_mask = sequence_mask
 
             kv_length = key_states.shape[1]
-            # [batch_size, seq_length, num_heads, d_qk]
+            # [batch_size, seq_len, num_heads, d_qk]
             # Shaping for use in `flash-attn` version of flash-attn: `flash_attn_unpadded_func`
             query_states = query_states.view(
                 batch_size * q_length, self.n_local_q_heads, self.d_qk
@@ -1053,7 +1827,7 @@ def __init__(self, tp_pg: dist.ProcessGroup, config: LlamaConfig, parallel_confi
         )
         self.pg = tp_pg
 
-    def forward(self, input_ids: torch.Tensor, input_mask: torch.Tensor):  # [batch_size, seq_length]
+    def forward(self, input_ids: torch.Tensor, input_mask: torch.Tensor):  # [batch_size, seq_len]
         store = self.get_local_store()
         if store is not None:
             if "past_length" in store:
@@ -1065,7 +1839,7 @@ def forward(self, input_ids: torch.Tensor, input_mask: torch.Tensor):  # [batch_
             # Store new past_length in store
             store["past_length"] = past_length + cumsum_mask[:, -1]
 
-        # Format input in `[seq_length, batch_size]` to support high TP with low batch_size
+        # Format input in `[seq_len, batch_size]` to support high TP with low batch_size
         # input_ids = input_ids.transpose(0, 1)
         input_embeds = self.token_embedding(input_ids)
         return {"input_embeds": input_embeds}
@@ -1159,15 +1933,15 @@ def __init__(
 
     def forward(
         self,
-        input_ids: Union[torch.Tensor, TensorPointer],  # [batch_size, seq_length]
-        input_mask: Union[torch.Tensor, TensorPointer],  # [batch_size, seq_length]
+        input_ids: Union[torch.Tensor, TensorPointer],  # [batch_size, seq_len]
+        input_mask: Union[torch.Tensor, TensorPointer],  # [batch_size, seq_len]
     ):
         return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
 
     def forward_with_hidden_states(
         self,
-        input_ids: Union[torch.Tensor, TensorPointer],  # [batch_size, seq_length]
-        input_mask: Union[torch.Tensor, TensorPointer],  # [batch_size, seq_length]
+        input_ids: Union[torch.Tensor, TensorPointer],  # [batch_size, seq_len]
+        input_mask: Union[torch.Tensor, TensorPointer],  # [batch_size, seq_len]
     ):
         # all tensors are optional as most ranks don't need anything from the dataloader.
 
@@ -1241,9 +2015,9 @@ def __init__(self, tp_pg: dist.ProcessGroup):
 
     def forward(
         self,
-        sharded_logits: torch.Tensor,  # [seq_length, batch_size, logits]
-        label_ids: torch.Tensor,  # [batch_size, seq_length]
-        label_mask: torch.Tensor,  # [batch_size, seq_length]
+        sharded_logits: torch.Tensor,  # [seq_len, batch_size, logits]
+        label_ids: torch.Tensor,  # [batch_size, seq_len]
+        label_mask: torch.Tensor,  # [batch_size, seq_len]
     ) -> Dict[str, torch.Tensor]:
         # Megatron by defaults cast everything in fp32. `--f16-lm-cross-entropy` is an option you can use to keep current precision.
         # https://github.com/NVIDIA/Megatron-LM/blob/f267e6186eae1d6e2055b412b00e2e545a8e896a/megatron/model/gpt_model.py#L38
diff --git a/src/nanotron/parallel/pipeline_parallel/engine.py b/src/nanotron/parallel/pipeline_parallel/engine.py
index 7ddabe25..babf875e 100644
--- a/src/nanotron/parallel/pipeline_parallel/engine.py
+++ b/src/nanotron/parallel/pipeline_parallel/engine.py
@@ -5,8 +5,8 @@
 from torch import nn as torch_nn
 from torch.nn.parallel import DistributedDataParallel
 
+from nanotron import constants, logging
 from nanotron import distributed as dist
-from nanotron import logging
 from nanotron.distributed import ProcessGroup
 from nanotron.logging import log_rank
 from nanotron.optim.gradient_accumulator import GradientAccumulator
@@ -284,19 +284,36 @@ def train_batch_iter(
 
             for micro_batch in batch:
                 if dist.get_rank() == 0:
-                    if self.idx == 1 or self.idx % 50 == 0:
+                    # if self.idx == 1 or self.idx % 50 == 0:
+                    if (
+                        constants.GLOBAL_STEP is not None
+                        and (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0
+                    ):
                         decoded_texts = self.tokenizer.batch_decode(micro_batch["input_ids"])
+                        from typing import cast
+
+                        from nanotron.config import Config
+
+                        constants.CONFIG = cast(Config, constants.CONFIG)
+                        run_name = constants.CONFIG.general.run
+                        import random
+
+                        sample_index = random.randint(0, len(decoded_texts) - 1)
 
                         with open(
-                            "/fsx/phuc/projects/nanotron/examples/infinite-context-length/configs/exp19/training_inputs.txt",
+                            f"/fsx/phuc/projects/nanotron/examples/infinite-context-length/training_logs/{run_name}_data_logs.txt",
                             "a",
                         ) as file:
                             # Write the self.idx number and the decoded text to the file
-                            file.write(f"idx: {self.idx}\n")
-
-                            for i, text in enumerate(decoded_texts):
-                                file.write(f"####### text_i = {i}\n")
-                                file.write(text + "\n\n\n")
+                            file.write(f"iteration_step: {constants.GLOBAL_STEP}\n")
+
+                            # for i, text in enumerate(decoded_texts):
+                            text = decoded_texts[sample_index]
+                            file.write(
+                                f"####### sample_index = {sample_index}, num_tokens={len(micro_batch['input_ids'][sample_index])}\n"
+                            )
+                            file.write(f"raw_tokens: {micro_batch['input_ids'][sample_index].tolist()}" + "\n\n\n")
+                            file.write(f"decoded_text: {text}" + "\n\n\n")
 
                 context = self._get_fwd_context(model=model)
                 output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
diff --git a/src/nanotron/trainer.py b/src/nanotron/trainer.py
index 5fa872f3..e6b26534 100644
--- a/src/nanotron/trainer.py
+++ b/src/nanotron/trainer.py
@@ -23,8 +23,8 @@
 from torch.nn.parallel import DistributedDataParallel
 from torch.utils.data import DataLoader
 
+from nanotron import constants, logging
 from nanotron import distributed as dist
-from nanotron import logging
 from nanotron.config import (
     Config,
     DatasetStageArgs,
@@ -131,6 +131,7 @@ def __init__(
         self.config = get_config_from_file(
             config_or_config_file, config_class=config_class, model_config_class=model_config_class
         )
+        constants.CONFIG = self.config
         self.model_config = self.config.model.model_config
         if model_class is not None:
             CONFIG_TO_MODEL_CLASS[self.model_config.__class__.__name__] = model_class
@@ -194,7 +195,11 @@ def __init__(
                 #     parallel_context=self.parallel_context, root_folder=self.init_checkpoint_path
                 # )
 
-                prev_config = get_config_from_file((self.init_checkpoint_path / "config.yaml").as_posix())
+                prev_config = get_config_from_file(
+                    (self.init_checkpoint_path / "config.yaml").as_posix(),
+                    config_class=config_class,
+                    model_config_class=model_config_class,
+                )
                 if (
                     prev_config.optimizer.accumulate_grad_in_fp32 is False
                     and self.config.optimizer.accumulate_grad_in_fp32 is True
@@ -426,14 +431,13 @@ def train(
         torch.cuda.empty_cache()
         with prof:
             for self.iteration_step in range(self.start_iteration_step + 1, self.config.tokens.train_steps + 1):
-                from nanotron import constants
-
                 constants.GLOBAL_STEP = self.iteration_step
 
                 if isinstance(prof, torch.profiler.profile):
                     prof.step()
 
-                nn_logs, nn_handles = monitor_nanotron_model(self.model, self.parallel_context)
+                if (self.iteration_step - 1) % constants.LOG_STATE_INTERVAL == 0:
+                    nn_logs, nn_handles = monitor_nanotron_model(self.model, self.parallel_context)
 
                 self.iteration_start_time = time.time()
                 self._update_dataloader_based_on_training_stages(dataloader_or_dls)
@@ -447,13 +451,14 @@ def train(
                 if (self.iteration_step - 1) % self.config.logging.iteration_step_info_interval == 0:
                     self.train_step_logs(outputs=outputs, loss_avg=loss_avg)
 
-                if dist.get_rank(self.parallel_context.world_pg) == self.logger_ranks[0] and wandb is not None:
+                if (self.iteration_step - 1) % constants.LOG_STATE_INTERVAL == 0:
                     from nanotron.debug.monitor import convert_logs_to_flat_logs
 
-                    wandb.log({**convert_logs_to_flat_logs(nn_logs), "iteration_step": self.iteration_step})
+                    if dist.get_rank(self.parallel_context.world_pg) == self.logger_ranks[0] and wandb is not None:
+                        wandb.log({**convert_logs_to_flat_logs(nn_logs), "iteration_step": self.iteration_step})
 
-                for handle in nn_handles:
-                    handle.remove()
+                    for handle in nn_handles:
+                        handle.remove()
 
                 # Checkpoint
                 if self.iteration_step % self.config.checkpoints.checkpoint_interval == 0:
@@ -471,10 +476,13 @@ def training_step(
         if self.iteration_step < 5:
             log_memory(logger=logger)
 
+        train_batches = (next(dataloader) for _ in range(self.n_micro_batches_per_batch))
+        assert 1 == 1
+
         outputs = self.pipeline_engine.train_batch_iter(
             model=self.model,
             pg=self.parallel_context.pp_pg,
-            batch=(next(dataloader) for _ in range(self.n_micro_batches_per_batch)),
+            batch=train_batches,
             nb_microbatches=self.n_micro_batches_per_batch,
             grad_accumulator=self.grad_accumulator,
         )
@@ -677,6 +685,12 @@ def init_model(self) -> Union[NanotronModel, DistributedDataParallel]:
                     rank=0,
                 )
             else:
+                log_rank(
+                    f"max_position_embeddings is {self.model_config.max_position_embeddings} and sequence_length is {self.config.tokens.sequence_length}. But i don't set it here",
+                    logger=logger,
+                    level=logging.INFO,
+                    rank=0,
+                )
                 # log_rank(
                 #     f"Setting max_position_embeddings to {self.config.tokens.sequence_length}. Previous value was {self.model_config.max_position_embeddings}.",
                 #     logger=logger,

From 4e18fac57d8df89255dfc458ac8b00cbeb5e3698 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Wed, 29 May 2024 12:34:47 +0000
Subject: [PATCH 24/43] save run evals and generate data

---
 .../infinite-context-length/generate_data.py  |   24 +-
 examples/infinite-context-length/run_evals.py | 2874 +++++++++++++++++
 run_generate.py                               |   14 +-
 3 files changed, 2901 insertions(+), 11 deletions(-)
 create mode 100644 examples/infinite-context-length/run_evals.py

diff --git a/examples/infinite-context-length/generate_data.py b/examples/infinite-context-length/generate_data.py
index 394f785d..48eace62 100644
--- a/examples/infinite-context-length/generate_data.py
+++ b/examples/infinite-context-length/generate_data.py
@@ -10,6 +10,20 @@
 PROMPT = "{} {}. \n\n{}"
 
 
+def get_keys_in_train_set():
+    from datasets import load_dataset
+
+    dataset = load_dataset("nanotron/needle_32k_finetuning_dataset")
+
+    unique_answers = set()
+    for split in dataset.keys():
+        for example in dataset[split]:
+            answer = example["answer"]
+            unique_answers.add(answer)
+
+    return unique_answers
+
+
 def token_length(tokenizer, text):
     # Exclude EOS token
     return len(tokenizer.encode(text))
@@ -143,6 +157,8 @@ def get_args():
     start_range = 1000 * (depth_percent + 1) * id
     end_range = start_range + start_range
 
+    keys_in_train_set = get_keys_in_train_set()
+
     print(
         f"Generating prompts for context length: {context_length} and depth percent: {depth_percent} and id: {id} \n"
     )
@@ -150,7 +166,7 @@ def get_args():
 
     def generate_dataset():
         # num_prompts = 1700
-        num_prompts = 100
+        num_prompts = 5
         # soft_prompt = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there."
         soft_prompt = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on."
         # context_lengths = [
@@ -170,12 +186,12 @@ def generate_dataset():
 
             while True:
                 pass_key = random.randint(start_range, end_range)
-                if pass_key not in generated_pass_keys:
+                if pass_key not in keys_in_train_set and pass_key not in generated_pass_keys:
                     generated_pass_keys.add(pass_key)
                     break
 
             needle_prompt = f". The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
-            retrieval_question = f"What is the pass key? The pass key is {pass_key}."
+            retrieval_question = "What is the pass key? The pass key is "
 
             prompt = generate_needle_in_haystack_test(
                 pass_key,
@@ -207,6 +223,6 @@ def generate_dataset():
 
     # Save the dataset to disk
     dataset.save_to_disk(
-        f"/fsx/phuc/projects/nanotron/examples/infinite-context-length/needle_finetune_datasets/needle_finetuning_ctx_len_32768_and_depth_{depth_percent}_and_id_{id}"
+        f"/fsx/phuc/projects/nanotron/examples/infinite-context-length/needle_eval_datasets/needle_eval_ctx_len_32768_and_depth_{depth_percent}_and_id_{id}"
     )
     # dataset.push_to_hub("nanotron/needle_in_a_hay_stack_finetuning_dataset")
diff --git a/examples/infinite-context-length/run_evals.py b/examples/infinite-context-length/run_evals.py
new file mode 100644
index 00000000..98f18e20
--- /dev/null
+++ b/examples/infinite-context-length/run_evals.py
@@ -0,0 +1,2874 @@
+"""
+Nanotron Inference Script
+
+Usage:
+```
+export CUDA_DEVICE_MAX_CONNECTIONS=1 # important for some distributed operations
+torchrun --nproc_per_node=4 run_generate.py ---ckpt-path checkpoints/test/4
+```
+"""
+
+import argparse
+import os
+from pathlib import Path
+
+import torch
+from nanotron import distributed as dist
+from nanotron import logging
+from nanotron.config import (
+    GenerationArgs,
+    LoggingArgs,
+    ParallelismArgs,
+    get_config_from_file,
+)
+from nanotron.generation.decode import (
+    GenerationInput,
+    TokenizerConfig,
+    decode_text,
+)
+from nanotron.logging import log_rank, set_ranks_logging_level
+from nanotron.models import build_model
+from nanotron.parallel import ParallelContext
+from nanotron.parallel.parameters import sanity_check
+from nanotron.parallel.pipeline_parallel.engine import (
+    OneForwardOneBackwardPipelineEngine,
+)
+from nanotron.parallel.pipeline_parallel.tensor_pointer import TensorPointer
+from nanotron.parallel.tensor_parallel.enum import TensorParallelLinearMode
+from nanotron.random import (
+    RandomStates,
+    get_current_random_state,
+    get_synced_random_state,
+    set_random_seed,
+)
+from nanotron.serialize import load_weights
+from nanotron.trainer import CONFIG_TO_MODEL_CLASS, mark_tied_parameters
+
+try:
+    from transformers import AutoTokenizer
+except ImportError:
+    AutoTokenizer = None
+
+logger = logging.get_logger(__name__)
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--ckpt-path", type=Path, required=True, help="Checkpoint path")
+    parser.add_argument("--dp", type=int, default=0)
+    parser.add_argument("--pp", type=int, default=0)
+    parser.add_argument("--tp", type=int, default=0)
+    parser.add_argument("--max-new-tokens", type=int, default=30, help="Maximum number of new tokens to generate")
+    parser.add_argument("--context_length", type=int, required=True)
+    parser.add_argument("--depth_percent", type=int, required=True)
+    return parser.parse_args()
+
+
+def generate(args, model, tokenizer, inputs, parallel_context) -> bool:
+    outputs = decode_text(
+        input_iter=(GenerationInput(text=text) for text in inputs),
+        tokenizer=tokenizer,
+        # TODO @thomasw21: From ModelWithLoss extract the model.
+        model=model.model,
+        parallel_context=parallel_context,
+        max_new_tokens=args.max_new_tokens,
+        max_micro_batch_size=1,
+        generation_config=GenerationArgs(sampler="greedy", use_cache=False),
+        tokenizer_config=TokenizerConfig(max_input_length=None),
+        is_bench=os.environ.get("USE_BENCH", "0") == "1",
+    )
+    responses = []
+    for output in outputs:
+        input_ids = output.input_ids
+        generated_ids = output.generation_ids
+        answer_ids = generated_ids[len(input_ids) :]
+        decoded_answer = tokenizer.decode(answer_ids, clean_up_tokenization_spaces=False)
+
+        if isinstance(input_ids, TensorPointer):
+            assert isinstance(generated_ids, TensorPointer)
+            continue
+        assert isinstance(generated_ids, torch.Tensor)
+
+        log_rank(
+            # f"input: {tokenizer.decode(input_ids, clean_up_tokenization_spaces=False)[:1000]}",
+            f"input: {tokenizer.decode(input_ids, clean_up_tokenization_spaces=False)}",
+            logger=logger,
+            level=logging.INFO,
+            rank=0,
+        )
+
+        log_rank(
+            f"generation: {decoded_answer}",
+            logger=logger,
+            level=logging.INFO,
+            rank=0,
+        )
+
+        log_rank(
+            "--------------------------------------------------",
+            logger=logger,
+            level=logging.INFO,
+            rank=0,
+        )
+
+        responses.append(decoded_answer)
+
+    return responses
+
+
+TEXT = """The United States Army (USA) is the land service branch of the United States Armed Forces. It is one of the eight U.S. uniformed services, and is designated as the Army of the United States in the U.S. Constitution.[14] The Army is the oldest branch of the U.S. military and the most senior in order of precedence.[15] It has its roots in the Continental Army, which was formed on 14 June 1775 to fight against the British for independence during the American Revolutionary War (1775–1783).[16] After the Revolutionary War, the Congress of the Confederation created the United States Army on 3 June 1784 to replace the disbanded Continental Army.[17][18] The United States Army considers itself a continuation of the Continental Army, and thus considers its institutional inception to be the origin of that armed force in 1775.[16]
+
+The U.S. Army is a uniformed service of the United States and is part of the Department of the Army, which is one of the three military departments of the Department of Defense. The U.S. Army is headed by a civilian senior appointed civil servant, the secretary of the Army (SECARMY), and by a chief military officer, the chief of staff of the Army (CSA) who is also a member of the Joint Chiefs of Staff. It is the largest military branch, and in the fiscal year 2022, the projected end strength for the Regular Army (USA) was 480,893 soldiers; the Army National Guard (ARNG) had 336,129 soldiers and the U.S. Army Reserve (USAR) had 188,703 soldiers; the combined-component strength of the U.S. Army was 1,005,725 soldiers.[19] As a branch of the armed forces, the mission of the U.S. Army is 'to fight and win our Nation's wars, by providing prompt, sustained land dominance, across the full range of military operations and the spectrum of conflict, in support of combatant commanders'.[20] The branch participates in conflicts worldwide and is the major ground-based offensive and defensive force of the United States of America.‌
+
+Mission
+The United States Army serves as the land-based branch of the U.S. Armed Forces. Section 7062 of Title 10, U.S. Code defines the purpose of the army as:[21][22]
+
+Preserving the peace and security and providing for the defense of the United States, the Commonwealths and possessions, and any areas occupied by the United States
+Supporting the national policies
+Implementing the national objectives
+Overcoming any nations responsible for aggressive acts that imperil the peace and security of the United States
+In 2018, the Army Strategy 2018 articulated an eight-point addendum to the Army Vision for 2028.[23] While the Army Mission remains constant, the Army Strategy builds upon the Army's Brigade Modernization by adding focus to corps and division-level echelons.[23] The Army Futures Command oversees reforms geared toward conventional warfare. The Army's current reorganization plan is due to be completed by 2028.[23]
+
+The Army's five core competencies are prompt and sustained land combat, combined arms operations (to include combined arms maneuver and wide–area security, armored and mechanized operations and airborne and air assault operations), special operations forces, to set and sustain the theater for the joint force, and to integrate national, multinational, and joint power on land.[24]
+
+History
+Main article: History of the United States Army
+Origins
+The Continental Army was created on 14 June 1775 by the Second Continental Congress[25] as a unified army for the colonies to fight Great Britain, with George Washington appointed as its commander.[16][26][27][28] The army was initially led by men who had served in the British Army or colonial militias and who brought much of British military heritage with them. As the Revolutionary War progressed, French aid, resources, and military thinking helped shape the new army. A number of European soldiers came on their own to help, such as Friedrich Wilhelm von Steuben, who taught Prussian Army tactics and organizational skills.
+
+
+The storming of Redoubt No. 10 in the Siege of Yorktown during the American Revolutionary War prompted Great Britain's government to begin negotiations, resulting in the Treaty of Paris and Great Britain's recognition of the United States as an independent state.
+The Army fought numerous pitched battles, and sometimes used Fabian strategy and hit-and-run tactics in the South in 1780 and 1781; under Major General Nathanael Greene, it hit where the British were weakest to wear down their forces. Washington led victories against the British at Trenton and Princeton, but lost a series of battles in the New York and New Jersey campaign in 1776 and the Philadelphia campaign in 1777. With a decisive victory at Yorktown and the help of the French, the Continental Army prevailed against the British.
+
+After the war, the Continental Army was quickly given land certificates and disbanded in a reflection of the republican distrust of standing armies. State militias became the new nation's sole ground army, except a regiment to guard the Western Frontier and one battery of artillery guarding West Point's arsenal. However, because of continuing conflict with Native Americans, it was soon considered necessary to field a trained standing army. The Regular Army was at first very small and after General St. Clair's defeat at the Battle of the Wabash,[29] where more than 800 soldiers were killed, the Regular Army was reorganized as the Legion of the United States, established in 1791 and renamed the United States Army in 1796.
+
+In 1798, during the Quasi-War with France, the U.S. Congress established a three-year 'Provisional Army' of 10,000 men, consisting of twelve regiments of infantry and six troops of light dragoons. In March 1799, Congress created an 'Eventual Army' of 30,000 men, including three regiments of cavalry. Both 'armies' existed only on paper, but equipment for 3,000 men and horses was procured and stored.[30]
+
+19th century
+War of 1812 and Indian Wars
+Further information: War of 1812 and Army on the Frontier
+
+General Andrew Jackson standing on the parapet of his makeshift defenses as his troops repulse attacking Highlanders during the defense of New Orleans, the final major and most one-sided battle of the War of 1812, mainly fought by militia and volunteers.
+The War of 1812, the second and last war between the United States and Great Britain, had mixed results. The U.S. Army did not conquer Canada but it did destroy Native American resistance to expansion in the Old Northwest and it validated its independence by stopping two major British invasions in 1814 and 1815. After taking control of Lake Erie in 1813, the U.S. Army seized parts of western Upper Canada, burned York and defeated Tecumseh, which caused his Western Confederacy to collapse. Following U.S. victories in the Canadian province of Upper Canada, British troops who had dubbed the U.S. Army 'Regulars, by God!', were able to capture and burn Washington, which was defended by militia, in 1814. The regular army, however, proved they were professional and capable of defeating the British army during the invasions of Plattsburgh and Baltimore, prompting British agreement on the previously rejected terms of a status quo antebellum.[dubious – discuss] Two weeks after a treaty was signed (but not ratified), Andrew Jackson defeated the British in the Battle of New Orleans and siege of Fort St. Philip with an army dominated by militia and volunteers, and became a national hero. U.S. troops and sailors captured HMS Cyane, Levant and Penguin in the final engagements of the war. Per the treaty, both sides (the United States and Great Britain) returned to the geographical status quo. Both navies kept the warships they had seized during the conflict.
+
+The army's major campaign against the Indians was fought in Florida against Seminoles. It took long wars (1818–1858) to finally defeat the Seminoles and move them to Oklahoma. The usual strategy in Indian wars was to seize control of the Indians' winter food supply, but that was no use in Florida where there was no winter. The second strategy was to form alliances with other Indian tribes, but that too was useless because the Seminoles had destroyed all the other Indians when they entered Florida in the late eighteenth century.[31]
+
+The U.S. Army fought and won the Mexican–American War (1846–1848), which was a defining event for both countries.[32] The U.S. victory resulted in acquisition of territory that eventually became all or parts of the states of California, Nevada, Utah, Colorado, Arizona, Wyoming and New Mexico.
+
+American Civil War
+Further information: Union Army
+
+The Battle of Gettysburg, the turning point of the American Civil War
+The American Civil War was the costliest war for the U.S. in terms of casualties. After most slave states, located in the southern U.S., formed the Confederate States, the Confederate States Army, led by former U.S. Army officers, mobilized a large fraction of Southern white manpower. Forces of the United States (the 'Union' or 'the North') formed the Union Army, consisting of a small body of regular army units and a large body of volunteer units raised from every state, north and south, except South Carolina.[33]
+
+For the first two years, Confederate forces did well in set battles but lost control of the border states.[34] The Confederates had the advantage of defending a large territory in an area where disease caused twice as many deaths as combat. The Union pursued a strategy of seizing the coastline, blockading the ports, and taking control of the river systems. By 1863, the Confederacy was being strangled. Its eastern armies fought well, but the western armies were defeated one after another until the Union forces captured New Orleans in 1862 along with the Tennessee River. In the Vicksburg Campaign of 1862–1863, General Ulysses Grant seized the Mississippi River and cut off the Southwest. Grant took command of Union forces in 1864 and after a series of battles with very heavy casualties, he had General Robert E. Lee under siege in Richmond as General William T. Sherman captured Atlanta and marched through Georgia and the Carolinas. The Confederate capital was abandoned in April 1865 and Lee subsequently surrendered his army at Appomattox Court House. All other Confederate armies surrendered within a few months.
+
+The war remains the deadliest conflict in U.S. history, resulting in the deaths of 620,000 men on both sides. Based on 1860 census figures, 8% of all white males aged 13 to 43 died in the war, including 6.4% in the North and 18% in the South.[35]
+
+Later 19th century
+
+Army soldiers in 1890
+Following the Civil War, the U.S. Army had the mission of containing western tribes of Native Americans on the Indian reservations. They set up many forts, and engaged in the last of the American Indian Wars. U.S. Army troops also occupied several Southern states during the Reconstruction Era to protect freedmen.
+
+The key battles of the Spanish–American War of 1898 were fought by the Navy. Using mostly new volunteers, the U.S. forces defeated Spain in land campaigns in Cuba and played the central role in the Philippine–American War.
+
+20th century
+Starting in 1910, the army began acquiring fixed-wing aircraft.[36] In 1910, during the Mexican Revolution, the army was deployed to U.S. towns near the border to ensure the safety of lives and property. In 1916, Pancho Villa, a major rebel leader, attacked Columbus, New Mexico, prompting a U.S. intervention in Mexico until 7 February 1917. They fought the rebels and the Mexican federal troops until 1918.
+
+World Wars
+For a list of campaigns see List of United States Army campaigns during World War II
+
+U.S. Army troops assaulting a German bunker in France, c. 1918
+The United States joined World War I as an 'Associated Power' in 1917 on the side of Britain, France, Russia, Italy and the other Allies. U.S. troops were sent to the Western Front and were involved in the last offensives that ended the war. With the armistice in November 1918, the army once again decreased its forces.
+
+In 1939, estimates of the Army's strength ranged between 174,000 and 200,000 soldiers, smaller than that of Portugal's, which ranked it 17th or 19th in the world in size. General George C. Marshall became Army chief of staff in September 1939 and set about expanding and modernizing the Army in preparation for war.[37][38]
+
+
+U.S. soldiers hunting for Japanese infiltrators during the Bougainville Campaign
+The United States joined World War II in December 1941 after the Japanese attack on Pearl Harbor. Some 11 million Americans were to serve in various Army operations.[39][40] On the European front, U.S. Army troops formed a significant portion of the forces that landed in French North Africa and took Tunisia and then moved on to Sicily and later fought in Italy. In the June 1944 landings in northern France and in the subsequent liberation of Europe and defeat of Nazi Germany, millions of U.S. Army troops played a central role. In 1947, the number of soldiers in the US Army had decreased from eight million in 1945 to 684,000 soldiers and the total number of active divisions had dropped from 89 to 12. The leaders of the Army saw this demobilization as a success.[41] In the Pacific War, U.S. Army soldiers participated alongside the United States Marine Corps in capturing the Pacific Islands from Japanese control. Following the Axis surrenders in May (Germany) and August (Japan) of 1945, army troops were deployed to Japan and Germany to occupy the two defeated nations. Two years after World War II, the Army Air Forces separated from the army to become the United States Air Force in September 1947. In 1948, the army was desegregated by order 9981 of President Harry S. Truman.
+
+Cold War
+1945–1960
+
+U.S. Army soldiers observing an atomic bomb test of Operation Buster-Jangle at the Nevada Test Site during the Korean War
+The end of World War II set the stage for the East–West confrontation known as the Cold War. With the outbreak of the Korean War, concerns over the defense of Western Europe rose. Two corps, V and VII, were reactivated under Seventh United States Army in 1950 and U.S. strength in Europe rose from one division to four. Hundreds of thousands of U.S. troops remained stationed in West Germany, with others in Belgium, the Netherlands and the United Kingdom, until the 1990s in anticipation of a possible Soviet attack.[42]: minute 9:00–10:00
+
+
+US tanks and Soviet tanks at Checkpoint Charlie, 1961
+During the Cold War, U.S. troops and their allies fought communist forces in Korea and Vietnam. The Korean War began in June 1950, when the Soviets walked out of a UN Security Council meeting, removing their possible veto. Under a United Nations umbrella, hundreds of thousands of U.S. troops fought to prevent the takeover of South Korea by North Korea and later to invade the northern nation. After repeated advances and retreats by both sides and the Chinese People's Volunteer Army's entry into the war, the Korean Armistice Agreement returned the peninsula to the status quo in July 1953.
+
+1960–1970
+The Vietnam War is often regarded as a low point for the U.S. Army due to the use of drafted personnel, the unpopularity of the war with the U.S. public and frustrating restrictions placed on the military by U.S. political leaders. While U.S. forces had been stationed in South Vietnam since 1959, in intelligence and advising/training roles, they were not deployed in large numbers until 1965, after the Gulf of Tonkin Incident. U.S. forces effectively established and maintained control of the 'traditional' battlefield, but they struggled to counter the guerrilla hit and run tactics of the communist Viet Cong and the People's Army Of Vietnam (NVA).[43][44]
+
+
+A U.S. Army infantry patrol moving up to assault the last North Vietnamese Army position at Dak To, South Vietnam during Operation Hawthorne
+During the 1960s, the Department of Defense continued to scrutinize the reserve forces and to question the number of divisions and brigades as well as the redundancy of maintaining two reserve components, the Army National Guard and the Army Reserve.[45] In 1967, Secretary of Defense Robert McNamara decided that 15 combat divisions in the Army National Guard were unnecessary and cut the number to eight divisions (one mechanized infantry, two armored, and five infantry), but increased the number of brigades from seven to 18 (one airborne, one armored, two mechanized infantry and 14 infantry). The loss of the divisions did not sit well with the states. Their objections included the inadequate maneuver element mix for those that remained and the end to the practice of rotating divisional commands among the states that supported them. Under the proposal, the remaining division commanders were to reside in the state of the division base. However, no reduction in total Army National Guard strength was to take place, which convinced the governors to accept the plan. The states reorganized their forces accordingly between 1 December 1967 and 1 May 1968.
+
+1970–1990
+
+U.S. Army soldiers preparing to take La Comandancia in the El Chorrillo neighborhood of Panama City during Operation Just Cause
+The Total Force Policy was adopted by Chief of Staff of the Army General Creighton Abrams in the aftermath of the Vietnam War and involved treating the three components of the army – the Regular Army, the Army National Guard and the Army Reserve as a single force.[46] General Abrams' intertwining of the three components of the army effectively made extended operations impossible without the involvement of both the Army National Guard and Army Reserve in a predominantly combat support role.[47] The army converted to an all-volunteer force with greater emphasis on training to specific performance standards driven by the reforms of General William E. DePuy, the first commander of United States Army Training and Doctrine Command. Following the Camp David Accords that was signed by Egypt, Israel that was brokered by president Jimmy Carter in 1978, as part of the agreement, both the United States and Egypt agreed that there would be a joint military training led by both countries that would usually take place every 2 years, that exercise is known as Exercise Bright Star.
+
+The 1980s was mostly a decade of reorganization. The Goldwater-Nichols Act of 1986 created unified combatant commands bringing the army together with the other four military services under unified, geographically organized command structures. The army also played a role in the invasions of Grenada in 1983 (Operation Urgent Fury) and Panama in 1989 (Operation Just Cause).
+
+By 1989 Germany was nearing reunification and the Cold War was coming to a close. Army leadership reacted by starting to plan for a reduction in strength. By November 1989 Pentagon briefers were laying out plans to reduce army end strength by 23%, from 750,000 to 580,000.[48] A number of incentives such as early retirement were used.
+
+1990s
+
+M1 Abrams tanks moving out before the Battle of Al Busayyah during the Gulf War
+In 1990, Iraq invaded its smaller neighbor, Kuwait, and U.S. land forces quickly deployed to assure the protection of Saudi Arabia. In January 1991 Operation Desert Storm commenced, a U.S.-led coalition which deployed over 500,000 troops, the bulk of them from U.S. Army formations, to drive out Iraqi forces. The campaign ended in total victory, as Western coalition forces routed the Iraqi Army. Some of the largest tank battles in history were fought during the Gulf war. The Battle of Medina Ridge, Battle of Norfolk and the Battle of 73 Easting were tank battles of historical significance.[49][50][51]
+
+
+Iraqi tanks destroyed by Task Force 1-41 Infantry during the Gulf War, February 1991
+After Operation Desert Storm, the army did not see major combat operations for the remainder of the 1990s but did participate in a number of peacekeeping activities. In 1990 the Department of Defense issued guidance for 'rebalancing' after a review of the Total Force Policy,[52] but in 2004, USAF Air War College scholars concluded the guidance would reverse the Total Force Policy which is an 'essential ingredient to the successful application of military force'.[53]
+
+21st century
+
+U.S. Army Rangers taking part in a raid during an operation in Nahr-e Saraj, Afghanistan
+On 11 September 2001, 53 Army civilians (47 employees and six contractors) and 22 soldiers were among the 125 victims killed in the Pentagon in a terrorist attack when American Airlines Flight 77 commandeered by five Al-Qaeda hijackers slammed into the western side of the building, as part of the September 11 attacks.[54] In response to the 11 September attacks and as part of the Global War on Terror, U.S. and NATO forces invaded Afghanistan in October 2001, displacing the Taliban government. The U.S. Army also led the combined U.S. and allied invasion of Iraq in 2003; it served as the primary source for ground forces with its ability to sustain short and long-term deployment operations. In the following years, the mission changed from conflict between regular militaries to counterinsurgency, resulting in the deaths of more than 4,000 U.S. service members (as of March 2008) and injuries to thousands more.[55][56] 23,813 insurgents were killed in Iraq between 2003 and 2011.[57]
+
+
+U.S. Army soldiers with the 2nd Battalion, 327th Infantry Regiment, 101st Airborne Division returning fire during a firefight with Taliban forces in Barawala Kalay Valley in Kunar province, Afghanistan, March 2011
+Until 2009, the army's chief modernization plan, its most ambitious since World War II,[58] was the Future Combat Systems program. In 2009, many systems were canceled, and the remaining were swept into the BCT modernization program.[59] By 2017, the Brigade Modernization project was completed and its headquarters, the Brigade Modernization Command, was renamed the Joint Modernization Command, or JMC.[60] In response to Budget sequestration in 2013, Army plans were to shrink to 1940 levels,[61] although actual Active-Army end-strengths were projected to fall to some 450,000 troops by the end of FY2017.[62][63] From 2016 to 2017, the Army retired hundreds of OH-58 Kiowa Warrior observation helicopters,[64] while retaining its Apache gunships.[65] The 2015 expenditure for Army research, development and acquisition changed from $32 billion projected in 2012 for FY15 to $21 billion for FY15 expected in 2014.[66]
+
+Organization
+
+Organization of the United States Army within the Department of Defense
+Planning
+By 2017, a task force was formed to address Army modernization,[67] which triggered shifts of units: CCDC, and ARCIC, from within Army Materiel Command (AMC), and Army Training and Doctrine Command (TRADOC), respectively, to a new Army Command (ACOM) in 2018.[68] The Army Futures Command (AFC), is a peer of FORSCOM, TRADOC, and AMC, the other ACOMs.[69] AFC's mission is modernization reform: to design hardware, as well as to work within the acquisition process which defines materiel for AMC. TRADOC's mission is to define the architecture and organization of the Army, and to train and supply soldiers to FORSCOM.[70]: minutes 2:30–15:00 [42] AFC's cross-functional teams (CFTs) are Futures Command's vehicle for sustainable reform of the acquisition process for the future.[71] In order to support the Army's modernization priorities, its FY2020 budget allocated $30 billion for the top six modernization priorities over the next five years.[72] The $30 billion came from $8 billion in cost avoidance and $22 billion in terminations.[72]
+
+Army Components
+See also: Structure of the United States Army
+
+U.S. Army organization chart[73]
+The task of organizing the U.S. Army commenced in 1775.[74] In the first one hundred years of its existence, the United States Army was maintained as a small peacetime force to man permanent forts and perform other non-wartime duties such as engineering and construction works. During times of war, the U.S. Army was augmented by the much larger United States Volunteers which were raised independently by various state governments. States also maintained full-time militias which could also be called into the service of the army.
+
+
+Senior American commanders of the European theatre of World War II.
+*Seated are (from left to right) Generals William H. Simpson, George S. Patton, Carl A. Spaatz, Dwight D. Eisenhower, Omar Bradley, Courtney H. Hodges, and Leonard T. Gerow
+*standing are (from left to right) Generals Ralph F. Stearley, Hoyt Vandenberg, Walter Bedell Smith, Otto P. Weyland, and Richard E. Nugent
+By the twentieth century, the U.S. Army had mobilized the U.S. Volunteers on four occasions during each of the major wars of the nineteenth century. During World War I, the 'National Army' was organized to fight the conflict, replacing the concept of U.S. Volunteers.[75] It was demobilized at the end of World War I, and was replaced by the Regular Army, the Organized Reserve Corps and the state militias. In the 1920s and 1930s, the 'career' soldiers were known as the 'Regular Army' with the 'Enlisted Reserve Corps' and 'Officer Reserve Corps' augmented to fill vacancies when needed.[76]
+
+In 1941, the 'Army of the United States' was founded to fight World War II. The Regular Army, Army of the United States, the National Guard and Officer/Enlisted Reserve Corps (ORC and ERC) existed simultaneously. After World War II, the ORC and ERC were combined into the United States Army Reserve. The Army of the United States was re-established for the Korean War and Vietnam War and was demobilized upon the suspension of the draft.[76]
+
+Currently, the Army is divided into the Regular Army, the Army Reserve and the Army National Guard.[75] Some states further maintain state defense forces, as a type of reserve to the National Guard, while all states maintain regulations for state militias.[77] State militias are both 'organized', meaning that they are armed forces usually part of the state defense forces, or 'unorganized' simply meaning that all able-bodied males may be eligible to be called into military service.
+
+The U.S. Army is also divided into several branches and functional areas. Branches include officers, warrant officers, and enlisted Soldiers while functional areas consist of officers who are reclassified from their former branch into a functional area. However, officers continue to wear the branch insignia of their former branch in most cases, as functional areas do not generally have discrete insignia. Some branches, such as Special Forces, operate similarly to functional areas in that individuals may not join their ranks until having served in another Army branch. Careers in the Army can extend into cross-functional areas for officer,[78] warrant officer, enlisted, and civilian personnel.
+
+U.S. Army branches and functional areas
+Branch	Insignia and colors		Branch	Insignia and colors		Functional Area (FA)
+Acquisition Corps (AC)			Air Defense Artillery (AD)			Information Network Engineering (FA 26)
+Adjutant General's Corps (AG)
+Includes Army Bands (AB)	 		Armor (AR)
+Includes Cavalry (CV)	 		Information Operations (FA 30)
+Aviation (AV)			Civil Affairs Corps (CA)			Strategic Intelligence (FA 34)
+Chaplain Corps (CH)
+  		Chemical Corps (CM)			Space Operations (FA 40)
+Cyber Corps (CY)			Dental Corps (DC)			Public Affairs Officer (FA 46)
+Corps of Engineers (EN)			Field Artillery (FA)			Academy Professor (FA 47)
+Finance Corps (FI)			Infantry (IN)			Foreign Area Officer (FA 48)
+Inspector General (IG)			Logistics (LG)			Operations Research/Systems Analysis (FA 49)
+Judge Advocate General's Corps (JA)			Military Intelligence Corps (MI)			Force Management (FA 50)
+Medical Corps (MC)			Medical Service Corps (MS)			Acquisition (FA 51)[78]
+Military Police Corps (MP)			Army Nurse Corps (AN)			Simulation Operations (FA 57)
+Psychological Operations (PO)			Medical Specialist Corps (SP)			Army Marketing (FA 58)[79]
+Quartermaster Corps (QM)			Staff Specialist Corps (SS)
+(USAR and ARNG only)			Health Services (FA 70)
+Special Forces (SF)			Ordnance Corps (OD)			Laboratory Sciences (FA 71)
+Veterinary Corps (VC)			Public Affairs (PA)			Preventive Medicine Sciences (FA 72)
+Transportation Corps (TC)			Signal Corps (SC)			Behavioral Sciences (FA 73)
+Special branch insignias (for some unique duty assignments)
+National Guard Bureau (NGB)			General Staff			U.S. Military Academy Staff
+Chaplain Candidate			Officer Candidate			Warrant Officer Candidate
+Aide-de-camp
+               		Senior Enlisted Advisor (SEA)
+
+Before 1933, members of the Army National Guard were considered state militia until they were mobilized into the U.S. Army, typically on the onset of war. Since the 1933 amendment to the National Defense Act of 1916, all Army National Guard soldiers have held dual status. They serve as National Guardsmen under the authority of the governor of their state or territory and as reserve members of the U.S. Army under the authority of the president, in the Army National Guard of the United States.
+
+Since the adoption of the total force policy, in the aftermath of the Vietnam War, reserve component soldiers have taken a more active role in U.S. military operations. For example, Reserve and Guard units took part in the Gulf War, peacekeeping in Kosovo, Afghanistan, and the 2003 invasion of Iraq.
+
+Army commands and army service component commands
+ Headquarters, United States Department of the Army (HQDA):
+
+Army Commands	Current commander	Location of headquarters[c]
+ United States Army Forces Command (FORSCOM)[80]	GEN Andrew P. Poppas	Fort Liberty, North Carolina
+ United States Army Futures Command (AFC)[81]	GEN James E. Rainey	Austin, Texas
+ United States Army Materiel Command (AMC)[82]	LTG Christopher O. Mohan (acting)	Redstone Arsenal, Alabama
+ United States Army Training and Doctrine Command (TRADOC)[83]	GEN Gary M. Brito	Fort Eustis, Virginia
+Army Service Component Commands	Current commander	Location of headquarters
+ United States Army Central (ARCENT)/Third Army[84]	LTG Patrick D. Frank	Shaw Air Force Base, South Carolina
+ United States Army Europe and Africa/Seventh Army	GEN Darryl A. Williams[85]	Clay Kaserne, Wiesbaden, Germany
+ United States Army North (ARNORTH)/Fifth Army[86]	LTG John R. Evans Jr.	Joint Base San Antonio, Texas
+ United States Army Pacific (USARPAC)[87]	GEN Charles A. Flynn	Fort Shafter, Hawaii
+ United States Army South (ARSOUTH)/Sixth Army[88]	MG William L. Thigpen	Joint Base San Antonio, Texas
+ Military Surface Deployment and Distribution Command (SDDC)[89]	MG Gavin A. Lawrence	Scott AFB, Illinois
+ United States Army Cyber Command (ARCYBER)[90][91][92]	LTG Maria B. Barrett	Fort Eisenhower, Georgia
+ United States Army Space and Missile Defense Command/United States Army Forces Strategic Command (USASMDC/ARSTRAT)[93]	LTG Daniel L. Karbler	Redstone Arsenal, Alabama
+ United States Army Special Operations Command (USASOC)[94]	LTG Jonathan P. Braga	Fort Liberty, North Carolina
+Operational Force Headquarters	Current commander	Location of headquarters
+ Eighth Army (EUSA)[95]	LTG Willard M. Burleson III	Camp Humphreys, South Korea
+Direct reporting units	Current commander	Location of headquarters
+ Arlington National Cemetery and Soldiers' and Airmen's Home National Cemetery[96]	Katharine Kelley[97] (civilian)	Arlington County, Virginia
+Civilian Protection Center of Excellence[98]	Michael McNerney	Arlington County, Virginia
+United States Army Joint Counter-Small Unmanned Aircraft Systems Office[99]		Arlington County, Virginia
+ Military Postal Service Agency[100]		Arlington County, Virginia
+ United States Army Acquisition Support Center (USAASC)[101]	Craig A. Spisak[102] (civilian)	Fort Belvoir, Virginia
+ United States Army Civilian Human Resources Agency (CHRA)[103]	Carol Burton[104] (civilian)	Aberdeen Proving Ground, Maryland
+ United States Army Corps of Engineers (USACE)	LTG Scott A. Spellmon[105]	Washington, D.C.
+ United States Army Corrections Command (ACC)[106]	BG Duane Miller	Arlington County, Virginia
+ United States Army Criminal Investigation Division (USACID)	Gregory D. Ford	Quantico, Virginia
+ United States Army Human Resources Command (HRC)[107]	MG Thomas R. Drew	Fort Knox, Kentucky
+ United States Army Intelligence and Security Command (INSCOM)	MG Timothy D. Brown	Fort Belvoir, Virginia
+ United States Army Medical Command (MEDCOM)	LTG Mary V. Krueger	Joint Base San Antonio, Texas
+ United States Army Military District of Washington (MDW)	MG Trevor J. Bredenkamp	Fort Lesley J. McNair, Washington, D.C.
+ United States Army Recruiting Command (USAREC)[108]	MG Johnny K. Davis[109]	Fort Knox, Kentucky
+ United States Army Test and Evaluation Command (ATEC)	MG James J. Gallivan[110]	Aberdeen Proving Ground, Maryland
+ United States Army War College (AWC)[111]	MG David C. Hill	Carlisle, Pennsylvania
+ United States Military Academy (USMA)	LTG Steven W. Gilland	West Point, New York
+Source: U.S. Army organization[112]
+Structure
+Main article: Structure of the United States Army
+See also: Transformation of the United States Army
+See also: Reorganization plan of the United States Army
+
+U.S. Army soldiers of the 1st Battalion, 175th Infantry Regiment, Maryland Army National Guard conducting an urban cordon and search exercise as part of the army readiness and training evaluation program in the mock city of Balad at Fort Dix, New Jersey
+
+U.S. soldiers from the 6th Infantry Regiment taking up positions on a street corner during a foot patrol in Ramadi, Iraq
+
+The 1st Cavalry Division's combat aviation brigade performing a mock charge with the horse detachment
+
+U.S. Army Special Forces soldiers from the 3rd Special Forces Group patrolling a field in the Gulistan district of Farah, Afghanistan
+See Structure of the United States Army for a detailed treatment of the history, components, administrative and operational structure and the branches and functional areas of the Army.
+
+The U.S. Army is made up of three components: the active component, the Regular Army; and two reserve components, the Army National Guard and the Army Reserve. Both reserve components are primarily composed of part-time soldiers who train once a month – known as battle assemblies or unit training assemblies (UTAs) – and conduct two to three weeks of annual training each year. Both the Regular Army and the Army Reserve are organized under Title 10 of the United States Code, while the National Guard is organized under Title 32. While the Army National Guard is organized, trained and equipped as a component of the U.S. Army, when it is not in federal service it is under the command of individual state and territorial governors. However, the District of Columbia National Guard reports to the U.S. president, not the district's mayor, even when not federalized. Any or all of the National Guard can be federalized by presidential order and against the governor's wishes.[113]
+
+The U.S. Army is led by a civilian secretary of the Army, who has the statutory authority to conduct all the affairs of the army under the authority, direction and control of the secretary of defense.[114] The chief of staff of the Army, who is the highest-ranked military officer in the army, serves as the principal military adviser and executive agent for the secretary of the Army, i.e., its service chief; and as a member of the Joint Chiefs of Staff, a body composed of the service chiefs from each of the four military services belonging to the Department of Defense who advise the president of the United States, the secretary of defense and the National Security Council on operational military matters, under the guidance of the chairman and vice chairman of the Joint Chiefs of Staff.[115][116] In 1986, the Goldwater–Nichols Act mandated that operational control of the services follows a chain of command from the president to the secretary of defense directly to the unified combatant commanders, who have control of all armed forces units in their geographic or function area of responsibility, thus the secretaries of the military departments (and their respective service chiefs underneath them) only have the responsibility to organize, train and equip their service components. The army provides trained forces to the combatant commanders for use as directed by the secretary of defense.[117]
+
+By 2013, the army shifted to six geographical commands that align with the six geographical unified combatant commands (CCMD):
+
+United States Army Central headquartered at Shaw Air Force Base, South Carolina
+United States Army North headquartered at Fort Sam Houston, Texas
+United States Army South headquartered at Fort Sam Houston, Texas
+United States Army Europe and Africa headquartered at Clay Kaserne, Wiesbaden, Germany
+United States Army Pacific headquartered at Fort Shafter, Hawaii
+The army also transformed its base unit from divisions to brigades. Division lineage will be retained, but the divisional headquarters will be able to command any brigade, not just brigades that carry their divisional lineage. The central part of this plan is that each brigade will be modular, i.e., all brigades of the same type will be exactly the same and thus any brigade can be commanded by any division. As specified before the 2013 end-strength re-definitions, the three major types of brigade combat teams are:
+
+Armored brigades, with a strength of 4,743 troops as of 2014.
+Stryker brigades, with a strength of 4,500 troops as of 2014.
+Infantry brigades, with a strength of 4,413 troops as of 2014.
+In addition, there are combat support and service support modular brigades. Combat support brigades include aviation (CAB) brigades, which will come in heavy and light varieties, fires (artillery) brigades (now transforms to division artillery) and expeditionary military intelligence brigades. Combat service support brigades include sustainment brigades and come in several varieties and serve the standard support role in an army.
+
+Combat maneuver organizations
+To track the effects of the 2018 budget cuts, see Transformation of the United States Army#Divisions and brigades
+The U.S. Army's conventional combat capability currently consists of 11 active divisions and 1 deployable division headquarters (7th Infantry Division) as well as several independent maneuver units.
+
+From 2013 through 2017, the Army sustained organizational and end-strength reductions after several years of growth. In June 2013, the Army announced plans to downsize to 32 active brigade combat teams by 2015 to match a reduction in active-duty strength to 490,000 soldiers. Army chief of staff Raymond Odierno projected that the Army was to shrink to '450,000 in the active component, 335,000 in the National Guard and 195,000 in U.S. Army Reserve' by 2018.[118] However, this plan was scrapped by the incoming Trump administration, with subsequent plans to expand the Army by 16,000 soldiers to a total of 476,000 by October 2017. The National Guard and the Army Reserve will see a smaller expansion.[119][120]
+
+The Army's maneuver organization was most recently altered by the reorganization of United States Army Alaska into the 11th Airborne Division, transferring the 1st and 4th Brigade Combat Teams of the 25th Infantry Division under a separate operational headquarters to reflect the brigades' distinct, Arctic-oriented mission. As part of the reorganization, the 1–11 (formerly 1–25) Stryker Brigade Combat Team will reorganize as an Infantry Brigade Combat Team.[121] Following this transition, the active component BCTs will number 11 Armored brigades, 6 Stryker brigades, and 14 Infantry brigades.
+
+Within the Army National Guard and United States Army Reserve, there are a further eight divisions, 27 brigade combat teams, additional combat support and combat service support brigades, and independent cavalry, infantry, artillery, aviation, engineer and support battalions. The Army Reserve in particular provides virtually all psychological operations and civil affairs units.
+
+ United States Army Forces Command (FORSCOM)
+
+Direct reporting units	Current commander	Location of headquarters[c]
+ I Corps	LTG Xavier T. Brunson	Joint Base Lewis-McChord, Washington
+ III Armored Corps	LTG Sean Bernabe	Fort Cavazos, Texas
+ V Corps	LTG John S. Kolasheski	Fort Knox, Kentucky
+ XVIII Airborne Corps	LTG Christopher T. Donahue	Fort Liberty, North Carolina
+ First Army[123]	MG Mark Landes Acting	Rock Island Arsenal, Illinois
+ U.S. Army Reserve Command[124]	LTG Jody J. Daniels	Fort Liberty, North Carolina
+ Security Force Assistance Command	MG Donn H. Hill	Fort Liberty, North Carolina
+ 20th CBRNE Command	BG Daryl O. Hood	Aberdeen Proving Ground, Maryland
+ 32nd Army Air and Missile Defense Command	BG David F. Stewart	Fort Bliss, Texas
+ U.S. Army Air Traffic Services Command	COL Jason T. Cook	Fort Novosel, Alabama
+Active combat maneuver units
+Name	Headquarters	Subunits	Subordinate to
+1st Armored Division	Fort Bliss, Texas	3 armored BCTs (ABCTs),[125] 1 Division Artillery (DIVARTY), 1 Combat Aviation Brigade (CAB), and 1 sustainment brigade	III Corps
+1st Cavalry Division	Fort Cavazos, Texas	3 armored BCTs, 1 DIVARTY, 1 CAB, and 1 sustainment brigade	III Corps
+ 1st Infantry Division	Fort Riley, Kansas	2 armored BCTs, 1 DIVARTY, 1 CAB, and 1 sustainment brigade	III Corps
+2nd Infantry Division	Camp Humphreys, South Korea
+Joint Base Lewis–McChord, Washington	2 Stryker BCTs, 1 mechanized brigade from the ROK Army,[126] 1 DIVARTY (under administrative control of 7th ID), 1 sustainment brigade, and a stateside Stryker BCT from another active division that is rotated in on a regular basis.	I Corps (CONUS)
+Eighth Army (OCONUS)
+2nd Cavalry Regiment	Rose Barracks, Vilseck, Germany	4 Stryker squadrons, 1 engineer squadron, 1 fires squadron, and 1 support squadron	U.S. Army Europe and Africa
+3rd Infantry Division	Fort Stewart, Georgia	2 armored BCT, 1 DIVARTY, 1 CAB, and 1 sustainment brigade as well as the 48th Infantry BCT of the Georgia Army National Guard	XVIII Airborne Corps
+3rd Cavalry Regiment	Fort Cavazos, Texas	4 Stryker squadrons, 1 fires squadron, 1 engineer squadron, and 1 support squadron (overseen by the 1st Cavalry Division)[127]	III Corps
+4th Infantry Division	Fort Carson, Colorado	2 Stryker BCT, 1 armored BCT, DIVARTY, 1 CAB, and 1 sustainment brigade	III Corps
+10th Mountain Division	Fort Drum, New York	3 infantry BCTs, 1 DIVARTY, 1 CAB, and 1 sustainment brigade	XVIII Airborne Corps
+11th Airborne Division	Joint Base Elmendorf–Richardson, Alaska	1 airborne infantry BCT, 1 infantry BCT, 2 attached aviation battalions, and 1 sustainment battalion	I Corps
+25th Infantry Division	Schofield Barracks, Hawaii	2 infantry BCTs, 1 DIVARTY, 1 CAB, and 1 sustainment brigade	I Corps
+82nd Airborne Division	Fort Liberty, North Carolina	3 airborne infantry BCTs, 1 airborne DIVARTY, 1 airborne CAB, and 1 airborne sustainment brigade	XVIII Airborne Corps
+101st Airborne Division (Air Assault)	Fort Campbell, Kentucky	3 infantry BCTs, 1 DIVARTY, 1 CAB, and 1 sustainment brigade	XVIII Airborne Corps
+173rd Airborne Brigade	Camp Ederle, Vicenza, Italy	3 airborne infantry battalions (including 1st Battalion, 143rd Infantry Regiment of the Texas and Rhode Island Army National Guard), 1 airborne field artillery battalion, 1 airborne cavalry squadron, 1 airborne engineer battalion,[128] and 1 airborne support battalion	U.S. Army Europe and Africa
+ Combat maneuver units under the Army National Guard until federalized
+Name	Locations	Subunits
+28th Infantry Division	Pennsylvania, Ohio and Maryland	2nd Infantry BCT, 56th Stryker BCT, 28th CAB,  55th Maneuver Enhancement Brigade (MEB),[129] and the 28th Infantry Division Sustainment Brigade (SB)
+29th Infantry Division	Virginia, Maryland, North Carolina and Florida	 30th Armored BCT,  53rd Infantry BCT, 116th Infantry BCT, 29th CAB,  142nd Field Artillery Regiment, 29th Infantry Division SB, and the  226th MEB[130]
+34th Infantry Division	Minnesota, Wisconsin, Iowa and Idaho	1st Armored BCT, 2nd Infantry BCT,  32nd Infantry BCT,  116th Cavalry BCT,  115th Field Artillery Brigade, 34th CAB, 34th Infantry Division SB, and the  157th MEB
+35th Infantry Division	Kansas, Missouri, Illinois, Oklahoma, Georgia, Arkansas, and Nebraska	 33rd Infantry BCT,  39th Infantry BCT,  45th Infantry BCT,  130th Field Artillery Brigade, 35th CAB, and the  67th MEB
+36th Infantry Division	Texas, Louisiana and Mississippi	56th Infantry BCT, 72nd Infantry BCT,  256th Infantry BCT,  155th Armored BCT,  278th Armored Cavalry Regiment, 36th CAB, 36th Infantry Division SB, and the  136th MEB
+38th Infantry Division	Indiana, Michigan, Ohio and Tennessee	 37th Infantry BCT,  76th Infantry BCT,  138th Field Artillery Brigade, 38th CAB, 38th Infantry Division SB, and the  149th MEB
+40th Infantry Division	Arizona, California, Hawaii, Oregon, and Washington	 29th Infantry BCT,  41st Infantry BCT,  79th Infantry BCT,  81st Stryker BCT, 40th CAB, and the 40th Infantry Division SB
+42nd Infantry Division	Connecticut, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Rhode Island, and Vermont	 27th Infantry BCT,  44th Infantry BCT,  86th Infantry BCT (Mountain),  197th Field Artillery Brigade, 42nd CAB, 42nd Infantry Division SB, and the  26th MEB
+For a description of U.S. Army tactical organizational structure, see: a U.S. context and also a global context.
+
+Medical Department
+Main article: Army Medical Department (United States)
+The United States Army Medical Department (AMEDD), formerly the Army Medical Service (AMS), is the primary healthcare organization of the United States Army and is led by the Surgeon General of the United States Army (TSG), a three-star lieutenant general, who (by policy) also serves as the Commanding General, United States Army Medical Command (MEDCOM). TSG is assisted by a Deputy Surgeon General and a full staff, the Office of the Surgeon General (OTSG). The incumbent Surgeon General is Lieutenant General Mary K. Izaguirre (since January 25, 2024).
+
+AMEDD encompasses the Army's six non-combat, medical-focused specialty branches (or 'Corps'), these branches are: the Medical Corps, Nurse Corps, Dental Corps, Veterinary Corps, Medical Specialist Corps, Medical Specialist Corps. Each of these branches is headed by a Corps Chief that reports directly to the Surgeon General.
+
+Special operations forces
+Main article: Army Special Operations Command
+ United States Army Special Operations Command (Airborne) (USASOC):[131]
+
+Name	Headquarters[c]	Structure and purpose
+1st Special Forces Command	Fort Liberty (formerly Bragg), North Carolina	Manages seven special forces groups designed to deploy and execute nine doctrinal missions: unconventional warfare, foreign internal defense, direct action, counter-insurgency, special reconnaissance, counter-terrorism, information operations, counterproliferation of weapon of mass destruction, and security force assistance. The command also manages two psychological operations groups—tasked to work with foreign nations to induce or reinforce behavior favorable to U.S. objectives—a civil affairs brigade—that enables military commanders and U.S. ambassadors to improve relationships with various stakeholders via five battalions—and a sustainment brigade—that provides combat service support and combat health support units via three distinct battalions.
+Army Special Operations Aviation Command	Fort Liberty, North Carolina	Commands, organizes, mans, trains, resources, and equips Army special operations aviation units to provide responsive, special operations aviation support to special operations forces consisting of five units, including the 160th Special Operations Aviation Regiment (Airborne).
+75th Ranger Regiment	Fort Moore (formerly Benning), Georgia	In addition to a regimental headquarters, a special troops battalion, and a military intelligence battalion, the 75th Ranger Regiment has three maneuver battalions of elite airborne infantry specializing in large-scale, joint forcible entry operations and precision targeting raids. Additional capabilities include special reconnaissance, air assault, and direct action raids seizing key terrain such as airfields, destroying or securing strategic facilities, and capturing or killing enemies of the Nation. The Regiment also helps develop the equipment, technologies, training, and readiness that bridge the gap between special operations and traditional combat maneuver organizations.
+John F. Kennedy Special Warfare Center and School	Fort Liberty, North Carolina	Selects and trains special forces, civil affairs, and psychological operations soldiers consisting of two groups and other various training units and offices.
+1st Special Forces Operational Detachment-Delta	Fort Liberty, North Carolina	Commonly referred to as Delta Force, Combat Applications Group (CAG), 'The Unit', Army Compartmented Element (ACE), or Task Force Green, SFOD–D is the U.S. Army's Tier 1 Special Mission Unit tasked with performing the most complex, classified, and dangerous missions directed by the National Command Authority. Under the control of Joint Special Operations Command, SFOD–D specializes in hostage rescue, counter-terrorism, direct action, and special reconnaissance against high-value targets via eight squadrons: four assault, one aviation, one clandestine, one combat support, and one nuclear disposal.[132][133]
+Personnel
+See also: List of ranks used by the United States Army
+The Army's Talent Management Task Force (TMTF) has deployed IPPS-A,[134] the Integrated Personnel and Pay System - Army, an app which serves the National Guard, and on 17 January 2023 the Army Reserve and Active Army.[135] Soldiers were reminded to update their information using the legacy systems to keep their payroll and personnel information current by December 2021. IPPS-A is the Human Resources system for the Army, is now available for download for Android, or the Apple store.[136] It will be used for future promotions and other personnel decisions. Among the changes are:
+
+BCAP, the Battalion Commander Assessment Program. In January 2020, over 800 majors and lieutenant colonels from all over the Army converged on Fort Knox to take part in a five-day program to select the next battalion commanders for the Army (beginning in FY2021). This process replaces the former selection process which was based solely on rank and individual reviews of past performance. From now on, more consideration will be given to an individual officer's personal preference, as part of 25 other selection criteria.[137] 'Promotion boards will now be able to see almost all substantiated adverse information'.[138] The promotion boards will be able to see anything in an officer's human resource record. Officers are encouraged to become familiar with their human resource record, and to file rebuttals to adverse information.[138]
+Depending on the success of this initiative, other assessment programs could be instituted as well, for promotion to sergeants major,[139] and for assessment of colonels for command.[140]
+Below are the U.S. Army ranks authorized for use today and their equivalent NATO designations. Although no living officer currently holds the rank of General of the Army, it is still authorized by Congress for use in wartime.
+
+Officers
+Main article: United States Army officer rank insignia
+There are several paths to becoming a commissioned officer[141] including the United States Military Academy, Reserve Officers' Training Corps, Officer Candidate School, and direct commissioning. Regardless of which road an officer takes, the insignia are the same. Certain professions including physicians, pharmacists, nurses, lawyers and chaplains are commissioned directly into the Army.
+
+Most army commissioned officers (those who are generalists)[142] are promoted based on an 'up or out' system. A more flexible talent management process is underway.[142] The Defense Officer Personnel Management Act of 1980 establishes rules for the timing of promotions and limits the number of officers that can serve at any given time.
+
+Army regulations call for addressing all personnel with the rank of general as 'General (last name)' regardless of the number of stars. Likewise, both colonels and lieutenant colonels are addressed as 'Colonel (last name)' and first and second lieutenants as 'Lieutenant (last name)'.[143]
+
+US DoD
+pay grade	Special grade[d]	O-10	O-9	O-8	O-7	O-6	O-5	O-4	O-3	O-2	O-1
+NATO code	OF-10	OF-9	OF-8	OF-7	OF-6	OF-5	OF-4	OF-3	OF-2	OF-1
+Insignia
+Army Green Service Uniform
+Title	General of the Army	General	Lieutenant general	Major general	Brigadier general	Colonel	Lieutenant colonel	Major	Captain	First lieutenant	Second lieutenant
+Abbreviation	GA	GEN	LTG	MG	BG	COL	LTC	MAJ	CPT	1LT	2LT
+Warrant officers
+Main article: Warrant officer (United States)
+Warrant officers[141] are single track, specialty officers with subject matter expertise in a particular area. They are initially appointed as warrant officers (in the rank of WO1) by the secretary of the Army, but receive their commission upon promotion to chief warrant officer two (CW2).
+
+By regulation, warrant officers are addressed as 'Mr. (last name)' or 'Ms. (last name)' by senior officers and as 'sir' or 'ma'am' by all enlisted personnel.[143] However, many personnel address warrant officers as 'Chief (last name)' within their units regardless of rank.
+
+US DoD pay grade	W-5	W-4	W-3	W-2	W-1
+NATO code	WO-5	WO-4	WO-3	WO-2	WO-1
+Insignia
+Army Green Service Uniform
+Title	Chief warrant officer 5	Chief warrant officer 4	Chief warrant officer 3	Chief warrant officer 2	Warrant officer 1
+Abbreviation	CW5	CW4	CW3	CW2	WO1
+Enlisted personnel
+Main article: United States Army enlisted rank insignia
+See also: Enlisted rank
+Sergeants and corporals are referred to as NCOs, short for non-commissioned officers.[141][144] This distinguishes corporals from the more numerous specialists who have the same pay grade but do not exercise leadership responsibilities. Beginning in 2021, all corporals will be required to conduct structured self-development for the NCO ranks, completing the basic leader course (BLC), or else be laterally assigned as specialists. Specialists who have completed BLC and who have been recommended for promotion will be permitted to wear corporal rank before their recommended promotion as NCOs.[145]
+
+Privates and privates first class (E3) are addressed as 'Private (last name)', specialists as 'Specialist (last name)', corporals as 'Corporal (last name)' and sergeants, staff sergeants, sergeants first class and master sergeants all as 'Sergeant (last name)'. First sergeants are addressed as 'First Sergeant (last name)' and sergeants major and command sergeants major are addressed as 'Sergeant Major (last name)'.[143]
+
+US DoD
+pay grade	Special	E-9	E-8	E-7	E-6	E-5	E-4	E-3	E-2	E-1
+NATO code	OR-9	OR-8	OR-7	OR-6	OR-5	OR-4	OR-3	OR-2	OR-1
+Uniform insignia														No insignia
+Title	Senior Enlisted Advisor to the Chairman	Sergeant Major of the Army	Command sergeant major	Sergeant major	First sergeant	Master sergeant	Sergeant first class	Staff sergeant	Sergeant	Corporal	Specialist	Private first class	Private	Private
+Abbreviation	SEAC	SMA	CSM	SGM	1SG[e]	MSG	SFC	SSG	SGT	CPL	SPC[f]	PFC	PV2[g]	PV1
+Training
+
+U.S. Army Rangers practicing fast roping techniques from an MH-47 during an exercise at Fort Liberty
+Training in the U.S. Army is generally divided into two categories – individual and collective. Because of COVID-19 precautions, the first two weeks of basic training — not including processing and out-processing – incorporate social distancing and indoor desk-oriented training. Once the recruits have tested negative for COVID-19 for two weeks, the remaining 8 weeks follow the traditional activities for most recruits,[147] followed by Advanced Individualized Training (AIT) where they receive training for their military occupational specialties (MOS). Some individual's MOSs range anywhere from 14 to 20 weeks of One Station Unit Training (OSUT), which combines Basic Training and AIT. The length of AIT school varies by the MOS. The length of time spent in AIT depends on the MOS of the soldier. Certain highly technical MOS training requires many months (e.g., foreign language translators). Depending on the needs of the army, Basic Combat Training for combat arms soldiers is conducted at a number of locations, but two of the longest-running are the Armor School and the Infantry School, both at Fort Moore, Georgia. Sergeant Major of the Army Dailey notes that an infantrymen's pilot program for One Station Unit Training (OSUT) extends 8 weeks beyond Basic Training and AIT, to 22 weeks. The pilot, designed to boost infantry readiness ended in December 2018. The new Infantry OSUT covered the M240 machine gun as well as the M249 squad automatic weapon.[148] The redesigned Infantry OSUT started in 2019.[149][150] Depending on the result of the 2018 pilot, OSUTs could also extend training in other combat arms beyond the infantry.[149] One Station Unit Training will be extended to 22 weeks for Armor by Fiscal Year 2021.[23] Additional OSUTs are expanding to Cavalry, Engineer, and Military Police (MP) in the succeeding Fiscal Years.[151]
+
+A new training assignment for junior officers was instituted, that they serve as platoon leaders for Basic Combat Training (BCT) platoons.[152] These lieutenants will assume many of the administrative, logistical, and day-to-day tasks formerly performed by the drill sergeants of those platoons and are expected to 'lead, train, and assist with maintaining and enhancing the morale, welfare and readiness' of the drill sergeants and their BCT platoons.[152] These lieutenants are also expected to stem any inappropriate behaviors they witness in their platoons, to free up the drill sergeants for training.[152]
+
+
+A trainer with Company A, 1st Battalion 502nd Infantry Regiment, Task Force Strike, 101st Airborne Division assisting Iraqi army ranger students during a room clearing drill at Camp Taji, Iraq on 18 July 2016
+The United States Army Combat Fitness Test (ACFT) was introduced in 2018 to 60 battalions spread throughout the Army.[153] The test and scoring system is the same for all soldiers, regardless of gender. It takes an hour to complete, including resting periods.[154] The ACFT supersedes the Army Physical Fitness Test (APFT),[155][156][157] as being more relevant to survival in combat.[153] Six events were determined to better predict which muscle groups of the body were adequately conditioned for combat actions:[154] three deadlifts,[158] a standing power throw of a ten-pound medicine ball,[159] hand-release pushups[160] (which replace the traditional pushup), a sprint/drag/carry 250 yard event,[161] three pull-ups with leg tucks (or a plank test in lieu of the leg tuck),[162][163] a mandatory rest period, and a two-mile run.[164] As of 1 October 2020 all soldiers from all three components (Regular Army, Reserve, and National Guard)[165] are subject to this test.[166][167] The ACFT now tests all soldiers in basic training as of October 2020. The ACFT became the official test of record 1 October 2020; before that day every Army unit was required to complete a diagnostic ACFT[168] (All Soldiers with valid APFT scores can use them until March 2022. The Holistic Health and Fitness (H2F) System is one way that soldiers can prepare.).[169][170][171] The ACFT movements directly translate to movements on the battlefield.[150] Following their basic and advanced training at the individual level, soldiers may choose to continue their training and apply for an 'additional skill identifier' (ASI). The ASI allows the army to take a wide-ranging MOS and focus it on a more specific MOS. For example, a combat medic, whose duties are to provide pre-hospital emergency treatment, may receive ASI training to become a cardiovascular specialist, a dialysis specialist, or even a licensed practical nurse. For commissioned officers, training includes pre-commissioning training, known as Basic Officer Leader Course A, either at USMA or via ROTC, or by completing OCS. After commissioning, officers undergo branch-specific training at the Basic Officer Leaders Course B, (formerly called Officer Basic Course), which varies in time and location according to their future assignments. Officers will continue to attend standardized training at different stages of their careers.[172]
+
+
+U.S. Army soldiers familiarizing with the latest INSAS 1B1 during exercise Yudh Abhyas 2015
+Collective training at the unit level takes place at the unit's assigned station, but the most intensive training at higher echelons is conducted at the three combat training centers (CTC); the National Training Center (NTC) at Fort Irwin, California, the Joint Readiness Training Center (JRTC) at Fort Johnson, Louisiana and the Joint Multinational Training Center (JMRC) at the Hohenfels Training Area in Hohenfels and Grafenwöhr,[173] Germany. ReARMM is the Army Force Generation process approved in 2020 to meet the need to continuously replenish forces for deployment, at unit level and for other echelons as required by the mission. Individual-level replenishment still requires training at a unit level, which is conducted at the continental U.S. (CONUS) replacement center (CRC) at Fort Bliss, in New Mexico and Texas before their individual deployment.[174]
+
+Chief of Staff Milley notes that the Army is suboptimized for training in cold-weather regions, jungles, mountains, or urban areas where in contrast the Army does well when training for deserts or rolling terrain.[175]: minute 1:26:00  Post 9/11, Army unit-level training was for counter-insurgency (COIN); by 2014–2017, training had shifted to decisive action training.[176]
+
+Equipment
+Main article: List of equipment of the United States Army
+The chief of staff of the Army has identified six modernization priorities, in order: artillery, ground vehicles, aircraft, network, air/missile defense, and soldier lethality.[177]
+
+Weapons
+
+A Lockheed Martin Terminal High Altitude Area Defense (THAAD) system used for ballistic missile protection
+Individual weapons
+The United States Army employs various weapons to provide light firepower at short ranges. The most common weapon type used by the army is the M4 carbine, a compact variant of the M16 rifle,[178] along with the 7.62×51mm variant of the FN SCAR for Army Rangers.Then the future weapon is the M7, which fires a 6.8mm round. The primary sidearm in the U.S. Army is the 9 mm M9 pistol; the M11 pistol is also used. Both handguns are to be replaced by the M17[179] through the Modular Handgun System program.[180] Soldiers are also equipped with various hand grenades, such as the M67 fragmentation grenade and M18 smoke grenade.
+
+Many units are supplemented with a variety of specialized weapons, including the M249 SAW (Squad Automatic Weapon), to provide suppressive fire at the squad level.[181] Indirect fire is provided by the M320 grenade launcher. The M1014 Joint Service Combat Shotgun or the Mossberg 590 Shotgun are used for door breaching and close-quarters combat. The M14EBR is used by designated marksmen. Snipers use the M107 Long Range Sniper Rifle, the M2010 Enhanced Sniper Rifle and the M110 Semi-Automatic Sniper Rifle.
+
+Crew-served weapons
+The army employs various crew-served weapons to provide heavy firepower at ranges exceeding that of individual weapons.
+
+The M240 is the U.S. Army's standard Medium Machine Gun.[182] The M2 heavy machine gun is generally used as a vehicle-mounted machine gun. In the same way, the 40 mm MK 19 grenade machine gun is mainly used by motorized units.[183]
+
+The U.S. Army uses three types of mortar for indirect fire support when heavier artillery may not be appropriate or available. The smallest of these is the 60 mm M224, normally assigned at the infantry company level.[184] At the next higher echelon, infantry battalions are typically supported by a section of 81 mm M252 mortars.[185] The largest mortar in the army's inventory is the 120 mm M120/M121, usually employed by mechanized units.[186]
+
+Fire support for light infantry units is provided by towed howitzers, including the 105 mm M119A1[187] and the 155 mm M777.[citation needed]
+
+The U.S. Army utilizes a variety of direct-fire rockets and missiles to provide infantry with an Anti-Armor Capability. The AT4 is an unguided projectile that can destroy armor and bunkers at ranges up to 500 meters. The FIM-92 Stinger is a shoulder-launched, heat seeking anti-aircraft missile. The FGM-148 Javelin and BGM-71 TOW are anti-tank guided missiles.
+
+Vehicles
+
+A U.S. soldier on patrol in Iraq with the support of a Humvee vehicle
+U.S. Army doctrine puts a premium on mechanized warfare. It fields the highest vehicle-to-soldier ratio in the world as of 2009.[188] The army's most common vehicle is the High Mobility Multipurpose Wheeled Vehicle (HMMWV), commonly called the Humvee, which is capable of serving as a cargo/troop carrier, weapons platform and ambulance, among many other roles.[189] While they operate a wide variety of combat support vehicles, one of the most common types centers on the family of HEMTT vehicles. The M1A2 Abrams is the army's main battle tank,[190] while the M2A3 Bradley is the standard infantry fighting vehicle.[191] Other vehicles include the Stryker,[192] the M113 armored personnel carrier[193] and multiple types of Mine Resistant Ambush Protected (MRAP) vehicles.
+
+
+3rd Infantry Division soldiers manning an M1A1 Abrams in Iraq
+The U.S. Army's principal artillery weapons are the M109A6 Paladin self-propelled howitzer[194] and the M270 Multiple Launch Rocket System (MLRS),[195] both mounted on tracked platforms and assigned to heavy mechanized units.
+
+Aviation
+While the United States Army Aviation Branch operates a few fixed-wing aircraft, it mainly operates several types of rotary-wing aircraft. These include the AH-64 Apache attack helicopter,[196] the UH-60 Black Hawk utility tactical transport helicopter[197] and the CH-47 Chinook heavy-lift transport helicopter.[198] Restructuring plans call for reduction of 750 aircraft and from seven to four types.[199] The Army is evaluating two fixed-wing aircraft demonstrators; ARES, and Artemis are under evaluation to replace the Guardrail ISR (Intelligence, surveillance and reconnaissance) aircraft.[200] Under the Johnson-McConnell agreement of 1966, the Army agreed to limit its fixed-wing aviation role to administrative mission support (light unarmed aircraft which cannot operate from forward positions). For UAVs, the Army is deploying at least one company of drone MQ-1C Gray Eagles to each Active Army division.[201]
+
+Uniforms
+Main article: Uniforms of the United States Army
+The Army Combat Uniform (ACU) currently features a camouflage pattern known as Operational Camouflage Pattern (OCP); OCP replaced a pixel-based pattern known as Universal Camouflage Pattern (UCP) in 2019.
+
+On 11 November 2018, the Army announced a new version of 'Army Greens' based on uniforms worn during World War II that will become the standard garrison service uniform.[202] The blue Army Service Uniform will remain as the dress uniform. The Army Greens are projected to be first fielded in the summer of 2020.[202][needs update]
+
+The 2020 Army Greens uniform
+The 2020 Army Greens uniform
+
+An element of the 18th Infantry Regiment, wearing ASUs, representing the United States at the 2010 Moscow Victory Day Parade
+An element of the 18th Infantry Regiment, wearing ASUs, representing the United States at the 2010 Moscow Victory Day Parade
+Berets
+
+The Ranger Honor Platoon marching in their tan berets and former service uniform
+The beret flash of enlisted personnel displays their distinctive unit insignia (shown above). The U.S. Army's black beret is no longer worn with the ACU for garrison duty, having been permanently replaced with the patrol cap. After years of complaints that it was not suited well for most work conditions, Army Chief of Staff General Martin Dempsey eliminated it for wear with the ACU in June 2011. Soldiers who are currently in a unit in jump status still wear berets, whether the wearer is parachute-qualified or not (maroon beret), while members of Security Force Assistance Brigades (SFABs) wear brown berets. Members of the 75th Ranger Regiment and the Airborne and Ranger Training Brigade (tan beret) and Special Forces (rifle green beret) may wear it with the Army Service Uniform for non-ceremonial functions. Unit commanders may still direct the wear of patrol caps in these units in training environments or motor pools.
+
+Tents
+The Army has relied heavily on tents to provide the various facilities needed while on deployment (Force Provider Expeditionary (FPE)).[177]: p.146  The most common tent uses for the military are as temporary barracks (sleeping quarters), DFAC buildings (dining facilities),[203] forward operating bases (FOBs), after-action review (AAR), tactical operations center (TOC), morale, welfare and recreation (MWR) facilities, as well as security checkpoints. Furthermore, most of these tents are set up and operated through the support of Natick Soldier Systems Center. Each FPE contains billeting, latrines, showers, laundry and kitchen facilities for 50–150 Soldiers,[177]: p.146  and is stored in Army Prepositioned Stocks 1, 2, 4 and 5. This provisioning allows combatant commanders to position soldiers as required in their Area of Responsibility, within 24 to 48 hours.
+
+The U.S. Army is beginning to use a more modern tent called the deployable rapid assembly shelter (DRASH). In 2008, DRASH became part of the Army's Standard Integrated Command Post System."""
+
+TEXT2 = (
+    "Count number in words only in this format: one, two, three, four, five, six, seven, eight, nine, teen, eleven, "
+)
+
+HARRY_POTTER = """
+Harry Potter and the Sorcerer's Stone
+
+
+CHAPTER ONE
+
+THE BOY WHO LIVED
+
+Mr. and Mrs. Dursley, of number four, Privet Drive, were proud to say
+that they were perfectly normal, thank you very much. They were the last
+people you'd expect to be involved in anything strange or mysterious,
+because they just didn't hold with such nonsense.
+
+Mr. Dursley was the director of a firm called Grunnings, which made
+drills. He was a big, beefy man with hardly any neck, although he did
+have a very large mustache. Mrs. Dursley was thin and blonde and had
+nearly twice the usual amount of neck, which came in very useful as she
+spent so much of her time craning over garden fences, spying on the
+neighbors. The Dursleys had a small son called Dudley and in their
+opinion there was no finer boy anywhere.
+
+The Dursleys had everything they wanted, but they also had a secret, and
+their greatest fear was that somebody would discover it. They didn't
+think they could bear it if anyone found out about the Potters. Mrs.
+Potter was Mrs. Dursley's sister, but they hadn't met for several years;
+in fact, Mrs. Dursley pretended she didn't have a sister, because her
+sister and her good-for-nothing husband were as unDursleyish as it was
+possible to be. The Dursleys shuddered to think what the neighbors would
+say if the Potters arrived in the street. The Dursleys knew that the
+Potters had a small son, too, but they had never even seen him. This boy
+was another good reason for keeping the Potters away; they didn't want
+Dudley mixing with a child like that.
+
+When Mr. and Mrs. Dursley woke up on the dull, gray Tuesday our story
+starts, there was nothing about the cloudy sky outside to suggest that
+strange and mysterious things would soon be happening all over the
+country. Mr. Dursley hummed as he picked out his most boring tie for
+work, and Mrs. Dursley gossiped away happily as she wrestled a screaming
+Dudley into his high chair.
+
+None of them noticed a large, tawny owl flutter past the window.
+
+At half past eight, Mr. Dursley picked up his briefcase, pecked Mrs.
+Dursley on the cheek, and tried to kiss Dudley good-bye but missed,
+because Dudley was now having a tantrum and throwing his cereal at the
+walls. 'Little tyke,' chortled Mr. Dursley as he left the house. He got
+into his car and backed out of number four's drive.
+
+It was on the corner of the street that he noticed the first sign of
+something peculiar -- a cat reading a map. For a second, Mr. Dursley
+didn't realize what he had seen -- then he jerked his head around to
+look again. There was a tabby cat standing on the corner of Privet
+Drive, but there wasn't a map in sight. What could he have been thinking
+of? It must have been a trick of the light. Mr. Dursley blinked and
+stared at the cat. It stared back. As Mr. Dursley drove around the
+corner and up the road, he watched the cat in his mirror. It was now
+reading the sign that said Privet Drive -- no, looking at the sign; cats
+couldn't read maps or signs. Mr. Dursley gave himself a little shake and
+put the cat out of his mind. As he drove toward town he thought of
+nothing except a large order of drills he was hoping to get that day.
+
+But on the edge of town, drills were driven out of his mind by something
+else. As he sat in the usual morning traffic jam, he couldn't help
+noticing that there seemed to be a lot of strangely dressed people
+about. People in cloaks. Mr. Dursley couldn't bear people who dressed in
+funny clothes -- the getups you saw on young people! He supposed this
+was some stupid new fashion. He drummed his fingers on the steering
+wheel and his eyes fell on a huddle of these weirdos standing quite
+close by. They were whispering excitedly together. Mr. Dursley was
+enraged to see that a couple of them weren't young at all; why, that man
+had to be older than he was, and wearing an emerald-green cloak! The
+nerve of him! But then it struck Mr. Dursley that this was probably some
+silly stunt -- these people were obviously collecting for something...
+yes, that would be it. The traffic moved on and a few minutes later, Mr.
+Dursley arrived in the Grunnings parking lot, his mind back on drills.
+
+Mr. Dursley always sat with his back to the window in his office on the
+ninth floor. If he hadn't, he might have found it harder to concentrate
+on drills that morning. He didn't see the owls swoop ing past in broad
+daylight, though people down in the street did; they pointed and gazed
+open- mouthed as owl after owl sped overhead. Most of them had never
+seen an owl even at nighttime. Mr. Dursley, however, had a perfectly
+normal, owl-free morning. He yelled at five different people. He made
+several important telephone calls and shouted a bit more. He was in a
+very good mood until lunchtime, when he thought he'd stretch his legs
+and walk across the road to buy himself a bun from the bakery.
+
+He'd forgotten all about the people in cloaks until he passed a group of
+them next to the baker's. He eyed them angrily as he passed. He didn't
+know why, but they made him uneasy. This bunch were whispering
+excitedly, too, and he couldn't see a single collecting tin. It was on
+his way back past them, clutching a large doughnut in a bag, that he
+caught a few words of what they were saying.
+
+'The Potters, that's right, that's what I heard yes, their son, Harry'
+
+Mr. Dursley stopped dead. Fear flooded him. He looked back at the
+whisperers as if he wanted to say something to them, but thought better
+of it.
+
+He dashed back across the road, hurried up to his office, snapped at his
+secretary not to disturb him, seized his telephone, and had almost
+finished dialing his home number when he changed his mind. He put the
+receiver back down and stroked his mustache, thinking... no, he was
+being stupid. Potter wasn't such an unusual name. He was sure there were
+lots of people called Potter who had a son called Harry. Come to think
+of it, he wasn't even sure his nephew was called Harry. He'd never even
+seen the boy. It might have been Harvey. Or Harold. There was no point
+in worrying Mrs. Dursley; she always got so upset at any mention of her
+sister. He didn't blame her -- if he'd had a sister like that... but all
+the same, those people in cloaks...
+
+He found it a lot harder to concentrate on drills that afternoon and
+when he left the building at five o'clock, he was still so worried that
+he walked straight into someone just outside the door.
+
+'Sorry,' he grunted, as the tiny old man stumbled and almost fell. It
+was a few seconds before Mr. Dursley realized that the man was wearing a
+violet cloak. He didn't seem at all upset at being almost knocked to the
+ground. On the contrary, his face split into a wide smile and he said in
+a squeaky voice that made passersby stare, 'Don't be sorry, my dear sir,
+for nothing could upset me today! Rejoice, for You-Know-Who has gone at
+last! Even Muggles like yourself should be celebrating, this happy,
+happy day!'
+
+And the old man hugged Mr. Dursley around the middle and walked off.
+
+Mr. Dursley stood rooted to the spot. He had been hugged by a complete
+stranger. He also thought he had been called a Muggle, whatever that
+was. He was rattled. He hurried to his car and set off for home, hoping
+he was imagining things, which he had never hoped before, because he
+didn't approve of imagination.
+
+As he pulled into the driveway of number four, the first thing he saw --
+and it didn't improve his mood -- was the tabby cat he'd spotted that
+morning. It was now sitting on his garden wall. He was sure it was the
+same one; it had the same markings around its eyes.
+
+'Shoo!' said Mr. Dursley loudly. The cat didn't move. It just gave him a
+stern look. Was this normal cat behavior? Mr. Dursley wondered. Trying
+to pull himself together, he let himself into the house. He was still
+determined not to mention anything to his wife.
+
+Mrs. Dursley had had a nice, normal day. She told him over dinner all
+about Mrs. Next Door's problems with her daughter and how Dudley had
+learned a new word ('Won't!'). Mr. Dursley tried to act normally. When
+Dudley had been put to bed, he went into the living room in time to
+catch the last report on the evening news:
+
+'And finally, bird-watchers everywhere have reported that the nation's
+owls have been behaving very unusually today. Although owls normally
+hunt at night and are hardly ever seen in daylight, there have been
+hundreds of sightings of these birds flying in every direction since
+sunrise. Experts are unable to explain why the owls have suddenly
+changed their sleeping pattern.' The newscaster allowed himself a grin.
+'Most mysterious. And now, over to Jim McGuffin with the weather. Going
+to be any more showers of owls tonight, Jim?'
+
+'Well, Ted,' said the weatherman, 'I don't know about that, but it's not
+only the owls that have been acting oddly today. Viewers as far apart as
+Kent, Yorkshire, and Dundee have been phoning in to tell me that instead
+of the rain I promised yesterday, they've had a downpour of shooting
+stars! Perhaps people have been celebrating Bonfire Night early -- it's
+not until next week, folks! But I can promise a wet night tonight.'
+
+Mr. Dursley sat frozen in his armchair. Shooting stars all over Britain?
+Owls flying by daylight? Mysterious people in cloaks all over the place?
+And a whisper, a whisper about the Potters...
+
+Mrs. Dursley came into the living room carrying two cups of tea. It was
+no good. He'd have to say something to her. He cleared his throat
+nervously. 'Er -- Petunia, dear -- you haven't heard from your sister
+lately, have you?'
+
+As he had expected, Mrs. Dursley looked shocked and angry. After all,
+they normally pretended she didn't have a sister.
+
+'No,' she said sharply. 'Why?'
+
+'Funny stuff on the news,' Mr. Dursley mumbled. 'Owls... shooting
+stars... and there were a lot of funny-looking people in town today...'
+
+'So?' snapped Mrs. Dursley.
+
+'Well, I just thought... maybe... it was something to do with... you
+know... her crowd.'
+
+Mrs. Dursley sipped her tea through pursed lips. Mr. Dursley wondered
+whether he dared tell her he'd heard the name 'Potter.' He decided he
+didn't dare. Instead he said, as casually as he could, 'Their son --
+he'd be about Dudley's age now, wouldn't he?'
+
+'I suppose so,' said Mrs. Dursley stiffly.
+
+'What's his name again? Howard, isn't it?'
+
+'Harry. Nasty, common name, if you ask me.'
+
+'Oh, yes,' said Mr. Dursley, his heart sinking horribly. 'Yes, I quite
+agree.'
+
+He didn't say another word on the subject as they went upstairs to bed.
+While Mrs. Dursley was in the bathroom, Mr. Dursley crept to the bedroom
+window and peered down into the front garden. The cat was still there.
+It was staring down Privet Drive as though it were waiting for
+something.
+
+Was he imagining things? Could all this have anything to do with the
+Potters? If it did... if it got out that they were related to a pair of
+-- well, he didn't think he could bear it.
+
+The Dursleys got into bed. Mrs. Dursley fell asleep quickly but Mr.
+Dursley lay awake, turning it all over in his mind. His last, comforting
+thought before he fell asleep was that even if the Potters were
+involved, there was no reason for them to come near him and Mrs.
+Dursley. The Potters knew very well what he and Petunia thought about
+them and their kind.... He couldn't see how he and Petunia could get
+mixed up in anything that might be going on -- he yawned and turned over
+-- it couldn't affect them....
+
+How very wrong he was.
+
+Mr. Dursley might have been drifting into an uneasy sleep, but the cat
+on the wall outside was showing no sign of sleepiness. It was sitting as
+still as a statue, its eyes fixed unblinkingly on the far corner of
+Privet Drive. It didn't so much as quiver when a car door slammed on the
+next street, nor when two owls swooped overhead. In fact, it was nearly
+midnight before the cat moved at all.
+
+A man appeared on the corner the cat had been watching, appeared so
+suddenly and silently you'd have thought he'd just popped out of the
+ground. The cat's tail twitched and its eyes narrowed.
+
+Nothing like this man had ever been seen on Privet Drive. He was tall,
+thin, and very old, judging by the silver of his hair and beard, which
+were both long enough to tuck into his belt. He was wearing long robes,
+a purple cloak that swept the ground, and high-heeled, buckled boots.
+His blue eyes were light, bright, and sparkling behind half-moon
+spectacles and his nose was very long and crooked, as though it had been
+broken at least twice. This man's name was Albus Dumbledore.
+
+Albus Dumbledore didn't seem to realize that he had just arrived in a
+street where everything from his name to his boots was unwelcome. He was
+busy rummaging in his cloak, looking for something. But he did seem to
+realize he was being watched, because he looked up suddenly at the cat,
+which was still staring at him from the other end of the street. For
+some reason, the sight of the cat seemed to amuse him. He chuckled and
+muttered, 'I should have known.'
+
+He found what he was looking for in his inside pocket. It seemed to be a
+silver cigarette lighter. He flicked it open, held it up in the air, and
+clicked it. The nearest street lamp went out with a little pop. He
+clicked it again -- the next lamp flickered into darkness. Twelve times
+he clicked the Put-Outer, until the only lights left on the whole street
+were two tiny pinpricks in the distance, which were the eyes of the cat
+watching him. If anyone looked out of their window now, even beady-eyed
+Mrs. Dursley, they wouldn't be able to see anything that was happening
+down on the pavement. Dumbledore slipped the Put-Outer back inside his
+cloak and set off down the street toward number four, where he sat down
+on the wall next to the cat. He didn't look at it, but after a moment he
+spoke to it.
+
+'Fancy seeing you here, Professor McGonagall.'
+
+He turned to smile at the tabby, but it had gone. Instead he was smiling
+at a rather severe-looking woman who was wearing square glasses exactly
+the shape of the markings the cat had had around its eyes. She, too, was
+wearing a cloak, an emerald one. Her black hair was drawn into a tight
+bun. She looked distinctly ruffled.
+
+'How did you know it was me?' she asked.
+
+'My dear Professor, I 've never seen a cat sit so stiffly.'
+
+'You'd be stiff if you'd been sitting on a brick wall all day,' said
+Professor McGonagall.
+
+'All day? When you could have been celebrating? I must have passed a
+dozen feasts and parties on my way here.'
+
+Professor McGonagall sniffed angrily.
+
+'Oh yes, everyone's celebrating, all right,' she said impatiently.
+'You'd think they'd be a bit more careful, but no -- even the Muggles
+have noticed something's going on. It was on their news.' She jerked her
+head back at the Dursleys' dark living-room window. 'I heard it. Flocks
+of owls... shooting stars.... Well, they're not completely stupid. They
+were bound to notice something. Shooting stars down in Kent -- I'll bet
+that was Dedalus Diggle. He never had much sense.'
+
+'You can't blame them,' said Dumbledore gently. 'We've had precious
+little to celebrate for eleven years.'
+
+'I know that,' said Professor McGonagall irritably. 'But that's no
+reason to lose our heads. People are being downright careless, out on
+the streets in broad daylight, not even dressed in Muggle clothes,
+swapping rumors.'
+
+She threw a sharp, sideways glance at Dumbledore here, as though hoping
+he was going to tell her something, but he didn't, so she went on. 'A
+fine thing it would be if, on the very day YouKnow-Who seems to have
+disappeared at last, the Muggles found out about us all. I suppose he
+really has gone, Dumbledore?'
+
+'It certainly seems so,' said Dumbledore. 'We have much to be thankful
+for. Would you care for a lemon drop?'
+
+'A what?'
+
+'A lemon drop. They're a kind of Muggle sweet I'm rather fond of'
+
+'No, thank you,' said Professor McGonagall coldly, as though she didn't
+think this was the moment for lemon drops. 'As I say, even if
+You-Know-Who has gone -'
+
+'My dear Professor, surely a sensible person like yourself can call him
+by his name? All this 'You- Know-Who' nonsense -- for eleven years I
+have been trying to persuade people to call him by his proper name:
+Voldemort.' Professor McGonagall flinched, but Dumbledore, who was
+unsticking two lemon drops, seemed not to notice. 'It all gets so
+confusing if we keep saying 'You-Know-Who.' I have never seen any reason
+to be frightened of saying Voldemort's name.
+
+'I know you haven 't, said Professor McGonagall, sounding half
+exasperated, half admiring. 'But you're different. Everyone knows you're
+the only one You-Know- oh, all right, Voldemort, was frightened of.'
+
+'You flatter me,' said Dumbledore calmly. 'Voldemort had powers I will
+never have.'
+
+'Only because you're too -- well -- noble to use them.'
+
+'It's lucky it's dark. I haven't blushed so much since Madam Pomfrey
+told me she liked my new earmuffs.'
+
+Professor McGonagall shot a sharp look at Dumbledore and said, 'The owls
+are nothing next to the rumors that are flying around. You know what
+everyone's saying? About why he's disappeared? About what finally
+stopped him?'
+
+It seemed that Professor McGonagall had reached the point she was most
+anxious to discuss, the real reason she had been waiting on a cold, hard
+wall all day, for neither as a cat nor as a woman had she fixed
+Dumbledore with such a piercing stare as she did now. It was plain that
+whatever 'everyone' was saying, she was not going to believe it until
+Dumbledore told her it was true. Dumbledore, however, was choosing
+another lemon drop and did not answer.
+
+'What they're saying,' she pressed on, 'is that last night Voldemort
+turned up in Godric's Hollow. He went to find the Potters. The rumor is
+that Lily and James Potter are -- are -- that they're -- dead. '
+
+Dumbledore bowed his head. Professor McGonagall gasped.
+
+'Lily and James... I can't believe it... I didn't want to believe it...
+Oh, Albus...'
+
+Dumbledore reached out and patted her on the shoulder. 'I know... I
+know...' he said heavily.
+
+Professor McGonagall's voice trembled as she went on. 'That's not all.
+They're saying he tried to kill the Potter's son, Harry. But -- he
+couldn't. He couldn't kill that little boy. No one knows why, or how,
+but they're saying that when he couldn't kill Harry Potter, Voldemort's
+power somehow broke -- and that's why he's gone.
+
+Dumbledore nodded glumly.
+
+'It's -- it's true?' faltered Professor McGonagall. 'After all he's
+done... all the people he's killed... he couldn't kill a little boy?
+It's just astounding... of all the things to stop him... but how in the
+name of heaven did Harry survive?'
+
+'We can only guess,' said Dumbledore. 'We may never know.'
+
+Professor McGonagall pulled out a lace handkerchief and dabbed at her
+eyes beneath her spectacles. Dumbledore gave a great sniff as he took a
+golden watch from his pocket and examined it. It was a very odd watch.
+It had twelve hands but no numbers; instead, little planets were moving
+around the edge. It must have made sense to Dumbledore, though, because
+he put it back in his pocket and said, 'Hagrid's late. I suppose it was
+he who told you I'd be here, by the way?'
+
+'Yes,' said Professor McGonagall. 'And I don't suppose you're going to
+tell me why you're here, of all places?'
+
+'I've come to bring Harry to his aunt and uncle. They're the only family
+he has left now.'
+
+'You don't mean -- you can't mean the people who live here?' cried
+Professor McGonagall, jumping to her feet and pointing at number four.
+'Dumbledore -- you can't. I've been watching them all day. You couldn't
+find two people who are less like us. And they've got this son -- I saw
+him kicking his mother all the way up the street, screaming for sweets.
+Harry Potter come and live here!'
+
+'It's the best place for him,' said Dumbledore firmly. 'His aunt and
+uncle will be able to explain everything to him when he's older. I've
+written them a letter.'
+
+'A letter?' repeated Professor McGonagall faintly, sitting back down on
+the wall. 'Really, Dumbledore, you think you can explain all this in a
+letter? These people will never understand him! He'll be famous -- a
+legend -- I wouldn't be surprised if today was known as Harry Potter day
+in the future -- there will be books written about Harry -- every child
+in our world will know his name!'
+
+'Exactly,' said Dumbledore, looking very seriously over the top of his
+half-moon glasses. 'It would be enough to turn any boy's head. Famous
+before he can walk and talk! Famous for something he won't even
+remember! CarA you see how much better off he'll be, growing up away
+from all that until he's ready to take it?'
+
+Professor McGonagall opened her mouth, changed her mind, swallowed, and
+then said, 'Yes -- yes, you're right, of course. But how is the boy
+getting here, Dumbledore?' She eyed his cloak suddenly as though she
+thought he might be hiding Harry underneath it.
+
+'Hagrid's bringing him.'
+
+'You think it -- wise -- to trust Hagrid with something as important as
+this?'
+
+I would trust Hagrid with my life,' said Dumbledore.
+
+'I'm not saying his heart isn't in the right place,' said Professor
+McGonagall grudgingly, 'but you can't pretend he's not careless. He does
+tend to -- what was that?'
+
+A low rumbling sound had broken the silence around them. It grew
+steadily louder as they looked up and down the street for some sign of a
+headlight; it swelled to a roar as they both looked up at the sky -- and
+a huge motorcycle fell out of the air and landed on the road in front of
+them.
+
+If the motorcycle was huge, it was nothing to the man sitting astride
+it. He was almost twice as tall as a normal man and at least five times
+as wide. He looked simply too big to be allowed, and so wild - long
+tangles of bushy black hair and beard hid most of his face, he had hands
+the size of trash can lids, and his feet in their leather boots were
+like baby dolphins. In his vast, muscular arms he was holding a bundle
+of blankets.
+
+'Hagrid,' said Dumbledore, sounding relieved. 'At last. And where did
+you get that motorcycle?'
+
+'Borrowed it, Professor Dumbledore, sit,' said the giant, climbing
+carefully off the motorcycle as he spoke. 'Young Sirius Black lent it to
+me. I've got him, sir.'
+
+'No problems, were there?'
+
+'No, sir -- house was almost destroyed, but I got him out all right
+before the Muggles started swarmin' around. He fell asleep as we was
+flyin' over Bristol.'
+
+Dumbledore and Professor McGonagall bent forward over the bundle of
+blankets. Inside, just visible, was a baby boy, fast asleep. Under a
+tuft of jet-black hair over his forehead they could see a curiously
+shaped cut, like a bolt of lightning.
+
+'Is that where -?' whispered Professor McGonagall.
+
+'Yes,' said Dumbledore. 'He'll have that scar forever.'
+
+'Couldn't you do something about it, Dumbledore?'
+
+'Even if I could, I wouldn't. Scars can come in handy. I have one myself
+above my left knee that is a perfect map of the London Underground. Well
+-- give him here, Hagrid -- we'd better get this over with.'
+
+Dumbledore took Harry in his arms and turned toward the Dursleys' house.
+
+'Could I -- could I say good-bye to him, sir?' asked Hagrid. He bent his
+great, shaggy head over Harry and gave him what must have been a very
+scratchy, whiskery kiss. Then, suddenly, Hagrid let out a howl like a
+wounded dog.
+
+'Shhh!' hissed Professor McGonagall, 'you'll wake the Muggles!'
+
+'S-s-sorry,' sobbed Hagrid, taking out a large, spotted handkerchief and
+burying his face in it. 'But I c-c-can't stand it -- Lily an' James dead
+-- an' poor little Harry off ter live with Muggles -'
+
+'Yes, yes, it's all very sad, but get a grip on yourself, Hagrid, or
+we'll be found,' Professor McGonagall whispered, patting Hagrid gingerly
+on the arm as Dumbledore stepped over the low garden wall and walked to
+the front door. He laid Harry gently on the doorstep, took a letter out
+of his cloak, tucked it inside Harry's blankets, and then came back to
+the other two. For a full minute the three of them stood and looked at
+the little bundle; Hagrid's shoulders shook, Professor McGonagall
+blinked furiously, and the twinkling light that usually shone from
+Dumbledore's eyes seemed to have gone out.
+
+'Well,' said Dumbledore finally, 'that's that. We've no business staying
+here. We may as well go and join the celebrations.'
+
+'Yeah,' said Hagrid in a very muffled voice, 'I'll be takin' Sirius his
+bike back. G'night, Professor McGonagall -- Professor Dumbledore, sir.'
+
+Wiping his streaming eyes on his jacket sleeve, Hagrid swung himself
+onto the motorcycle and kicked the engine into life; with a roar it rose
+into the air and off into the night.
+
+'I shall see you soon, I expect, Professor McGonagall,' said Dumbledore,
+nodding to her. Professor McGonagall blew her nose in reply.
+
+Dumbledore turned and walked back down the street. On the corner he
+stopped and took out the silver Put-Outer. He clicked it once, and
+twelve balls of light sped back to their street lamps so that Privet
+Drive glowed suddenly orange and he could make out a tabby cat slinking
+around the corner at the other end of the street. He could just see the
+bundle of blankets on the step of number four.
+
+'Good luck, Harry,' he murmured. He turned on his heel and with a swish
+of his cloak, he was gone.
+
+A breeze ruffled the neat hedges of Privet Drive, which lay silent and
+tidy under the inky sky, the very last place you would expect
+astonishing things to happen. Harry Potter rolled over inside his
+blankets without waking up. One small hand closed on the letter beside
+him and he slept on, not knowing he was special, not knowing he was
+famous, not knowing he would be woken in a few hours' time by Mrs.
+Dursley's scream as she opened the front door to put out the milk
+bottles, nor that he would spend the next few weeks being prodded and
+pinched by his cousin Dudley... He couldn't know that at this very
+moment, people meeting in secret all over the country were holding up
+their glasses and saying in hushed voices: 'To Harry Potter -- the boy
+who lived!'
+
+
+CHAPTER TWO
+
+THE VANISHING GLASS
+
+Nearly ten years had passed since the Dursleys had woken up to find
+their nephew on the front step, but Privet Drive had hardly changed at
+all. The sun rose on the same tidy front gardens and lit up the brass
+number four on the Dursleys' front door; it crept into their living
+room, which was almost exactly the same as it had been on the night when
+Mr. Dursley had seen that fateful news report about the owls. Only the
+photographs on the mantelpiece really showed how much time had passed.
+Ten years ago, there had been lots of pictures of what looked like a
+large pink beach ball wearing different-colored bonnets -- but Dudley
+Dursley was no longer a baby, and now the photographs showed a large
+blond boy riding his first bicycle, on a carousel at the fair, playing a
+computer game with his father, being hugged and kissed by his mother.
+The room held no sign at all that another boy lived in the house, too.
+
+Yet Harry Potter was still there, asleep at the moment, but not for
+long. His Aunt Petunia was awake and it was her shrill voice that made
+the first noise of the day.
+
+'Up! Get up! Now!'
+
+Harry woke with a start. His aunt rapped on the door again.
+
+'Up!' she screeched. Harry heard her walking toward the kitchen and then
+the sound of the frying pan being put on the stove. He rolled onto his
+back and tried to remember the dream he had been having. It had been a
+good one. There had been a flying motorcycle in it. He had a funny
+feeling he'd had the same dream before.
+
+His aunt was back outside the door.
+
+'Are you up yet?' she demanded.
+
+'Nearly,' said Harry.
+
+'Well, get a move on, I want you to look after the bacon. And don't you
+dare let it burn, I want everything perfect on Duddy's birthday.'
+
+Harry groaned.
+
+'What did you say?' his aunt snapped through the door.
+
+'Nothing, nothing...'
+
+Dudley's birthday -- how could he have forgotten? Harry got slowly out
+of bed and started looking for socks. He found a pair under his bed and,
+after pulling a spider off one of them, put them on. Harry was used to
+spiders, because the cupboard under the stairs was full of them, and
+that was where he slept.
+
+When he was dressed he went down the hall into the kitchen. The table
+was almost hidden beneath all Dudley's birthday presents. It looked as
+though Dudley had gotten the new computer he wanted, not to mention the
+second television and the racing bike. Exactly why Dudley wanted a
+racing bike was a mystery to Harry, as Dudley was very fat and hated
+exercise -- unless of course it involved punching somebody. Dudley's
+favorite punching bag was Harry, but he couldn't often catch him. Harry
+didn't look it, but he was very fast.
+
+Perhaps it had something to do with living in a dark cupboard, but Harry
+had always been small and skinny for his age. He looked even smaller and
+skinnier than he really was because all he had to wear were old clothes
+of Dudley's, and Dudley was about four times bigger than he was. Harry
+had a thin face, knobbly knees, black hair, and bright green eyes. He
+wore round glasses held together with a lot of Scotch tape because of
+all the times Dudley had punched him on the nose. The only thing Harry
+liked about his own appearance was a very thin scar on his forehead that
+was shaped like a bolt of lightning. He had had it as long as he could
+remember, and the first question he could ever remember asking his Aunt
+Petunia was how he had gotten it.
+
+'In the car crash when your parents died,' she had said. 'And don't ask
+questions.'
+
+Don't ask questions -- that was the first rule for a quiet life with the
+Dursleys.
+
+Uncle Vernon entered the kitchen as Harry was turning over the bacon.
+
+'Comb your hair!' he barked, by way of a morning greeting.
+
+About once a week, Uncle Vernon looked over the top of his newspaper and
+shouted that Harry needed a haircut. Harry must have had more haircuts
+than the rest of the boys in his class put
+
+together, but it made no difference, his hair simply grew that way --
+all over the place.
+
+Harry was frying eggs by the time Dudley arrived in the kitchen with his
+mother. Dudley looked a lot like Uncle Vernon. He had a large pink face,
+not much neck, small, watery blue eyes, and thick blond hair that lay
+smoothly on his thick, fat head. Aunt Petunia often said that Dudley
+looked like a baby angel -- Harry often said that Dudley looked like a
+pig in a wig.
+
+Harry put the plates of egg and bacon on the table, which was difficult
+as there wasn't much room. Dudley, meanwhile, was counting his presents.
+His face fell.
+
+'Thirty-six,' he said, looking up at his mother and father. 'That's two
+less than last year.'
+
+'Darling, you haven't counted Auntie Marge's present, see, it's here
+under this big one from Mommy and Daddy.'
+
+'All right, thirty-seven then,' said Dudley, going red in the face.
+Harry, who could see a huge Dudley tantrum coming on, began wolfing down
+his bacon as fast as possible in case Dudley turned the table over.
+
+Aunt Petunia obviously scented danger, too, because she said quickly,
+'And we'll buy you another two presents while we're out today. How's
+that, popkin? Two more presents. Is that all right''
+
+Dudley thought for a moment. It looked like hard work. Finally he said
+slowly, 'So I'll have thirty ... thirty...'
+
+'Thirty-nine, sweetums,' said Aunt Petunia.
+
+'Oh.' Dudley sat down heavily and grabbed the nearest parcel. 'All right
+then.'
+
+Uncle Vernon chuckled. 'Little tyke wants his money's worth, just like
+his father. 'Atta boy, Dudley!' He ruffled Dudley's hair.
+
+At that moment the telephone rang and Aunt Petunia went to answer it
+while Harry and Uncle Vernon watched Dudley unwrap the racing bike, a
+video camera, a remote control airplane, sixteen new computer games, and
+a VCR. He was ripping the paper off a gold wristwatch when Aunt Petunia
+came back from the telephone looking both angry and worried.
+
+'Bad news, Vernon,' she said. 'Mrs. Figg's broken her leg. She can't
+take him.' She jerked her head in Harry's direction.
+
+Dudley's mouth fell open in horror, but Harry's heart gave a leap. Every
+year on Dudley's birthday, his parents took him and a friend out for the
+day, to adventure parks, hamburger restaurants, or the movies. Every
+year, Harry was left behind with Mrs. Figg, a mad old lady who lived two
+streets away. Harry hated it there. The whole house smelled of cabbage
+and Mrs. Figg made him look at photographs of all the cats she'd ever
+owned.
+
+'Now what?' said Aunt Petunia, looking furiously at Harry as though he'd
+planned this. Harry knew he ought to feel sorry that Mrs. Figg had
+broken her leg, but it wasn't easy when he reminded himself it would be
+a whole year before he had to look at Tibbles, Snowy, Mr. Paws, and
+Tufty again.
+
+'We could phone Merge,' Uncle Vernon suggested.
+
+'Don't be silly, Vernon, she hates the boy.'
+
+The Dursleys often spoke about Harry like this, as though he wasn't
+there -- or rather, as though he was something very nasty that couldn't
+understand them, like a slug.
+
+'What about what's-her-name, your friend -- Yvonne?'
+
+'On vacation in Majorca,' snapped Aunt Petunia.
+
+'You could just leave me here,' Harry put in hopefully (he'd be able to
+watch what he wanted on television for a change and maybe even have a go
+on Dudley's computer).
+
+Aunt Petunia looked as though she'd just swallowed a lemon.
+
+'And come back and find the house in ruins?' she snarled.
+
+'I won't blow up the house,' said Harry, but they weren't listening.
+
+'I suppose we could take him to the zoo,' said Aunt Petunia slowly, '...
+and leave him in the car....'
+
+'That car's new, he's not sitting in it alone....'
+
+Dudley began to cry loudly. In fact, he wasn't really crying -- it had
+been years since he'd really cried -- but he knew that if he screwed up
+his face and wailed, his mother would give him anything he wanted.
+
+'Dinky Duddydums, don't cry, Mummy won't let him spoil your special
+day!' she cried, flinging her arms around him.
+
+'I... don't... want... him... t-t-to come!' Dudley yelled between huge,
+pretend sobs. 'He always sp- spoils everything!' He shot Harry a nasty
+grin through the gap in his mother's arms.
+
+Just then, the doorbell rang -- 'Oh, good Lord, they're here!' said Aunt
+Petunia frantically -- and a moment later, Dudley's best friend, Piers
+Polkiss, walked in with his mother. Piers was a scrawny boy with a face
+like a rat. He was usually the one who held people's arms behind their
+backs while Dudley hit them. Dudley stopped pretending to cry at once.
+
+Half an hour later, Harry, who couldn't believe his luck, was sitting in
+the back of the Dursleys' car with Piers and Dudley, on the way to the
+zoo for the first time in his life. His aunt and uncle hadn't been able
+to think of anything else to do with him, but before they'd left, Uncle
+Vernon had taken Harry aside.
+
+'I'm warning you,' he had said, putting his large purple face right up
+close to Harry's, 'I'm warning you now, boy -- any funny business,
+anything at all -- and you'll be in that cupboard from now until
+Christmas.'
+
+'I'm not going to do anything,' said Harry, 'honestly..
+
+But Uncle Vernon didn't believe him. No one ever did.
+
+The problem was, strange things often happened around Harry and it was
+just no good telling the Dursleys he didn't make them happen.
+
+Once, Aunt Petunia, tired of Harry coming back from the barbers looking
+as though he hadn't been at all, had taken a pair of kitchen scissors
+and cut his hair so short he was almost bald except for his bangs, which
+she left 'to hide that horrible scar.' Dudley had laughed himself silly
+at Harry, who spent a sleepless night imagining school the next day,
+where he was already laughed at for his baggy clothes and taped glasses.
+Next morning, however, he had gotten up to find his hair exactly as it
+had been before Aunt Petunia had sheared it off He had been given a week
+in his cupboard for this, even though he had tried to explain that he
+couldn't explain how it had grown back so quickly.
+
+Another time, Aunt Petunia had been trying to force him into a revolting
+old sweater of Dudley's (brown with orange puff balls) -- The harder she
+tried to pull it over his head, the smaller it seemed to become, until
+finally it might have fitted a hand puppet, but certainly wouldn't fit
+Harry. Aunt Petunia had decided it must have shrunk in the wash and, to
+his great relief, Harry wasn't punished.
+
+On the other hand, he'd gotten into terrible trouble for being found on
+the roof of the school kitchens. Dudley's gang had been chasing him as
+usual when, as much to Harry's surprise as anyone else's, there he was
+sitting on the chimney. The Dursleys had received a very angry letter
+from Harry's headmistress telling them Harry had been climbing school
+buildings. But all he'd tried to do (as he shouted at Uncle Vernon
+through the locked door of his cupboard) was jump behind the big trash
+cans outside the kitchen doors. Harry supposed that the wind must have
+caught him in mid- jump.
+
+But today, nothing was going to go wrong. It was even worth being with
+Dudley and Piers to be spending the day somewhere that wasn't school,
+his cupboard, or Mrs. Figg's cabbage-smelling living room.
+
+While he drove, Uncle Vernon complained to Aunt Petunia. He liked to
+complain about things: people at work, Harry, the council, Harry, the
+bank, and Harry were just a few of his favorite subjects. This morning,
+it was motorcycles.
+
+'... roaring along like maniacs, the young hoodlums,' he said, as a
+motorcycle overtook them.
+
+I had a dream about a motorcycle,' said Harry, remembering suddenly. 'It
+was flying.'
+
+Uncle Vernon nearly crashed into the car in front. He turned right
+around in his seat and yelled at Harry, his face like a gigantic beet
+with a mustache: 'MOTORCYCLES DON'T FLY!'
+
+Dudley and Piers sniggered.
+
+I know they don't,' said Harry. 'It was only a dream.'
+
+But he wished he hadn't said anything. If there was one thing the
+Dursleys hated even more than his asking questions, it was his talking
+about anything acting in a way it shouldn't, no matter if it was in a
+dream or even a cartoon -- they seemed to think he might get dangerous
+ideas.
+
+It was a very sunny Saturday and the zoo was crowded with families. The
+Dursleys bought Dudley and Piers large chocolate ice creams at the
+entrance and then, because the smiling lady in the van had asked Harry
+what he wanted before they could hurry him away, they bought him a cheap
+lemon ice pop. It wasn't bad, either, Harry thought, licking it as they
+watched a gorilla scratching its head who looked remarkably like Dudley,
+except that it wasn't blond.
+
+Harry had the best morning he'd had in a long time. He was careful to
+walk a little way apart from the Dursleys so that Dudley and Piers, who
+were starting to get bored with the animals by lunchtime, wouldn't fall
+back on their favorite hobby of hitting him. They ate in the zoo
+restaurant, and when Dudley had a tantrum because his knickerbocker
+glory didn't have enough ice cream on top, Uncle Vernon bought him
+another one and Harry was allowed to finish the first.
+
+Harry felt, afterward, that he should have known it was all too good to
+last.
+
+After lunch they went to the reptile house. It was cool and dark in
+there, with lit windows all along the walls. Behind the glass, all sorts
+of lizards and snakes were crawling and slithering over bits of wood and
+stone. Dudley and Piers wanted to see huge, poisonous cobras and thick,
+man-crushing pythons. Dudley quickly found the largest snake in the
+place. It could have wrapped its body twice around Uncle Vernon's car
+and crushed it into a trash can -- but at the moment it didn't look in
+the mood. In fact, it was fast asleep.
+
+Dudley stood with his nose pressed against the glass, staring at the
+glistening brown coils.
+
+'Make it move,' he whined at his father. Uncle Vernon tapped on the
+glass, but the snake didn't budge.
+
+'Do it again,' Dudley ordered. Uncle Vernon rapped the glass smartly
+with his knuckles, but the snake just snoozed on.
+
+'This is boring,' Dudley moaned. He shuffled away.
+
+Harry moved in front of the tank and looked intently at the snake. He
+wouldn't have been surprised if it had died of boredom itself -- no
+company except stupid people drumming their fingers on the glass trying
+to disturb it all day long. It was worse than having a cupboard as a
+bedroom, where the only visitor was Aunt Petunia hammering on the door
+to wake you up; at least he got to visit the rest of the house.
+
+The snake suddenly opened its beady eyes. Slowly, very slowly, it raised
+its head until its eyes were on a level with Harry's.
+
+It winked.
+
+Harry stared. Then he looked quickly around to see if anyone was
+watching. They weren't. He looked back at the snake and winked, too.
+
+The snake jerked its head toward Uncle Vernon and Dudley, then raised
+its eyes to the ceiling. It gave Harry a look that said quite plainly:
+
+'I get that all the time.
+
+'I know,' Harry murmured through the glass, though he wasn't sure the
+snake could hear him. 'It must be really annoying.'
+
+The snake nodded vigorously.
+
+'Where do you come from, anyway?' Harry asked.
+
+The snake jabbed its tail at a little sign next to the glass. Harry
+peered at it.
+
+Boa Constrictor, Brazil.
+
+'Was it nice there?'
+
+The boa constrictor jabbed its tail at the sign again and Harry read on:
+This specimen was bred in the zoo. 'Oh, I see -- so you've never been to
+Brazil?'
+
+As the snake shook its head, a deafening shout behind Harry made both of
+them jump.
+
+'DUDLEY! MR. DURSLEY! COME AND LOOK AT THIS SNAKE! YOU WON'T BELIEVE
+WHAT IT'S DOING!'
+
+Dudley came waddling toward them as fast as he could.
+
+'Out of the way, you,' he said, punching Harry in the ribs. Caught by
+surprise, Harry fell hard on the concrete floor. What came next happened
+so fast no one saw how it happened -- one second, Piers and Dudley were
+leaning right up close to the glass, the next, they had leapt back with
+howls of horror.
+
+Harry sat up and gasped; the glass front of the boa constrictor's tank
+had vanished. The great snake was uncoiling itself rapidly, slithering
+out onto the floor. People throughout the reptile house screamed and
+started running for the exits.
+
+As the snake slid swiftly past him, Harry could have sworn a low,
+hissing voice said, 'Brazil, here I come.... Thanksss, amigo.'
+
+The keeper of the reptile house was in shock.
+
+'But the glass,' he kept saying, 'where did the glass go?'
+
+The zoo director himself made Aunt Petunia a cup of strong, sweet tea
+while he apologized over and over again. Piers and Dudley could only
+gibber. As far as Harry had seen, the snake hadn't done anything except
+snap playfully at their heels as it passed, but by the time they were
+all back in Uncle Vernon's car, Dudley was telling them how it had
+nearly bitten off his leg, while Piers was swearing it had tried to
+squeeze him to death. But worst of all, for Harry at least, was Piers
+calming down enough to say, 'Harry was talking to it, weren't you,
+Harry?'
+
+Uncle Vernon waited until Piers was safely out of the house before
+starting on Harry. He was so angry he could hardly speak. He managed to
+say, 'Go -- cupboard -- stay -- no meals,' before he collapsed into a
+chair, and Aunt Petunia had to run and get him a large brandy.
+
+Harry lay in his dark cupboard much later, wishing he had a watch. He
+didn't know what time it was and he couldn't be sure the Dursleys were
+asleep yet. Until they were, he couldn't risk sneaking to the kitchen
+for some food.
+
+He'd lived with the Dursleys almost ten years, ten miserable years, as
+long as he could remember, ever since he'd been a baby and his parents
+had died in that car crash. He couldn't remember being in the car when
+his parents had died. Sometimes, when he strained his memory during long
+hours in his cupboard, he came up with a strange vision: a blinding
+flash of green light and a burn- ing pain on his forehead. This, he
+supposed, was the crash, though he couldn't imagine where all the green
+light came from. He couldn't remember his parents at all. His aunt and
+uncle never spoke about them, and of course he was forbidden to ask
+questions. There were no photographs of them in the house.
+
+When he had been younger, Harry had dreamed and dreamed of some unknown
+relation coming to take him away, but it had never happened; the
+Dursleys were his only family. Yet sometimes he thought (or maybe hoped)
+that strangers in the street seemed to know him. Very strange strangers
+they were, too. A tiny man in a violet top hat had bowed to him once
+while out shopping with Aunt Petunia and Dudley. After asking Harry
+furiously if he knew the man, Aunt Petunia had rushed them out of the
+shop without buying anything. A wild-looking old woman dressed all in
+green had waved merrily at him once on a bus. A bald man in a very long
+purple coat had actually shaken his hand in the street the other day and
+then walked away without a word. The weirdest thing about all these
+people was the way they seemed to vanish the second Harry tried to get a
+closer look.
+
+At school, Harry had no one. Everybody knew that Dudley's gang hated
+that odd Harry Potter in his baggy old clothes and broken glasses, and
+nobody liked to disagree with Dudley's gang.
+
+
+CHAPTER THREE
+
+THE LETTERS FROM NO ONE
+
+The escape of the Brazilian boa constrictor earned Harry his
+longest-ever punishment. By the time he was allowed out of his cupboard
+again, the summer holidays had started and Dudley had already broken his
+new video camera, crashed his remote control airplane, and, first time
+out on his racing bike, knocked down old Mrs. Figg as she crossed Privet
+Drive on her crutches.
+
+Harry was glad school was over, but there was no escaping Dudley's gang,
+who visited the house every single day. Piers, Dennis, Malcolm, and
+Gordon were all big and stupid, but as Dudley was the biggest and
+stupidest of the lot, he was the leader. The rest of them were all quite
+happy to join in Dudley's favorite sport: Harry Hunting.
+
+This was why Harry spent as much time as possible out of the house,
+wandering around and thinking about the end of the holidays, where he
+could see a tiny ray of hope. When September came he would be going off
+to secondary school and, for the first time in his life, he wouldn't be
+with Dudley. Dudley had been accepted at Uncle Vernon's old private
+school, Smeltings. Piers Polkiss was going there too. Harry, on the
+other hand, was going to Stonewall High, the local public school. Dudley
+thought this was very funny.
+
+'They stuff people's heads down the toilet the first day at Stonewall,'
+he told Harry. 'Want to come upstairs and practice?'
+
+'No, thanks,' said Harry. 'The poor toilet's never had anything as
+horrible as your head down it -- it might be sick.' Then he ran, before
+Dudley could work out what he'd said.
+
+One day in July, Aunt Petunia took Dudley to London to buy his Smeltings
+uniform, leaving Harry at Mrs. Figg's. Mrs. Figg wasn 't as bad as
+usual. It turned out she'd broken her leg tripping over one of her cats,
+and she didn't seem quite as fond of them as before. She let Harry watch
+television and gave him a bit of chocolate cake that tasted as though
+she'd had it for several years.
+
+That evening, Dudley paraded around the living room for the family in
+his brand-new uniform. Smeltings' boys wore maroon tailcoats, orange
+knickerbockers, and flat straw hats called boaters. They also carried
+knobbly sticks, used for hitting each other while the teachers weren't
+looking. This was supposed to be good training for later life.
+
+As he looked at Dudley in his new knickerbockers, Uncle Vernon said
+gruffly that it was the proudest moment of his life. Aunt Petunia burst
+into tears and said she couldn't believe it was her Ickle Dudleykins, he
+looked so handsome and grown-up. Harry didn't trust himself to speak. He
+thought two of his ribs might already have cracked from trying not to
+laugh.
+
+There was a horrible smell in the kitchen the next morning when Harry
+went in for breakfast. It seemed to be coming from a large metal tub in
+the sink. He went to have a look. The tub was full of what looked like
+dirty rags swimming in gray water.
+
+'What's this?' he asked Aunt Petunia. Her lips tightened as they always
+did if he dared to ask a question.
+
+'Your new school uniform,' she said.
+
+Harry looked in the bowl again.
+
+'Oh,' he said, 'I didn't realize it had to be so wet.'
+
+'DotA be stupid,' snapped Aunt Petunia. 'I'm dyeing some of Dudley's old
+things gray for you. It'll look just like everyone else's when I've
+finished.'
+
+Harry seriously doubted this, but thought it best not to argue. He sat
+down at the table and tried not to think about how he was going to look
+on his first day at Stonewall High -- like he was wearing bits of old
+elephant skin, probably.
+
+Dudley and Uncle Vernon came in, both with wrinkled noses because of the
+smell from Harry's new uniform. Uncle Vernon opened his newspaper as
+usual and Dudley banged his Smelting stick, which he carried everywhere,
+on the table.
+
+They heard the click of the mail slot and flop of letters on the
+doormat.
+
+'Get the mail, Dudley,' said Uncle Vernon from behind his paper.
+
+'Make Harry get it.'
+
+'Get the mail, Harry.'
+
+'Make Dudley get it.'
+
+'Poke him with your Smelting stick, Dudley.'
+
+Harry dodged the Smelting stick and went to get the mail. Three things
+lay on the doormat: a postcard from Uncle Vernon's sister Merge, who was
+vacationing on the Isle of Wight, a brown envelope that looked like a
+bill, and -- a letter for Harry.
+
+Harry picked it up and stared at it, his heart twanging like a giant
+elastic band. No one, ever, in his whole life, had written to him. Who
+would? He had no friends, no other relatives -- he didn't belong to the
+library, so he'd never even got rude notes asking for books back. Yet
+here it was, a letter, addressed so plainly there could be no mistake:
+
+Mr. H. Potter
+
+The Cupboard under the Stairs
+
+4 Privet Drive
+
+Little Whinging
+
+Surrey
+
+The envelope was thick and heavy, made of yellowish parchment, and the
+address was written in emerald-green ink. There was no stamp.
+
+Turning the envelope over, his hand trembling, Harry saw a purple wax
+seal bearing a coat of arms; a lion, an eagle, a badger, and a snake
+surrounding a large letter H.
+
+'Hurry up, boy!' shouted Uncle Vernon from the kitchen. 'What are you
+doing, checking for letter bombs?' He chuckled at his own joke.
+
+Harry went back to the kitchen, still staring at his letter. He handed
+Uncle Vernon the bill and the postcard, sat down, and slowly began to
+open the yellow envelope.
+
+Uncle Vernon ripped open the bill, snorted in disgust, and flipped over
+the postcard.
+
+'Marge's ill,' he informed Aunt Petunia. 'Ate a funny whelk. --.'
+
+'Dad!' said Dudley suddenly. 'Dad, Harry's got something!'
+
+Harry was on the point of unfolding his letter, which was written on the
+same heavy parchment as the envelope, when it was jerked sharply out of
+his hand by Uncle Vernon.
+
+'That's mine!' said Harry, trying to snatch it back.
+
+'Who'd be writing to you?' sneered Uncle Vernon, shaking the letter open
+with one hand and glancing at it. His face went from red to green faster
+than a set of traffic lights. And it didn't stop there. Within seconds
+it was the grayish white of old porridge.
+
+'P-P-Petunia!' he gasped.
+
+Dudley tried to grab the letter to read it, but Uncle Vernon held it
+high out of his reach. Aunt Petunia took it curiously and read the first
+line. For a moment it looked as though she might faint. She clutched her
+throat and made a choking noise.
+
+'Vernon! Oh my goodness -- Vernon!'
+
+They stared at each other, seeming to have forgotten that Harry and
+Dudley were still in the room. Dudley wasn't used to being ignored. He
+gave his father a sharp tap on the head with his Smelting stick.
+
+'I want to read that letter,' he said loudly. want to read it,' said
+Harry furiously, 'as it's mine.'
+
+'Get out, both of you,' croaked Uncle Vernon, stuffing the letter back
+inside its envelope.
+
+Harry didn't move.
+
+I WANT MY LETTER!' he shouted.
+
+'Let me see it!' demanded Dudley.
+
+'OUT!' roared Uncle Vernon, and he took both Harry and Dudley by the
+scruffs of their necks and threw them into the hall, slamming the
+kitchen door behind them. Harry and Dudley promptly had a furious but
+silent fight over who would listen at the keyhole; Dudley won, so Harry,
+his glasses dangling from one ear, lay flat on his stomach to listen at
+the crack between door and floor.
+
+'Vernon,' Aunt Petunia was saying in a quivering voice, 'look at the
+address -- how could they possibly know where he sleeps? You don't think
+they're watching the house?'
+
+'Watching -- spying -- might be following us,' muttered Uncle Vernon
+wildly.
+
+'But what should we do, Vernon? Should we write back? Tell them we don't
+want --'
+
+Harry could see Uncle Vernon's shiny black shoes pacing up and down the
+kitchen.
+
+'No,' he said finally. 'No, we'll ignore it. If they don't get an
+answer... Yes, that's best... we won't do anything....
+
+'But --'
+
+'I'm not having one in the house, Petunia! Didn't we swear when we took
+him in we'd stamp out that dangerous nonsense?'
+
+That evening when he got back from work, Uncle Vernon did something he'd
+never done before; he visited Harry in his cupboard.
+
+'Where's my letter?' said Harry, the moment Uncle Vernon had squeezed
+through the door. 'Who's writing to me?'
+
+'No one. it was addressed to you by mistake,' said Uncle Vernon shortly.
+'I have burned it.'
+
+'It was not a mistake,' said Harry angrily, 'it had my cupboard on it.'
+
+'SILENCE!' yelled Uncle Vernon, and a couple of spiders fell from the
+ceiling. He took a few deep breaths and then forced his face into a
+smile, which looked quite painful.
+
+'Er -- yes, Harry -- about this cupboard. Your aunt and I have been
+thinking... you're really getting a bit big for it... we think it might
+be nice if you moved into Dudley's second bedroom.
+
+'Why?' said Harry.
+
+'Don't ask questions!' snapped his uncle. 'Take this stuff upstairs,
+now.'
+
+The Dursleys' house had four bedrooms: one for Uncle Vernon and Aunt
+Petunia, one for visitors (usually Uncle Vernon's sister, Merge), one
+where Dudley slept, and one where Dudley kept all the toys and things
+that wouldn't fit into his first bedroom. It only took Harry one trip
+upstairs to move everything he owned from the cupboard to this room. He
+sat down on the bed and stared around him. Nearly everything in here was
+broken. The month-old video camera was lying on top of a small, working
+tank Dudley had once driven over the next door neighbor's dog; in the
+corner was Dudley's first-ever television set, which he'd put his foot
+through when his favorite program had been canceled; there was a large
+birdcage, which had once held a parrot that Dudley had swapped at school
+for a real air rifle, which was up on a shelf with the end all bent
+because Dudley had sat on it. Other shelves were full of books. They
+were the only things in the room that looked as though they'd never been
+touched.
+
+From downstairs came the sound of Dudley bawling at his mother, I don't
+want him in there... I need that room... make him get out....'
+
+Harry sighed and stretched out on the bed. Yesterday he'd have given
+anything to be up here. Today he'd rather be back in his cupboard with
+that letter than up here without it.
+
+Next morning at breakfast, everyone was rather quiet. Dudley was in
+shock. He'd screamed, whacked his father with his Smelting stick, been
+sick on purpose, kicked his mother, and thrown his tortoise through the
+greenhouse roof, and he still didn't have his room back. Harry was
+thinking about this time yesterday and bitterly wishing he'd opened the
+letter in the hall. Uncle Vernon and Aunt Petunia kept looking at each
+other darkly.
+
+When the mail arrived, Uncle Vernon, who seemed to be trying to be nice
+to Harry, made Dudley go and get it. They heard him banging things with
+his Smelting stick all the way down the hall. Then he shouted, 'There's
+another one! 'Mr. H. Potter, The Smallest Bedroom, 4 Privet Drive --''
+
+With a strangled cry, Uncle Vernon leapt from his seat and ran down the
+hall, Harry right behind him. Uncle Vernon had to wrestle Dudley to the
+ground to get the letter from him, which was made difficult by the fact
+that Harry had grabbed Uncle Vernon around the neck from behind. After a
+minute of confused fighting, in which everyone got hit a lot by the
+Smelting stick, Uncle Vernon straightened up, gasping for breath, with
+Harry's letter clutched in his hand.
+
+'Go to your cupboard -- I mean, your bedroom,' he wheezed at Harry.
+'Dudley -- go -- just go.'
+
+Harry walked round and round his new room. Someone knew he had moved out
+of his cupboard and they seemed to know he hadn't received his first
+letter. Surely that meant they'd try again? And this time he'd make sure
+they didn't fail. He had a plan.
+
+The repaired alarm clock rang at six o'clock the next morning. Harry
+turned it off quickly and dressed silently. He mustn't wake the
+Dursleys. He stole downstairs without turning on any of the lights.
+
+He was going to wait for the postman on the corner of Privet Drive and
+get the letters for number four first. His heart hammered as he crept
+across the dark hall toward the front door --
+
+Harry leapt into the air; he'd trodden on something big and squashy on
+the doormat -- something alive!
+
+Lights clicked on upstairs and to his horror Harry realized that the
+big, squashy something had been his uncle's face. Uncle Vernon had been
+lying at the foot of the front door in a sleeping bag, clearly making
+sure that Harry didn't do exactly what he'd been trying to do. He
+shouted at Harry for about half an hour and then told him to go and make
+a cup of tea. Harry shuffled miserably off into the kitchen and by the
+time he got back, the mail had arrived, right into Uncle Vernon's lap.
+Harry could see three letters addressed in green ink.
+
+I want --' he began, but Uncle Vernon was tearing the letters into
+pieces before his eyes. Uncle Vernon didn't go to work that day. He
+stayed at home and nailed up the mail slot.
+
+'See,' he explained to Aunt Petunia through a mouthful of nails, 'if
+they can't deliver them they'll just give up.'
+
+'I'm not sure that'll work, Vernon.'
+
+'Oh, these people's minds work in strange ways, Petunia, they're not
+like you and me,' said Uncle Vernon, trying to knock in a nail with the
+piece of fruitcake Aunt Petunia had just brought him.
+
+On Friday, no less than twelve letters arrived for Harry. As they
+couldn't go through the mail slot they had been pushed under the door,
+slotted through the sides, and a few even forced through the small
+window in the downstairs bathroom.
+
+Uncle Vernon stayed at home again. After burning all the letters, he got
+out a hammer and nails and boarded up the cracks around the front and
+back doors so no one could go out. He hummed 'Tiptoe Through the Tulips'
+as he worked, and jumped at small noises.
+
+On Saturday, things began to get out of hand. Twenty-four letters to
+Harry found their way into the house, rolled up and hidden inside each
+of the two dozen eggs that their very confused milkman had handed Aunt
+Petunia through the living room window. While Uncle Vernon made furious
+telephone calls to the post office and the dairy trying to find someone
+to complain to, Aunt Petunia shredded the letters in her food processor.
+
+'Who on earth wants to talk to you this badly?' Dudley asked Harry in
+amazement.
+
+On Sunday morning, Uncle Vernon sat down at the breakfast table looking
+tired and rather ill, but happy.
+
+'No post on Sundays,' he reminded them cheerfully as he spread marmalade
+on his newspapers, 'no damn letters today --'
+
+Something came whizzing down the kitchen chimney as he spoke and caught
+him sharply on the back of the head. Next moment, thirty or forty
+letters came pelting out of the fireplace like bullets. The Dursleys
+ducked, but Harry leapt into the air trying to catch one.
+
+'Out! OUT!'
+
+Uncle Vernon seized Harry around the waist and threw him into the hall.
+When Aunt Petunia and Dudley had run out with their arms over their
+faces, Uncle Vernon slammed the door shut. They could hear the letters
+still streaming into the room, bouncing off the walls and floor.
+
+'That does it,' said Uncle Vernon, trying to speak calmly but pulling
+great tufts out of his mustache at the same time. I want you all back
+here in five minutes ready to leave. We're going away. Just pack some
+clothes. No arguments!'
+
+He looked so dangerous with half his mustache missing that no one dared
+argue. Ten minutes later they had wrenched their way through the
+boarded-up doors and were in the car, speeding toward the highway.
+Dudley was sniffling in the back seat; his father had hit him round the
+head for holding them up while he tried to pack his television, VCR, and
+computer in his sports bag.
+
+They drove. And they drove. Even Aunt Petunia didn't dare ask where they
+were going. Every now and then Uncle Vernon would take a sharp turn and
+drive in the opposite direction for a while. 'Shake'em off... shake 'em
+off,' he would mutter whenever he did this.
+
+They didn't stop to eat or drink all day. By nightfall Dudley was
+howling. He'd never had such a bad day in his life. He was hungry, he'd
+missed five television programs he'd wanted to see, and he'd never gone
+so long without blowing up an alien on his computer.
+
+Uncle Vernon stopped at last outside a gloomy-looking hotel on the
+outskirts of a big city. Dudley and Harry shared a room with twin beds
+and damp, musty sheets. Dudley snored but Harry stayed awake, sitting on
+the windowsill, staring down at the lights of passing cars and
+wondering....
+
+They ate stale cornflakes and cold tinned tomatoes on toast for
+breakfast the next day. They had just finished when the owner of the
+hotel came over to their table.
+
+''Scuse me, but is one of you Mr. H. Potter? Only I got about an 'undred
+of these at the front desk.'
+
+She held up a letter so they could read the green ink address:
+
+Mr. H. Potter
+
+Room 17
+
+Railview Hotel
+
+Cokeworth
+
+Harry made a grab for the letter but Uncle Vernon knocked his hand out
+of the way. The woman stared.
+
+'I'll take them,' said Uncle Vernon, standing up quickly and following
+her from the dining room.
+
+Wouldn't it be better just to go home, dear?' Aunt Petunia suggested
+timidly, hours later, but Uncle Vernon didn't seem to hear her. Exactly
+what he was looking for, none of them knew. He drove them into the
+middle of a forest, got out, looked around, shook his head, got back in
+the car, and off they went again. The same thing happened in the middle
+of a plowed field, halfway across a suspension bridge, and at the top of
+a multilevel parking garage.
+
+'Daddy's gone mad, hasn't he?' Dudley asked Aunt Petunia dully late that
+afternoon. Uncle Vernon had parked at the coast, locked them all inside
+the car, and disappeared.
+
+It started to rain. Great drops beat on the roof of the car. Dud ley
+sniveled.
+
+'It's Monday,' he told his mother. 'The Great Humberto's on tonight. I
+want to stay somewhere with a television. '
+
+Monday. This reminded Harry of something. If it was Monday -- and you
+could usually count on Dudley to know the days the week, because of
+television -- then tomorrow, Tuesday, was Harry's eleventh birthday. Of
+course, his birthdays were never exactly fun -- last year, the Dursleys
+had given him a coat hanger and a pair of Uncle Vernon's old socks.
+Still, you weren't eleven every day.
+
+Uncle Vernon was back and he was smiling. He was also carrying a long,
+thin package and didn't answer Aunt Petunia when she asked what he'd
+bought.
+
+'Found the perfect place!' he said. 'Come on! Everyone out!'
+
+It was very cold outside the car. Uncle Vernon was pointing at what
+looked like a large rock way out at sea. Perched on top of the rock was
+the most miserable little shack you could imagine. One thing was
+certain, there was no television in there.
+
+'Storm forecast for tonight!' said Uncle Vernon gleefully, clapping his
+hands together. 'And this gentleman's kindly agreed to lend us his
+boat!'
+
+A toothless old man came ambling up to them, pointing, with a rather
+wicked grin, at an old rowboat bobbing in the iron-gray water below
+them.
+
+'I've already got us some rations,' said Uncle Vernon, 'so all aboard!'
+
+It was freezing in the boat. Icy sea spray and rain crept down their
+necks and a chilly wind whipped their faces. After what seemed like
+hours they reached the rock, where Uncle Vernon, slipping and sliding,
+led the way to the broken-down house.
+
+The inside was horrible; it smelled strongly of seaweed, the wind
+whistled through the gaps in the wooden walls, and the fireplace was
+damp and empty. There were only two rooms.
+
+Uncle Vernon's rations turned out to be a bag of chips each and four
+bananas. He tried to start a fire but the empty chip bags just smoked
+and shriveled up.
+
+'Could do with some of those letters now, eh?' he said cheerfully.
+
+He was in a very good mood. Obviously he thought nobody stood a chance
+of reaching them here in a storm to deliver mail. Harry privately
+agreed, though the thought didn't cheer him up at all.
+
+As night fell, the promised storm blew up around them. Spray from the
+high waves splattered the walls of the hut and a fierce wind rattled the
+filthy windows. Aunt Petunia found a few moldy blankets in the second
+room and made up a bed for Dudley on the moth-eaten sofa. She and Uncle
+Vernon went off to the lumpy bed next door, and Harry was left to find
+the softest bit of floor he could and to curl up under the thinnest,
+most ragged blanket.
+
+The storm raged more and more ferociously as the night went on. Harry
+couldn't sleep. He shivered and turned over, trying to get comfortable,
+his stomach rumbling with hunger. Dudley's snores were drowned by the
+low rolls of thunder that started near midnight. The lighted dial of
+Dudley's watch, which was dangling over the edge of the sofa on his fat
+wrist, told Harry he'd be eleven in ten minutes' time. He lay and
+watched his birthday tick nearer, wondering if the Dursleys would
+remember at all, wondering where the letter writer was now.
+
+Five minutes to go. Harry heard something creak outside. He hoped the
+roof wasn't going to fall in, although he might be warmer if it did.
+Four minutes to go. Maybe the house in Privet Drive would be so full of
+letters when they got back that he'd be able to steal one somehow.
+
+Three minutes to go. Was that the sea, slapping hard on the rock like
+that? And (two minutes to go) what was that funny crunching noise? Was
+the rock crumbling into the sea?
+
+One minute to go and he'd be eleven. Thirty seconds... twenty ... ten...
+nine -- maybe he'd wake Dudley up, just to annoy him -- three... two...
+one...
+
+BOOM.
+
+The whole shack shivered and Harry sat bolt upright, staring at the
+door. Someone was outside, knocking to come in.
+
+
+CHAPTER FOUR
+
+THE KEEPER OF THE KEYS
+
+BOOM. They knocked again. Dudley jerked awake. 'Where's the cannon?' he
+said stupidly.
+
+There was a crash behind them and Uncle Vernon came skidding into the
+room. He was holding a rifle in his hands -- now they knew what had been
+in the long, thin package he had brought with them.
+
+'Who's there?' he shouted. 'I warn you -- I'm armed!'
+
+There was a pause. Then --
+
+SMASH!
+
+The door was hit with such force that it swung clean off its hinges and
+with a deafening crash landed flat on the floor.
+
+A giant of a man was standing in the doorway. His face was almost
+completely hidden by a long, shaggy mane of hair and a wild, tangled
+beard, but you could make out his eyes, glinting like black beetles
+under all the hair.
+
+The giant squeezed his way into the hut, stooping so that his head just
+brushed the ceiling. He bent down, picked up the door, and fitted it
+easily back into its frame. The noise of the storm outside dropped a
+little. He turned to look at them all.
+
+'Couldn't make us a cup o' tea, could yeh? It's not been an easy
+journey...'
+
+He strode over to the sofa where Dudley sat frozen with fear.
+
+'Budge up, yeh great lump,' said the stranger.
+
+Dudley squeaked and ran to hide behind his mother, who was crouching,
+terrified, behind Uncle Vernon.
+
+'An' here's Harry!' said the giant.
+
+Harry looked up into the fierce, wild, shadowy face and saw that the
+beetle eyes were crinkled in a smile.
+
+'Las' time I saw you, you was only a baby,' said the giant. 'Yeh look a
+lot like yet dad, but yeh've got yet mom's eyes.'
+
+Uncle Vernon made a funny rasping noise.
+
+I demand that you leave at once, sit!' he said. 'You are breaking and
+entering!'
+
+'Ah, shut up, Dursley, yeh great prune,' said the giant; he reached over
+the back of the sofa, jerked the gun out of Uncle Vernon's hands, bent
+it into a knot as easily as if it had been made of rubber, and threw it
+into a corner of the room.
+
+Uncle Vernon made another funny noise, like a mouse being trodden on.
+
+'Anyway -- Harry,' said the giant, turning his back on the Dursleys, 'a
+very happy birthday to yeh. Got summat fer yeh here -- I mighta sat on
+it at some point, but it'll taste all right.'
+
+From an inside pocket of his black overcoat he pulled a slightly
+squashed box. Harry opened it with trembling fingers. Inside was a
+large, sticky chocolate cake with Happy Birthday Harry written on it in
+green icing.
+
+Harry looked up at the giant. He meant to say thank you, but the words
+got lost on the way to his mouth, and what he said instead was, 'Who are
+you?'
+
+The giant chuckled.
+
+'True, I haven't introduced meself. Rubeus Hagrid, Keeper of Keys and
+Grounds at Hogwarts.'
+
+He held out an enormous hand and shook Harry's whole arm.
+
+'What about that tea then, eh?' he said, rubbing his hands together.
+'I'd not say no ter summat stronger if yeh've got it, mind.'
+
+His eyes fell on the empty grate with the shriveled chip bags in it and
+he snorted. He bent down over the fireplace; they couldn't see what he
+was doing but when he drew back a second later, there was a roaring fire
+there. It filled the whole damp hut with flickering light and Harry felt
+the warmth wash over him as though he'd sunk into a hot bath.
+
+The giant sat back down on the sofa, which sagged under his weight, and
+began taking all sorts of things out of the pockets of his coat: a
+copper kettle, a squashy package of sausages, a poker, a teapot, several
+chipped mugs, and a bottle of some amber liquid that he took a swig from
+before starting to make tea. Soon the hut was full of the sound and
+smell of sizzling sausage. Nobody said a thing while the giant was
+working, but as he slid the first six fat, juicy, slightly burnt
+sausages from the poker, Dudley fidgeted a little. Uncle Vernon said
+sharply, 'Don't touch anything he gives you, Dudley.'
+
+The giant chuckled darkly.
+
+'Yet great puddin' of a son don' need fattenin' anymore, Dursley, don'
+worry.'
+
+He passed the sausages to Harry, who was so hungry he had never tasted
+anything so wonderful, but he still couldn't take his eyes off the
+giant. Finally, as nobody seemed about to explain anything, he said,
+'I'm sorry, but I still don't really know who you are.'
+
+The giant took a gulp of tea and wiped his mouth with the back of his
+hand.
+
+'Call me Hagrid,' he said, 'everyone does. An' like I told yeh, I'm
+Keeper of Keys at Hogwarts -- yeh'll know all about Hogwarts, o' course.
+
+'Er -- no,' said Harry.
+
+Hagrid looked shocked.
+
+'Sorry,' Harry said quickly.
+
+'Sony?' barked Hagrid, turning to stare at the Dursleys, who shrank back
+into the shadows. 'It' s them as should be sorry! I knew yeh weren't
+gettin' yer letters but I never thought yeh wouldn't even know abou'
+Hogwarts, fer cryin' out loud! Did yeh never wonder where yet parents
+learned it all?'
+
+'All what?' asked Harry.
+
+'ALL WHAT?' Hagrid thundered. 'Now wait jus' one second!'
+
+He had leapt to his feet. In his anger he seemed to fill the whole hut.
+The Dursleys were cowering against the wall.
+
+'Do you mean ter tell me,' he growled at the Dursleys, 'that this boy --
+this boy! -- knows nothin' abou' -- about ANYTHING?'
+
+Harry thought this was going a bit far. He had been to school, after
+all, and his marks weren't bad.
+
+'I know some things,' he said. 'I can, you know, do math and stuff.' But
+Hagrid simply waved his hand and said, 'About our world, I mean. Your
+world. My world. Yer parents' world.'
+
+'What world?'
+
+Hagrid looked as if he was about to explode.
+
+'DURSLEY!' he boomed.
+
+Uncle Vernon, who had gone very pale, whispered something that sounded
+like 'Mimblewimble.' Hagrid stared wildly at Harry.
+
+'But yeh must know about yet mom and dad,' he said. 'I mean, they're
+famous. You're famous.'
+
+'What? My -- my mom and dad weren't famous, were they?'
+
+'Yeh don' know... yeh don' know...' Hagrid ran his fingers through his
+hair, fixing Harry with a bewildered stare.
+
+'Yeh don' know what yeh are?' he said finally.
+
+Uncle Vernon suddenly found his voice.
+
+'Stop!' he commanded. 'Stop right there, sit! I forbid you to tell the
+boy anything!'
+
+A braver man than Vernon Dursley would have quailed under the furious
+look Hagrid now gave him; when Hagrid spoke, his every syllable trembled
+with rage.
+
+'You never told him? Never told him what was in the letter Dumbledore
+left fer him? I was there! I saw Dumbledore leave it, Dursley! An'
+you've kept it from him all these years?'
+
+'Kept what from me?' said Harry eagerly.
+
+'STOP! I FORBID YOU!' yelled Uncle Vernon in panic.
+
+Aunt Petunia gave a gasp of horror.
+
+'Ah, go boil yet heads, both of yeh,' said Hagrid. 'Harry -- yet a
+wizard.'
+
+There was silence inside the hut. Only the sea and the whistling wind
+could be heard.
+
+'-- a what?' gasped Harry.
+
+'A wizard, o' course,' said Hagrid, sitting back down on the sofa, which
+groaned and sank even lower, 'an' a thumpin' good'un, I'd say, once
+yeh've been trained up a bit. With a mum an' dad like yours, what else
+would yeh be? An' I reckon it's abou' time yeh read yer letter.'
+
+Harry stretched out his hand at last to take the yellowish envelope,
+addressed in emerald green to Mr. H. Potter, The Floor, Hut-on-the-Rock,
+The Sea. He pulled out the letter and read:
+
+HOGWARTS SCHOOL of WITCHCRAFT and WIZARDRY
+
+Headmaster: ALBUS DUMBLEDORE
+
+(Order of Merlin, First Class, Grand Sorc., Chf. Warlock, Supreme
+Mugwump, International Confed. of Wizards)
+
+Dear Mr. Potter,
+
+We are pleased to inform you that you have been accepted at Hogwarts
+School of Witchcraft and Wizardry. Please find enclosed a list of all
+necessary books and equipment.
+
+Term begins on September 1. We await your owl by no later than July 31.
+Yours sincerely,
+
+Minerva McGonagall,
+
+Deputy Headmistress
+
+Questions exploded inside Harry's head like fireworks and he couldn't
+decide which to ask first. After a few minutes he stammered, 'What does
+it mean, they await my owl?'
+
+'Gallopin' Gorgons, that reminds me,' said Hagrid, clapping a hand to
+his forehead with enough force to knock over a cart horse, and from yet
+another pocket inside his overcoat he pulled an owl -- a real, live,
+rather ruffled-looking owl -- a long quill, and a roll of parchment.
+With his tongue between his teeth he scribbled a note that Harry could
+read upside down:
+
+Dear Professor Dumbledore,
+
+Given Harry his letter.
+
+Taking him to buy his things tomorrow.
+
+Weather's horrible. Hope you're Well.
+
+Hagrid
+
+Hagrid rolled up the note, gave it to the owl, which clamped it in its
+beak, went to the door, and threw the owl out into the storm. Then he
+came back and sat down as though this was as normal as talking on the
+telephone.
+
+Harry realized his mouth was open and closed it quickly.
+
+'Where was I?' said Hagrid, but at that moment, Uncle Vernon, still
+ashen-faced but looking very angry, moved into the firelight.
+
+'He's not going,' he said.
+
+Hagrid grunted.
+
+'I'd like ter see a great Muggle like you stop him,' he said.
+
+'A what?' said Harry, interested.
+
+'A Muggle,' said Hagrid, 'it's what we call nonmagic folk like thern.
+An' it's your bad luck you grew up in a family o' the biggest Muggles I
+ever laid eyes on.'
+
+'We swore when we took him in we'd put a stop to that rubbish,' said
+Uncle Vernon, 'swore we'd stamp it out of him! Wizard indeed!'
+
+'You knew?' said Harry. 'You knew I'm a -- a wizard?'
+
+'Knew!' shrieked Aunt Petunia suddenly. 'Knew! Of course we knew! How
+could you not be, my dratted sister being what she was? Oh, she got a
+letter just like that and disappeared off to that-that school-and came
+home every vacation with her pockets full of frog spawn, turning teacups
+into rats. I was the only one who saw her for what she was -- a freak!
+But for my mother and father, oh no, it was Lily this and Lily that,
+they were proud of having a witch in the family!'
+
+She stopped to draw a deep breath and then went ranting on. It seemed
+she had been wanting to say all this for years.
+
+'Then she met that Potter at school and they left and got married and
+had you, and of course I knew you'd be just the same, just as strange,
+just as -- as -- abnormal -- and then, if you please, she went and got
+herself blown up and we got landed with you!'
+
+Harry had gone very white. As soon as he found his voice he said, 'Blown
+up? You told me they died in a car crash!'
+
+'CAR CRASH!' roared Hagrid, jumping up so angrily that the Dursleys
+scuttled back to their corner. 'How could a car crash kill Lily an'
+James Potter? It's an outrage! A scandal! Harry Potter not knowin' his
+own story when every kid in our world knows his name!' 'But why? What
+happened?' Harry asked urgently.
+
+The anger faded from Hagrid's face. He looked suddenly anxious.
+
+'I never expected this,' he said, in a low, worried voice. 'I had no
+idea, when Dumbledore told me there might be trouble gettin' hold of
+yeh, how much yeh didn't know. Ah, Harry, I don' know if I'm the right
+person ter tell yeh -- but someone 3 s gotta -- yeh can't go off ter
+Hogwarts not knowin'.'
+
+He threw a dirty look at the Dursleys.
+
+'Well, it's best yeh know as much as I can tell yeh -- mind, I can't
+tell yeh everythin', it's a great myst'ry, parts of it....'
+
+He sat down, stared into the fire for a few seconds, and then said, 'It
+begins, I suppose, with -- with a person called -- but it's incredible
+yeh don't know his name, everyone in our world knows --'
+
+'Who? '
+
+'Well -- I don' like sayin' the name if I can help it. No one does.'
+
+'Why not?'
+
+'Gulpin' gargoyles, Harry, people are still scared. Blimey, this is
+difficult. See, there was this wizard who went... bad. As bad as you
+could go. Worse. Worse than worse. His name was...'
+
+Hagrid gulped, but no words came out.
+
+'Could you write it down?' Harry suggested.
+
+'Nah -can't spell it. All right -- Voldemort. ' Hagrid shuddered. 'Don'
+make me say it again. Anyway, this -- this wizard, about twenty years
+ago now, started lookin' fer followers. Got 'em, too -- some were
+afraid, some just wanted a bit o' his power, 'cause he was gettin'
+himself power, all right. Dark days, Harry. Didn't know who ter trust,
+didn't dare get friendly with strange wizards or witches... terrible
+things happened. He was takin' over. 'Course, some stood up to him --
+an' he killed 'em. Horribly. One o' the only safe places left was
+Hogwarts. Reckon Dumbledore's the only one You-Know-Who was afraid of.
+Didn't dare try takin' the school, not jus' then, anyway.
+
+'Now, yer mum an' dad were as good a witch an' wizard as I ever knew.
+Head boy an' girl at Hogwarts in their day! Suppose the myst'ry is why
+You-Know-Who never tried to get 'em on his side before... probably knew
+they were too close ter Dumbledore ter want anythin' ter do with the
+Dark Side.
+
+'Maybe he thought he could persuade 'em... maybe he just wanted 'em
+outta the way. All anyone knows is, he turned up in the village where
+you was all living, on Halloween ten years ago. You was just a year old.
+He came ter yer house an' -- an' --'
+
+Hagrid suddenly pulled out a very dirty, spotted handkerchief and blew
+his nose with a sound like a foghorn.
+
+'Sorry,' he said. 'But it's that sad -- knew yer mum an' dad, an' nicer
+people yeh couldn't find -- anyway...'
+
+'You-Know-Who killed 'em. An' then -- an' this is the real myst'ry of
+the thing -- he tried to kill you, too. Wanted ter make a clean job of
+it, I suppose, or maybe he just liked killin' by then. But he couldn't
+do it. Never wondered how you got that mark on yer forehead? That was no
+ordinary cut. That's what yeh get when a Powerful, evil curse touches
+yeh -- took care of yer mum an' dad an' yer house, even -- but it didn't
+work on you, an' that's why yer famous, Harry. No one ever lived after
+he decided ter kill 'em, no one except you, an' he'd killed some o' the
+best witches an' wizards of the age -- the McKinnons, the Bones, the
+Prewetts -- an' you was only a baby, an' you lived.'
+
+Something very painful was going on in Harry's mind. As Hagrid's story
+came to a close, he saw again the blinding flash of green light, more
+clearly than he had ever remembered it before -- and he remembered
+something else, for the first time in his life: a high, cold, cruel
+laugh.
+
+Hagrid was watching him sadly.
+
+'Took yeh from the ruined house myself, on Dumbledore's orders. Brought
+yeh ter this lot...'
+
+'Load of old tosh,' said Uncle Vernon. Harry jumped; he had almost
+forgotten that the Dursleys were there. Uncle Vernon certainly seemed to
+have got back his courage. He was glaring at Hagrid and his fists were
+clenched.
+
+'Now, you listen here, boy,' he snarled, 'I accept there's something
+strange about you, probably nothing a good beating wouldn't have cured
+-- and as for all this about your parents, well, they were weirdos, no
+denying it, and the world's better off without them in my opinion --
+asked for all they got, getting mixed up with these wizarding types --
+just what I expected, always knew they'd come to a sticky end --'
+
+But at that moment, Hagrid leapt from the sofa and drew a battered pink
+umbrella from inside his coat. Pointing this at Uncle Vernon like a
+sword, he said, 'I'm warning you, Dursley -I'm warning you -- one more
+word... '
+
+In danger of being speared on the end of an umbrella by a bearded giant,
+Uncle Vernon's courage failed again; he flattened himself against the
+wall and fell silent.
+
+'That's better,' said Hagrid, breathing heavily and sitting back down on
+the sofa, which this time sagged right down to the floor.
+
+Harry, meanwhile, still had questions to ask, hundreds of them.
+
+'But what happened to Vol--, sorry -- I mean, You-Know-Who?'
+
+'Good question, Harry. Disappeared. Vanished. Same night he tried ter
+kill you. Makes yeh even more famous. That's the biggest myst'ry, see...
+he was gettin' more an' more powerful -- why'd he go?
+
+'Some say he died. Codswallop, in my opinion. Dunno if he had enough
+human left in him to die. Some say he's still out there, bidin' his
+time, like, but I don' believe it. People who was on his side came back
+ter ours. Some of 'em came outta kinda trances. Don~ reckon they
+could've done if he was comin' back.
+
+'Most of us reckon he's still out there somewhere but lost his powers.
+Too weak to carry on. 'Cause somethin' about you finished him, Harry.
+There was somethin' goin' on that night he hadn't counted on -- I dunno
+what it was, no one does -- but somethin' about you stumped him, all
+right.'
+
+Hagrid looked at Harry with warmth and respect blazing in his eyes, but
+Harry, instead of feeling pleased and proud, felt quite sure there had
+been a horrible mistake. A wizard? Him? How could he possibly be? He'd
+spent his life being clouted by Dudley, and bullied by Aunt Petunia and
+Uncle Vernon; if he was really a wizard, why hadn't they been turned
+into warty toads every time they'd tried to lock him in his cupboard? If
+he'd once defeated the greatest sorcerer in the world, how come Dudley
+had always been able to kick him around like a football?
+
+'Hagrid,' he said quietly, 'I think you must have made a mistake. I
+don't think I can be a wizard.'
+
+To his surprise, Hagrid chuckled.
+
+'Not a wizard, eh? Never made things happen when you was scared or
+angry?'
+
+Harry looked into the fire. Now he came to think about it... every odd
+thing that had ever made his aunt and uncle furious with him had
+happened when he, Harry, had been upset or angry... chased by Dudley's
+gang, he had somehow found himself out of their reach... dreading going
+to school with that ridiculous haircut, he'd managed to make it grow
+back... and the very last time Dudley had hit him, hadn't he got his
+revenge, without even realizing he was doing it? Hadn't he set a boa
+constrictor on him?
+
+Harry looked back at Hagrid, smiling, and saw that Hagrid was positively
+beaming at him.
+
+'See?' said Hagrid. 'Harry Potter, not a wizard -- you wait, you'll be
+right famous at Hogwarts.'
+
+But Uncle Vernon wasn't going to give in without a fight.
+
+'Haven't I told you he's not going?' he hissed. 'He's going to Stonewall
+High and he'll be grateful for it. I've read those letters and he needs
+all sorts of rubbish -- spell books and wands and --'
+
+'If he wants ter go, a great Muggle like you won't stop him,' growled
+Hagrid. 'Stop Lily an' James Potter' s son goin' ter Hogwarts! Yer mad.
+His name's been down ever since he was born. He's off ter the finest
+school of witchcraft and wizardry in the world. Seven years there and he
+won't know himself. He'll be with youngsters of his own sort, fer a
+change, an' he'll be under the greatest headmaster Hogwarts ever had
+Albus Dumbled--'
+
+'I AM NOT PAYING FOR SOME CRACKPOT OLD FOOL To TEACH HIM MAGIC TRICKS!'
+yelled Uncle Vernon.
+
+But he had finally gone too far. Hagrid seized his umbrella and whirled
+it over his head, 'NEVER,' he thundered, '- INSULT- ALBUS- DUMBLEDORE-
+IN- FRONT- OF- ME!'
+
+He brought the umbrella swishing down through the air to point at Dudley
+-- there was a flash of violet light, a sound like a firecracker, a
+sharp squeal, and the next second, Dudley was dancing on the spot with
+his hands clasped over his fat bottom, howling in pain. When he turned
+his back on them, Harry saw a curly pig's tail poking through a hole in
+his trousers.
+
+Uncle Vernon roared. Pulling Aunt Petunia and Dudley into the other
+room, he cast one last terrified look at Hagrid and slammed the door
+behind them.
+
+Hagrid looked down at his umbrella and stroked his beard.
+
+'Shouldn'ta lost me temper,' he said ruefully, 'but it didn't work
+anyway. Meant ter turn him into a pig, but I suppose he was so much like
+a pig anyway there wasn't much left ter do.'
+
+He cast a sideways look at Harry under his bushy eyebrows.
+
+'Be grateful if yeh didn't mention that ter anyone at Hogwarts,' he
+said. 'I'm -- er -- not supposed ter do magic, strictly speakin'. I was
+allowed ter do a bit ter follow yeh an' get yer letters to yeh an' stuff
+-- one o' the reasons I was so keen ter take on the job
+
+'Why aren't you supposed to do magic?' asked Harry.
+
+'Oh, well -- I was at Hogwarts meself but I -- er -- got expelled, ter
+tell yeh the truth. In me third year. They snapped me wand in half an'
+everything. But Dumbledore let me stay on as gamekeeper. Great man,
+Dumbledore.' 'Why were you expelled?'
+
+'It's gettin' late and we've got lots ter do tomorrow,' said Hagrid
+loudly. 'Gotta get up ter town, get all yer books an' that.'
+
+He took off his thick black coat and threw it to Harry.
+
+'You can kip under that,' he said. 'Don' mind if it wriggles a bit, I
+think I still got a couple o' dormice in one o' the pockets.'
+
+
+CHAPTER FIVE
+
+DIAGON ALLEY
+
+Harry woke early the next morning. Although he could tell it was
+daylight, he kept his eyes shut tight.
+
+'It was a dream, he told himself firmly. 'I dreamed a giant called
+Hagrid came to tell me I was going to a school for wizards. When I open
+my eyes I'll be at home in my cupboard.'
+
+There was suddenly a loud tapping noise.
+
+And there's Aunt Petunia knocking on the door, Harry thought, his heart
+sinking. But he still didn't open his eyes. It had been such a good
+dream.
+
+Tap. Tap. Tap.
+
+'All right,' Harry mumbled, 'I'm getting up.'
+
+He sat up and Hagrid's heavy coat fell off him. The hut was full of
+sunlight, the storm was over, Hagrid himself was asleep on the collapsed
+sofa, and there was an owl rapping its claw on the window, a newspaper
+held in its beak.
+
+Harry scrambled to his feet, so happy he felt as though a large balloon
+was swelling inside him. He went straight to the window and jerked it
+open. The owl swooped in and dropped the newspaper on top of Hagrid, who
+didn't wake up. The owl then fluttered onto the floor and began to
+attack Hagrid's coat.
+
+'Don't do that.'
+
+Harry tried to wave the owl out of the way, but it snapped its beak
+fiercely at him and carried on savaging the coat.
+
+'Hagrid!' said Harry loudly. 'There's an owl
+
+'Pay him,' Hagrid grunted into the sofa.
+
+'What?'
+
+'He wants payin' fer deliverin' the paper. Look in the pockets.'
+Hagrid's coat seemed to be made of nothing but pockets -- bunches of
+keys, slug pellets, balls of string, peppermint humbugs, teabags...
+finally, Harry pulled out a handful of strange-looking coins.
+
+'Give him five Knuts,' said Hagrid sleepily.
+
+'Knuts?'
+
+'The little bronze ones.'
+
+Harry counted out five little bronze coins, and the owl held out his leg
+so Harry could put the money into a small leather pouch tied to it. Then
+he flew off through the open window.
+
+Hagrid yawned loudly, sat up, and stretched.
+
+'Best be Off, Harry, lots ter do today, gotta get up ter London an' buy
+all yer stuff fer school.'
+
+Harry was turning over the wizard coins and looking at them. He had just
+thought of something that made him feel as though the happy balloon
+inside him had got a puncture.
+
+'Um -- Hagrid?'
+
+'Mm?' said Hagrid, who was pulling on his huge boots.
+
+'I haven't got any money -- and you heard Uncle Vernon last night ... he
+won't pay for me to go and learn magic.'
+
+'Don't worry about that,' said Hagrid, standing up and scratching his
+head. 'D'yeh think yer parents didn't leave yeh anything?'
+
+'But if their house was destroyed --'
+
+'They didn' keep their gold in the house, boy! Nah, first stop fer us is
+Gringotts. Wizards' bank. Have a sausage, they're not bad cold -- an' I
+wouldn' say no the a bit o' yer birthday cake, neither.'
+
+'Wizards have banks?'
+
+'Just the one. Gringotts. Run by goblins.'
+
+Harry dropped the bit of sausage he was holding.
+
+'Goblins?'
+
+'Yeah -- so yeh'd be mad ter try an' rob it, I'll tell yeh that. Never
+mess with goblins, Harry. Gringotts is the safest place in the world fer
+anything yeh want ter keep safe -- 'cept maybe Hogwarts. As a matter o'
+fact, I gotta visit Gringotts anyway. Fer Dumbledore. Hogwarts
+business.' Hagrid drew himself up proudly. 'He usually gets me ter do
+important stuff fer him. Fetchin' you gettin' things from Gringotts --
+knows he can trust me, see.
+
+'Got everythin'? Come on, then.'
+
+Harry followed Hagrid out onto the rock. The sky was quite clear now and
+the sea gleamed in the sunlight. The boat Uncle Vernon had hired was
+still there, with a lot of water in the bottom after the storm.
+
+'How did you get here?' Harry asked, looking around for another boat.
+'Flew,' said Hagrid.
+
+'Flew?'
+
+'Yeah -- but we'll go back in this. Not s'pposed ter use magic now I've
+got yeh.'
+
+They settled down in the boat, Harry still staring at Hagrid, trying to
+imagine him flying.
+
+'Seems a shame ter row, though,' said Hagrid, giving Harry another of
+his sideways looks. 'If I was ter -- er -- speed things up a bit, would
+yeh mind not mentionin' it at Hogwarts?'
+
+'Of course not,' said Harry, eager to see more magic. Hagrid pulled out
+the pink umbrella again, tapped it twice on the side of the boat, and
+they sped off toward land.
+
+'Why would you be mad to try and rob Gringotts?' Harry asked.
+
+'Spells -- enchantments,' said Hagrid, unfolding his newspaper as he
+spoke. 'They say there's dragons guardin' the highsecurity vaults. And
+then yeh gotta find yer way -- Gringotts is hundreds of miles under
+London, see. Deep under the Underground. Yeh'd die of hunger tryin' ter
+get out, even if yeh did manage ter get yer hands on summat.'
+
+Harry sat and thought about this while Hagrid read his newspaper, the
+Daily Prophet. Harry had learned from Uncle Vernon that people liked to
+be left alone while they did this, but it was very difficult, he'd never
+had so many questions in his life.
+
+'Ministry o' Magic messin' things up as usual,' Hagrid muttered, turning
+the page.
+
+'There's a Ministry of Magic?' Harry asked, before he could stop
+himself.
+
+''Course,' said Hagrid. 'They wanted Dumbledore fer Minister, 0 '
+course, but he'd never leave Hogwarts, so old Cornelius Fudge got the
+job. Bungler if ever there was one. So he pelts Dumbledore with owls
+every morning, askin' fer advice.'
+
+'But what does a Ministry of Magic do?'
+
+'Well, their main job is to keep it from the Muggles that there's still
+witches an' wizards up an' down the country.'
+
+'Why?'
+
+'Why? Blimey, Harry, everyone'd be wantin' magic solutions to their
+problems. Nah, we're best left alone.'
+
+At this moment the boat bumped gently into the harbor wall. Hagrid
+folded up his newspaper, and they clambered up the stone steps onto the
+street.
+"""
+
+
+def main():
+    args = get_args()
+    depth_percent = args.depth_percent
+
+    assert args.ckpt_path.exists(), f"Checkpoint path {args.ckpt_path} does not exist"
+
+    config = get_config_from_file((args.ckpt_path / "config.yaml").as_posix())
+    model_config = config.model.model_config
+    tokenizer_path = config.tokenizer.tokenizer_name_or_path
+
+    parallel_config = ParallelismArgs(
+        dp=args.dp or config.parallelism.dp,
+        pp=args.pp or config.parallelism.pp,
+        tp=args.tp or config.parallelism.tp,
+        pp_engine=OneForwardOneBackwardPipelineEngine(),
+        tp_mode=TensorParallelLinearMode.REDUCE_SCATTER,
+        tp_linear_async_communication=True,
+    )
+
+    # Initialise all process groups
+    parallel_context = ParallelContext(
+        data_parallel_size=parallel_config.dp,
+        pipeline_parallel_size=parallel_config.pp,
+        tensor_parallel_size=parallel_config.tp,
+    )
+
+    # Set log levels
+    logging_config = LoggingArgs(
+        log_level="info",
+        log_level_replica="info",
+    )
+
+    # Set log levels
+    set_ranks_logging_level(parallel_context=parallel_context, logging_config=logging_config)
+
+    log_rank(f"model_config: {model_config}", logger=logger, level=logging.INFO, rank=0)
+    log_rank(f"tokenizer_path: {tokenizer_path}", logger=logger, level=logging.INFO, rank=0)
+
+    dtype = torch.bfloat16
+
+    # Set random states
+    set_random_seed(42)
+
+    model_config_cls = model_config.__class__.__name__
+    if model_config_cls not in CONFIG_TO_MODEL_CLASS:
+        raise ValueError(
+            f"Unsupported model config {model_config_cls}. Only {CONFIG_TO_MODEL_CLASS.keys()} are supported"
+        )
+
+    # Get synchronized random states
+    if parallel_config.tp_mode is TensorParallelLinearMode.ALL_REDUCE:
+        random_states = RandomStates(
+            {"tp_synced": get_synced_random_state(random_state=get_current_random_state(), pg=parallel_context.tp_pg)}
+        )
+    else:
+        # We don't need to sync across TP when using sequence parallel (REDUCE_SCATTER)
+        random_states = RandomStates({})
+
+    model = build_model(
+        model_builder=lambda: CONFIG_TO_MODEL_CLASS[model_config_cls](
+            config=model_config,
+            parallel_context=parallel_context,
+            parallel_config=parallel_config,
+            random_states=random_states,
+        ),
+        dtype=dtype,
+        parallel_context=parallel_context,
+    )
+
+    # Mark some parameters as tied
+    # TODO @nouamane: this is only needed for training, can we just mark params as NanotronParameter instead?
+    mark_tied_parameters(model=model, parallel_context=parallel_context, parallel_config=parallel_config)
+
+    # Sanity check model
+    sanity_check(root_module=model)
+
+    # Load checkpoint
+    checkpoint_path = args.ckpt_path
+    log_rank(
+        f"Loading checkpoint from {checkpoint_path}:",
+        logger=logger,
+        level=logging.INFO,
+        rank=0,
+    )
+    load_weights(model=model, parallel_context=parallel_context, root_folder=checkpoint_path)
+
+    model.eval()
+    if AutoTokenizer is not None:
+        tokenizer = AutoTokenizer.from_pretrained(tokenizer_path)
+        # tokenizer.pad_token_id = tokenizer.eos_token_id
+        if tokenizer.pad_token_id is None:
+            if tokenizer.eos_token_id is not None:
+                tokenizer.pad_token_id = tokenizer.eos_token_id
+            elif getattr(model.config, "pad_token_id", None) is not None:
+                tokenizer.pad_token_id = int(model.config.pad_token_id)
+            elif getattr(model.config, "eos_token_id", None) is not None:
+                tokenizer.pad_token_id = int(model.config.eos_token_id)
+            else:
+                tokenizer.add_special_tokens({"pad_token": "[PAD]"})
+        tokenizer.padding_side = "left"
+        tokenizer.truncation_side = "left"  # TODO @nouamane: do we want this?
+
+        import wandb
+
+        if dist.get_rank() == 0:
+            wandb.init(
+                project="debug_infini_attention",
+                name="debug_infini_attention",
+            )
+
+        # dummy_inputs = [
+        #     # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
+        #     # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
+        #     # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
+        #     # "def fib(n)",
+        #     # "This film was probably inspired by Godzilla",
+        #     # END_PASSKEY,
+        #     PASSKEY_NINETY_PERCENT,
+        #     # FINETUNE
+        # ]
+
+        # generate(args, model, tokenizer, [HARRY_POTTER], parallel_context)
+
+        # dataset = load_dataset("nanotron/simple_needle_in_a_hay_stack", split="train")
+        # df = load_dataset("nanotron/simple_needle_in_a_hay_stack", split="train")
+        # from datasets import load_dataset
+
+        # dataset = load_dataset("lvwerra/needle-llama3-16x512", split="train")
+        # df = load_dataset("lvwerra/needle-llama3-16x512", split="train")
+
+        # dataset = load_dataset("nanotron/needle_in_a_hay_stack_eval_dataset", split="train")
+        # df = load_dataset("nanotron/needle_in_a_hay_stack_eval_dataset", split="train")
+
+        # NOTE: filter out only samples with context_length is 32768
+        dataset = dataset.filter(lambda x: x["context_length"] == 32768 and x["depth_percent"] == depth_percent)
+        df = df.filter(lambda x: x["context_length"] == 32768 and x["depth_percent"] == depth_percent)
+
+        # # Filter and select the first 2 samples for each unique 'depth_percent' value
+        # dataset = dataset.group_by("depth_percent").select(keep_from_disk=True, indices=lambda group: group[:2])
+        # df = df.group_by("depth_percent").select(keep_from_disk=True, indices=lambda group: group[:2])
+
+        # # NOTE: only take 2 sample for each unique depth_percent
+        # dataset = dataset.groupby('depth_percent').head(2)
+        # df = df.groupby('depth_percent').head(2)
+
+        # dataset = dataset.select(range(len(dataset)-1, -1, -1))
+        # df = df.select(range(len(df)-1, -1, -1))
+
+        # nOTE: only take 10 samples
+        # dataset = dataset.select(range(10))
+        # df = df.select(range(10))
+
+        # NOTE: now reverse these dataset
+
+        dataloader = torch.utils.data.DataLoader(dataset, batch_size=1, shuffle=False)
+
+        df.set_format("pandas")
+        df = df[:]
+
+        # for i in range(10):
+        #     texts = [dataset["prompt"][i]]
+        #     needle = dataset["answer"][i]
+        #     generate(args, model, tokenizer, texts, needle, parallel_context)
+
+        responses = []
+        from tqdm import tqdm
+
+        for batch in tqdm(dataloader):
+            print("--------------------------------------------------")
+            print(f"target answer: {batch['answer']}")
+            texts = batch["prompt"]
+            # texts = batch["haystack_text"]
+            # needle = batch["answer"]
+            from nanotron import constants
+
+            constants.NEEDLE = batch["answer"].item()
+
+            responses.append(generate(args, model, tokenizer, texts, parallel_context))
+
+        # NOTE: now flatten the responses
+        responses = [response for sublist in responses for response in sublist]
+        df["response"] = responses
+        # df["match"] = df.apply(lambda x: int(str(x["needle"]) in x["response"]), axis=1)
+
+        # NOTE: move anything from gpu to cpu in df
+
+        # nOTE: now save df
+        # df.to_pickle(f'needle_finetune_format_dataset_but_for_evals_{context_length}_ctx_and_{depth_percent}_depth.pkl')
+
+    dist.barrier()
+
+
+if __name__ == "__main__":
+    main()
diff --git a/run_generate.py b/run_generate.py
index c50dde94..642fb3c3 100644
--- a/run_generate.py
+++ b/run_generate.py
@@ -53,9 +53,11 @@
 logger = logging.get_logger(__name__)
 
 
-END_PASSKEY = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. The pass key is 5666. Remember it. 5666 is the pass key. What is the pass key? The pass key is"
+END_PASSKEY_EXTACT_32K_TOKENS = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................... The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe. The pass key is 1995242. Remember it. 1995242 is the pass key. . \n\nWhat is the pass key? The pass key is "
+
+
+END_PASSKEY_NOT_EXTACT_32K_TOKENS = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe. The pass key is 1995242. Remember it. 1995242 is the pass key. . \n\nWhat is the pass key? The pass key is "
 
-PASSKEY_NINETY_PERCENT = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The pass key is 9918. Remember it. 9918 is the pass key. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. From coast to coast. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The mountain is high. The snow is cold. The air is thin. Upward we climb. From base to peak. The forest is dense. The trees are tall. The path is winding. Into the woods. Out and back. The river is wide. The current is strong. The banks are muddy. Down the stream. Back and forth. The ocean is vast. The waves are calming. The sand is warm. Onward we sail. What is the pass key? The pass key is"
 
 FINETUNE = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with peopleThe pass key is 1853. Remember it. 1853 is the pass key. . Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The ur What is the pass key? The pass key is"
 
@@ -171,15 +173,13 @@ def main():
         tokenizer.padding_side = "left"
         tokenizer.truncation_side = "left"  # TODO @nouamane: do we want this?
         dummy_inputs = [
-            # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
-            # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
             # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
             # "def fib(n)",
             # "This film was probably inspired by Godzilla",
             # "Paris is the capital of",
-            # END_PASSKEY,
+            END_PASSKEY_EXTACT_32K_TOKENS,
             # PASSKEY_NINETY_PERCENT,
-            "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The grass is green. The sky is blue. The pass key is 2. Remember it. 2 is the pass key. What is the pass key? The pass key is ",
+            # "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The grass is green. The sky is blue. The pass key is 1. Remember it. 1 is the pass key. What is the pass key? The pass key is ",
             # FINETUNE
         ]
 
@@ -190,7 +190,7 @@ def main():
             model=model.model,
             parallel_context=parallel_context,
             max_new_tokens=args.max_new_tokens,
-            max_micro_batch_size=2,
+            max_micro_batch_size=1,
             generation_config=GenerationArgs(sampler="greedy", use_cache=False),
             tokenizer_config=TokenizerConfig(max_input_length=None),
             is_bench=os.environ.get("USE_BENCH", "0") == "1",

From 97d3861b5755eb124da74326a59ea1e8d045c080 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Fri, 31 May 2024 11:35:02 +0000
Subject: [PATCH 25/43] save generation

---
 run_generate.py                   | 231 ++++++++++++++++++++++++++++--
 src/nanotron/generation/decode.py |  86 ++++++-----
 2 files changed, 272 insertions(+), 45 deletions(-)

diff --git a/run_generate.py b/run_generate.py
index 642fb3c3..5d6ed4a0 100644
--- a/run_generate.py
+++ b/run_generate.py
@@ -61,6 +61,193 @@
 
 FINETUNE = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with peopleThe pass key is 1853. Remember it. 1853 is the pass key. . Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The ur What is the pass key? The pass key is"
 
+TRAINING_DATA_4K = """
+of CaterBuzz, a vibrant community where food, technology, and insect enthusiasts converge.
+
+First, let's get acquainted with some key players mentioned in the webpage extract:
+
+* Lon Lan III, RollingBee, Dianne Evans, and Vince Pavone are caterBuzz members who actively contribute to discussions about the catering industry.
+* Pauline Hoogmoed and the Catersource team organize events like #cses2014, which brings professionals together to learn and share knowledge.
+* Roll-e-Bee is the latest addition to the caterBuzz family, serving as both a social media mascot and source of humor.
+
+Now, back to entomology and apiculture. While they may seem unrelated at first glance, these fields intersect when discussing the use of insects, specifically honeybees, in culinary applications. Honeybees play a crucial role in pollinating plants and producing honey, but did you know their larvae can also be consumed? Rich in protein, iron, calcium, and essential fatty acids, bee larvae present an intriguing alternative protein source worth considering.
+
+The caterBuzz community embraces this idea by incorporating elements of entomophagy and apiculture into their conversations. By sharing recipes, resources, and insights related to these practices, they foster creativity and innovation among members while promoting sustainability and responsible consumption.
+
+Moreover, the lighthearted nature of the extract showcases another aspect of caterBuzz: its ability to engage users through entertaining content. From punny captions ("got rubber? - chef rubber girl is awesome!") to clever hashtags (#buzzie twins), the platform encourages interaction and camaraderie among participants. This unique blend of education, entertainment, and engagement makes caterBuzz stand out as a go-to destination for catering professionals looking to expand their horizons.
+
+In conclusion, exploring the intersection of entomology, apiculture, and social media provides us with valuable lessons about adaptability, inclusivity, and forward-thinking approaches within various industries. As consumers continue seeking novel experiences and sustainable options, communities like caterBuzz will remain vital hubs for inspiration and growth.
+
+So why not join the conversation? Visit caterBuzz today and discover new ways to incorporate insects and honeybees into your culinary creations. Who knows – you might even find yourself becoming an advocate for entomophagy or apiculture along the way!<|endoftext|>import numpy as np
+
+from ml_algorithms import utils
+
+
+class LogisticRegression:
+    def __init__(self, penalty='l2', C=1, l1_ratio=0, fit_intercept=True):
+        self.penalty = penalty.lower()
+        self.C = C
+        self.l1_ratio = l1_ratio
+        self.fit_intercept = fit_intercept
+        self.n_features = 0
+        self.n_classes = 0
+        self.weights = []
+        self.bias = 0
+
+    def _penalty_cost(self):
+        if self.penalty == 'l1':
+            return utils.l1_penalty(self.C, self.weights)
+        elif self.penalty == 'l2':
+            return utils.l2_penalty(self.C, self.weights)
+        elif self.penalty == 'elasticnet':
+            return utils.elasticnet_penalty(self.C, self.l1_ratio, self.weights)
+        else:
+            return utils.no_penalty(self.C, self.weights)
+
+    def _penalty_gradient(self):
+        if self.penalty == 'l1':
+            return utils.l1_penalty_gradient(self.C, self.weights)
+        elif self.penalty == 'l2':
+            return utils.l2_penalty_gradient(self.C, self.weights)
+        elif self.penalty == 'elasticnet':
+            return utils.elasticnet_penalty_gradient(self.C, self.l1_ratio, self.weights)
+        else:
+            return utils.no_penalty_gradient(self.C, self.weights)
+
+    def fit(self, X, y, epochs=100, lr=1e-3):
+        X = np.array(X)
+        y = np.array(y)
+        n, k = X.shape
+
+        self.n_features = k
+        self.n_classes = 2
+
+        if self.fit_intercept:
+            ones = np.ones((n, 1))
+            X = np.concatenate((ones, X), 1)
+
+        training_loss = []
+        training_acc = []
+
+        # random weight initialization
+        beta = np.random.randn(k) / np.sqrt(k)
+
+        # gradient descent
+        for _ in range(epochs):
+            z = np.dot(X, beta)
+            a = utils.sigmoid(z)
+            gradient = np.dot(X.T, a - y) / n
+            penalty = self._penalty_gradient()
+            beta -= lr * (gradient + penalty)
+
+            if self.fit_intercept:
+                self.bias = beta[0]
+                self.weights = beta[1:]
+            else:
+                self.bias = 0
+                self.weights = beta
+
+            # cross entropy + penalty loss
+            loss = utils.binary_cross_entropy(a, y) + self._penalty_cost()
+            # binary accuracy
+            acc = np.mean(np.around(a) == y)
+
+            training_loss.append(loss)
+            training_acc.append(acc)
+
+        return training_loss, training_acc
+
+    def predict_proba(self, X):
+        return utils.sigmoid(np.dot(X, self.weights) + self.bias)
+
+    def predict_log_proba(self, X):
+        return np.log(self.predict_proba(X))
+
+    def predict(self, X):
+        return np.around(self.predict_proba(X))
+
+    def evaluate(self, X, y):
+        y = np.array(y)
+        y_pred_prob = self.predict_proba(X)
+        y_pred = np.argmax(y_pred_prob, axis=1)
+
+        # binary cross entropy + penalty loss
+        loss = utils.binary_cross_entropy(y_pred_prob, y) + self._penalty_cost()
+        # binary accuracy
+        acc = np.mean(y_pred == y)
+
+        return loss, acc
+<|endoftext|> Title: Unleashing the Power of Cannabis and CBD Products: A Closer Look at the Magma-sized Prize Pack
+
+Have you ever thought about growing marijuana? Whether you're an experienced grower or just starting, one thing's for sure - it's both exciting and challenging. With the right knowledge, resources, and a little bit of patience, cultivating cannabis can yield fantastic rewards. And speaking of rewards, let's dive into the incredible prize pack mentioned in our opening extract! This amazing collection includes products from two prominent players in the cannabis scene - WholesomeCo and UTTHC (Utah Therapeutic Healing Centers). So buckle up as we explore each item and discuss what makes them so special in today's world of cannabis and CBD products.
+
+First off, we have the Silver Analog Volcano Vaporizer by Storz & Bickel, proudly presented by WholesomeCo. If you're familiar with high-quality vaporizers, then chances are you've heard of this German engineering marvel. The Volcano Vaporizer has been around since 2000, consistently winning awards and impressing users with its unparalleled performance. Its unique pure convection heating system ensures even heat distribution, delivering intense flavors while preserving delicate terpenes and avoiding combustion altogether. Using the Volcano provides smooth draws filled with delicious, aromatic vapor, setting itself apart from other devices in the market. Enjoying premium flowers like WholesomeCo's Wombat Juice Flower through such technology elevates your experience to new heights. Known for providing uplifting, calming, stress-relieving, and mood-enhancing benefits, this strain embodies all things delightful about quality cannabis. It might not erupt physically, but trust us when we say that these buds burst with potential!
+
+Moving on to offerings from UTTHC, they provide essential tools any cannabis enthusiast would appreciate. First up is their Med Card Evaluation or Renewal Visit, allowing easy access to medical cannabis programs if needed. Telehealth services make consultations convenient and hassle-free, especially during times when visiting clinics may pose challenges. Additionally, owning a top-notch grinder is vital for consistent grinding results; fortunately, UTMMJ offers a sleek model designed specifically for herbs. No need to worry about uneven grounds messing up your rolling technique anymore! Lastly, rock some style with swaggy merchandise - receive a comfy UTMMJ t-shirt and cap to flaunt your love for medicinal plants anywhere you go. These useful items showcase support towards organizations advocating for safe and responsible use of cannabinoids.
+
+Combined, these extraordinary gifts total more than $800 worth of value, waiting patiently for ONE lucky person who participates in the giveaway. Make sure to follow the instructions provided carefully, subscribing to Discover Marijuana on YouTube, leaving comments, and filling out the required form. Remember, winners will be announced on August 1st, giving everyone ample opportunity to join beforehand. For full rules and regulations, head over to utmmj.org/terms.
+
+As discussed earlier, exploring the world of cannabis and CBD products requires patience, dedication, and curiosity. But armed with reliable sources and trusted brands, navigating becomes significantly easier. By supporting companies committed to education, innovation, and social responsibility, consumers help shape the future landscape of legalized cannabis consumption positively. Happy growing and best wishes for those entering the contest!<|endoftext|> The world of medicine is constantly evolving, and it's not just about breakthrough treatments or innovative surgical procedures. Sometimes, even something as seemingly mundane as managing office equipment can have a significant impact on healthcare providers' operations and bottom line. This is where managed print services come into play, providing solutions that help medical organizations streamline their printing processes while reducing costs and improving efficiency.
+
+Let's take a closer look at how Vein Clinics of America benefited from implementing managed print services by using the extract provided as our starting point.
+
+First, let's understand what Vein Clinics of America does - they specialize in treating various venous disorders such as varicose veins, spider veins, and leg ulcers across multiple clinics nationwide. With so many locations and employees, effective communication becomes crucial. Having reliable printing infrastructure plays an essential role in ensuring smooth internal workflows and patient care.
+
+Before transitioning to managed print services, Vein Clinics faced several challenges related to their printer management. These issues include relying on local dealers for copiers, having excess inventory at every clinic, and buying new replacements whenever printers malfunctioned instead of repairing them. Such practices led to unnecessary expenses and inefficiencies.
+
+Now imagine if similar problems existed within larger hospital systems or research institutions. Mismanagement of print resources could lead to substantial financial losses and hinder important scientific advancements due to preventable operational hurdles.
+
+When Vein Clinics decided to partner with a managed print provider, they gained access to more strategic and cost-effective solutions tailored specifically to their unique requirements. By recommending keeping existing assets functioning rather than replacing them prematurely, the managed print provider helped extend the lifespan of the devices and lower capital expenditures. Moreover, focusing on servicing rather than merely selling hardware allowed for quicker resolution times when issues did arise.
+
+Additionally, introducing a hardware assurance guarantee ensured maximum uptime, minimizing disruptions to daily activities. Finally, the flexible agreement enabled Vein Clinics to scale its printing capabilities according to changing demands seamlessly.
+
+The benefits experienced by Vein Clinics offer insights into how managed print services can revolutionize print management within the broader scope of medicine. Some key takeaways include:
+
+1. Cost savings: Managed print services help reduce overall spending through optimized device utilization, efficient consumables management, and proactive maintenance.
+2. Improved productivity: Quick response times to service requests and regular updates mean less downtime and increased employee output.
+3. Scalability: Flexible agreements allow healthcare providers to adjust their printing capacity based on growth trajectories or fluctuations in demand.
+4. Environmental sustainability: Efficient resource allocation leads to reduced waste generation, contributing positively towards environmental goals.
+5. Focus on core competencies: Outsourcing print management enables healthcare professionals to concentrate on delivering quality care without worrying about peripheral tasks.
+
+In conclusion, adopting managed print services offers numerous advantages beyond mere cost reduction. It allows healthcare providers to streamline their operations, enhance productivity, promote sustainability, and ultimately improve focus on patient care. Whether you're running a small chain of clinics or managing a large hospital network, embracing smart print management strategies can make a considerable difference in your organization's success.<|endoftext|> Title: The New Polymer Banknote and the Future of Cryptocurrency: Is There a Intersection?
+
+Hello there, savvy readers! Today we'll be discussing the recent release of the new £20 polymer banknote by the Bank of England and how it relates to the ever-evolving world of cryptocurrency and blockchain technology. So let's dive right in!
+
+On February 20th, 2020, the Bank of England introduced its latest addition to the British currency family - the new polymer £20 note featuring the prominent artist J.M.W Turner. While this may seem unrelated to digital currencies at first glance, it raises some fascinating questions about the future of money and transactions. Will physical cash become obsolete as more people turn towards cryptocurrencies such as Bitcoin, Ethereum, Ripple etc., or will it continue to coexist alongside them? Let us explore further!
+
+Firstly, what makes these new polymer notes so special? Well, they are designed to last longer than traditional paper bills while also being harder to counterfeit due to advanced security features. This could potentially extend the lifespan of physical cash, thereby slowing down the transition to fully digital finance systems. However, even with improved durability, many experts believe that cash might eventually phase out completely – but when exactly would that happen? And what implications does this have for crypto enthusiasts?
+
+Interestingly enough, cryptocurrencies can learn quite a bit from these new polymer notes. For instance, one common criticism against digital coins is their susceptibility to hacking and cyber theft. By incorporating cutting-edge encryption methods used in blockchain technology, virtual currencies could enhance user protection and foster greater trust among potential investors. Additionally, just like how the BoE implemented public engagement campaigns during the rollout process of the new £20 note, crypto platforms need to ensure clear communication channels to address any concerns or misconceptions held by users.
+
+Another point worth noting is central banks' growing interest in creating their own digital currencies. Sweden's Riksbank and China's People's Bank of China are already exploring possibilities in this area. These Central Bank Digital Currencies (CBDCs), if successful, could provide stiff competition to decentralized alternatives like Bitcoin and Ether. After all, who wouldn't prefer using a state-backed digital coin over ones plagued by volatility issues?
+
+However, despite CBDCs posing challenges for cryptos, they also present opportunities for collaboration. With both relying on distributed ledger technologies, merging forces could result in stronger financial networks capable of handling large volumes of transactions efficiently and securely. Imagine transferring funds across borders seamlessly without worrying about conversion rates or hidden fees! Sounds promising, doesn't it?
+
+In conclusion, although the launch of the new polymer £20 note may appear detached from the realm of cryptocurrencies, it serves as a reminder of how innovation drives evolution in our monetary systems. Whether you're pro-cash, pro-crypto, or somewhere in between, understanding the dynamics shaping each sphere allows us to better navigate this exciting landscape of endless possibilities.
+
+Remember, change is inevitable, especially in something as dynamic as currency. Embrace it, adapt to it, and keep learning because knowledge empowers us to make informed decisions about our financial futures. Until next time, stay curious and informed!<|endoftext|> Title: Navigating Student Enquiries: A Key Component of Real Estate & Investment Education
+
+Introduction
+
+As a prospective or current real estate investor, education plays a crucial role in shaping your success. One essential aspect of this learning journey involves seeking assistance to manage various student enquiries effectively. Whether it's clarifying concepts through frequently asked questions (FAQs), submitting specific queries via online forms, or connecting directly with support staff, these channels enable students to access vital resources efficiently. Let's explore how each method contributes to enhancing your understanding of real estate investment principles while fostering a sense of community among learners.
+
+The Power of FAQs: Harnessing Collective Wisdom
+
+Imagine being able to tap into the collective knowledge of fellow students who have already encountered similar challenges as you embark on your real estate investment studies. That's precisely what FAQ sections offer! These repositories contain answers to common questions posed by previous learners, allowing you to glean insights from their experiences and potentially save time searching for solutions independently. By perusing through carefully curated FAQs, you can quickly grasp key concepts related to property valuation, market trends, financing options, and risk management strategies. Moreover, regularly updated FAQs ensure that the content remains relevant and responsive to evolving industry dynamics.
+
+Online Enquiry Forms: Tailored Assistance at Your Fingertips
+
+Sometimes, your unique situation may not align perfectly with general FAQ entries. This is where customized online enquiry forms shine! By submitting a detailed description of your concern, you provide subject matter experts with sufficient context to craft targeted responses tailored specifically to your needs. As such, this approach often yields more precise and comprehensive solutions than broad searches might yield. Additionally, tracking past interactions within your account facilitates continuity in communication, enabling both parties to reference prior exchanges effortlessly. Over time, building rapport with dedicated support teams can significantly enhance your overall educational experience, particularly when navigating intricate topics like taxation implications, legal considerations, or portfolio diversification tactics.
+
+Phone Support: The Human Touch in Digital Learning
+
+Despite rapid advancements in technology, there remains no substitute for human connection—especially during challenging moments in one's academic journey. Speaking directly with a representative provides immediate reassurance, addressing any lingering doubts or concerns that haven't been adequately addressed through other channels. Furthermore, telephone conversations allow for spontaneous dialogue, prompting follow-up questions or alternative viewpoints that might otherwise go unexplored in written correspondence. While waiting times and availability may vary depending on demand, having access to expert advice during regular business hours helps maintain momentum in your studies, ultimately contributing to long-term retention and proficiency in real estate investment practices.
+
+ID Cards & Official Documents: Streamlined Verifications for Accreditation
+
+Lastly, obtaining verifiable credentials is paramount for demonstrating competence within the competitive realm of real estate investing. Securing physical or digital ID cards and certificates serves as
+"""
+
 
 def get_args():
     parser = argparse.ArgumentParser()
@@ -174,13 +361,34 @@ def main():
         tokenizer.truncation_side = "left"  # TODO @nouamane: do we want this?
         dummy_inputs = [
             # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
+            # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
+            # "This is a math lesson. Answer the question. What is the result of 1 + 1? The result is ",
+            # "This is a math lesson. Answer the question. What is the result of 1 + 1? The result is ",
             # "def fib(n)",
-            # "This film was probably inspired by Godzilla",
-            # "Paris is the capital of",
-            END_PASSKEY_EXTACT_32K_TOKENS,
+            # "This film was probably inspired by Godzilla, ",
+            # "This film was probably inspired by Godzilla, ",
+            # "Paris is the capital of ",
+            # "Paris is the capital of ",
+            # END_PASSKEY_EXTACT_32K_TOKENS,
+            # END_PASSKEY_EXTACT_32K_TOKENS,
             # PASSKEY_NINETY_PERCENT,
-            # "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The grass is green. The sky is blue. The pass key is 1. Remember it. 1 is the pass key. What is the pass key? The pass key is ",
-            # FINETUNE
+            # "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The grass is green. The sky is blue. The pass key is 24. Remember it. 24 is the pass key. What is the pass key? The pass key is ",
+            # "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The grass is green. The sky is blue. The pass key is 24. Remember it. 24 is the pass key. What is the pass key? The pass key is ",
+            # FINETUNE,
+            # "1234",
+            # "1234",
+            # "Hi there, I'm from the USA, my name is ",
+            # "Hi there, I'm from the USA, my name is ",
+            # NOTE: training data
+            # "InterruptEnumeration of all the interrupts. This enum is seldom used in application or library crates. It is present primarily for",
+            # "InterruptEnumeration of all the interrupts. This enum is seldom used in application or library crates. It is present primarily for",
+            # "If the parser encounters a syntax error, an error event value incl. a description and input position will be produced (but no JS error will be thrown) and the entire ",
+            # "If the parser encounters a syntax error, an error event value incl. a description and input position will be produced (but no JS error will be thrown) and the entire ",
+            # "This work introduces an efficient method to scale Transformer-based ",
+            # "This work introduces an efficient method to scale Transformer-based "
+            # NOTE: last training data
+            # "Effectively managing student enquiries lies at the heart of successful real estate and investment education. Through leveraging diverse resources such as FAQs, online enquiry ",
+            TRAINING_DATA_4K,
         ]
 
         outputs = decode_text(
@@ -190,8 +398,9 @@ def main():
             model=model.model,
             parallel_context=parallel_context,
             max_new_tokens=args.max_new_tokens,
-            max_micro_batch_size=1,
-            generation_config=GenerationArgs(sampler="greedy", use_cache=False),
+            max_micro_batch_size=2,
+            generation_config=GenerationArgs(sampler="top_k", use_cache=False),
+            # generation_config=GenerationArgs(sampler="top_p", use_cache=False),
             tokenizer_config=TokenizerConfig(max_input_length=None),
             is_bench=os.environ.get("USE_BENCH", "0") == "1",
         )
@@ -205,14 +414,17 @@ def main():
 
             log_rank(
                 # f"input: {tokenizer.decode(input_ids, clean_up_tokenization_spaces=False)[:1000]}",
-                f"input: {tokenizer.decode(input_ids, clean_up_tokenization_spaces=False)}",
+                f"""input_ids: {input_ids} \n
+                decoded_input: {tokenizer.decode(input_ids, clean_up_tokenization_spaces=False)}
+                """,
                 logger=logger,
                 level=logging.INFO,
                 rank=0,
             )
 
             log_rank(
-                f"generation: {tokenizer.decode(generated_ids[len(input_ids) :], clean_up_tokenization_spaces=False)}",
+                f"""generation_ids: {generated_ids[len(input_ids) :]}
+                decoded_generation: {tokenizer.decode(generated_ids[len(input_ids) :], clean_up_tokenization_spaces=False)}""",
                 logger=logger,
                 level=logging.INFO,
                 rank=0,
@@ -231,6 +443,7 @@ def main():
             model=model.model,
             parallel_context=parallel_context,
             generation_config=GenerationArgs(sampler="greedy", use_cache=False),
+            # generation_config=GenerationArgs(sampler="top_p", use_cache=False),
             max_micro_batch_size=1,
             max_new_tokens=12,
             returns_logits=False,
diff --git a/src/nanotron/generation/decode.py b/src/nanotron/generation/decode.py
index 8e4bae94..f8caafcf 100644
--- a/src/nanotron/generation/decode.py
+++ b/src/nanotron/generation/decode.py
@@ -131,9 +131,55 @@ def find_sequence_positions(tensor, sequence):
 
         if dist.get_rank(parallel_context.pp_pg) == input_rank:
 
-            # tokenizer.eos_token_id = 2
-            # tokenizer.bos_token_id = 1
-            # tokenizer.pad_token_id = tokenizer.eos_token_id
+            tokenizer.eos_token_id = 2
+            tokenizer.bos_token_id = 1
+            tokenizer.pad_token_id = tokenizer.eos_token_id
+
+            # encodings = tokenizer(
+            #     [elt.text for elt in micro_batch],
+            #     return_tensors="pt",
+            #     return_attention_mask=True,
+            #     padding=tokenizer_config.padding,
+            #     max_length=tokenizer_config.max_input_length,
+            #     truncation=tokenizer_config.truncation,
+            #     # pad_to_multiple_of=8
+            # )
+
+            # # encodings = tokenizer(
+            # #     [elt.text for elt in micro_batch],
+            # #     return_tensors="pt",
+            # #     return_attention_mask=True,
+            # #     padding="max_length",
+            # #     max_length=32768,
+            # #     truncation=False,
+            # #     # pad_to_multiple_of=8
+            # # )
+
+            # # TARGET_INPUT_IDS = tokenizer(["Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?"], return_tensors="pt")["input_ids"][0]
+            # # LENGTH = TARGET_INPUT_IDS.shape[0]
+            # # assert encodings["input_ids"][0].shape[0] == 32768
+            # # encodings["input_ids"] = encodings["input_ids"][:, :2049]
+            # # encodings["attention_mask"] = encodings["attention_mask"][:, :2049]
+            # # encodings["input_ids"][:, 2048-LENGTH:2048] = TARGET_INPUT_IDS
+
+            # # import math
+            # # seq_len = encodings["input_ids"].shape[1]
+            # # segment_length = 2048
+
+            # # n_segments = math.ceil(seq_len / segment_length)
+            # # segment_lengths = [segment_length] * (n_segments - 1) + [seq_len - (n_segments - 1) * segment_length]
+            # # xs_input_ids = torch.split(encodings["input_ids"][0], segment_lengths, dim=0)
+
+            # # from nanotron.constants import NEEDLE
+            # # last_segment_text = tokenizer.decode(xs_input_ids[-1])
+            # # if str(NEEDLE) in last_segment_text:
+            # #     print(f"{NEEDLE} is in the last segment")
+            # # else:
+            # #     print(f"can't find the needle {NEEDLE} in the last segment")
+
+            # encodings["attention_mask"] = encodings.attention_mask.to(dtype=torch.bool, device="cuda")
+            # encodings.to("cuda")
+            # yield GenerationInputs(input_ids=encodings.input_ids, input_masks=encodings.attention_mask)
             encodings = tokenizer(
                 [elt.text for elt in micro_batch],
                 return_tensors="pt",
@@ -144,41 +190,10 @@ def find_sequence_positions(tensor, sequence):
                 # pad_to_multiple_of=8
             )
 
-            # encodings = tokenizer(
-            #     [elt.text for elt in micro_batch],
-            #     return_tensors="pt",
-            #     return_attention_mask=True,
-            #     padding="max_length",
-            #     max_length=32768,
-            #     truncation=False,
-            #     # pad_to_multiple_of=8
-            # )
-
-            # TARGET_INPUT_IDS = tokenizer(["Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?"], return_tensors="pt")["input_ids"][0]
-            # LENGTH = TARGET_INPUT_IDS.shape[0]
-            # assert encodings["input_ids"][0].shape[0] == 32768
-            encodings["input_ids"] = encodings["input_ids"][:, :2049]
-            encodings["attention_mask"] = encodings["attention_mask"][:, :2049]
-            # encodings["input_ids"][:, 2048-LENGTH:2048] = TARGET_INPUT_IDS
-
-            # import math
-            # seq_len = encodings["input_ids"].shape[1]
-            # segment_length = 2048
-
-            # n_segments = math.ceil(seq_len / segment_length)
-            # segment_lengths = [segment_length] * (n_segments - 1) + [seq_len - (n_segments - 1) * segment_length]
-            # xs_input_ids = torch.split(encodings["input_ids"][0], segment_lengths, dim=0)
-
-            # from nanotron.constants import NEEDLE
-            # last_segment_text = tokenizer.decode(xs_input_ids[-1])
-            # if str(NEEDLE) in last_segment_text:
-            #     print(f"{NEEDLE} is in the last segment")
-            # else:
-            #     print(f"can't find the needle {NEEDLE} in the last segment")
-
             encodings["attention_mask"] = encodings.attention_mask.to(dtype=torch.bool, device="cuda")
             encodings.to("cuda")
             yield GenerationInputs(input_ids=encodings.input_ids, input_masks=encodings.attention_mask)
+
         else:
             yield GenerationInputs(
                 input_ids=TensorPointer(group_rank=input_rank), input_masks=TensorPointer(group_rank=input_rank)
@@ -334,7 +349,6 @@ def decode_text(
                             input_ids=batch_generated_ids,
                             input_mask=batch_generated_mask,
                         )
-                        # sharded_logits = sharded_logits.transpose(0, 1)
 
                         assert 1 == 1
 

From 5a15f2e07d94c1a21c4dd287f1335753cc492555 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Fri, 31 May 2024 12:13:24 +0000
Subject: [PATCH 26/43] add specifying segment length, ctx length, and turn
 on/off memory from config

---
 src/nanotron/config/config.py |   7 +++
 src/nanotron/constants.py     |   2 +
 src/nanotron/models/llama.py  | 107 +++++++++++++++++++---------------
 3 files changed, 68 insertions(+), 48 deletions(-)

diff --git a/src/nanotron/config/config.py b/src/nanotron/config/config.py
index 18a03d38..814ad0ee 100644
--- a/src/nanotron/config/config.py
+++ b/src/nanotron/config/config.py
@@ -297,6 +297,12 @@ def __post_init__(self):
             self.seed = DEFAULT_SEED
 
 
+@dataclass
+class InfiniAttentionArgs:
+    segment_length: int
+    turn_on_memory: bool
+
+
 @dataclass
 class Config:
     """Main configuration class"""
@@ -305,6 +311,7 @@ class Config:
     parallelism: ParallelismArgs
     model: ModelArgs
     tokenizer: TokenizerArgs
+    infini_attention: InfiniAttentionArgs
     checkpoints: Optional[CheckpointsArgs] = None
     logging: Optional[LoggingArgs] = None
     tokens: Optional[TokensArgs] = None
diff --git a/src/nanotron/constants.py b/src/nanotron/constants.py
index 7ba33101..05555003 100644
--- a/src/nanotron/constants.py
+++ b/src/nanotron/constants.py
@@ -18,3 +18,5 @@
 GLOBAL_STEP: Optional[int] = None
 LOG_STATE_INTERVAL = 500
 CONFIG = None
+
+TRAINING_CONFIG = None
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 4063627a..baea8487 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -381,17 +381,17 @@ def pad_to_right(tensor, mask, new_tensor=None):
 #         )  # TODO @nouamane: compute based on free memory, because in rope we can surpass max_position_embeddings
 
 #         # self.n_segments = 16
-#         # self.segment_lengths = config.max_position_embeddings // self.n_segments
+#         # self.segment_length = config.max_position_embeddings // self.n_segments
 #         # assert config.max_position_embeddings == 32768
 
 #         # NOTE: for 1b training
-#         self.segment_lengths = 2048
-#         # self.segment_lengths = 4096
+#         self.segment_length = 2048
+#         # self.segment_length = 4096
 
 #         # NOTE: for sanity 200m training
 #         # prev 16
-#         # self.segment_lengths = 256
-#         # self.segment_lengths = 16
+#         # self.segment_length = 256
+#         # self.segment_length = 16
 
 #         device = self.o_proj.weight.device
 #         dtype = self.o_proj.weight.dtype
@@ -431,16 +431,16 @@ def pad_to_right(tensor, mask, new_tensor=None):
 #         # segment_length = seq_len // self.n_segments
 #         # hidden_size = hidden_states.shape[2]
 
-#         if seq_len > self.segment_lengths:
-#             # n_segments = seq_len // self.segment_lengths
+#         if seq_len > self.segment_length:
+#             # n_segments = seq_len // self.segment_length
 #             # segment_hidden_states = torch.chunk(hidden_states, chunks=n_segments, dim=0)
 #             # segment_sequence_masks = torch.chunk(sequence_mask, chunks=n_segments, dim=1)
 
 #             import math
 
-#             n_segments = math.ceil(seq_len / self.segment_lengths)
-#             segment_lengths = [self.segment_lengths] * (n_segments - 1) + [
-#                 seq_len - (n_segments - 1) * self.segment_lengths
+#             n_segments = math.ceil(seq_len / self.segment_length)
+#             segment_lengths = [self.segment_length] * (n_segments - 1) + [
+#                 seq_len - (n_segments - 1) * self.segment_length
 #             ]
 #             assert sum(segment_lengths) == seq_len
 #             # assert hidden_states.shape[0] == seq_len
@@ -482,13 +482,13 @@ def pad_to_right(tensor, mask, new_tensor=None):
 #             query_states, key_states, value_states = attn_outputs["qkv_states_without_pe"]
 
 #             # # NOTE: these are the shape for non-megatron-sp
-#             # assert query_states.shape[0] == self.segment_lengths
-#             # assert local_attn_outputs.shape[1] == self.segment_lengths
+#             # assert query_states.shape[0] == self.segment_length
+#             # assert local_attn_outputs.shape[1] == self.segment_length
 
 #             query_states = rearrange(
 #                 query_states,
 #                 "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
-#                 seq_len=self.segment_lengths,
+#                 seq_len=self.segment_length,
 #                 n_heads=self.n_local_q_heads,
 #                 d_head=self.d_qk,
 #             )
@@ -497,7 +497,7 @@ def pad_to_right(tensor, mask, new_tensor=None):
 #                 key_states,
 #                 "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
 #                 # batch_size=batch_size,
-#                 seq_len=self.segment_lengths,
+#                 seq_len=self.segment_length,
 #                 n_heads=self.n_local_kv_heads,
 #                 d_head=self.d_qk,
 #             )
@@ -506,7 +506,7 @@ def pad_to_right(tensor, mask, new_tensor=None):
 #                 value_states,
 #                 "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
 #                 # batch_size=batch_size,
-#                 seq_len=self.segment_lengths,
+#                 seq_len=self.segment_length,
 #                 n_heads=self.n_local_kv_heads,
 #                 d_head=self.d_qk,
 #             )
@@ -543,7 +543,7 @@ def pad_to_right(tensor, mask, new_tensor=None):
 #             local_attn_outputs = rearrange(
 #                 local_attn_outputs,
 #                 "batch_size seq_len (n_heads d_head) -> batch_size n_heads seq_len d_head",
-#                 seq_len=self.segment_lengths,
+#                 seq_len=self.segment_length,
 #                 d_head=self.d_qk,
 #             )
 
@@ -582,7 +582,7 @@ def pad_to_right(tensor, mask, new_tensor=None):
 #                 attention_output, "batch_size n_heads seq_len d_head -> seq_len batch_size (n_heads d_head)",
 #                 n_heads=self.n_local_q_heads,
 #                 d_head=self.d_qk,
-#                 seq_len=self.segment_lengths,
+#                 seq_len=self.segment_length,
 #             )
 
 #             output = self.o_proj(attention_output)
@@ -776,7 +776,7 @@ def pad_to_right(tensor, mask, new_tensor=None):
 #             value_states, "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head"
 #         )
 
-#         assert query_states_without_pe.shape[0] == self.segment_lengths
+#         assert query_states_without_pe.shape[0] == self.segment_length
 
 #         store = self.get_local_store()
 #         if store is not None:  # Inference case
@@ -1096,18 +1096,19 @@ def __init__(
         )  # TODO @nouamane: compute based on free memory, because in rope we can surpass max_position_embeddings
 
         # self.n_segments = 16
-        # self.segment_lengths = config.max_position_embeddings // self.n_segments
+        # self.segment_length = config.max_position_embeddings // self.n_segments
         # assert config.max_position_embeddings == 32768
 
         # NOTE: for 1b training
-        # self.segment_lengths = 2048
-        # self.segment_lengths = 4096
-        self.segment_lengths = 1024  # for 4096 context length
+        # self.segment_length = 2048
+        # self.segment_length = 4096
+        # self.segment_length = 1024  # for 4096 context length
+        self.segment_length = constants.CONFIG.infini_attention.segment_length  # for 1024 context length
 
         # NOTE: for sanity 200m training
         # prev 16
-        # self.segment_lengths = 256
-        # self.segment_lengths = 16
+        # self.segment_length = 256
+        # self.segment_length = 16
 
         device = self.o_proj.weight.device
         dtype = self.o_proj.weight.dtype
@@ -1124,6 +1125,13 @@ def __init__(
             ),
         )
 
+        log_rank(
+            f"Segment length is {self.segment_length}, turn_on_memory: {constants.CONFIG.infini_attention.turn_on_memory is True}",
+            logger=logger,
+            level=logging.WARNING,
+            rank=0,
+        )
+
     def forward(
         self,
         # hidden_states: TensorType["sharded_seq_len", "batch_size", "hidden_size"],
@@ -1147,16 +1155,16 @@ def forward(
         # segment_length = seq_len // self.n_segments
         # hidden_size = hidden_states.shape[2]
 
-        if seq_len > self.segment_lengths:
-            # n_segments = seq_len // self.segment_lengths
+        if seq_len > self.segment_length:
+            # n_segments = seq_len // self.segment_length
             # segment_hidden_states = torch.chunk(hidden_states, chunks=n_segments, dim=0)
             # segment_sequence_masks = torch.chunk(sequence_mask, chunks=n_segments, dim=1)
 
             import math
 
-            n_segments = math.ceil(seq_len / self.segment_lengths)
-            segment_lengths = [self.segment_lengths] * (n_segments - 1) + [
-                seq_len - (n_segments - 1) * self.segment_lengths
+            n_segments = math.ceil(seq_len / self.segment_length)
+            segment_lengths = [self.segment_length] * (n_segments - 1) + [
+                seq_len - (n_segments - 1) * self.segment_length
             ]
             assert sum(segment_lengths) == seq_len
             # assert hidden_states.shape[0] == seq_len
@@ -1198,13 +1206,13 @@ def forward(
             query_states, key_states, value_states = attn_outputs["qkv_states_without_pe"]
 
             # # NOTE: these are the shape for non-megatron-sp
-            # assert query_states.shape[0] == self.segment_lengths
-            # assert local_attn_outputs.shape[1] == self.segment_lengths
+            # assert query_states.shape[0] == self.segment_length
+            # assert local_attn_outputs.shape[1] == self.segment_length
 
             query_states = rearrange(
                 query_states,
                 "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
-                # seq_len=self.segment_lengths,
+                # seq_len=self.segment_length,
                 n_heads=self.n_local_q_heads,
                 d_head=self.d_qk,
             )
@@ -1213,7 +1221,7 @@ def forward(
                 key_states,
                 "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
                 # batch_size=batch_size,
-                # seq_len=self.segment_lengths,
+                # seq_len=self.segment_length,
                 n_heads=self.n_local_kv_heads,
                 d_head=self.d_qk,
             )
@@ -1222,7 +1230,7 @@ def forward(
                 value_states,
                 "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
                 # batch_size=batch_size,
-                # seq_len=self.segment_lengths,
+                # seq_len=self.segment_length,
                 n_heads=self.n_local_kv_heads,
                 d_head=self.d_qk,
             )
@@ -1259,7 +1267,7 @@ def forward(
             local_attn_outputs = rearrange(
                 local_attn_outputs,
                 "batch_size seq_len (n_heads d_head) -> batch_size n_heads seq_len d_head",
-                # seq_len=self.segment_lengths,
+                # seq_len=self.segment_length,
                 d_head=self.d_qk,
             )
 
@@ -1292,14 +1300,17 @@ def forward(
             #     rank=0,
             # )
 
-            attention_output = global_weights * retrieved_memory + local_weights * local_attn_outputs
+            if constants.CONFIG.infini_attention.turn_on_memory is True:
+                attention_output = global_weights * retrieved_memory + local_weights * local_attn_outputs
+            else:
+                attention_output = local_weights * local_attn_outputs
 
             attention_output = rearrange(
                 attention_output,
                 "batch_size n_heads seq_len d_head -> batch_size seq_len (n_heads d_head)",
                 n_heads=self.n_local_q_heads,
                 d_head=self.d_qk,
-                # seq_len=self.segment_lengths,
+                # seq_len=self.segment_length,
             )
 
             output = self.o_proj(attention_output)
@@ -1379,7 +1390,7 @@ def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
             sigma_query_states,
             prev_memory,
             "batch_size n_heads seq_len d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_len d_v",
-            # seq_len=self.segment_lengths,
+            # seq_len=self.segment_length,
             # n_heads=self.n_local_kv_heads,
             # d_k=self.d_qk,
         )
@@ -1390,13 +1401,13 @@ def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
             "batch_size n_heads seq_len d_head, batch_size n_heads d_head -> batch_size n_heads seq_len",
             # n_heads=self.n_local_kv_heads,
             # d_head=self.d_qk,
-            # seq_len=self.segment_lengths,
+            # seq_len=self.segment_length,
         )
         denominator = rearrange(
             denominator,
             "batch_size n_heads seq_len -> batch_size n_heads seq_len 1",
             # n_heads=self.n_local_kv_heads,
-            # seq_len=self.segment_lengths,
+            # seq_len=self.segment_length,
         )
         # [batch_size, n_heads, seq_len, d_v] / [batch_size, n_heads, seq_len, 1], so each d_v is divide by the normalized value
 
@@ -1420,7 +1431,7 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
                 "batch_size n_heads seq_len d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_len d_v",
                 # n_heads=self.n_local_kv_heads,
                 # d_k=self.d_qk,
-                # seq_len=self.segment_lengths,
+                # seq_len=self.segment_length,
             )
             denominator = einsum(
                 sigma_key_states,
@@ -1428,13 +1439,13 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
                 "batch_size n_heads seq_len d_k, batch_size n_heads d_k -> batch_size n_heads seq_len",
                 # n_heads=self.n_local_kv_heads,
                 # d_k=self.d_qk,
-                # seq_len=self.segment_lengths,
+                # seq_len=self.segment_length,
             )
             denominator = rearrange(
                 denominator,
                 "batch_size n_heads seq_len -> batch_size n_heads seq_len 1",
                 # n_heads=self.n_local_kv_heads,
-                # seq_len=self.segment_lengths,
+                # seq_len=self.segment_length,
             )
 
             prev_v = numerator / denominator
@@ -1448,7 +1459,7 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
             reduction="sum",
             n_heads=self.n_local_kv_heads,
             d_head=self.d_qk,
-            # seq_len=self.segment_lengths,
+            # seq_len=self.segment_length,
         )
 
         memory += prev_memory if prev_memory is not None else 0
@@ -1515,23 +1526,23 @@ def forward_with_hidden_states(
         query_states_without_pe = rearrange(
             query_states,
             "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
-            # seq_len=self.segment_lengths,
+            # seq_len=self.segment_length,
             seq_len=seq_len,
         )
         key_states_without_pe = rearrange(
             key_states,
             "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
-            # seq_len=self.segment_lengths,
+            # seq_len=self.segment_length,
             seq_len=seq_len,
         )
         value_states_without_pe = rearrange(
             value_states,
             "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
-            # seq_len=self.segment_lengths,
+            # seq_len=self.segment_length,
             seq_len=seq_len,
         )
 
-        # assert query_states_without_pe.shape[0] == self.segment_lengths
+        # assert query_states_without_pe.shape[0] == self.segment_length
         assert query_states_without_pe.shape[0] == seq_len
 
         store = self.get_local_store()

From 6273da1192bb3d142ca5a47483389dd7be2e02d3 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Fri, 31 May 2024 12:39:48 +0000
Subject: [PATCH 27/43] support turning off memory

---
 src/nanotron/models/llama.py | 165 ++++++++++++++++++-----------------
 1 file changed, 85 insertions(+), 80 deletions(-)

diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index baea8487..6cb501b7 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -1115,22 +1115,23 @@ def __init__(
 
         from nanotron.parallel.sharded_parameters import SplitConfig, create_sharded_parameter_from_config
 
-        balance_factors = nn.Parameter(torch.zeros(self.n_local_q_heads, device=device, dtype=dtype))
-        self.balance_factors = create_sharded_parameter_from_config(
-            parameter=balance_factors,
-            pg=tp_pg,
-            split_config=SplitConfig(
-                split_dim=0,
-                # contiguous_chunks=(self.n_local_heads, self.n_local_heads)
-            ),
-        )
+        if constants.CONFIG.infini_attention.turn_on_memory is True:
+            balance_factors = nn.Parameter(torch.zeros(self.n_local_q_heads, device=device, dtype=dtype))
+            self.balance_factors = create_sharded_parameter_from_config(
+                parameter=balance_factors,
+                pg=tp_pg,
+                split_config=SplitConfig(
+                    split_dim=0,
+                    # contiguous_chunks=(self.n_local_heads, self.n_local_heads)
+                ),
+            )
 
-        log_rank(
-            f"Segment length is {self.segment_length}, turn_on_memory: {constants.CONFIG.infini_attention.turn_on_memory is True}",
-            logger=logger,
-            level=logging.WARNING,
-            rank=0,
-        )
+            log_rank(
+                f"Segment length is {self.segment_length}, turn_on_memory: {constants.CONFIG.infini_attention.turn_on_memory is True}",
+                logger=logger,
+                level=logging.WARNING,
+                rank=0,
+            )
 
     def forward(
         self,
@@ -1235,30 +1236,6 @@ def forward(
                 d_head=self.d_qk,
             )
 
-            # NOTE: because in generation, the sequence length increases
-            # assert query_states.shape == (batch_size, self.n_local_q_heads, segment_length, self.d_qk)
-            # assert query_states.shape == key_states.shape == value_states.shape
-            retrieved_memory = self._retrieve_from_memory(
-                query_states, prev_memory=memory, prev_normalization=normalization
-            )
-
-            # log_rank(
-            #     f"[idx={idx}] retrieved_memory.shape = {retrieved_memory.shape}, retrieve_memory is zero? {(retrieved_memory == 0).all()}",
-            #     logger=logger,
-            #     level=logging.INFO,
-            #     rank=0,
-            # )
-
-            # if memory is not None:
-            #     log_rank(
-            #         f"[idx={idx}] memory.shape = {memory.shape}, normalization.shape = {normalization.shape}",
-            #         logger=logger,
-            #         level=logging.INFO,
-            #         rank=0,
-            #     )
-
-            # retrieved_memory = retrieved_memory.detach()
-
             # local_attn_outputs = rearrange(
             #     local_attn_outputs,
             #     "seq_len batch_size (n_heads d_head) -> batch_size n_heads seq_len d_head",
@@ -1278,32 +1255,56 @@ def forward(
             #     rank=0,
             # )
 
-            global_weights = F.sigmoid(self.balance_factors)
-            global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
-
-            local_weights = 1 - F.sigmoid(self.balance_factors)
-            local_weights = rearrange(local_weights, "n_heads -> 1 n_heads 1 1")
-
-            # assert torch.allclose(global_weights + local_weights, torch.ones_like(global_weights))
-
-            # log_rank(
-            #     f"[idx={idx}] global_weights.shape = {global_weights.shape}, global_weights: {global_weights}",
-            #     logger=logger,
-            #     level=logging.INFO,
-            #     rank=0,
-            # )
+            if constants.CONFIG.infini_attention.turn_on_memory is True:
+                # NOTE: because in generation, the sequence length increases
+                # assert query_states.shape == (batch_size, self.n_local_q_heads, segment_length, self.d_qk)
+                # assert query_states.shape == key_states.shape == value_states.shape
+                retrieved_memory = self._retrieve_from_memory(
+                    query_states, prev_memory=memory, prev_normalization=normalization
+                )
 
-            # log_rank(
-            #     f"[idx={idx}] local_weights.shape = {local_weights.shape}, local_weights: {local_weights}",
-            #     logger=logger,
-            #     level=logging.INFO,
-            #     rank=0,
-            # )
+                # log_rank(
+                #     f"[idx={idx}] retrieved_memory.shape = {retrieved_memory.shape}, retrieve_memory is zero? {(retrieved_memory == 0).all()}",
+                #     logger=logger,
+                #     level=logging.INFO,
+                #     rank=0,
+                # )
+
+                # if memory is not None:
+                #     log_rank(
+                #         f"[idx={idx}] memory.shape = {memory.shape}, normalization.shape = {normalization.shape}",
+                #         logger=logger,
+                #         level=logging.INFO,
+                #         rank=0,
+                #     )
+
+                # retrieved_memory = retrieved_memory.detach()
+
+                global_weights = F.sigmoid(self.balance_factors)
+                global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
+
+                local_weights = 1 - F.sigmoid(self.balance_factors)
+                local_weights = rearrange(local_weights, "n_heads -> 1 n_heads 1 1")
+
+                # assert torch.allclose(global_weights + local_weights, torch.ones_like(global_weights))
+
+                # log_rank(
+                #     f"[idx={idx}] global_weights.shape = {global_weights.shape}, global_weights: {global_weights}",
+                #     logger=logger,
+                #     level=logging.INFO,
+                #     rank=0,
+                # )
+
+                # log_rank(
+                #     f"[idx={idx}] local_weights.shape = {local_weights.shape}, local_weights: {local_weights}",
+                #     logger=logger,
+                #     level=logging.INFO,
+                #     rank=0,
+                # )
 
-            if constants.CONFIG.infini_attention.turn_on_memory is True:
                 attention_output = global_weights * retrieved_memory + local_weights * local_attn_outputs
             else:
-                attention_output = local_weights * local_attn_outputs
+                attention_output = local_attn_outputs
 
             attention_output = rearrange(
                 attention_output,
@@ -1315,25 +1316,29 @@ def forward(
 
             output = self.o_proj(attention_output)
 
-            if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0:
-                if dist.get_rank() == 0:
-                    logs[f"layer_{self.layer_idx}:seg_{idx}:query_states"] = compute_stas(query_states)
-                    logs[f"layer_{self.layer_idx}:seg_{idx}:key_states"] = compute_stas(key_states)
-                    logs[f"layer_{self.layer_idx}:seg_{idx}:value_states"] = compute_stas(value_states)
-
-                    logs[f"layer_{self.layer_idx}:seg_{idx}:global_weights"] = compute_stas(global_weights)
-                    logs[f"layer_{self.layer_idx}:seg_{idx}:local_weights"] = compute_stas(local_weights)
-                    logs[f"layer_{self.layer_idx}:seg_{idx}:local_attn_outputs"] = compute_stas(local_attn_outputs)
-                    logs[f"layer_{self.layer_idx}:seg_{idx}:retrieved_memory"] = compute_stas(retrieved_memory)
-                    logs[f"layer_{self.layer_idx}:seg_{idx}:attention_output"] = compute_stas(attention_output)
-                    logs[f"layer_{self.layer_idx}:seg_{idx}:output"] = compute_stas(output)
-                    logs[f"layer_{self.layer_idx}:seg_{idx}:memory"] = compute_stas(memory)
-                    logs[f"layer_{self.layer_idx}:seg_{idx}:normalization"] = compute_stas(normalization)
-
-            # assert output.shape == (segment_length, batch_size, hidden_size)
-
-            memory, normalization = self._update_memory(memory, normalization, key_states, value_states)
-            # memory = prev_memory if prev_memory is not None else 0.detach()
+            if constants.CONFIG.infini_attention.turn_on_memory is True:
+                if (
+                    constants.GLOBAL_STEP is not None
+                    and (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0
+                ):
+                    if dist.get_rank() == 0:
+                        logs[f"layer_{self.layer_idx}:seg_{idx}:query_states"] = compute_stas(query_states)
+                        logs[f"layer_{self.layer_idx}:seg_{idx}:key_states"] = compute_stas(key_states)
+                        logs[f"layer_{self.layer_idx}:seg_{idx}:value_states"] = compute_stas(value_states)
+
+                        logs[f"layer_{self.layer_idx}:seg_{idx}:global_weights"] = compute_stas(global_weights)
+                        logs[f"layer_{self.layer_idx}:seg_{idx}:local_weights"] = compute_stas(local_weights)
+                        logs[f"layer_{self.layer_idx}:seg_{idx}:local_attn_outputs"] = compute_stas(local_attn_outputs)
+                        logs[f"layer_{self.layer_idx}:seg_{idx}:retrieved_memory"] = compute_stas(retrieved_memory)
+                        logs[f"layer_{self.layer_idx}:seg_{idx}:attention_output"] = compute_stas(attention_output)
+                        logs[f"layer_{self.layer_idx}:seg_{idx}:output"] = compute_stas(output)
+                        logs[f"layer_{self.layer_idx}:seg_{idx}:memory"] = compute_stas(memory)
+                        logs[f"layer_{self.layer_idx}:seg_{idx}:normalization"] = compute_stas(normalization)
+
+                # assert output.shape == (segment_length, batch_size, hidden_size)
+
+                memory, normalization = self._update_memory(memory, normalization, key_states, value_states)
+                # memory = prev_memory if prev_memory is not None else 0.detach()
 
             outputs.append(output)
             # memory, normalization = memory.detach(), normalization.detach()

From 18b3ef37b507fe8cd4b3dc6079cc6b25d3b446e9 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Fri, 7 Jun 2024 08:56:51 +0000
Subject: [PATCH 28/43] fix modeling code for bs = 1

---
 run_generate.py                               |  25 ++-
 src/nanotron/debug/monitor.py                 |  37 ++--
 src/nanotron/models/llama.py                  | 167 ++++++++++++------
 .../parallel/tensor_parallel/functional.py    |  15 +-
 src/nanotron/trainer.py                       |  17 +-
 5 files changed, 180 insertions(+), 81 deletions(-)

diff --git a/run_generate.py b/run_generate.py
index 5d6ed4a0..c25ef8bf 100644
--- a/run_generate.py
+++ b/run_generate.py
@@ -52,6 +52,8 @@
 
 logger = logging.get_logger(__name__)
 
+USE_CACHE = False
+
 
 END_PASSKEY_EXTACT_32K_TOKENS = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................... The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe. The pass key is 1995242. Remember it. 1995242 is the pass key. . \n\nWhat is the pass key? The pass key is "
 
@@ -265,6 +267,9 @@ def main():
     assert args.ckpt_path.exists(), f"Checkpoint path {args.ckpt_path} does not exist"
 
     config = get_config_from_file((args.ckpt_path / "config.yaml").as_posix())
+    from nanotron import constants
+
+    constants.CONFIG = config
     model_config = config.model.model_config
     tokenizer_path = config.tokenizer.tokenizer_name_or_path
 
@@ -273,8 +278,11 @@ def main():
         pp=args.pp or config.parallelism.pp,
         tp=args.tp or config.parallelism.tp,
         pp_engine=OneForwardOneBackwardPipelineEngine(),
-        tp_mode=TensorParallelLinearMode.REDUCE_SCATTER,
-        tp_linear_async_communication=True,
+        # tp_mode=TensorParallelLinearMode.REDUCE_SCATTER,
+        # tp_linear_async_communication=True,
+        # # NOTE: the one from main branch
+        tp_mode=TensorParallelLinearMode.ALL_REDUCE,
+        tp_linear_async_communication=False,
     )
 
     # Initialise all process groups
@@ -345,6 +353,10 @@ def main():
     load_weights(model=model, parallel_context=parallel_context, root_folder=checkpoint_path)
 
     model.eval()
+
+    # from nanotron.debug.monitor import monitor_nanotron_model
+    # monitor_nanotron_model(model=model, parallel_context=parallel_context)
+
     if AutoTokenizer is not None:
         tokenizer = AutoTokenizer.from_pretrained(tokenizer_path)
         # tokenizer.pad_token_id = tokenizer.eos_token_id
@@ -364,6 +376,7 @@ def main():
             # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
             # "This is a math lesson. Answer the question. What is the result of 1 + 1? The result is ",
             # "This is a math lesson. Answer the question. What is the result of 1 + 1? The result is ",
+            "def fib(n)",
             # "def fib(n)",
             # "This film was probably inspired by Godzilla, ",
             # "This film was probably inspired by Godzilla, ",
@@ -388,7 +401,7 @@ def main():
             # "This work introduces an efficient method to scale Transformer-based "
             # NOTE: last training data
             # "Effectively managing student enquiries lies at the heart of successful real estate and investment education. Through leveraging diverse resources such as FAQs, online enquiry ",
-            TRAINING_DATA_4K,
+            # TRAINING_DATA_4K,
         ]
 
         outputs = decode_text(
@@ -398,8 +411,8 @@ def main():
             model=model.model,
             parallel_context=parallel_context,
             max_new_tokens=args.max_new_tokens,
-            max_micro_batch_size=2,
-            generation_config=GenerationArgs(sampler="top_k", use_cache=False),
+            max_micro_batch_size=1,
+            generation_config=GenerationArgs(sampler="greedy", use_cache=USE_CACHE),
             # generation_config=GenerationArgs(sampler="top_p", use_cache=False),
             tokenizer_config=TokenizerConfig(max_input_length=None),
             is_bench=os.environ.get("USE_BENCH", "0") == "1",
@@ -442,7 +455,7 @@ def main():
             input_mask=torch.ones(1, 1).to(dtype=torch.bool, device="cuda"),
             model=model.model,
             parallel_context=parallel_context,
-            generation_config=GenerationArgs(sampler="greedy", use_cache=False),
+            generation_config=GenerationArgs(sampler="greedy", use_cache=USE_CACHE),
             # generation_config=GenerationArgs(sampler="top_p", use_cache=False),
             max_micro_batch_size=1,
             max_new_tokens=12,
diff --git a/src/nanotron/debug/monitor.py b/src/nanotron/debug/monitor.py
index 184fe9fe..e9f119c7 100644
--- a/src/nanotron/debug/monitor.py
+++ b/src/nanotron/debug/monitor.py
@@ -1,4 +1,4 @@
-from typing import Dict, List, Tuple, Union
+from typing import Dict, List, Optional, Tuple, Union
 
 import torch
 import torch.distributed as dist
@@ -56,17 +56,6 @@ def _save_output_stats(module: nn.Module, input: torch.Tensor, output: torch.Ten
                 if stats is not None:
                     logs[name][param_name] = stats
 
-        # if hasattr(module, "weight") and module.weight is not None:
-        #     stats = compute_stats(name, module.weight.data)
-
-        #     if stats is not None:
-        #         logs[name]["weight"] = stats
-
-        # if hasattr(module, "bias") and module.bias is not None:
-        #     stats = compute_stats(name, module.bias)
-        #     if stats is not None:
-        #         logs[name]["bias"] = stats
-
         inputs = input if isinstance(input, tuple) else (input,)
         outputs = output if isinstance(output, tuple) else (output,)
 
@@ -82,13 +71,31 @@ def _save_output_stats(module: nn.Module, input: torch.Tensor, output: torch.Ten
             stats = compute_stats(name, inputs[0])
             if stats is not None:
                 logs[name]["input"] = stats
+
+        dp_rank = dist.get_rank(group=parallel_context.dp_pg)
+        tp_rank = dist.get_rank(group=parallel_context.tp_pg)
+        pp_rank = dist.get_rank(group=parallel_context.pp_pg)
+
+        def save(name, tensor):
+            import os
+
+            # from nanotron.constants import
+            DIR = "./debug/nn_states_after_fix/acts/"
+
+            os.makedirs(DIR, exist_ok=True)
+
+            if dp_rank == 0:
+                torch.save(tensor, f"{DIR}/{name}_dp_rank_{dp_rank}_and_pp_rank_{pp_rank}_and_tp_rank_{tp_rank}.pt")
+
         if len(outputs) > 1:
             for i, out in enumerate(outputs):
                 stats = compute_stats(name, out)
+                save(name, out)
                 if stats is not None:
                     logs[name][f"output:{i}"] = stats
         elif len(outputs) == 1:
             stats = compute_stats(name, outputs[0])
+            save(name, outputs[0])
             if stats is not None:
                 logs[name]["output"] = stats
 
@@ -124,7 +131,9 @@ def _save_grad_stats(module: nn.Linear, grad_input, grad_output: torch.Tensor):
     return logs, handles
 
 
-def monitor_nanotron_model(model: NanotronModel, parallel_context: ParallelContext):
+def monitor_nanotron_model(model: NanotronModel, parallel_context: Optional[ParallelContext] = None):
+    assert parallel_context is not None
+
     def get_leaf_modules(module: nn.Module) -> List[Tuple[str, nn.Module]]:
         """
         Return all the leaf modules (modules without any child modules) in a PyTorch module.
@@ -149,7 +158,7 @@ def get_leaf_modules(module: nn.Module) -> List[Tuple[str, nn.Module]]:
 
 
 def convert_logs_to_flat_logs(
-    logs: Dict[str, Dict[str, Dict[str, Union[torch.Tensor, float]]]]
+    logs: Dict[str, Dict[str, Dict[str, Union[torch.Tensor, float]]]],
 ) -> Dict[str, Union[torch.Tensor, float]]:
     flat_logs = {}
     for module_name, components in logs.items():
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 6cb501b7..5b953b22 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -1126,14 +1126,14 @@ def __init__(
                 ),
             )
 
-            log_rank(
-                f"Segment length is {self.segment_length}, turn_on_memory: {constants.CONFIG.infini_attention.turn_on_memory is True}",
-                logger=logger,
-                level=logging.WARNING,
-                rank=0,
-            )
+            # log_rank(
+            #     f"Segment length is {self.segment_length}, turn_on_memory: {constants.CONFIG.infini_attention.turn_on_memory is True}",
+            #     logger=logger,
+            #     level=logging.WARNING,
+            #     rank=0,
+            # )
 
-    def forward(
+    def _forward(
         self,
         # hidden_states: TensorType["sharded_seq_len", "batch_size", "hidden_size"],
         hidden_states: TensorType["sharded_batch_size", "seq_len", "hidden_size"],
@@ -1350,12 +1350,12 @@ def forward(
         outputs = torch.cat(outputs, dim=1)  # concat along sequence dimension
         assert outputs.shape == hidden_states.shape
 
-        if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0:
-            if dist.get_rank() == 0:
-                import wandb
+        # if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0:
+        #     if dist.get_rank() == 0:
+        #         import wandb
 
-                logs[f"layer_{self.layer_idx}:outputs"] = compute_stas(outputs)
-                wandb.log({**logs, "iteration_step": constants.GLOBAL_STEP})
+        #         logs[f"layer_{self.layer_idx}:outputs"] = compute_stas(outputs)
+        #         wandb.log({**logs, "iteration_step": constants.GLOBAL_STEP})
 
         # sequence_masks = torch.cat(sequence_masks, dim=1)
         # assert sequence_masks.shape == sequence_mask.shape
@@ -1472,11 +1472,11 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
 
         return memory, normalization
 
-    def forward_with_hidden_states(
+    def forward(
         self,
         hidden_states,  # [seq_len, batch_size, hidden_size]
         sequence_mask,  # [batch_size, seq_len]
-        return_qkv_states: bool = False,
+        # return_qkv_states: bool = False,
     ):
         from flash_attn import bert_padding
         from flash_attn.flash_attn_interface import (
@@ -1484,12 +1484,16 @@ def forward_with_hidden_states(
             flash_attn_with_kvcache,
         )
 
-        seq_len = hidden_states.shape[1]
+        # seq_len = hidden_states.shape[1]
 
         qkv_states = self.qkv_proj(
             hidden_states
         )  # [seq_len, batch_size, n_local_q_heads * d_qk + 2 * n_local_kv_heads * d_qk]
-        q_length, batch_size, _ = qkv_states.shape
+
+        # qkv_states = qkv_states.transpose(0, 1)
+        # q_length, batch_size, _ = qkv_states.shape
+        # NOTE: this is the new splitting dimension
+        batch_size, q_length, _ = qkv_states.shape
 
         if self.is_gqa:
             query_states, key_states, value_states = torch.split(
@@ -1528,27 +1532,27 @@ def forward_with_hidden_states(
         #     value_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
         # )
 
-        query_states_without_pe = rearrange(
-            query_states,
-            "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
-            # seq_len=self.segment_length,
-            seq_len=seq_len,
-        )
-        key_states_without_pe = rearrange(
-            key_states,
-            "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
-            # seq_len=self.segment_length,
-            seq_len=seq_len,
-        )
-        value_states_without_pe = rearrange(
-            value_states,
-            "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
-            # seq_len=self.segment_length,
-            seq_len=seq_len,
-        )
+        # query_states_without_pe = rearrange(
+        #     query_states,
+        #     "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
+        #     # seq_len=self.segment_length,
+        #     seq_len=seq_len,
+        # )
+        # key_states_without_pe = rearrange(
+        #     key_states,
+        #     "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
+        #     # seq_len=self.segment_length,
+        #     seq_len=seq_len,
+        # )
+        # value_states_without_pe = rearrange(
+        #     value_states,
+        #     "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
+        #     # seq_len=self.segment_length,
+        #     seq_len=seq_len,
+        # )
 
         # assert query_states_without_pe.shape[0] == self.segment_length
-        assert query_states_without_pe.shape[0] == seq_len
+        # assert query_states_without_pe.shape[0] == seq_len
 
         store = self.get_local_store()
         if store is not None:  # Inference case
@@ -1756,18 +1760,19 @@ def forward_with_hidden_states(
         attention_output = (
             attention_output.contiguous().view(batch_size, q_length, self.n_local_q_heads * self.d_v).transpose(0, 1)
         )
-        # output = self.o_proj(attention_output)
-        # return {"hidden_states": output, "sequence_mask": sequence_mask}
-
-        return_outputs = {"hidden_states": None, "sequence_mask": sequence_mask}
-        return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
-        return_outputs["qkv_states_without_pe"] = (
-            query_states_without_pe,
-            key_states_without_pe,
-            value_states_without_pe,
-        )
-        return_outputs["attention_output"] = attention_output
-        return return_outputs
+        output = self.o_proj(attention_output)
+        output = output.transpose(0, 1)
+        return {"hidden_states": output, "sequence_mask": sequence_mask}
+
+        # return_outputs = {"hidden_states": None, "sequence_mask": sequence_mask}
+        # return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
+        # return_outputs["qkv_states_without_pe"] = (
+        #     query_states_without_pe,
+        #     key_states_without_pe,
+        #     value_states_without_pe,
+        # )
+        # return_outputs["attention_output"] = attention_output
+        # return return_outputs
 
 
 class LlamaDecoderLayer(nn.Module):
@@ -1809,6 +1814,13 @@ def forward(
         residual = hidden_states
         hidden_states = self.input_layernorm(hidden_states)
 
+        # log_rank(
+        #     f"hidden_states after input_layernorm: hidden_states.shape={hidden_states.shape}",
+        #     logger=logger,
+        #     level=logging.INFO,
+        #     rank=0,
+        # )
+
         output = self.attn(
             hidden_states=hidden_states,
             sequence_mask=sequence_mask,
@@ -1816,11 +1828,35 @@ def forward(
             # prev_normalization=normalization,
         )
         hidden_states = output["hidden_states"]
+
+        # log_rank(
+        #     f"hidden_states after attn: hidden_states.shape={hidden_states.shape}",
+        #     logger=logger,
+        #     level=logging.INFO,
+        #     rank=0,
+        # )
+
         hidden_states = hidden_states + residual
 
         residual = hidden_states
         hidden_states = self.post_attention_layernorm(hidden_states)
+
+        # log_rank(
+        #     f"hidden_states after post_attention_layernorm: hidden_states.shape={hidden_states.shape}",
+        #     logger=logger,
+        #     level=logging.INFO,
+        #     rank=0,
+        # )
+
         hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
+
+        # log_rank(
+        #     f"hidden_states after mlp: hidden_states.shape={hidden_states.shape}",
+        #     logger=logger,
+        #     level=logging.INFO,
+        #     rank=0,
+        # )
+
         hidden_states = hidden_states + residual
 
         return {
@@ -1960,8 +1996,20 @@ def forward_with_hidden_states(
         input_mask: Union[torch.Tensor, TensorPointer],  # [batch_size, seq_len]
     ):
         # all tensors are optional as most ranks don't need anything from the dataloader.
+        # log_rank(
+        #     f"Idxs of inputs: input_ids.shape={input_ids.shape}, input_mask.shape={input_mask.shape}",
+        #     logger=logger,
+        #     level=logging.INFO,
+        #     rank=0,
+        # )
 
         output = self.token_position_embeddings(input_ids=input_ids, input_mask=input_mask)
+        # log_rank(
+        #     f"output['input_embeds'] of token_position_embeddings: output['input_embeds'].shape={output['input_embeds'].shape}",
+        #     logger=logger,
+        #     level=logging.INFO,
+        #     rank=0,
+        # )
 
         hidden_encoder_states = {
             "hidden_states": output["input_embeds"],
@@ -1969,13 +2017,32 @@ def forward_with_hidden_states(
             # "memory": None,
             # "normalization": None,
         }
-        for encoder_block in self.decoder:
+        for i, encoder_block in enumerate(self.decoder):
+            # log_rank(
+            #     f"Starting transformer block {i}",
+            #     logger=logger,
+            #     level=logging.INFO,
+            #     rank=0,
+            # )
             hidden_encoder_states = encoder_block(**hidden_encoder_states)
 
         hidden_states = self.final_layer_norm(input=hidden_encoder_states["hidden_states"])["hidden_states"]
+        # log_rank(
+        #     f"hidden_states after final_layer_norm: hidden_states.shape={hidden_states.shape}",
+        #     logger=logger,
+        #     level=logging.INFO,
+        #     rank=0,
+        # )
 
         sharded_logits = self.lm_head(x=hidden_states)["logits"]
 
+        # log_rank(
+        #     f"sharded_logits after lm_head: sharded_logits.shape={sharded_logits.shape}",
+        #     logger=logger,
+        #     level=logging.INFO,
+        #     rank=0,
+        # )
+
         fp32_sharded_logits = self.cast_to_fp32(x=sharded_logits)["output"]
 
         return fp32_sharded_logits, hidden_states
@@ -2142,9 +2209,9 @@ def init_model_randomly(self, config: Config):
                 continue
 
             if "balance_factors" in param_name:
-                import torch.nn.init as init
 
-                init.normal_(param, mean=0.0, std=0.01)
+                # init.normal_(param, mean=0.0, std=0.01)
+                param.zero_()
             else:
                 module = model.get_submodule(module_name)
                 parametrizator.parametrize(param_name, module)
diff --git a/src/nanotron/parallel/tensor_parallel/functional.py b/src/nanotron/parallel/tensor_parallel/functional.py
index fdef48ac..a951c588 100644
--- a/src/nanotron/parallel/tensor_parallel/functional.py
+++ b/src/nanotron/parallel/tensor_parallel/functional.py
@@ -19,6 +19,8 @@
 from torch.nn import functional as F
 
 import nanotron.distributed as dist
+from nanotron import logging
+from nanotron.logging import log_rank
 from nanotron.parallel.tensor_parallel.distributed_differentiable_primitives import (
     differentiable_all_gather,
     differentiable_all_reduce_sum,
@@ -28,6 +30,8 @@
 from nanotron.parallel.tensor_parallel.enum import TensorParallelLinearMode
 from nanotron.parallel.utils import assert_cuda_max_connections_set_to_1
 
+logger = logging.get_logger(__name__)
+
 
 class _ShardedCrossEntropy(torch.autograd.Function):
     @staticmethod
@@ -37,6 +41,13 @@ def forward(
         target,  # (batch_size, length)
         group: dist.ProcessGroup,
     ):
+        log_rank(
+            f"sharded_logits input of _ShardedCrossEntropy: sharded_logits.shape={sharded_logits.shape}",
+            logger=logger,
+            level=logging.INFO,
+            rank=0,
+        )
+
         # Maximum value along last dimension across all GPUs.
         logits_max = torch.max(sharded_logits, dim=-1)[0]
         dist.all_reduce(logits_max, op=dist.ReduceOp.MAX, group=group)
@@ -89,10 +100,10 @@ def forward(
 
     @staticmethod
     def backward(ctx, grad_output):
-        # Retreive tensors from the forward path.
+        # Retrieve tensors from the forward path.
         softmax, target_mask, masked_target_1d = ctx.saved_tensors
 
-        # All the inputs have softmax as thier gradient.
+        # All the inputs have softmax as their gradient.
         grad_input = softmax
         # For simplicity, work with the 2D gradient.
         sharded_hidden_size = softmax.size()[-1]
diff --git a/src/nanotron/trainer.py b/src/nanotron/trainer.py
index e6b26534..27ed32ed 100644
--- a/src/nanotron/trainer.py
+++ b/src/nanotron/trainer.py
@@ -36,7 +36,6 @@
 )
 from nanotron.constants import LR_SCHEDULER_CKP_PATH, METADATA_CKP_PATH, OPTIMIZER_CKP_PATH
 from nanotron.dataloader import sanity_check_dataloader
-from nanotron.debug.monitor import monitor_nanotron_model
 from nanotron.helpers import (
     _vocab_size_with_padding,
     get_profiler,
@@ -436,8 +435,8 @@ def train(
                 if isinstance(prof, torch.profiler.profile):
                     prof.step()
 
-                if (self.iteration_step - 1) % constants.LOG_STATE_INTERVAL == 0:
-                    nn_logs, nn_handles = monitor_nanotron_model(self.model, self.parallel_context)
+                # if (self.iteration_step - 1) % constants.LOG_STATE_INTERVAL == 0:
+                #     nn_logs, nn_handles = monitor_nanotron_model(self.model, self.parallel_context)
 
                 self.iteration_start_time = time.time()
                 self._update_dataloader_based_on_training_stages(dataloader_or_dls)
@@ -451,14 +450,14 @@ def train(
                 if (self.iteration_step - 1) % self.config.logging.iteration_step_info_interval == 0:
                     self.train_step_logs(outputs=outputs, loss_avg=loss_avg)
 
-                if (self.iteration_step - 1) % constants.LOG_STATE_INTERVAL == 0:
-                    from nanotron.debug.monitor import convert_logs_to_flat_logs
+                # if (self.iteration_step - 1) % constants.LOG_STATE_INTERVAL == 0:
+                #     from nanotron.debug.monitor import convert_logs_to_flat_logs
 
-                    if dist.get_rank(self.parallel_context.world_pg) == self.logger_ranks[0] and wandb is not None:
-                        wandb.log({**convert_logs_to_flat_logs(nn_logs), "iteration_step": self.iteration_step})
+                #     if dist.get_rank(self.parallel_context.world_pg) == self.logger_ranks[0] and wandb is not None:
+                #         wandb.log({**convert_logs_to_flat_logs(nn_logs), "iteration_step": self.iteration_step})
 
-                    for handle in nn_handles:
-                        handle.remove()
+                #     for handle in nn_handles:
+                #         handle.remove()
 
                 # Checkpoint
                 if self.iteration_step % self.config.checkpoints.checkpoint_interval == 0:

From 692b052bc6c5ce5a789753479c81b00d62168b00 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Tue, 11 Jun 2024 08:36:09 +0000
Subject: [PATCH 29/43] fix wrong interdimate activations after splitting qkv
 with bs > 1

---
 src/nanotron/models/llama.py                  | 761 +-----------------
 .../parallel/tensor_parallel/functional.py    |  14 +
 2 files changed, 58 insertions(+), 717 deletions(-)

diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 5b953b22..e923d66d 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -283,720 +283,6 @@ def pad_to_right(tensor, mask, new_tensor=None):
 from einops import einsum, rearrange, reduce
 from torchtyping import TensorType
 
-# class CausalSelfAttention(nn.Module, AttachableStore):
-#     def __init__(
-#         self,
-#         config: LlamaConfig,
-#         parallel_config: Optional[ParallelismArgs],
-#         tp_pg: dist.ProcessGroup,
-#         layer_idx: int,
-#     ):
-#         from flash_attn.layers.rotary import RotaryEmbedding as FlashRotaryEmbedding
-
-#         super().__init__()
-#         # Tensor parallel considerations: We split tensors along head dimension
-#         assert (
-#             config.num_attention_heads % tp_pg.size() == 0
-#         ), f"Number of attention heads ({config.num_attention_heads}) must be divisible by TP size ({tp_pg.size()})."
-#         try:
-#             assert (
-#                 config.num_key_value_heads % tp_pg.size() == 0
-#             ), f"Number of key/value heads ({config.num_key_value_heads}) must be divisible by TP size ({tp_pg.size()})."
-#         except AttributeError:
-#             log_rank(
-#                 "WARNING: num_key_value_heads not defined, assuming it is equal to num_attention_heads",
-#                 logger=logger,
-#                 level=logging.WARNING,
-#                 rank=0,
-#             )
-#             # If num_key_value_heads is not defined, we assume that it is equal to num_attention_heads
-#             config.num_key_value_heads = config.num_attention_heads
-#         assert (
-#             config.num_attention_heads % config.num_key_value_heads == 0
-#         ), f"Number of attention heads ({config.num_attention_heads}) must be divisible by number of key/value heads ({config.num_key_value_heads})."
-#         self.n_local_q_heads = config.num_attention_heads // tp_pg.size()
-#         self.n_local_kv_heads = config.num_key_value_heads // tp_pg.size()
-#         self.n_repeats = config.num_attention_heads // config.num_key_value_heads
-#         self.is_gqa = config.num_attention_heads != config.num_key_value_heads  # Whether we are using GQA or not
-#         self.d_qk = config.hidden_size // config.num_attention_heads
-#         self.d_v = config.hidden_size // config.num_attention_heads
-#         self.d_model = config.hidden_size
-#         self.is_using_mup = config.is_using_mup
-
-#         # TODO @thomasw21: refactor so that we store that default in a single place.
-#         tp_mode = parallel_config.tp_mode if parallel_config is not None else TensorParallelLinearMode.ALL_REDUCE
-#         tp_linear_async_communication = (
-#             parallel_config.tp_linear_async_communication if parallel_config is not None else False
-#         )
-
-#         # build the slice config for self.qkv for save/load
-#         # shard are done within the contiguous chunk
-#         qkv_contiguous_chunks = (
-#             config.num_attention_heads * self.d_qk,  # shape of q
-#             config.num_key_value_heads * self.d_qk,  # shape of k
-#             config.num_key_value_heads * self.d_qk,  # shape of v
-#         )
-#         self.config = config
-#         self.qkv_proj = TensorParallelColumnLinear(
-#             self.d_model,
-#             config.num_attention_heads * self.d_qk + 2 * config.num_key_value_heads * self.d_qk,
-#             pg=tp_pg,
-#             mode=tp_mode,
-#             bias=False,
-#             async_communication=tp_linear_async_communication,
-#             contiguous_chunks=qkv_contiguous_chunks,
-#         )
-#         # TODO(kunhao): We want to have only one version per device and not one version per layer.
-#         self.rotary_embedding = RotaryEmbedding(dim=self.d_qk, end=config.max_position_embeddings)
-#         log_rank(
-#             f"self.rotary_embedding.end is {self.rotary_embedding.end}",
-#             logger=logger,
-#             level=logging.INFO,
-#             rank=0,
-#         )
-#         # self.rotary_embedding = RotaryEmbedding(dim=self.d_qk, end=2048)
-
-#         # NOTE: Only supported for training (TODO(fmom): position_ids not supported yet)
-#         self.flash_rotary_embedding = FlashRotaryEmbedding(dim=self.d_qk, interleaved=True)
-
-#         self.o_proj = TensorParallelRowLinear(
-#             config.num_attention_heads * self.d_qk,
-#             self.d_model,
-#             pg=tp_pg,
-#             mode=tp_mode,
-#             bias=False,
-#             async_communication=tp_linear_async_communication,
-#         )
-
-#         self.attention = CoreAttention(
-#             config,
-#             parallel_config=parallel_config,
-#             layer_idx=layer_idx,
-#         )
-#         self.layer_idx = layer_idx
-
-#         self.prefill_kv_len = (
-#             config.max_position_embeddings
-#             # 2048
-#         )  # TODO @nouamane: compute based on free memory, because in rope we can surpass max_position_embeddings
-
-#         # self.n_segments = 16
-#         # self.segment_length = config.max_position_embeddings // self.n_segments
-#         # assert config.max_position_embeddings == 32768
-
-#         # NOTE: for 1b training
-#         self.segment_length = 2048
-#         # self.segment_length = 4096
-
-#         # NOTE: for sanity 200m training
-#         # prev 16
-#         # self.segment_length = 256
-#         # self.segment_length = 16
-
-#         device = self.o_proj.weight.device
-#         dtype = self.o_proj.weight.dtype
-
-#         from nanotron.parallel.sharded_parameters import SplitConfig, create_sharded_parameter_from_config
-
-#         balance_factors = nn.Parameter(torch.zeros(self.n_local_q_heads, device=device, dtype=dtype))
-#         self.balance_factors = create_sharded_parameter_from_config(
-#             parameter=balance_factors,
-#             pg=tp_pg,
-#             split_config=SplitConfig(
-#                 split_dim=0,
-#                 # contiguous_chunks=(self.n_local_heads, self.n_local_heads)
-#             ),
-#         )
-
-#     def forward(
-#         self,
-#         # hidden_states: TensorType["sharded_seq_len", "batch_size", "hidden_size"],
-#         hidden_states: TensorType["sharded_batch_size", "seq_len", "hidden_size"],
-#         sequence_mask: TensorType["batch_size", "seq_len"],
-#     ):
-#         # if self.layer_idx == 4:
-#         #     assert 1 == 1
-
-#         # batch_size = hidden_states.shape[1]
-#         # seq_len = hidden_states.shape[0]
-
-#         batch_size = hidden_states.shape[0]
-#         seq_len = hidden_states.shape[1]
-
-#         # assert seq_len == 1024
-#         # assert seq_len == 32768
-
-#         # assert seq_len % self.n_segments == 0
-
-#         # segment_length = seq_len // self.n_segments
-#         # hidden_size = hidden_states.shape[2]
-
-#         if seq_len > self.segment_length:
-#             # n_segments = seq_len // self.segment_length
-#             # segment_hidden_states = torch.chunk(hidden_states, chunks=n_segments, dim=0)
-#             # segment_sequence_masks = torch.chunk(sequence_mask, chunks=n_segments, dim=1)
-
-#             import math
-
-#             n_segments = math.ceil(seq_len / self.segment_length)
-#             segment_lengths = [self.segment_length] * (n_segments - 1) + [
-#                 seq_len - (n_segments - 1) * self.segment_length
-#             ]
-#             assert sum(segment_lengths) == seq_len
-#             # assert hidden_states.shape[0] == seq_len
-#             assert hidden_states.shape[1] == seq_len
-#             # segment_hidden_states = torch.split(hidden_states, segment_lengths, dim=0)
-#             segment_hidden_states = torch.split(hidden_states, segment_lengths, dim=1)
-#             # NOTE: assume that mask are all the same
-#             # because we split across sequence length
-#             # NOTE: take the assumption that all the masks are the same
-#             assert torch.all(sequence_mask)
-#             segment_sequence_masks = torch.split(sequence_mask[:, :seq_len], segment_lengths, dim=1)
-#         else:
-#             segment_hidden_states = [hidden_states]
-#             segment_sequence_masks = [sequence_mask]
-
-#         memory = None
-#         normalization = None
-
-#         # memory = prev_memory
-#         # normalization = prev_normalization
-
-#         outputs = []
-
-#         # sequence_masks = []
-#         idx = 0
-#         logs = {}
-
-#         for segment_hidden_state, segment_sequence_mask in zip(segment_hidden_states, segment_sequence_masks):
-#             # if idx == 1:
-#             #     memory = None
-#             #     normalization = None
-
-#             attn_outputs = self.forward_with_hidden_states(
-#                 hidden_states=segment_hidden_state, sequence_mask=segment_sequence_mask, return_qkv_states=True
-#             )
-
-#             local_attn_outputs = attn_outputs["attention_output"]
-#             # query_states, key_states, value_states = attn_outputs["qkv_states"]
-#             query_states, key_states, value_states = attn_outputs["qkv_states_without_pe"]
-
-#             # # NOTE: these are the shape for non-megatron-sp
-#             # assert query_states.shape[0] == self.segment_length
-#             # assert local_attn_outputs.shape[1] == self.segment_length
-
-#             query_states = rearrange(
-#                 query_states,
-#                 "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
-#                 seq_len=self.segment_length,
-#                 n_heads=self.n_local_q_heads,
-#                 d_head=self.d_qk,
-#             )
-
-#             key_states = rearrange(
-#                 key_states,
-#                 "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
-#                 # batch_size=batch_size,
-#                 seq_len=self.segment_length,
-#                 n_heads=self.n_local_kv_heads,
-#                 d_head=self.d_qk,
-#             )
-
-#             value_states = rearrange(
-#                 value_states,
-#                 "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
-#                 # batch_size=batch_size,
-#                 seq_len=self.segment_length,
-#                 n_heads=self.n_local_kv_heads,
-#                 d_head=self.d_qk,
-#             )
-
-#             # NOTE: because in generation, the sequence length increases
-#             # assert query_states.shape == (batch_size, self.n_local_q_heads, segment_length, self.d_qk)
-#             # assert query_states.shape == key_states.shape == value_states.shape
-#             retrieved_memory = self._retrieve_from_memory(
-#                 query_states, prev_memory=memory, prev_normalization=normalization
-#             )
-
-#             # log_rank(
-#             #     f"[idx={idx}] retrieved_memory.shape = {retrieved_memory.shape}, retrieve_memory is zero? {(retrieved_memory == 0).all()}",
-#             #     logger=logger,
-#             #     level=logging.INFO,
-#             #     rank=0,
-#             # )
-
-#             # if memory is not None:
-#             #     log_rank(
-#             #         f"[idx={idx}] memory.shape = {memory.shape}, normalization.shape = {normalization.shape}",
-#             #         logger=logger,
-#             #         level=logging.INFO,
-#             #         rank=0,
-#             #     )
-
-#             # retrieved_memory = retrieved_memory.detach()
-
-#             # local_attn_outputs = rearrange(
-#             #     local_attn_outputs,
-#             #     "seq_len batch_size (n_heads d_head) -> batch_size n_heads seq_len d_head",
-#             #     d_head=self.d_qk,
-#             # )
-#             local_attn_outputs = rearrange(
-#                 local_attn_outputs,
-#                 "batch_size seq_len (n_heads d_head) -> batch_size n_heads seq_len d_head",
-#                 seq_len=self.segment_length,
-#                 d_head=self.d_qk,
-#             )
-
-#             # log_rank(
-#             #     f"[idx={idx}] local_attn_outputs.shape = {local_attn_outputs.shape}, local_attn_outputs is zero? {(local_attn_outputs == 0).all()}",
-#             #     logger=logger,
-#             #     level=logging.INFO,
-#             #     rank=0,
-#             # )
-
-#             global_weights = F.sigmoid(self.balance_factors)
-#             global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
-
-#             local_weights = 1 - F.sigmoid(self.balance_factors)
-#             local_weights = rearrange(local_weights, "n_heads -> 1 n_heads 1 1")
-
-#             # assert torch.allclose(global_weights + local_weights, torch.ones_like(global_weights))
-
-#             # log_rank(
-#             #     f"[idx={idx}] global_weights.shape = {global_weights.shape}, global_weights: {global_weights}",
-#             #     logger=logger,
-#             #     level=logging.INFO,
-#             #     rank=0,
-#             # )
-
-#             # log_rank(
-#             #     f"[idx={idx}] local_weights.shape = {local_weights.shape}, local_weights: {local_weights}",
-#             #     logger=logger,
-#             #     level=logging.INFO,
-#             #     rank=0,
-#             # )
-
-#             attention_output = global_weights * retrieved_memory + local_weights * local_attn_outputs
-
-#             attention_output = rearrange(
-#                 attention_output, "batch_size n_heads seq_len d_head -> seq_len batch_size (n_heads d_head)",
-#                 n_heads=self.n_local_q_heads,
-#                 d_head=self.d_qk,
-#                 seq_len=self.segment_length,
-#             )
-
-#             output = self.o_proj(attention_output)
-
-#             if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % 50 == 0:
-#                 if dist.get_rank() == 0:
-#                     logs[f"layer_{self.layer_idx}:seg_{idx}:query_states"] = compute_stas(query_states)
-#                     logs[f"layer_{self.layer_idx}:seg_{idx}:key_states"] = compute_stas(key_states)
-#                     logs[f"layer_{self.layer_idx}:seg_{idx}:value_states"] = compute_stas(value_states)
-
-#                     logs[f"layer_{self.layer_idx}:seg_{idx}:global_weights"] = compute_stas(global_weights)
-#                     logs[f"layer_{self.layer_idx}:seg_{idx}:local_weights"] = compute_stas(local_weights)
-#                     logs[f"layer_{self.layer_idx}:seg_{idx}:local_attn_outputs"] = compute_stas(local_attn_outputs)
-#                     logs[f"layer_{self.layer_idx}:seg_{idx}:retrieved_memory"] = compute_stas(retrieved_memory)
-#                     logs[f"layer_{self.layer_idx}:seg_{idx}:attention_output"] = compute_stas(attention_output)
-#                     logs[f"layer_{self.layer_idx}:seg_{idx}:output"] = compute_stas(output)
-#                     logs[f"layer_{self.layer_idx}:seg_{idx}:memory"] = compute_stas(memory)
-#                     logs[f"layer_{self.layer_idx}:seg_{idx}:normalization"] = compute_stas(normalization)
-
-#             # assert output.shape == (segment_length, batch_size, hidden_size)
-
-#             memory, normalization = self._update_memory(memory, normalization, key_states, value_states)
-#             # memory = prev_memory if prev_memory is not None else 0.detach()
-
-#             outputs.append(output)
-#             # memory, normalization = memory.detach(), normalization.detach()
-
-#             idx += 1
-
-#             # NOTE: update memory
-#         # outputs = torch.cat(outputs, dim=0)  # concat along sequence dimension
-#         outputs = torch.cat(outputs, dim=2)  # concat along sequence dimension
-#         assert outputs.shape == hidden_states.shape
-
-#         if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % 50 == 0:
-#             if dist.get_rank() == 0:
-#                 import wandb
-
-#                 logs[f"layer_{self.layer_idx}:outputs"] = compute_stas(outputs)
-#                 wandb.log({**logs, "iteration_step": constants.GLOBAL_STEP})
-
-#         # sequence_masks = torch.cat(sequence_masks, dim=1)
-#         # assert sequence_masks.shape == sequence_mask.shape
-#         return_outputs = {
-#             "hidden_states": outputs,
-#             "sequence_mask": sequence_mask,
-#             # "memory": memory,
-#             # "normalization": normalization,
-#         }
-#         return return_outputs
-
-#     def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
-#         # return torch.zeros_like(query_states)
-#         if prev_memory is None or prev_normalization is None:
-#             return torch.zeros_like(query_states)
-
-#         assert (prev_memory is None and prev_normalization is None) or (
-#             prev_memory is not None and prev_normalization is not None
-#         )
-
-#         if self.n_repeats > 1:
-#             from einops import repeat
-
-#             prev_memory = repeat(
-#                 prev_memory,
-#                 "batch_size n_kv_heads d_k d_v -> batch_size (n_kv_heads n) d_k d_v",
-#                 n=self.n_repeats,
-#             )
-#             prev_normalization = repeat(
-#                 prev_normalization,
-#                 "batch_size n_kv_heads d_head -> batch_size (n_kv_heads n) d_head",
-#                 n=self.n_repeats,
-#             )
-
-#         sigma_query_states = F.elu(query_states) + 1
-#         retrieved_memory = einsum(
-#             sigma_query_states,
-#             prev_memory,
-#             "batch_size n_heads seq_len d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_len d_v",
-#         )
-
-#         denominator = einsum(
-#             sigma_query_states,
-#             prev_normalization,
-#             "batch_size n_heads seq_len d_head, batch_size n_heads d_head -> batch_size n_heads seq_len",
-#         )
-#         denominator = rearrange(denominator, "batch_size n_heads seq_len -> batch_size n_heads seq_len 1")
-#         # [batch_size, n_heads, seq_len, d_v] / [batch_size, n_heads, seq_len, 1], so each d_v is divide by the normalized value
-
-#         # NOTE: because normalization is the sum of all the keys, so each word should have the same normalization
-#         retrieved_memory = retrieved_memory / denominator
-#         return retrieved_memory
-
-#     def _update_memory(self, prev_memory, prev_normalization, key_states, value_states):
-#         assert (prev_memory is None and prev_normalization is None) or (
-#             prev_memory is not None and prev_normalization is not None
-#         )
-
-#         sigma_key_states = F.elu(key_states) + 1
-
-#         if prev_memory is None or prev_normalization is None:
-#             new_value_states = value_states
-#         else:
-#             numerator = einsum(
-#                 sigma_key_states,
-#                 prev_memory,
-#                 "batch_size n_heads seq_len d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_len d_v",
-#             )
-#             denominator = einsum(
-#                 sigma_key_states,
-#                 prev_normalization,
-#                 "batch_size n_heads seq_len d_k, batch_size n_heads d_k -> batch_size n_heads seq_len",
-#             )
-#             denominator = rearrange(denominator, "batch_size n_heads seq_len -> batch_size n_heads seq_len 1")
-
-#             prev_v = numerator / denominator
-#             new_value_states = value_states - prev_v
-
-#         memory = torch.matmul(sigma_key_states.transpose(-2, -1), new_value_states)
-
-#         normalization = reduce(
-#             sigma_key_states, "batch_size n_heads seq_len d_head -> batch_size n_heads d_head", reduction="sum"
-#         )
-
-#         memory += prev_memory if prev_memory is not None else 0
-#         normalization += prev_normalization if prev_normalization is not None else 0
-
-#         return memory, normalization
-
-#     def forward_with_hidden_states(
-#         self,
-#         hidden_states,  # [seq_len, batch_size, hidden_size]
-#         sequence_mask,  # [batch_size, seq_len]
-#         return_qkv_states: bool = False,
-#     ):
-#         from flash_attn import bert_padding
-#         from flash_attn.flash_attn_interface import (
-#             flash_attn_varlen_func,
-#             flash_attn_with_kvcache,
-#         )
-
-#         qkv_states = self.qkv_proj(
-#             hidden_states
-#         )  # [seq_len, batch_size, n_local_q_heads * d_qk + 2 * n_local_kv_heads * d_qk]
-#         q_length, batch_size, _ = qkv_states.shape
-
-#         if self.is_gqa:
-#             query_states, key_states, value_states = torch.split(
-#                 qkv_states,
-#                 [
-#                     self.n_local_q_heads * self.d_qk,
-#                     self.n_local_kv_heads * self.d_qk,
-#                     self.n_local_kv_heads * self.d_qk,
-#                 ],
-#                 dim=-1,
-#             )
-
-#             query_states = (
-#                 query_states.transpose(0, 1).contiguous().view(batch_size, q_length, self.n_local_q_heads, self.d_qk)
-#             )
-#             key_states = (
-#                 key_states.transpose(0, 1).contiguous().view(batch_size, q_length, self.n_local_kv_heads, self.d_qk)
-#             )
-#             value_states = (
-#                 value_states.transpose(0, 1).contiguous().view(batch_size, q_length, self.n_local_kv_heads, self.d_qk)
-#             )
-#         else:
-#             query_states, key_states, value_states = (
-#                 qkv_states.view(q_length, batch_size, 3, self.n_local_q_heads, self.d_qk)
-#                 .permute(2, 1, 0, 3, 4)
-#                 .contiguous()
-#             )  # [3, batch_size, seq_len, n_local_q_heads, d_qk]
-
-#         # query_states_without_pe = rearrange(
-#         #     query_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
-#         # )
-#         # key_states_without_pe = rearrange(
-#         #     key_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
-#         # )
-#         # value_states_without_pe = rearrange(
-#         #     value_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
-#         # )
-
-#         query_states_without_pe = rearrange(
-#             query_states, "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head"
-#         )
-#         key_states_without_pe = rearrange(
-#             key_states, "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head"
-#         )
-#         value_states_without_pe = rearrange(
-#             value_states, "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head"
-#         )
-
-#         assert query_states_without_pe.shape[0] == self.segment_length
-
-#         store = self.get_local_store()
-#         if store is not None:  # Inference case
-#             # Double check that we use store only at inference time
-#             assert key_states.requires_grad is False
-#             assert value_states.requires_grad is False
-#             if "position_offsets" in store:
-#                 old_position_offsets = store["position_offsets"]
-#                 position_ids = old_position_offsets[:, None] + sequence_mask
-#             else:
-#                 position_ids = torch.cumsum(sequence_mask, dim=-1, dtype=torch.int32) - 1
-#             position_offsets = position_ids[:, -1]
-
-#             # Compute rotary embeddings
-#             # Note: keep track of old rotary embedding end to check if we need to enlarge k_cache and v_cache
-#             old_rotary_embed_end = self.rotary_embedding.end
-#             query_states = self.rotary_embedding(query_states, position_ids=position_ids)
-#             key_states = self.rotary_embedding(key_states, position_ids=position_ids)
-
-#             if "key" not in store:
-#                 # First inference iteration (Prefill)
-#                 # TODO @nouamane: support custom masking
-#                 # assert that [ False, False, False, False,  True,  True,  True,  True,  True,  True] is accepted
-#                 # but [ False, False, False, False,  True,  True,  False,  False,  True,  True] is not (can't mask in the middle of sequence)
-#                 assert ~(
-#                     sequence_mask[:, :-1] & (~sequence_mask[:, 1:])  # True is never followed by False
-#                 ).any(), "Can't mask in the middle of sequence, please make sure that pads are at the left of the sequence if existing"
-
-#                 # preallocate k_cache, v_cache to self.prefill_kv_len
-#                 k_cache = torch.zeros(
-#                     (
-#                         batch_size,
-#                         self.prefill_kv_len,
-#                         self.n_local_kv_heads,
-#                         self.d_qk,
-#                     ),
-#                     dtype=query_states.dtype,
-#                     device=query_states.device,
-#                 )
-#                 v_cache = torch.zeros(
-#                     (batch_size, self.prefill_kv_len, self.n_local_kv_heads, self.d_v),
-#                     dtype=query_states.dtype,
-#                     device=query_states.device,
-#                 )
-#                 # Remove pad tokens from key_states and concatenate samples in key_unpad
-#                 # cu_seqlens_k is the cumulative sequence lengths of key_states
-#                 (query_unpad, indices_q, cu_seqlens_q, max_seqlen_q) = bert_padding.unpad_input(
-#                     query_states,
-#                     sequence_mask,
-#                 )
-#                 (key_unpad, indices_k, cu_seqlens_k, max_seqlen_k) = bert_padding.unpad_input(
-#                     key_states, sequence_mask
-#                 )
-#                 (value_unpad, _, _, _) = bert_padding.unpad_input(value_states, sequence_mask)
-
-#                 # NOTE: this scale is for µTransfer,
-#                 # in SP, we use sqrt(1/d_h)
-#                 softmax_scale = 1 / query_states.shape[-1] if self.is_using_mup else None
-#                 output_unpad = flash_attn_varlen_func(
-#                     q=query_unpad,  # (total_q, n_local_q_heads, d_qk)
-#                     k=key_unpad,  # (total_kv, n_local_kv_heads, d_qk)
-#                     v=value_unpad,  # (total_kv, n_local_kv_heads, d_v)
-#                     cu_seqlens_q=cu_seqlens_q,
-#                     cu_seqlens_k=cu_seqlens_k,
-#                     max_seqlen_q=max_seqlen_q,
-#                     max_seqlen_k=max_seqlen_k,
-#                     dropout_p=0.0,
-#                     softmax_scale=softmax_scale,
-#                     causal=True,  # True in prefill phase, False in subsequent phases
-#                     return_attn_probs=False,
-#                 )  # (total_unpadded, n_local_q_heads, d_v)
-
-#                 attention_output = bert_padding.pad_input(
-#                     output_unpad, indices_q, batch_size, q_length
-#                 )  # (batch_size, q_length, n_local_q_heads, d_v)
-
-#                 pad_to_right(key_states, sequence_mask, new_tensor=k_cache)
-#                 pad_to_right(value_states, sequence_mask, new_tensor=v_cache)
-
-#             else:
-#                 # Pull pre-computed key/value states
-#                 # Subsequent inference iterations (q_length=1)
-#                 k_cache = store["key"]
-#                 v_cache = store["value"]
-
-#                 # NOTE(fmom): According to flash_attn_with_kvcache, "If you pass in k / v, you must make sure that the cache is large enough to hold the new values"
-#                 # Since rotary embedding has changed (to enable larger context), we need to enlarge k_cache and v_cache
-#                 if self.rotary_embedding.end > old_rotary_embed_end:
-#                     k_cache = torch.cat(
-#                         [
-#                             k_cache,
-#                             torch.zeros(
-#                                 (
-#                                     batch_size,
-#                                     self.rotary_embedding.end - old_rotary_embed_end,
-#                                     self.n_local_kv_heads,
-#                                     self.d_qk,
-#                                 ),
-#                                 dtype=query_states.dtype,
-#                                 device=query_states.device,
-#                             ),
-#                         ],
-#                         dim=1,
-#                     )
-
-#                     v_cache = torch.cat(
-#                         [
-#                             v_cache,
-#                             torch.zeros(
-#                                 (
-#                                     batch_size,
-#                                     self.rotary_embedding.end - old_rotary_embed_end,
-#                                     self.n_local_kv_heads,
-#                                     self.d_v,
-#                                 ),
-#                                 dtype=query_states.dtype,
-#                                 device=query_states.device,
-#                             ),
-#                         ],
-#                         dim=1,
-#                     )
-
-#                 assert (
-#                     k_cache.shape[1] == self.rotary_embedding.end
-#                 ), f"Cache size {k_cache.shape[1]} is smaller than rotary embedding end {self.rotary_embedding.end}"
-#                 assert (
-#                     v_cache.shape[1] == self.rotary_embedding.end
-#                 ), f"Cache size {v_cache.shape[1]} is smaller than rotary embedding end {self.rotary_embedding.end}"
-
-#                 # [batch_size, seq_len, num_heads, d_qk]
-#                 query_states = query_states.view(
-#                     batch_size, q_length, self.n_local_q_heads, self.d_qk
-#                 )  # [batch_size, q_length, self.n_heads, d_qk]
-#                 kv_length = key_states.shape[1]
-#                 key_states = key_states.view(
-#                     batch_size, kv_length, self.n_local_kv_heads, self.d_qk
-#                 )  # [batch_size, kv_length, self.n_heads, d_qk]
-#                 value_states = value_states.view(
-#                     batch_size, kv_length, self.n_local_kv_heads, self.d_v
-#                 )  # [batch_size, kv_length, self.n_heads, d_v]
-
-#                 # NOTE: this scale is for µTransfer,
-#                 # in SP, we use sqrt(1/d_h)
-#                 softmax_scale = 1 / query_states.shape[-1] if self.is_using_mup else None
-#                 attention_output = flash_attn_with_kvcache(
-#                     query_states,
-#                     k_cache,
-#                     v_cache,
-#                     key_states,
-#                     value_states,
-#                     rotary_cos=None,
-#                     rotary_sin=None,
-#                     # TODO @nouamane: seems like this doesn't help to indicate padding in (for first iteration it's just 0)
-#                     cache_seqlens=position_offsets.contiguous(),
-#                     softmax_scale=softmax_scale,
-#                     causal=True,
-#                     rotary_interleaved=False,  # GPT-NeoX style
-#                 )
-
-#             store.update(
-#                 {
-#                     "key": k_cache,  # flash-attn has updated with new key_states using cache_seqlens
-#                     "value": v_cache,
-#                     "position_offsets": position_offsets,
-#                 }
-#             )
-
-#         else:  # Training case
-#             # Apply rotary embeddings to query/key states
-#             # NOTE: The layout is different from models/llama.py which is [batch_size, num_heads, seq_len, d_qk]
-#             # Here it is, [batch_size, seq_len, num_heads, d_qk]
-#             # [2, batch_size, seq_len, num_heads, d_qk]
-#             key_value_states = torch.cat([key_states.unsqueeze(0), value_states.unsqueeze(0)], dim=0)
-#             # [batch_size, seq_len, 2, num_heads, d_qk]
-#             key_value_states = key_value_states.permute(1, 2, 0, 3, 4).contiguous()
-#             query_states, key_value_states = self.flash_rotary_embedding(query_states, kv=key_value_states)
-#             # [batch_size, seq_len, num_heads, d_qk]
-#             key_states, value_states = torch.split(key_value_states, 1, dim=2)
-
-#             q_sequence_mask = sequence_mask
-#             kv_sequence_mask = sequence_mask
-
-#             kv_length = key_states.shape[1]
-#             # [batch_size, seq_len, num_heads, d_qk]
-#             # Shaping for use in `flash-attn` version of flash-attn: `flash_attn_unpadded_func`
-#             query_states = query_states.view(
-#                 batch_size * q_length, self.n_local_q_heads, self.d_qk
-#             )  # [batch_size * q_length, self.n_heads, d_qk]
-
-#             key_states = key_states.view(
-#                 batch_size * kv_length, self.n_local_kv_heads, self.d_qk
-#             )  # [batch_size * kv_length, self.n_heads, d_qk]
-#             value_states = value_states.view(
-#                 batch_size * kv_length, self.n_local_kv_heads, self.d_v
-#             )  # [batch_size * kv_length, self.n_heads, d_v]
-
-#             attention_output = self.attention(
-#                 query_states=query_states,
-#                 key_states=key_states,
-#                 value_states=value_states,
-#                 q_sequence_mask=q_sequence_mask,
-#                 kv_sequence_mask=kv_sequence_mask,
-#             )
-
-#         attention_output = (
-#             attention_output.contiguous().view(batch_size, q_length, self.n_local_q_heads * self.d_v).transpose(0, 1)
-#         )
-#         # output = self.o_proj(attention_output)
-#         # return {"hidden_states": output, "sequence_mask": sequence_mask}
-
-#         return_outputs = {"hidden_states": None, "sequence_mask": sequence_mask}
-#         return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
-#         return_outputs["qkv_states_without_pe"] = (
-#             query_states_without_pe,
-#             key_states_without_pe,
-#             value_states_without_pe,
-#         )
-#         return_outputs["attention_output"] = attention_output
-#         return return_outputs
-
 
 class CausalSelfAttention(nn.Module, AttachableStore):
     def __init__(
@@ -1029,6 +315,7 @@ def __init__(
         assert (
             config.num_attention_heads % config.num_key_value_heads == 0
         ), f"Number of attention heads ({config.num_attention_heads}) must be divisible by number of key/value heads ({config.num_key_value_heads})."
+        self.tp_pg = tp_pg
         self.n_local_q_heads = config.num_attention_heads // tp_pg.size()
         self.n_local_kv_heads = config.num_key_value_heads // tp_pg.size()
         self.n_repeats = config.num_attention_heads // config.num_key_value_heads
@@ -1490,10 +777,16 @@ def forward(
             hidden_states
         )  # [seq_len, batch_size, n_local_q_heads * d_qk + 2 * n_local_kv_heads * d_qk]
 
-        # qkv_states = qkv_states.transpose(0, 1)
-        # q_length, batch_size, _ = qkv_states.shape
+        # log_rank(
+        #     f"qkv_states after qkv_proj: qkv_states.shape={qkv_states.shape}",
+        #     logger=logger,
+        #     level=logging.INFO,
+        # )
+
+        qkv_states = qkv_states.transpose(0, 1)
+        q_length, batch_size, _ = qkv_states.shape
         # NOTE: this is the new splitting dimension
-        batch_size, q_length, _ = qkv_states.shape
+        # batch_size, q_length, _ = qkv_states.shape
 
         if self.is_gqa:
             query_states, key_states, value_states = torch.split(
@@ -1522,6 +815,31 @@ def forward(
                 .contiguous()
             )  # [3, batch_size, seq_len, n_local_q_heads, d_qk]
 
+        # import os
+
+        # os.makedirs(DEBUG_PATH, exist_ok=True)
+        # tp_rank = dist.get_rank(group=self.tp_pg)
+
+        # torch.save(query_states, f"{DEBUG_PATH}/query_states_before_pos_tp_rank_{tp_rank}.pt")
+        # torch.save(key_states, f"{DEBUG_PATH}/query_states_before_pos_tp_rank_{tp_rank}.pt")
+        # torch.save(value_states, f"{DEBUG_PATH}/query_states_before_pos_tp_rank_{tp_rank}.pt")
+
+        # log_rank(
+        #     f"query_states: query_states.shape={query_states.shape}",
+        #     logger=logger,
+        #     level=logging.INFO,
+        # )
+        # log_rank(
+        #     f"key_states: key_states.shape={key_states.shape}",
+        #     logger=logger,
+        #     level=logging.INFO,
+        # )
+        # log_rank(
+        #     f"value_states: value_states.shape={value_states.shape}",
+        #     logger=logger,
+        #     level=logging.INFO,
+        # )
+
         # query_states_without_pe = rearrange(
         #     query_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
         # )
@@ -1749,6 +1067,10 @@ def forward(
                 batch_size * kv_length, self.n_local_kv_heads, self.d_v
             )  # [batch_size * kv_length, self.n_heads, d_v]
 
+            # torch.save(query_states, f"{DEBUG_PATH}/query_states_after_pos_tp_rank_{tp_rank}.pt")
+            # torch.save(key_states, f"{DEBUG_PATH}/query_states_after_pos_tp_rank_{tp_rank}.pt")
+            # torch.save(value_states, f"{DEBUG_PATH}/query_states_after_pos_tp_rank_{tp_rank}.pt")
+
             attention_output = self.attention(
                 query_states=query_states,
                 key_states=key_states,
@@ -1757,9 +1079,14 @@ def forward(
                 kv_sequence_mask=kv_sequence_mask,
             )
 
+            # torch.save(attention_output, f"{DEBUG_PATH}/attention_output_before_reshape_{tp_rank}.pt")
+
         attention_output = (
             attention_output.contiguous().view(batch_size, q_length, self.n_local_q_heads * self.d_v).transpose(0, 1)
         )
+
+        # torch.save(attention_output, f"{DEBUG_PATH}/attention_output_after_reshape_{tp_rank}.pt")
+
         output = self.o_proj(attention_output)
         output = output.transpose(0, 1)
         return {"hidden_states": output, "sequence_mask": sequence_mask}
diff --git a/src/nanotron/parallel/tensor_parallel/functional.py b/src/nanotron/parallel/tensor_parallel/functional.py
index a951c588..eb436df2 100644
--- a/src/nanotron/parallel/tensor_parallel/functional.py
+++ b/src/nanotron/parallel/tensor_parallel/functional.py
@@ -48,12 +48,20 @@ def forward(
             rank=0,
         )
 
+        # import os
+        # os.makedirs(DEBUG_PATH, exist_ok=True)
+        # tp_rank = dist.get_rank(group=group)
+        # torch.save(sharded_logits, f"{DEBUG_PATH}/step1_sharded_logits_tp_rank_{tp_rank}.pt")
+
         # Maximum value along last dimension across all GPUs.
         logits_max = torch.max(sharded_logits, dim=-1)[0]
         dist.all_reduce(logits_max, op=dist.ReduceOp.MAX, group=group)
         # Subtract the maximum value.
         sharded_logits = sharded_logits - logits_max.unsqueeze(dim=-1)
 
+        # torch.save(logits_max, f"{DEBUG_PATH}/logits_max_tp_rank_{tp_rank}.pt")
+        # torch.save(sharded_logits, f"{DEBUG_PATH}/step2_sharded_logits_tp_rank_{tp_rank}.pt")
+
         # Get the shard's indices
         sharded_hidden_size = sharded_logits.shape[-1]
         rank = dist.get_rank(group)
@@ -81,15 +89,21 @@ def forward(
         # All reduce is needed to get the chunks from other GPUs.
         dist.all_reduce(predicted_logits, op=dist.ReduceOp.SUM, group=group)
 
+        # torch.save(predicted_logits, f"{DEBUG_PATH}/predicted_logits_tp_rank_{tp_rank}.pt")
+
         # Sum of exponential of logits along vocab dimension across all GPUs.
         exp_logits = sharded_logits
         torch.exp(sharded_logits, out=exp_logits)
         sum_exp_logits = exp_logits.sum(dim=-1)
         dist.all_reduce(sum_exp_logits, op=dist.ReduceOp.SUM, group=group)
 
+        # torch.save(sum_exp_logits, f"{DEBUG_PATH}/sum_exp_logits_tp_rank_{tp_rank}.pt")
+
         # Loss = log(sum(exp(logits))) - predicted-logit.
         loss = torch.log(sum_exp_logits) - predicted_logits
 
+        # torch.save(loss, f"{DEBUG_PATH}/loss_tp_rank_{tp_rank}.pt")
+
         # Normalize and optionally smooth logits
         exp_logits.div_(sum_exp_logits.unsqueeze(dim=-1))
 

From 328fb710532a71fdd2b99ca5523f85df5521db45 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Wed, 12 Jun 2024 12:28:29 +0000
Subject: [PATCH 30/43] code use for exp 33

---
 src/nanotron/constants.py                     |  5 +-
 src/nanotron/debug/monitor.py                 | 13 ++-
 src/nanotron/models/llama.py                  | 97 ++++++++++---------
 .../parallel/tensor_parallel/functional.py    | 13 ++-
 src/nanotron/trainer.py                       | 18 ++--
 5 files changed, 81 insertions(+), 65 deletions(-)

diff --git a/src/nanotron/constants.py b/src/nanotron/constants.py
index 05555003..ed651077 100644
--- a/src/nanotron/constants.py
+++ b/src/nanotron/constants.py
@@ -16,7 +16,10 @@
 NEEDLE = None
 
 GLOBAL_STEP: Optional[int] = None
-LOG_STATE_INTERVAL = 500
+LOG_STATE_INTERVAL = 5000
 CONFIG = None
 
 TRAINING_CONFIG = None
+
+
+DEBUG_PATH = "./debug/nn_states_with_bs_2_and_transpose_qkv/acts/"
diff --git a/src/nanotron/debug/monitor.py b/src/nanotron/debug/monitor.py
index e9f119c7..81c51f52 100644
--- a/src/nanotron/debug/monitor.py
+++ b/src/nanotron/debug/monitor.py
@@ -2,6 +2,7 @@
 
 import torch
 import torch.distributed as dist
+from nanotron.constants import DEBUG_PATH
 from nanotron.models.base import NanotronModel
 from nanotron.parallel import ParallelContext
 from torch import nn
@@ -22,13 +23,13 @@ def compute_stats(name, tensors):
 
             stats[key] = {}
             stats[key] = {
-                "mean": tensor.mean().item(),
+                "mean": tensor.cpu().mean().item(),
                 # "std": tensor.std().item(),
                 # "var": tensor.var().item(),
                 # "norm": tensor.norm().item(),
                 # "min": tensor.min().item(),
                 # "max": tensor.max().item(),
-                "amax": tensor.abs().max().item(),
+                "amax": tensor.cpu().abs().max().item(),
             }
 
             # NOTE: now all reduce mean this across tp ranks
@@ -80,12 +81,14 @@ def save(name, tensor):
             import os
 
             # from nanotron.constants import
-            DIR = "./debug/nn_states_after_fix/acts/"
+            # DIR = "./debug/nn_states_with_bs_1/acts/"
 
-            os.makedirs(DIR, exist_ok=True)
+            os.makedirs(DEBUG_PATH, exist_ok=True)
 
             if dp_rank == 0:
-                torch.save(tensor, f"{DIR}/{name}_dp_rank_{dp_rank}_and_pp_rank_{pp_rank}_and_tp_rank_{tp_rank}.pt")
+                torch.save(
+                    tensor, f"{DEBUG_PATH}/{name}_dp_rank_{dp_rank}_and_pp_rank_{pp_rank}_and_tp_rank_{tp_rank}.pt"
+                )
 
         if len(outputs) > 1:
             for i, out in enumerate(outputs):
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index e923d66d..cb799bc3 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -413,14 +413,14 @@ def __init__(
                 ),
             )
 
-            # log_rank(
-            #     f"Segment length is {self.segment_length}, turn_on_memory: {constants.CONFIG.infini_attention.turn_on_memory is True}",
-            #     logger=logger,
-            #     level=logging.WARNING,
-            #     rank=0,
-            # )
+            log_rank(
+                f"Segment length is {self.segment_length}, turn_on_memory: {constants.CONFIG.infini_attention.turn_on_memory is True}",
+                logger=logger,
+                level=logging.WARNING,
+                rank=0,
+            )
 
-    def _forward(
+    def forward(
         self,
         # hidden_states: TensorType["sharded_seq_len", "batch_size", "hidden_size"],
         hidden_states: TensorType["sharded_batch_size", "seq_len", "hidden_size"],
@@ -602,6 +602,7 @@ def _forward(
             )
 
             output = self.o_proj(attention_output)
+            output = output.transpose(0, 1)
 
             if constants.CONFIG.infini_attention.turn_on_memory is True:
                 if (
@@ -637,12 +638,12 @@ def _forward(
         outputs = torch.cat(outputs, dim=1)  # concat along sequence dimension
         assert outputs.shape == hidden_states.shape
 
-        # if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0:
-        #     if dist.get_rank() == 0:
-        #         import wandb
+        if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0:
+            if dist.get_rank() == 0:
+                import wandb
 
-        #         logs[f"layer_{self.layer_idx}:outputs"] = compute_stas(outputs)
-        #         wandb.log({**logs, "iteration_step": constants.GLOBAL_STEP})
+                logs[f"layer_{self.layer_idx}:outputs"] = compute_stas(outputs)
+                wandb.log({**logs, "iteration_step": constants.GLOBAL_STEP})
 
         # sequence_masks = torch.cat(sequence_masks, dim=1)
         # assert sequence_masks.shape == sequence_mask.shape
@@ -759,11 +760,11 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
 
         return memory, normalization
 
-    def forward(
+    def forward_with_hidden_states(
         self,
         hidden_states,  # [seq_len, batch_size, hidden_size]
         sequence_mask,  # [batch_size, seq_len]
-        # return_qkv_states: bool = False,
+        return_qkv_states: bool = False,
     ):
         from flash_attn import bert_padding
         from flash_attn.flash_attn_interface import (
@@ -840,33 +841,41 @@ def forward(
         #     level=logging.INFO,
         # )
 
-        # query_states_without_pe = rearrange(
-        #     query_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
-        # )
-        # key_states_without_pe = rearrange(
-        #     key_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
-        # )
-        # value_states_without_pe = rearrange(
-        #     value_states, "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head"
-        # )
+        ############ START EXP33 #####
+        query_states_without_pe = rearrange(
+            query_states,
+            "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head",
+            seq_len=self.segment_length,
+        )
+        key_states_without_pe = rearrange(
+            key_states,
+            "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head",
+            seq_len=self.segment_length,
+        )
+        value_states_without_pe = rearrange(
+            value_states,
+            "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head",
+            seq_len=self.segment_length,
+        )
+        ############ END EXP32 ############
 
         # query_states_without_pe = rearrange(
         #     query_states,
-        #     "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
-        #     # seq_len=self.segment_length,
-        #     seq_len=seq_len,
+        #     "batch_size seq_len n_heads d_head -> seq_len n_heads batch_size d_head",
+        #     seq_len=self.segment_length,
+        #     # seq_len=seq_len,
         # )
         # key_states_without_pe = rearrange(
         #     key_states,
-        #     "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
-        #     # seq_len=self.segment_length,
-        #     seq_len=seq_len,
+        #     "batch_size seq_len n_heads d_head -> seq_len n_heads batch_size d_head",
+        #     seq_len=self.segment_length,
+        #     # seq_len=seq_len,
         # )
         # value_states_without_pe = rearrange(
         #     value_states,
-        #     "seq_len batch_size n_heads d_head -> seq_len n_heads batch_size d_head",
-        #     # seq_len=self.segment_length,
-        #     seq_len=seq_len,
+        #     "batch_size seq_len n_heads d_head -> seq_len n_heads batch_size d_head",
+        #     seq_len=self.segment_length,
+        #     # seq_len=seq_len,
         # )
 
         # assert query_states_without_pe.shape[0] == self.segment_length
@@ -1087,19 +1096,19 @@ def forward(
 
         # torch.save(attention_output, f"{DEBUG_PATH}/attention_output_after_reshape_{tp_rank}.pt")
 
-        output = self.o_proj(attention_output)
-        output = output.transpose(0, 1)
-        return {"hidden_states": output, "sequence_mask": sequence_mask}
+        # output = self.o_proj(attention_output)
+        # output = output.transpose(0, 1)
+        # return {"hidden_states": output, "sequence_mask": sequence_mask}
 
-        # return_outputs = {"hidden_states": None, "sequence_mask": sequence_mask}
-        # return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
-        # return_outputs["qkv_states_without_pe"] = (
-        #     query_states_without_pe,
-        #     key_states_without_pe,
-        #     value_states_without_pe,
-        # )
-        # return_outputs["attention_output"] = attention_output
-        # return return_outputs
+        return_outputs = {"hidden_states": None, "sequence_mask": sequence_mask}
+        return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
+        return_outputs["qkv_states_without_pe"] = (
+            query_states_without_pe,
+            key_states_without_pe,
+            value_states_without_pe,
+        )
+        return_outputs["attention_output"] = attention_output
+        return return_outputs
 
 
 class LlamaDecoderLayer(nn.Module):
diff --git a/src/nanotron/parallel/tensor_parallel/functional.py b/src/nanotron/parallel/tensor_parallel/functional.py
index eb436df2..fabd0262 100644
--- a/src/nanotron/parallel/tensor_parallel/functional.py
+++ b/src/nanotron/parallel/tensor_parallel/functional.py
@@ -20,7 +20,6 @@
 
 import nanotron.distributed as dist
 from nanotron import logging
-from nanotron.logging import log_rank
 from nanotron.parallel.tensor_parallel.distributed_differentiable_primitives import (
     differentiable_all_gather,
     differentiable_all_reduce_sum,
@@ -41,12 +40,12 @@ def forward(
         target,  # (batch_size, length)
         group: dist.ProcessGroup,
     ):
-        log_rank(
-            f"sharded_logits input of _ShardedCrossEntropy: sharded_logits.shape={sharded_logits.shape}",
-            logger=logger,
-            level=logging.INFO,
-            rank=0,
-        )
+        # log_rank(
+        #     f"sharded_logits input of _ShardedCrossEntropy: sharded_logits.shape={sharded_logits.shape}",
+        #     logger=logger,
+        #     level=logging.INFO,
+        #     rank=0,
+        # )
 
         # import os
         # os.makedirs(DEBUG_PATH, exist_ok=True)
diff --git a/src/nanotron/trainer.py b/src/nanotron/trainer.py
index 27ed32ed..8fc1b605 100644
--- a/src/nanotron/trainer.py
+++ b/src/nanotron/trainer.py
@@ -435,8 +435,10 @@ def train(
                 if isinstance(prof, torch.profiler.profile):
                     prof.step()
 
-                # if (self.iteration_step - 1) % constants.LOG_STATE_INTERVAL == 0:
-                #     nn_logs, nn_handles = monitor_nanotron_model(self.model, self.parallel_context)
+                if (self.iteration_step - 1) % constants.LOG_STATE_INTERVAL == 0:
+                    from nanotron.debug.monitor import monitor_nanotron_model
+
+                    nn_logs, nn_handles = monitor_nanotron_model(self.model, self.parallel_context)
 
                 self.iteration_start_time = time.time()
                 self._update_dataloader_based_on_training_stages(dataloader_or_dls)
@@ -450,14 +452,14 @@ def train(
                 if (self.iteration_step - 1) % self.config.logging.iteration_step_info_interval == 0:
                     self.train_step_logs(outputs=outputs, loss_avg=loss_avg)
 
-                # if (self.iteration_step - 1) % constants.LOG_STATE_INTERVAL == 0:
-                #     from nanotron.debug.monitor import convert_logs_to_flat_logs
+                if (self.iteration_step - 1) % constants.LOG_STATE_INTERVAL == 0:
+                    from nanotron.debug.monitor import convert_logs_to_flat_logs
 
-                #     if dist.get_rank(self.parallel_context.world_pg) == self.logger_ranks[0] and wandb is not None:
-                #         wandb.log({**convert_logs_to_flat_logs(nn_logs), "iteration_step": self.iteration_step})
+                    if dist.get_rank(self.parallel_context.world_pg) == self.logger_ranks[0] and wandb is not None:
+                        wandb.log({**convert_logs_to_flat_logs(nn_logs), "iteration_step": self.iteration_step})
 
-                #     for handle in nn_handles:
-                #         handle.remove()
+                    for handle in nn_handles:
+                        handle.remove()
 
                 # Checkpoint
                 if self.iteration_step % self.config.checkpoints.checkpoint_interval == 0:

From 838cce606351a7cb211227b9590208d585cbf88d Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Thu, 13 Jun 2024 05:32:08 +0000
Subject: [PATCH 31/43] fix inference

---
 run_generate.py              |  29 ++++++-
 src/nanotron/models/llama.py | 158 +++++------------------------------
 2 files changed, 46 insertions(+), 141 deletions(-)

diff --git a/run_generate.py b/run_generate.py
index c25ef8bf..c4f3310e 100644
--- a/run_generate.py
+++ b/run_generate.py
@@ -250,6 +250,22 @@ def evaluate(self, X, y):
 Lastly, obtaining verifiable credentials is paramount for demonstrating competence within the competitive realm of real estate investing. Securing physical or digital ID cards and certificates serves as
 """
 
+PASSKEY_1024_CTX_AND_20_DEPTH = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on............................... The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the. The pass key is 5. Remember it. 5 is the pass key.  salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world iThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The. \n\nWhat is the pass key? The pass key is "
+
+
+PASSKEY_1024_CTX_AND_0_DEPTH = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on............................................................... . The pass key is 7. Remember it. 7 is the pass key. The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world iThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The. \n\nWhat is the pass key? The pass key is "
+
+
+PASSKEY_1024_CTX_AND_90_DEPTH = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on............................................................... The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar.. The pass key is 3. Remember it. 3 is the pass key.  The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world iThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The. \n\nWhat is the pass key? The pass key is "
+
+HARRY_POTTER_256_TOKENS = """
+\nMr. and Mrs. Dursley, of number four, Privet Drive, were proud to say\nthat they were perfectly normal, thank you very much. They were the last\npeople you'd expect to be involved in anything strange or mysterious,\nbecause they just didn't hold with such nonsense.\n\nMr. Dursley was the director of a firm called Grunnings, which made\ndrills. He was a big, beefy man with hardly any neck, although he did\nhave a very large mustache. Mrs. Dursley was thin and blonde and had\nnearly twice the usual amount of neck, which came in very useful as she\nspent so much of her time craning over garden fences, spying on the\nneighbors. The Dursleys had a small son called Dudley and in their\nopinion there was no finer boy anywhere.\n\nThe Dursleys had everything they wanted, but they also had a secret, and\ntheir greatest fear was that somebody would discover it. They didn't\nthink they could bear it if anyone found out about the Potters. Mrs.\nPotter was Mrs. Dursley's sister, but they hadn't met for several
+"""
+
+MATH_TEXT_256_TOKENS = """
+\nThe problem provided is derived from the 1980 American High School Mathematics Examination (AHSME), specifically problem number 17. This problem requires knowledge of complex numbers and algebraic manipulations. We will break down the solution into smaller steps and explain the underlying mathematical principles. Complex numbers can be represented as ordered pairs (a, b) or in the form of a + bi, where a and b are real numbers, and i is the square root of -1. When squaring i, you get (-1). Let's examine the given expression more closely: (n + i)^4 = n^4 + 4in³ - 6n² - 4in + 1 For this expression to result in an integer value, both its real and imaginary components must equal integers. First, let us focus on the imaginary part of the expression: 4in³ - 4in. For these terms to cancel out when adding the whole expression, they need to be equivalent; hence: 4in³ - 4in = 0 Now, factor out 4in: 4in(n² - 1) = 0 The equation above implies two possible scenarios. Either 4in equals zero
+"""
+
 
 def get_args():
     parser = argparse.ArgumentParser()
@@ -257,7 +273,7 @@ def get_args():
     parser.add_argument("--dp", type=int, default=0)
     parser.add_argument("--pp", type=int, default=0)
     parser.add_argument("--tp", type=int, default=0)
-    parser.add_argument("--max-new-tokens", type=int, default=128, help="Maximum number of new tokens to generate")
+    parser.add_argument("--max-new-tokens", type=int, default=40, help="Maximum number of new tokens to generate")
     return parser.parse_args()
 
 
@@ -376,8 +392,8 @@ def main():
             # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
             # "This is a math lesson. Answer the question. What is the result of 1 + 1? The result is ",
             # "This is a math lesson. Answer the question. What is the result of 1 + 1? The result is ",
-            "def fib(n)",
             # "def fib(n)",
+            # "def fib(x)",
             # "This film was probably inspired by Godzilla, ",
             # "This film was probably inspired by Godzilla, ",
             # "Paris is the capital of ",
@@ -386,7 +402,8 @@ def main():
             # END_PASSKEY_EXTACT_32K_TOKENS,
             # PASSKEY_NINETY_PERCENT,
             # "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The grass is green. The sky is blue. The pass key is 24. Remember it. 24 is the pass key. What is the pass key? The pass key is ",
-            # "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The grass is green. The sky is blue. The pass key is 24. Remember it. 24 is the pass key. What is the pass key? The pass key is ",
+            "The pass key is 24. Remember it. 24 is the pass key. The grass is green. The sky is blue. What is the pass key? The pass key is ",
+            # "The pass key is 4. Remember it. 4 is the pass key. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue. What is the pass key? The pass key is ",
             # FINETUNE,
             # "1234",
             # "1234",
@@ -402,6 +419,12 @@ def main():
             # NOTE: last training data
             # "Effectively managing student enquiries lies at the heart of successful real estate and investment education. Through leveraging diverse resources such as FAQs, online enquiry ",
             # TRAINING_DATA_4K,
+            # TRAINING_DATA_4K,
+            # PASSKEY_1024_CTX_AND_0_DEPTH,
+            # PASSKEY_1024_CTX_AND_0_DEPTH
+            # PASSKEY_1024_CTX_AND_90_DEPTH,
+            # PASSKEY_1024_CTX_AND_90_DEPTH,
+            # MATH_TEXT_256_TOKENS
         ]
 
         outputs = decode_text(
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index cb799bc3..c9dc5b15 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -379,24 +379,11 @@ def __init__(
 
         self.prefill_kv_len = (
             config.max_position_embeddings
-            # 2048
         )  # TODO @nouamane: compute based on free memory, because in rope we can surpass max_position_embeddings
 
-        # self.n_segments = 16
-        # self.segment_length = config.max_position_embeddings // self.n_segments
         # assert config.max_position_embeddings == 32768
-
-        # NOTE: for 1b training
-        # self.segment_length = 2048
-        # self.segment_length = 4096
-        # self.segment_length = 1024  # for 4096 context length
         self.segment_length = constants.CONFIG.infini_attention.segment_length  # for 1024 context length
 
-        # NOTE: for sanity 200m training
-        # prev 16
-        # self.segment_length = 256
-        # self.segment_length = 16
-
         device = self.o_proj.weight.device
         dtype = self.o_proj.weight.dtype
 
@@ -426,28 +413,10 @@ def forward(
         hidden_states: TensorType["sharded_batch_size", "seq_len", "hidden_size"],
         sequence_mask: TensorType["batch_size", "seq_len"],
     ):
-        # if self.layer_idx == 4:
-        #     assert 1 == 1
-
-        # batch_size = hidden_states.shape[1]
-        # seq_len = hidden_states.shape[0]
-
         hidden_states.shape[0]
         seq_len = hidden_states.shape[1]
 
-        # assert seq_len == 1024
-        # assert seq_len == 32768
-
-        # assert seq_len % self.n_segments == 0
-
-        # segment_length = seq_len // self.n_segments
-        # hidden_size = hidden_states.shape[2]
-
         if seq_len > self.segment_length:
-            # n_segments = seq_len // self.segment_length
-            # segment_hidden_states = torch.chunk(hidden_states, chunks=n_segments, dim=0)
-            # segment_sequence_masks = torch.chunk(sequence_mask, chunks=n_segments, dim=1)
-
             import math
 
             n_segments = math.ceil(seq_len / self.segment_length)
@@ -455,9 +424,7 @@ def forward(
                 seq_len - (n_segments - 1) * self.segment_length
             ]
             assert sum(segment_lengths) == seq_len
-            # assert hidden_states.shape[0] == seq_len
             assert hidden_states.shape[1] == seq_len
-            # segment_hidden_states = torch.split(hidden_states, segment_lengths, dim=0)
             segment_hidden_states = torch.split(hidden_states, segment_lengths, dim=1)
             # NOTE: assume that mask are all the same
             # because we split across sequence length
@@ -471,67 +438,26 @@ def forward(
         memory = None
         normalization = None
 
-        # memory = prev_memory
-        # normalization = prev_normalization
-
         outputs = []
 
-        # sequence_masks = []
         idx = 0
         logs = {}
 
         for segment_hidden_state, segment_sequence_mask in zip(segment_hidden_states, segment_sequence_masks):
-            # if idx == 1:
-            #     memory = None
-            #     normalization = None
-
             attn_outputs = self.forward_with_hidden_states(
                 hidden_states=segment_hidden_state, sequence_mask=segment_sequence_mask, return_qkv_states=True
             )
 
             local_attn_outputs = attn_outputs["attention_output"]
-            # query_states, key_states, value_states = attn_outputs["qkv_states"]
             query_states, key_states, value_states = attn_outputs["qkv_states_without_pe"]
-
-            # # NOTE: these are the shape for non-megatron-sp
-            # assert query_states.shape[0] == self.segment_length
-            # assert local_attn_outputs.shape[1] == self.segment_length
-
-            query_states = rearrange(
-                query_states,
-                "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
-                # seq_len=self.segment_length,
-                n_heads=self.n_local_q_heads,
-                d_head=self.d_qk,
-            )
-
-            key_states = rearrange(
-                key_states,
-                "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
-                # batch_size=batch_size,
-                # seq_len=self.segment_length,
-                n_heads=self.n_local_kv_heads,
-                d_head=self.d_qk,
-            )
-
-            value_states = rearrange(
-                value_states,
-                "seq_len n_heads batch_size d_head -> batch_size n_heads seq_len d_head",
-                # batch_size=batch_size,
-                # seq_len=self.segment_length,
-                n_heads=self.n_local_kv_heads,
-                d_head=self.d_qk,
-            )
-
-            # local_attn_outputs = rearrange(
-            #     local_attn_outputs,
-            #     "seq_len batch_size (n_heads d_head) -> batch_size n_heads seq_len d_head",
-            #     d_head=self.d_qk,
-            # )
+            q_bs = query_states.shape[0]
+            q_length = query_states.shape[2]
             local_attn_outputs = rearrange(
                 local_attn_outputs,
-                "batch_size seq_len (n_heads d_head) -> batch_size n_heads seq_len d_head",
+                "seq_len batch_size (n_heads d_head) -> batch_size n_heads seq_len d_head",
                 # seq_len=self.segment_length,
+                batch_size=q_bs,
+                seq_len=q_length,
                 d_head=self.d_qk,
             )
 
@@ -544,8 +470,6 @@ def forward(
 
             if constants.CONFIG.infini_attention.turn_on_memory is True:
                 # NOTE: because in generation, the sequence length increases
-                # assert query_states.shape == (batch_size, self.n_local_q_heads, segment_length, self.d_qk)
-                # assert query_states.shape == key_states.shape == value_states.shape
                 retrieved_memory = self._retrieve_from_memory(
                     query_states, prev_memory=memory, prev_normalization=normalization
                 )
@@ -565,16 +489,12 @@ def forward(
                 #         rank=0,
                 #     )
 
-                # retrieved_memory = retrieved_memory.detach()
-
                 global_weights = F.sigmoid(self.balance_factors)
                 global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
 
                 local_weights = 1 - F.sigmoid(self.balance_factors)
                 local_weights = rearrange(local_weights, "n_heads -> 1 n_heads 1 1")
 
-                # assert torch.allclose(global_weights + local_weights, torch.ones_like(global_weights))
-
                 # log_rank(
                 #     f"[idx={idx}] global_weights.shape = {global_weights.shape}, global_weights: {global_weights}",
                 #     logger=logger,
@@ -598,11 +518,10 @@ def forward(
                 "batch_size n_heads seq_len d_head -> batch_size seq_len (n_heads d_head)",
                 n_heads=self.n_local_q_heads,
                 d_head=self.d_qk,
-                # seq_len=self.segment_length,
+                seq_len=q_length,
             )
 
             output = self.o_proj(attention_output)
-            output = output.transpose(0, 1)
 
             if constants.CONFIG.infini_attention.turn_on_memory is True:
                 if (
@@ -623,18 +542,16 @@ def forward(
                         logs[f"layer_{self.layer_idx}:seg_{idx}:memory"] = compute_stas(memory)
                         logs[f"layer_{self.layer_idx}:seg_{idx}:normalization"] = compute_stas(normalization)
 
-                # assert output.shape == (segment_length, batch_size, hidden_size)
+                if idx >= 1:
+                    assert 1 == 1
 
                 memory, normalization = self._update_memory(memory, normalization, key_states, value_states)
-                # memory = prev_memory if prev_memory is not None else 0.detach()
 
             outputs.append(output)
-            # memory, normalization = memory.detach(), normalization.detach()
 
             idx += 1
 
             # NOTE: update memory
-        # outputs = torch.cat(outputs, dim=0)  # concat along sequence dimension
         outputs = torch.cat(outputs, dim=1)  # concat along sequence dimension
         assert outputs.shape == hidden_states.shape
 
@@ -645,18 +562,13 @@ def forward(
                 logs[f"layer_{self.layer_idx}:outputs"] = compute_stas(outputs)
                 wandb.log({**logs, "iteration_step": constants.GLOBAL_STEP})
 
-        # sequence_masks = torch.cat(sequence_masks, dim=1)
-        # assert sequence_masks.shape == sequence_mask.shape
         return_outputs = {
             "hidden_states": outputs,
             "sequence_mask": sequence_mask,
-            # "memory": memory,
-            # "normalization": normalization,
         }
         return return_outputs
 
     def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
-        # return torch.zeros_like(query_states)
         if prev_memory is None or prev_normalization is None:
             return torch.zeros_like(query_states)
 
@@ -664,20 +576,6 @@ def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
             prev_memory is not None and prev_normalization is not None
         )
 
-        # if self.n_repeats > 1:
-        #     from einops import repeat
-
-        #     prev_memory = repeat(
-        #         prev_memory,
-        #         "batch_size n_kv_heads d_k d_v -> batch_size (n_kv_heads n) d_k d_v",
-        #         n=self.n_repeats,
-        #     )
-        #     prev_normalization = repeat(
-        #         prev_normalization,
-        #         "batch_size n_kv_heads d_head -> batch_size (n_kv_heads n) d_head",
-        #         n=self.n_repeats,
-        #     )
-
         sigma_query_states = F.elu(query_states) + 1
         retrieved_memory = einsum(
             sigma_query_states,
@@ -787,7 +685,6 @@ def forward_with_hidden_states(
         qkv_states = qkv_states.transpose(0, 1)
         q_length, batch_size, _ = qkv_states.shape
         # NOTE: this is the new splitting dimension
-        # batch_size, q_length, _ = qkv_states.shape
 
         if self.is_gqa:
             query_states, key_states, value_states = torch.split(
@@ -841,45 +738,30 @@ def forward_with_hidden_states(
         #     level=logging.INFO,
         # )
 
-        ############ START EXP33 #####
         query_states_without_pe = rearrange(
             query_states,
             "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head",
-            seq_len=self.segment_length,
+            batch_size=batch_size,
+            seq_len=q_length,
+            n_heads=self.n_local_q_heads,
+            d_head=self.d_qk,
         )
         key_states_without_pe = rearrange(
             key_states,
             "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head",
-            seq_len=self.segment_length,
+            batch_size=batch_size,
+            seq_len=q_length,
+            n_heads=self.n_local_kv_heads,
+            d_head=self.d_qk,
         )
         value_states_without_pe = rearrange(
             value_states,
             "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head",
-            seq_len=self.segment_length,
+            batch_size=batch_size,
+            seq_len=q_length,
+            n_heads=self.n_local_kv_heads,
+            d_head=self.d_qk,
         )
-        ############ END EXP32 ############
-
-        # query_states_without_pe = rearrange(
-        #     query_states,
-        #     "batch_size seq_len n_heads d_head -> seq_len n_heads batch_size d_head",
-        #     seq_len=self.segment_length,
-        #     # seq_len=seq_len,
-        # )
-        # key_states_without_pe = rearrange(
-        #     key_states,
-        #     "batch_size seq_len n_heads d_head -> seq_len n_heads batch_size d_head",
-        #     seq_len=self.segment_length,
-        #     # seq_len=seq_len,
-        # )
-        # value_states_without_pe = rearrange(
-        #     value_states,
-        #     "batch_size seq_len n_heads d_head -> seq_len n_heads batch_size d_head",
-        #     seq_len=self.segment_length,
-        #     # seq_len=seq_len,
-        # )
-
-        # assert query_states_without_pe.shape[0] == self.segment_length
-        # assert query_states_without_pe.shape[0] == seq_len
 
         store = self.get_local_store()
         if store is not None:  # Inference case

From 25f1f35c9a51d2b7500cfec56b04cc416ed3782c Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Wed, 19 Jun 2024 09:28:51 +0000
Subject: [PATCH 32/43] refactor passkey retrivial data generation script

---
 .../infinite-context-length/generate_data.py  | 123 ++--
 .../infinite-context-length/generate_evals.py | 593 ------------------
 2 files changed, 68 insertions(+), 648 deletions(-)
 delete mode 100644 examples/infinite-context-length/generate_evals.py

diff --git a/examples/infinite-context-length/generate_data.py b/examples/infinite-context-length/generate_data.py
index 48eace62..1ea1f051 100644
--- a/examples/infinite-context-length/generate_data.py
+++ b/examples/infinite-context-length/generate_data.py
@@ -62,35 +62,21 @@ def read_context_files(tokenizer, soft_prompt, retrieval_question, target_cut_le
     return context
 
 
-# def insert_needle(context, needle):
-#     # Get the position to insert the needle
-#     insertion_point = random.randint(0, len(context) - len(needle)) - 1
-
-#     # Insert the needle at the appropriate position
-#     new_context = context[:insertion_point] + needle + context[insertion_point:]
-
-#     return new_context
-
-
 def insert_needle_with_depth(needle, context, depth_percent, target_cut_length, tokenizer):
     content_ids = tokenizer.encode(context)
-    # content_length = len(content_ids)
     needle_ids = tokenizer.encode(needle)
 
     if depth_percent == 100:
         # If depth percent is 100, place the needle at the end
-        # new_context = context[: len(context) - len(needle)] + needle
         new_context_ids = content_ids[: len(content_ids) - len(needle_ids)] + needle_ids
     else:
         # Get the position to insert the needle
-        # insertion_point = int(context_length * (depth_percent / 100))
         insertion_point = int(len(content_ids) * (depth_percent / 100))
 
         # Find the nearest period to the insertion point
         while context[insertion_point] != "." and insertion_point > 0:
             insertion_point -= 1
 
-        # Insert the needle at the appropriate position
         # new_context = context[:insertion_point] + needle + context[insertion_point:content_length]
         new_context_ids = (
             content_ids[:insertion_point]
@@ -98,16 +84,21 @@ def insert_needle_with_depth(needle, context, depth_percent, target_cut_length,
             + content_ids[insertion_point : (target_cut_length - len(needle_ids))]
         )
 
-    new_content = tokenizer.decode(new_context_ids)
+    new_content = tokenizer.decode(new_context_ids, skip_special_tokens=True, clean_up_tokenization_spaces=True)
 
     return new_content
 
 
 def generate_needle_in_haystack_test(
-    needle, needle_prompt, haystack_dir, soft_prompt: str, retrieval_question, context_length, depth_percent
+    needle,
+    needle_prompt,
+    soft_prompt: str,
+    retrieval_question,
+    context_length,
+    depth_percent,
+    tokenizer,
+    is_padding: bool,
 ):
-    # Load up the haystack context
-    tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
     target_cut_length = context_length - token_length(tokenizer, PROMPT.format(soft_prompt, 1, retrieval_question)) - 1
 
     context = read_context_files(tokenizer, soft_prompt, retrieval_question, target_cut_length)
@@ -119,20 +110,21 @@ def generate_needle_in_haystack_test(
     prompt = f"{soft_prompt} {context_with_needle}. \n\n{retrieval_question}"
 
     assert str(needle) in context_with_needle, f"depth_percent: {depth_percent}"
-    # assert abs(context_length - token_length(tokenizer, prompt)) <= 10
-    # assert context_length - token_length(tokenizer, prompt)
 
-    # remaining_tokens = context_length - token_length(tokenizer, prompt)
     # NOTE: now add `.` to soft_prompt so that the token length is exactly equal to context_length
-    while (
-        token_length(tokenizer, PROMPT.format(soft_prompt, context_with_needle, retrieval_question)) < context_length
-    ):
-        soft_prompt += "."
+    if is_padding is True:
+        while (
+            token_length(tokenizer, PROMPT.format(soft_prompt, context_with_needle, retrieval_question))
+            < context_length
+        ):
+            soft_prompt += "."
 
     prompt = PROMPT.format(soft_prompt, context_with_needle, retrieval_question)
-    assert (
-        token_length(tokenizer, prompt) == context_length
-    ), f"Token length: {token_length(tokenizer, prompt)}, Context length: {context_length}, depth_percent: {depth_percent}"
+
+    if is_padding is True:
+        assert (
+            token_length(tokenizer, prompt) == context_length
+        ), f"Token length: {token_length(tokenizer, prompt)}, Context length: {context_length}, depth_percent: {depth_percent}"
 
     return prompt
 
@@ -141,66 +133,85 @@ def get_args():
     parser = argparse.ArgumentParser()
     parser.add_argument("--context_length", type=int, required=True)
     parser.add_argument("--depth_percent", type=int, required=True)
+    parser.add_argument("--num_prompts", type=int, default=5)
+    parser.add_argument(
+        "--tokenizer_path", type=str, default="/fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B"
+    )
     parser.add_argument("--id", type=int, required=True)
+    parser.add_argument("--haystack_dir", type=str, default="./haystack_txt/")
+    parser.add_argument("--is_push_to_hub", type=bool, default=False)
+    parser.add_argument("--is_exact_context_length", type=int, default=1)  # 1 is True, 0 is False
+    parser.add_argument("--is_padding", type=int, default=1)  # 1 is True, 0 is False
     return parser.parse_args()
 
 
 if __name__ == "__main__":
     args = get_args()
 
+    for key, value in vars(args).items():
+        print(f"{key}: {value}")
+
     context_length = args.context_length
     depth_percent = args.depth_percent
+    tokenizer_path = args.tokenizer_path
+    num_prompts = args.num_prompts
     id = args.id
+    haystack_dir = args.haystack_dir
+    is_push_to_hub = args.is_push_to_hub
+    # is_exact_context_length = args.is_exact_context_length
+    is_exact_context_length = False if args.is_exact_context_length == 0 else True
+    is_padding = False if args.is_padding == 0 else True
 
-    haystack_dir = "./"
-    # NOTE: depth_percent + 1 to avoid 0
-    start_range = 1000 * (depth_percent + 1) * id
-    end_range = start_range + start_range
+    gen_context_length = context_length if is_exact_context_length is True else context_length - random.randint(0, 700)
 
-    keys_in_train_set = get_keys_in_train_set()
+    # NOTE: depth_percent + 1 to avoid 0
+    RANGE = 500
+    start_range = 30 * (depth_percent + 1) * id
+    end_range = start_range + RANGE
 
     print(
-        f"Generating prompts for context length: {context_length} and depth percent: {depth_percent} and id: {id} \n"
+        f"Generating prompts for context length: {gen_context_length} (original {context_length}) and depth percent: {depth_percent} and id: {id} \n"
     )
     print(f"start_range: {start_range}, end_range: {end_range} \n")
 
+    tokenizer = AutoTokenizer.from_pretrained(tokenizer_path)
+
     def generate_dataset():
-        # num_prompts = 1700
-        num_prompts = 5
-        # soft_prompt = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there."
         soft_prompt = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on."
-        # context_lengths = [
-        #     32768,
-        # ]
-        # depth_percents = np.linspace(0, 100, num=21)
 
-        dataset_dict = {"id": [], "prompt": [], "answer": [], "context_length": [], "depth_percent": []}
+        dataset_dict = {
+            "id": [],
+            "prompt": [],
+            "answer": [],
+            "context_length": [],
+            "num_tokens": [],
+            "depth_percent": [],
+        }
         generated_ids = set()
         generated_pass_keys = set()
 
-        # for context_length in context_lengths:
-        #     print(f"Generating prompts for context length: {context_length} \n")
-        #     for depth_percent in depth_percents:
         for i in range(num_prompts):
             print(f"generating prompt {i} \n")
 
             while True:
                 pass_key = random.randint(start_range, end_range)
-                if pass_key not in keys_in_train_set and pass_key not in generated_pass_keys:
+                if pass_key not in generated_pass_keys:
                     generated_pass_keys.add(pass_key)
                     break
 
             needle_prompt = f". The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
+            # retrieval_question = f"What is the pass key? The pass key is {pass_key}"
             retrieval_question = "What is the pass key? The pass key is "
 
             prompt = generate_needle_in_haystack_test(
-                pass_key,
-                needle_prompt,
-                haystack_dir,
-                soft_prompt,
-                retrieval_question,
-                context_length,
-                depth_percent,
+                needle=pass_key,
+                needle_prompt=needle_prompt,
+                soft_prompt=soft_prompt,
+                retrieval_question=retrieval_question,
+                context_length=gen_context_length,
+                depth_percent=depth_percent,
+                tokenizer=tokenizer,
+                is_padding=is_padding,
             )
 
             while True:
@@ -213,6 +224,7 @@ def generate_dataset():
             dataset_dict["prompt"].append(prompt)
             dataset_dict["answer"].append(pass_key)
             dataset_dict["context_length"].append(context_length)
+            dataset_dict["num_tokens"].append(token_length(tokenizer, prompt))
             dataset_dict["depth_percent"].append(depth_percent)
 
         dataset = Dataset.from_dict(dataset_dict)
@@ -223,6 +235,7 @@ def generate_dataset():
 
     # Save the dataset to disk
     dataset.save_to_disk(
-        f"/fsx/phuc/projects/nanotron/examples/infinite-context-length/needle_eval_datasets/needle_eval_ctx_len_32768_and_depth_{depth_percent}_and_id_{id}"
+        f"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/eval_data/needle_eval_and_{context_length}_ctx_and_depth_{depth_percent}_and_id_{id}"
     )
-    # dataset.push_to_hub("nanotron/needle_in_a_hay_stack_finetuning_dataset")
+    if is_push_to_hub:
+        dataset.push_to_hub("nanotron/llama3-16k-passkey-retrieval-eval")
diff --git a/examples/infinite-context-length/generate_evals.py b/examples/infinite-context-length/generate_evals.py
deleted file mode 100644
index 4286624d..00000000
--- a/examples/infinite-context-length/generate_evals.py
+++ /dev/null
@@ -1,593 +0,0 @@
-import glob
-import os
-
-
-def generate_needle_in_haystack_test(
-    needle, haystack_dir, soft_prompt: str, retrieval_question, context_length, depth_percent
-):
-    def read_context_files():
-        context = ""
-        base_dir = os.path.abspath(os.path.dirname(__file__))  # Package directory
-
-        while len(context) < context_length:
-            for file in glob.glob(os.path.join(base_dir, haystack_dir, "*.txt")):
-                with open(file, "r") as f:
-                    context += f.read()
-        return context
-
-    def insert_needle(context):
-        if depth_percent == 100:
-            # If depth percent is 100, place the needle at the end
-            new_context = context[: context_length - len(needle)] + needle
-        else:
-            # Get the position to insert the needle
-            insertion_point = int(context_length * (depth_percent / 100))
-
-            # Find the nearest period to the insertion point
-            while context[insertion_point] != "." and insertion_point > 0:
-                insertion_point -= 1
-
-            # Insert the needle at the appropriate position
-            new_context = context[:insertion_point] + needle + context[insertion_point:context_length]
-
-        return new_context
-
-    # Load up the haystack context
-    context = read_context_files()
-
-    # Truncate the context to the desired context length
-    context = context[:context_length]
-
-    # Insert the needle into the context at the specified depth percent
-    context_with_needle = insert_needle(context)
-
-    # Generate the prompt using the context with the needle
-    prompt = f"{soft_prompt} {context_with_needle} \n\n{retrieval_question}"
-
-    return prompt, needle
-
-
-# # Working example
-haystack_dir = "./"
-
-import random
-import uuid
-
-import numpy as np
-from datasets import Dataset
-
-
-def generate_dataset():
-    num_prompts = 100
-    soft_prompt = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there."
-    context_lengths = [
-        1024,
-        2048,
-        4096,
-        8192,
-        16384,
-        32768,
-        # 65536,
-        # 131072,
-        # 262144,
-        # 524288,
-        # 1048576,
-    ]
-    depth_percents = np.linspace(0, 100, num=21)
-
-    dataset_dict = {"id": [], "prompt": [], "answer": [], "context_length": [], "depth_percent": []}
-    generated_ids = set()
-
-    for context_length in context_lengths:
-        print(f"Generating prompts for context length: {context_length} \n")
-        for depth_percent in depth_percents:
-            for _ in range(num_prompts):
-                pass_key = random.randint(10000, 50000)
-                needle = f"The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
-                retrieval_question = "What is the pass key? The pass key is "
-
-                prompt, _ = generate_needle_in_haystack_test(
-                    needle, haystack_dir, soft_prompt, retrieval_question, context_length, depth_percent
-                )
-                # answer = f"The pass key is {pass_key}"
-
-                while True:
-                    text_id = str(uuid.uuid4())
-                    if text_id not in generated_ids:
-                        generated_ids.add(text_id)
-                        break
-
-                dataset_dict["id"].append(text_id)
-                dataset_dict["prompt"].append(prompt)
-                dataset_dict["answer"].append(pass_key)
-                dataset_dict["context_length"].append(context_length)
-                dataset_dict["depth_percent"].append(depth_percent)
-
-    dataset = Dataset.from_dict(dataset_dict)
-    return dataset
-
-
-# Generate the dataset
-dataset = generate_dataset()
-
-# Save the dataset to disk
-dataset.save_to_disk("needle_in_a_hay_stack_eval_dataset")
-dataset.push_to_hub("nanotron/needle_in_a_hay_stack_eval_dataset")
-
-
-############################################################################################################
-
-
-# import glob
-# import os
-# import random
-# import uuid
-
-# import numpy as np
-# from datasets import Dataset
-# from transformers import AutoTokenizer
-
-
-# if __name__ == "__main__":
-#     def generate_needle_in_haystack_test(
-#         needle, haystack_dir, soft_prompt: str, retrieval_question, context_length, depth_percent
-#     ):
-#         def read_context_files():
-#             context = ""
-#             base_dir = os.path.abspath(os.path.dirname(__file__))  # Package directory
-
-#             while len(tokenizer.encode(context)) < context_length:
-#                 for file in glob.glob(os.path.join(base_dir, haystack_dir, "*.txt")):
-#                     with open(file, "r") as f:
-#                         context += f.read()
-#             return context
-
-#         def insert_needle(context):
-#             if depth_percent == 100:
-#                 # If depth percent is 100, place the needle at the end
-#                 new_context = context[: context_length - len(tokenizer.encode(needle))] + needle
-#             else:
-#                 # Get the position to insert the needle
-#                 insertion_point = int(context_length * (depth_percent / 100))
-
-#                 # Find the nearest period to the insertion point
-#                 while context[insertion_point] != "." and insertion_point > 0:
-#                     insertion_point -= 1
-
-#                 # Insert the needle at the appropriate position
-#                 new_context = context[:insertion_point] + needle + context[insertion_point:context_length]
-
-#             return new_context
-
-#         # Load up the haystack context
-#         context = read_context_files()
-
-#         # Truncate the context to the desired context length
-#         context = tokenizer.decode(tokenizer.encode(context)[:context_length])
-
-#         # Insert the needle into the context at the specified depth percent
-#         context_with_needle = insert_needle(context)
-
-#         # Generate the prompt using the context with the needle
-#         prompt = f"{soft_prompt} {context_with_needle} \n\n{retrieval_question}"
-
-#         return prompt, needle
-
-#     # Working example
-#     haystack_dir = "./"
-
-#     # Load the tokenizer
-#     tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
-
-
-#     def generate_dataset():
-#         num_prompts = 1
-#         soft_prompt = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there."
-#         context_lengths = [
-#             # 1024,
-#             # 2048,
-#             # 4096,
-#             # 8192,
-#             # 16384,
-#             32768,
-#             # 65536,
-#             # 131072,
-#             # 262144,
-#             # 524288,
-#             # 1048576,
-#         ]
-#         depth_percents = np.linspace(0, 100, num=21)
-
-#         dataset_dict = {"id": [], "prompt": [], "answer": [], "context_length": [], "depth_percent": []}
-#         generated_ids = set()
-
-#         for context_length in context_lengths:
-#             print(f"Generating prompts for context length: {context_length} \n")
-#             for depth_percent in depth_percents:
-#                 for _ in range(num_prompts):
-#                     pass_key = random.randint(10000, 50000)
-#                     needle = f"The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
-#                     retrieval_question = f"What is the pass key? The pass key is "
-
-#                     prompt, _ = generate_needle_in_haystack_test(
-#                         needle, haystack_dir, soft_prompt, retrieval_question, context_length, depth_percent
-#                     )
-
-#                     while True:
-#                         text_id = str(uuid.uuid4())
-#                         if text_id not in generated_ids:
-#                             generated_ids.add(text_id)
-#                             break
-
-#                     dataset_dict["id"].append(text_id)
-#                     dataset_dict["prompt"].append(prompt)
-#                     dataset_dict["answer"].append(pass_key)
-#                     dataset_dict["context_length"].append(context_length)
-#                     dataset_dict["depth_percent"].append(depth_percent)
-
-#         dataset = Dataset.from_dict(dataset_dict)
-#         return dataset
-
-
-#     # Generate the dataset
-#     dataset = generate_dataset()
-
-#     # Save the dataset to disk
-#     dataset.save_to_disk("needle_in_a_hay_stack_finetuning_dataset")
-#     dataset.push_to_hub("nanotron/needle_in_a_hay_stack_finetuning_dataset")
-
-
-############################################################################################################
-
-# import glob
-# import os
-# import random
-# import uuid
-
-# import numpy as np
-# from datasets import Dataset
-# from transformers import AutoTokenizer
-
-# if __name__ == "__main__":
-#     def generate_needle_in_haystack_test(
-#         needle, haystack_dir, soft_prompt: str, retrieval_question, context_length, depth_percent
-#     ):
-#         def read_context_files():
-#             context = ""
-#             base_dir = os.path.abspath(os.path.dirname(__file__))  # Package directory
-#             files = glob.glob(os.path.join(base_dir, haystack_dir, "*.txt"))
-#             file_index = 0
-
-#             while len(tokenizer.encode(f"{soft_prompt} {context} {needle} \n\n{retrieval_question}")) < context_length:
-#                 with open(files[file_index], "r") as f:
-#                     context += f.read()
-#                 file_index = (file_index + 1) % len(files)
-
-#             return context
-
-#         def insert_needle(context):
-#             if depth_percent == 100:
-#                 # If depth percent is 100, place the needle at the end
-#                 new_context = context[: -len(needle)] + needle
-#             else:
-#                 # Get the position to insert the needle
-#                 insertion_point = int(len(context) * (depth_percent / 100))
-
-#                 # Find the nearest period to the insertion point
-#                 while context[insertion_point] != "." and insertion_point > 0:
-#                     insertion_point -= 1
-
-#                 # Insert the needle at the appropriate position
-#                 new_context = context[:insertion_point] + needle + context[insertion_point:]
-
-#             return new_context
-
-#         # Load up the haystack context
-#         context = read_context_files()
-
-#         # Insert the needle into the context at the specified depth percent
-#         context_with_needle = insert_needle(context)
-
-#         # Generate the prompt using the context with the needle
-#         prompt = f"{soft_prompt} {context_with_needle} \n\n{retrieval_question}"
-
-#         # Truncate the prompt to the desired context length
-#         prompt = tokenizer.decode(tokenizer.encode(prompt)[:context_length])
-
-#         return prompt, needle
-
-
-#     # Working example
-#     haystack_dir = "./"
-
-#     # Load the tokenizer
-#     tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
-
-
-#     def generate_dataset():
-#         num_prompts = 1
-#         soft_prompt = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there."
-#         context_lengths = [
-#             # 1024,
-#             # 2048,
-#             # 4096,
-#             # 8192,
-#             # 16384,
-#             32768,
-#             # 65536,
-#             # 131072,
-#             # 262144,
-#             # 524288,
-#             # 1048576,
-#         ]
-#         depth_percents = np.linspace(0, 100, num=21)
-
-#         dataset_dict = {"id": [], "prompt": [], "answer": [], "context_length": [], "depth_percent": []}
-#         generated_ids = set()
-
-#         for context_length in context_lengths:
-#             print(f"Generating prompts for context length: {context_length} \n")
-#             for depth_percent in depth_percents:
-#                 for _ in range(num_prompts):
-#                     pass_key = random.randint(10000, 50000)
-#                     needle = f"The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
-#                     retrieval_question = f"What is the pass key? The pass key is "
-
-#                     prompt, _ = generate_needle_in_haystack_test(
-#                         needle, haystack_dir, soft_prompt, retrieval_question, context_length, depth_percent
-#                     )
-
-#                     while True:
-#                         text_id = str(uuid.uuid4())
-#                         if text_id not in generated_ids:
-#                             generated_ids.add(text_id)
-#                             break
-
-#                     dataset_dict["id"].append(text_id)
-#                     dataset_dict["prompt"].append(prompt)
-#                     dataset_dict["answer"].append(pass_key)
-#                     dataset_dict["context_length"].append(context_length)
-#                     dataset_dict["depth_percent"].append(depth_percent)
-
-#         dataset = Dataset.from_dict(dataset_dict)
-#         return dataset
-
-
-#     # Generate the dataset
-#     dataset = generate_dataset()
-
-#     # Save the dataset to disk
-#     dataset.save_to_disk("needle_in_a_hay_stack_eval_dataset")
-#     dataset.push_to_hub("nanotron/needle_in_a_hay_stack_eval_dataset")
-
-
-# import glob
-# import os
-# import random
-# import uuid
-
-# import numpy as np
-# from datasets import Dataset
-# from transformers import AutoTokenizer
-
-# if __name__ == "__main__":
-#     def generate_needle_in_haystack_test(
-#         needle, haystack_dir, soft_prompt: str, retrieval_question, context_length, depth_percent
-#     ):
-#         def read_context_files():
-#             base_dir = os.path.abspath(os.path.dirname(__file__))  # Package directory
-#             files = glob.glob(os.path.join(base_dir, haystack_dir, "*.txt"))
-#             file_contents = []
-#             for file in files:
-#                 with open(file, "r") as f:
-#                     file_contents.append(f.read())
-#             return file_contents
-
-#         def insert_needle(context):
-#             if depth_percent == 100:
-#                 # If depth percent is 100, place the needle at the end
-#                 new_context = context[: -len(needle)] + needle
-#             else:
-#                 # Get the position to insert the needle
-#                 insertion_point = int(len(context) * (depth_percent / 100))
-
-#                 # Find the nearest period to the insertion point
-#                 while context[insertion_point] != "." and insertion_point > 0:
-#                     insertion_point -= 1
-
-#                 # Insert the needle at the appropriate position
-#                 new_context = context[:insertion_point] + needle + context[insertion_point:]
-
-#             return new_context
-
-#         # Load up the haystack context
-#         file_contents = read_context_files()
-#         context = "".join(file_contents)
-
-#         # Calculate the number of tokens for soft_prompt and retrieval_question
-#         soft_prompt_tokens = len(tokenizer.encode(soft_prompt))
-#         retrieval_question_tokens = len(tokenizer.encode(retrieval_question))
-
-#         # Calculate the remaining tokens for the context
-#         remaining_tokens = context_length - soft_prompt_tokens - retrieval_question_tokens
-
-#         # Repeat the context to make it long enough
-#         repeated_context = (context * ((remaining_tokens // len(tokenizer.encode(context))) + 1))[:remaining_tokens]
-
-#         # Insert the needle into the repeated context at the specified depth percent
-#         context_with_needle = insert_needle(repeated_context)
-
-#         # Generate the prompt using the context with the needle
-#         prompt = f"{soft_prompt} {context_with_needle} \n\n{retrieval_question}"
-
-#         return prompt, needle
-
-
-#     # Working example
-#     haystack_dir = "./"
-
-#     # Load the tokenizer
-#     tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
-
-
-#     def generate_dataset():
-#         num_prompts = 1
-#         soft_prompt = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there."
-#         context_lengths = [
-#             # 1024,
-#             # 2048,
-#             # 4096,
-#             # 8192,
-#             # 16384,
-#             32768,
-#             # 65536,
-#             # 131072,
-#             # 262144,
-#             # 524288,
-#             # 1048576,
-#         ]
-#         depth_percents = np.linspace(0, 100, num=21)
-
-#         dataset_dict = {"id": [], "prompt": [], "answer": [], "context_length": [], "depth_percent": []}
-#         generated_ids = set()
-
-#         for context_length in context_lengths:
-#             print(f"Generating prompts for context length: {context_length} \n")
-#             for depth_percent in depth_percents:
-#                 for _ in range(num_prompts):
-#                     pass_key = random.randint(10000, 50000)
-#                     needle = f"The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
-#                     retrieval_question = f"What is the pass key? The pass key is "
-
-#                     prompt, _ = generate_needle_in_haystack_test(
-#                         needle, haystack_dir, soft_prompt, retrieval_question, context_length, depth_percent
-#                     )
-
-#                     while True:
-#                         text_id = str(uuid.uuid4())
-#                         if text_id not in generated_ids:
-#                             generated_ids.add(text_id)
-#                             break
-
-#                     dataset_dict["id"].append(text_id)
-#                     dataset_dict["prompt"].append(prompt)
-#                     dataset_dict["answer"].append(pass_key)
-#                     dataset_dict["context_length"].append(context_length)
-#                     dataset_dict["depth_percent"].append(depth_percent)
-
-#         dataset = Dataset.from_dict(dataset_dict)
-#         return dataset
-
-
-#     # Generate the dataset
-#     dataset = generate_dataset()
-
-#     # Save the dataset to disk
-#     dataset.save_to_disk("needle_in_a_hay_stack_eval_dataset")
-#     dataset.push_to_hub("nanotron/needle_in_a_hay_stack_eval_dataset")
-
-import glob
-import os
-import random
-import uuid
-
-import numpy as np
-from datasets import Dataset
-from transformers import AutoTokenizer
-
-
-def token_length(tokenizer, text):
-    return len(tokenizer.encode(text)[:-1])  # -1 to exclude the EOS token
-
-
-def read_context_files(tokenizer, soft_prompt, retrieval_question, context_length):
-    context = ""
-    base_dir = os.path.abspath(os.path.dirname(__file__))
-    files = glob.glob(os.path.join(base_dir, haystack_dir, "*.txt"))
-    file_index = 0
-
-    target_context_length = (
-        context_length - token_length(tokenizer, soft_prompt) - token_length(tokenizer, retrieval_question)
-    )
-
-    while token_length(tokenizer, context) < target_context_length:
-        with open(files[file_index], "r") as f:
-            context += f.read()
-        file_index = (file_index + 1) % len(files)
-
-    return context
-
-
-def insert_needle(context, needle):
-    # Get the position to insert the needle
-    insertion_point = random.randint(0, len(context)) - len(needle)
-
-    # Insert the needle at the appropriate position
-    new_context = context[:insertion_point] + needle + context[insertion_point:]
-
-    return new_context
-
-
-def generate_needle_in_haystack_test(
-    needle, haystack_dir, soft_prompt: str, retrieval_question, context_length, depth_percent
-):
-    # Load up the haystack context
-    tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
-    context = read_context_files(tokenizer, soft_prompt, retrieval_question, context_length)
-
-    # Insert the needle into the context at the specified depth percent
-    context_with_needle = insert_needle(context, needle)
-
-    # Generate the prompt using the context with the needle
-    prompt = f"{soft_prompt} {context_with_needle} \n\n{retrieval_question}"
-
-    return prompt, needle
-
-
-if __name__ == "__main__":
-    haystack_dir = "./"
-
-    def generate_dataset():
-        num_prompts = 1
-        soft_prompt = "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there."
-        context_lengths = [
-            32768,
-        ]
-        depth_percents = np.linspace(0, 100, num=21)
-
-        dataset_dict = {"id": [], "prompt": [], "answer": [], "context_length": [], "depth_percent": []}
-        generated_ids = set()
-
-        for context_length in context_lengths:
-            print(f"Generating prompts for context length: {context_length} \n")
-            for depth_percent in depth_percents:
-                for _ in range(num_prompts):
-                    pass_key = random.randint(10000, 50000)
-                    needle = f"The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
-                    retrieval_question = "What is the pass key? The pass key is "
-
-                    prompt, _ = generate_needle_in_haystack_test(
-                        needle, haystack_dir, soft_prompt, retrieval_question, context_length, depth_percent
-                    )
-
-                    while True:
-                        text_id = str(uuid.uuid4())
-                        if text_id not in generated_ids:
-                            generated_ids.add(text_id)
-                            break
-
-                    dataset_dict["id"].append(text_id)
-                    dataset_dict["prompt"].append(prompt)
-                    dataset_dict["answer"].append(pass_key)
-                    dataset_dict["context_length"].append(context_length)
-                    dataset_dict["depth_percent"].append(depth_percent)
-
-        dataset = Dataset.from_dict(dataset_dict)
-        return dataset
-
-    # Generate the dataset
-    dataset = generate_dataset()
-
-    # Save the dataset to disk
-    dataset.save_to_disk("needle_in_a_hay_stack_eval_dataset")
-    dataset.push_to_hub("nanotron/needle_in_a_hay_stack_eval_dataset")

From dcbe86e83d99749ec0d6d49209c1d66347d71345 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Thu, 20 Jun 2024 07:29:19 +0000
Subject: [PATCH 33/43] refactor for generating finetuning data and run evals

---
 .../infinite-context-length/generate_data.py  | 45 ++++++++++++++-----
 examples/infinite-context-length/run_evals.py | 17 -------
 2 files changed, 33 insertions(+), 29 deletions(-)

diff --git a/examples/infinite-context-length/generate_data.py b/examples/infinite-context-length/generate_data.py
index 1ea1f051..e687d706 100644
--- a/examples/infinite-context-length/generate_data.py
+++ b/examples/infinite-context-length/generate_data.py
@@ -4,17 +4,13 @@
 import random
 import uuid
 
-from datasets import Dataset
+from datasets import Dataset, load_dataset
 from transformers import AutoTokenizer
 
 PROMPT = "{} {}. \n\n{}"
 
 
-def get_keys_in_train_set():
-    from datasets import load_dataset
-
-    dataset = load_dataset("nanotron/needle_32k_finetuning_dataset")
-
+def get_keys_in_train_set(dataset):
     unique_answers = set()
     for split in dataset.keys():
         for example in dataset[split]:
@@ -142,6 +138,9 @@ def get_args():
     parser.add_argument("--is_push_to_hub", type=bool, default=False)
     parser.add_argument("--is_exact_context_length", type=int, default=1)  # 1 is True, 0 is False
     parser.add_argument("--is_padding", type=int, default=1)  # 1 is True, 0 is False
+    parser.add_argument("--is_eval", type=int, default=1)  # 1 is True, 0 is False
+    parser.add_argument("--check_key_in_dataset", type=str, default=None)  # 1 is True, 0 is False
+    parser.add_argument("--save_path", type=str, required=True)  # 1 is True, 0 is False
     return parser.parse_args()
 
 
@@ -161,8 +160,23 @@ def get_args():
     # is_exact_context_length = args.is_exact_context_length
     is_exact_context_length = False if args.is_exact_context_length == 0 else True
     is_padding = False if args.is_padding == 0 else True
+    is_eval = False if args.is_eval == 0 else True
+    check_key_in_dataset = args.check_key_in_dataset
+    save_path = args.save_path
+
+    assert save_path is not None
 
-    gen_context_length = context_length if is_exact_context_length is True else context_length - random.randint(0, 700)
+    if check_key_in_dataset is not None:
+        eval_dataset = load_dataset(check_key_in_dataset)
+        eval_keys = get_keys_in_train_set(eval_dataset)
+
+    if context_length >= 2000:
+        # NOTE: don't minus short context
+        gen_context_length = (
+            context_length if is_exact_context_length is True else context_length - random.randint(0, 700)
+        )
+    else:
+        gen_context_length = context_length
 
     # NOTE: depth_percent + 1 to avoid 0
     RANGE = 500
@@ -196,12 +210,19 @@ def generate_dataset():
             while True:
                 pass_key = random.randint(start_range, end_range)
                 if pass_key not in generated_pass_keys:
+                    if check_key_in_dataset is not None:
+                        if str(pass_key) in eval_keys:
+                            continue
+
                     generated_pass_keys.add(pass_key)
                     break
 
             needle_prompt = f". The pass key is {pass_key}. Remember it. {pass_key} is the pass key. "
-            # retrieval_question = f"What is the pass key? The pass key is {pass_key}"
-            retrieval_question = "What is the pass key? The pass key is "
+
+            if is_eval is True:
+                retrieval_question = "What is the pass key? The pass key is "
+            else:
+                retrieval_question = f"What is the pass key? The pass key is {pass_key}."
 
             prompt = generate_needle_in_haystack_test(
                 needle=pass_key,
@@ -235,7 +256,7 @@ def generate_dataset():
 
     # Save the dataset to disk
     dataset.save_to_disk(
-        f"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/eval_data/needle_eval_and_{context_length}_ctx_and_depth_{depth_percent}_and_id_{id}"
+        f"{save_path}/needle_finetune_data_and_{context_length}_ctx_and_depth_{depth_percent}_and_id_{id}"
     )
-    if is_push_to_hub:
-        dataset.push_to_hub("nanotron/llama3-16k-passkey-retrieval-eval")
+    # if is_push_to_hub:
+    #     dataset.push_to_hub("nanotron/llama3-16k-passkey-retrieval-eval")
diff --git a/examples/infinite-context-length/run_evals.py b/examples/infinite-context-length/run_evals.py
index 98f18e20..90032b2e 100644
--- a/examples/infinite-context-length/run_evals.py
+++ b/examples/infinite-context-length/run_evals.py
@@ -2815,23 +2815,6 @@ def main():
         dataset = dataset.filter(lambda x: x["context_length"] == 32768 and x["depth_percent"] == depth_percent)
         df = df.filter(lambda x: x["context_length"] == 32768 and x["depth_percent"] == depth_percent)
 
-        # # Filter and select the first 2 samples for each unique 'depth_percent' value
-        # dataset = dataset.group_by("depth_percent").select(keep_from_disk=True, indices=lambda group: group[:2])
-        # df = df.group_by("depth_percent").select(keep_from_disk=True, indices=lambda group: group[:2])
-
-        # # NOTE: only take 2 sample for each unique depth_percent
-        # dataset = dataset.groupby('depth_percent').head(2)
-        # df = df.groupby('depth_percent').head(2)
-
-        # dataset = dataset.select(range(len(dataset)-1, -1, -1))
-        # df = df.select(range(len(df)-1, -1, -1))
-
-        # nOTE: only take 10 samples
-        # dataset = dataset.select(range(10))
-        # df = df.select(range(10))
-
-        # NOTE: now reverse these dataset
-
         dataloader = torch.utils.data.DataLoader(dataset, batch_size=1, shuffle=False)
 
         df.set_format("pandas")

From a6b8b5eca6edd79e42356f23b46f0004f123dad8 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Tue, 25 Jun 2024 06:38:39 +0000
Subject: [PATCH 34/43] add debugging

---
 .../data/exp34/debug_weights.py               | 310 ++++++++++++++++++
 1 file changed, 310 insertions(+)
 create mode 100644 examples/infinite-context-length/data/exp34/debug_weights.py

diff --git a/examples/infinite-context-length/data/exp34/debug_weights.py b/examples/infinite-context-length/data/exp34/debug_weights.py
new file mode 100644
index 00000000..e7d3234b
--- /dev/null
+++ b/examples/infinite-context-length/data/exp34/debug_weights.py
@@ -0,0 +1,310 @@
+import os
+
+import gradio as gr
+import numpy as np
+import torch
+
+
+def load_folder_structure(root_dir):
+    folder_structure = {}
+    for step_dir in sorted(os.listdir(root_dir), key=lambda x: int(x)):
+        step = int(step_dir)
+        step_path = os.path.join(root_dir, step_dir)
+        folder_structure[step] = []
+        for folder in os.listdir(step_path):
+            if os.path.isdir(os.path.join(step_path, folder)):
+                folder_structure[step].append(folder)
+    return folder_structure
+
+
+def load_tensors(root_dir, selected_steps, selected_folders):
+    tensors = {}
+    for step in selected_steps:
+        step_dir = os.path.join(root_dir, str(step))
+        for folder in selected_folders:
+            folder_path = os.path.join(step_dir, folder)
+            if os.path.isdir(folder_path):
+                for tensor_file in os.listdir(folder_path):
+                    tensor_name = os.path.splitext(tensor_file)[0]
+                    tensor_path = os.path.join(folder_path, tensor_file)
+
+                    # Load the tensor
+                    tensor = torch.load(tensor_path)
+
+                    # Calculate mean and standard deviation
+                    if not isinstance(tensor, torch.Tensor):
+                        continue
+
+                    mean = tensor.mean().item()
+                    std = tensor.std().item()
+
+                    if tensor_name not in tensors:
+                        tensors[tensor_name] = {"steps": [], "means": [], "stds": []}
+
+                    tensors[tensor_name]["steps"].append(step)
+                    tensors[tensor_name]["means"].append(mean)
+                    tensors[tensor_name]["stds"].append(std)
+    return tensors
+
+
+def create_gradio_interface():
+    def update_steps(root_dir):
+        folder_structure = load_folder_structure(root_dir)
+        steps = list(folder_structure.keys())
+        return gr.Dropdown(choices=steps, multiselect=True, value=steps)
+
+    def update_folders(root_dir, selected_steps):
+        folder_structure = load_folder_structure(root_dir)
+        folders = set()
+        for step in selected_steps:
+            folders.update(folder_structure[step])
+        return gr.Dropdown(choices=list(folders), multiselect=True, value=list(folders))
+
+    def update_tensor_names(root_dir, selected_steps, selected_folders):
+        tensors = load_tensors(root_dir, selected_steps, selected_folders)
+        tensor_names = list(tensors.keys())
+        default_tensor = np.random.choice(tensor_names) if tensor_names else None
+        return gr.Dropdown(choices=tensor_names, multiselect=True, value=[default_tensor] if default_tensor else [])
+
+    def update_line_plot(root_dir, selected_steps, selected_folders, selected_tensors, show_std):
+        tensors = load_tensors(root_dir, selected_steps, selected_folders)
+
+        fig = go.Figure()
+
+        all_means = []
+        for tensor_name in selected_tensors:
+            if tensor_name in tensors:
+                data = tensors[tensor_name]
+                steps = data["steps"]
+                means = data["means"]
+                stds = data["stds"]
+                all_means.extend(means)
+
+                fig.add_trace(
+                    go.Scatter(
+                        x=steps,
+                        y=means,
+                        mode="lines+markers",
+                        name=tensor_name,
+                        line={"width": 2},
+                        hovertemplate="Step: %{x}<br>Mean: %{y:.4f}<br>Std: %{text:.4f}<extra></extra>",
+                        text=stds,
+                    )
+                )
+
+                if show_std:
+                    fig.add_trace(
+                        go.Scatter(
+                            x=steps + steps[::-1],
+                            y=[m + s for m, s in zip(means, stds)] + [m - s for m, s in zip(means[::-1], stds[::-1])],
+                            fill="toself",
+                            fillcolor="rgba(0,100,80,0.2)",
+                            line={"color": "rgba(255,255,255,0)"},
+                            hoverinfo="skip",
+                            showlegend=False,
+                            name=tensor_name + " Std Dev",
+                        )
+                    )
+
+        fig.update_layout(
+            title="Tensor Means and Variances Across Training Steps",
+            xaxis_title="Training Step",
+            yaxis_title="Mean of Tensors",
+            hovermode="x unified",
+            legend_title="Tensor Names",
+        )
+
+        # Adjust y-axis range to focus on the trend
+        if all_means:
+            y_mean = np.mean(all_means)
+            y_std = np.std(all_means)
+            y_range = [y_mean - 3 * y_std, y_mean + 3 * y_std]
+            fig.update_yaxes(range=y_range)
+
+        return fig
+
+    import plotly.graph_objects as go
+
+    def update_plots(root_dir, selected_steps, selected_folders, selected_tensors, exp_min, exp_max):
+        if not selected_tensors:
+            return None, None, "No tensors selected", None
+
+        tensors = load_tensors(root_dir, selected_steps, selected_folders)
+
+        all_values = {}
+        for step in selected_steps:
+            all_values[step] = []
+            for tensor_name in selected_tensors:
+                if tensor_name in tensors:
+                    step_dir = os.path.join(root_dir, str(step))
+                    for folder in selected_folders:
+                        tensor_path = os.path.join(step_dir, folder, f"{tensor_name}.pt")
+                        if os.path.exists(tensor_path):
+                            tensor = torch.load(tensor_path)
+                            all_values[step].extend(tensor.flatten().tolist())
+
+        if not all_values:
+            return None, None, "No data available", None
+
+        # Create histogram with slider
+        hist_fig = go.Figure()
+
+        max_hist_value = 0
+        for step in selected_steps:
+            values = np.array(all_values[step])
+            hist, bin_edges = np.histogram(values, bins=50)
+            hist_fig.add_trace(go.Bar(x=bin_edges[:-1], y=hist, name=f"Step {step}", visible=False))
+            max_hist_value = max(max_hist_value, np.max(hist))
+
+        # Make the first trace visible
+        hist_fig.data[0].visible = True
+
+        # Create and add slider
+        steps = []
+        for i, step in enumerate(selected_steps):
+            step = {
+                "method": "update",
+                "args": [
+                    {"visible": [False] * len(hist_fig.data)},
+                    {"title": f"Distribution of Tensor Values (Step {step})"},
+                ],
+                "label": str(step),
+            }
+            step["args"][0]["visible"][i] = True  # Toggle i'th trace to "visible"
+            steps.append(step)
+
+        sliders = [{"active": 0, "currentvalue": {"prefix": "Step: "}, "pad": {"t": 50}, "steps": steps}]
+
+        hist_fig.update_layout(
+            sliders=sliders,
+            xaxis_title="Tensor Values",
+            yaxis_title="Frequency",
+            bargap=0.1,
+        )
+
+        # Auto-zoom for histogram
+        all_values_flat = np.concatenate(list(all_values.values()))
+        q1, q3 = np.percentile(all_values_flat, [25, 75])
+        iqr = q3 - q1
+        lower_bound = q1 - 1.5 * iqr
+        upper_bound = q3 + 1.5 * iqr
+        hist_fig.update_yaxes(range=[0, max_hist_value * 1.1])
+        hist_fig.update_xaxes(range=[lower_bound, upper_bound])
+
+        # Create scatter plot (unchanged)
+        scatter_fig = go.Figure()
+        for step, values in all_values.items():
+            scatter_fig.add_trace(
+                go.Scatter(
+                    x=np.arange(len(values)),
+                    y=values,
+                    mode="markers",
+                    marker={"size": 2, "opacity": 0.5},
+                    name=f"Step {step}",
+                )
+            )
+        scatter_fig.update_layout(
+            title="Scatter Plot of Tensor Values",
+            xaxis_title="Index",
+            yaxis_title="Tensor Value",
+        )
+        scatter_fig.update_yaxes(range=[lower_bound, upper_bound])
+
+        # Calculate percentages for the first step (you might want to adjust this)
+        first_step = selected_steps[0]
+        current_values = np.array(all_values[first_step])
+        total = len(current_values)
+        within_range = np.sum((current_values >= exp_min) & (current_values <= exp_max))
+        below_min = np.sum(current_values < exp_min)
+        above_max = np.sum(current_values > exp_max)
+
+        percentage_text = f"""
+        Step {first_step}:
+        Within range [{exp_min}, {exp_max}]: {within_range/total*100:.2f}%
+        Below {exp_min}: {below_min/total*100:.2f}%
+        Above {exp_max}: {above_max/total*100:.2f}%
+        """
+
+        # Create distribution table data for the first step
+        hist, bin_edges = np.histogram(current_values, bins=50)
+        table_data = []
+        for i in range(len(hist)):
+            range_start = bin_edges[i]
+            range_end = bin_edges[i + 1]
+            count = hist[i]
+            percentage = count / total * 100
+            table_data.append([f"{range_start:.4f} - {range_end:.4f}", f"{percentage:.2f}%", f"{count}"])
+
+        return hist_fig, scatter_fig, percentage_text, table_data
+
+    with gr.Blocks() as iface:
+        gr.Markdown("# Neural Networks Debugging Tool")
+
+        with gr.Row():
+            root_dir_input = gr.Textbox(label="Root Directory")
+
+        with gr.Row():
+            step_dropdown = gr.Dropdown(multiselect=True, label="Select Training Steps")
+
+        with gr.Row():
+            folder_dropdown = gr.Dropdown(multiselect=True, label="Select Folders")
+
+        with gr.Row():
+            tensor_dropdown = gr.Dropdown(multiselect=True, label="Select Tensors to Display")
+
+        with gr.Row():
+            show_std = gr.Checkbox(label="Show Standard Deviation", value=True)
+            update_line_plot_button = gr.Button("Update Line Plot")
+
+        with gr.Row():
+            line_plot_output = gr.Plot()
+
+        with gr.Row():
+            with gr.Column(scale=1):
+                exp_min = gr.Number(label="Expected Minimum")
+                exp_max = gr.Number(label="Expected Maximum")
+                percentage_output = gr.Textbox(label="Value Distribution")
+                update_plots_button = gr.Button("Update Plots")
+            with gr.Column(scale=2):
+                with gr.Tabs():
+                    with gr.TabItem("Distribution of Tensor Values"):
+                        histogram_output = gr.Plot()
+                    with gr.TabItem("Scatter Plot of Tensor Values"):
+                        scatter_output = gr.Plot()
+
+        with gr.Row():
+            distribution_table = gr.Dataframe(headers=["Range", "Percentage", "Count"], label="Distribution Table")
+
+        root_dir_input.change(fn=update_steps, inputs=[root_dir_input], outputs=[step_dropdown])
+
+        step_dropdown.change(fn=update_folders, inputs=[root_dir_input, step_dropdown], outputs=[folder_dropdown])
+
+        folder_dropdown.change(
+            fn=update_tensor_names, inputs=[root_dir_input, step_dropdown, folder_dropdown], outputs=[tensor_dropdown]
+        )
+
+        update_line_plot_button.click(
+            fn=update_line_plot,
+            inputs=[root_dir_input, step_dropdown, folder_dropdown, tensor_dropdown, show_std],
+            outputs=[line_plot_output],
+        )
+
+        # Add this new event handler
+        show_std.change(
+            fn=update_line_plot,
+            inputs=[root_dir_input, step_dropdown, folder_dropdown, tensor_dropdown, show_std],
+            outputs=[line_plot_output],
+        )
+
+        update_plots_button.click(
+            fn=update_plots,
+            inputs=[root_dir_input, step_dropdown, folder_dropdown, tensor_dropdown, exp_min, exp_max],
+            outputs=[histogram_output, scatter_output, percentage_output, distribution_table],
+        )
+
+    return iface
+
+
+# Usage
+iface = create_gradio_interface()
+iface.launch(share=True, debug=True)

From 15fd9dd109e0fb23958d50ea88b723a0db093c72 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Tue, 25 Jun 2024 11:17:09 +0000
Subject: [PATCH 35/43] add l2 nor, kurtosis, abmax, weight update magnitude

---
 .../data/exp34/debug_weights.py               | 317 +++++++++++++++---
 1 file changed, 269 insertions(+), 48 deletions(-)

diff --git a/examples/infinite-context-length/data/exp34/debug_weights.py b/examples/infinite-context-length/data/exp34/debug_weights.py
index e7d3234b..0df7df28 100644
--- a/examples/infinite-context-length/data/exp34/debug_weights.py
+++ b/examples/infinite-context-length/data/exp34/debug_weights.py
@@ -2,9 +2,17 @@
 
 import gradio as gr
 import numpy as np
+import plotly.graph_objects as go
 import torch
 
 
+def calculate_kurtosis(tensor):
+    s = torch.sqrt(torch.mean(tensor**2, dim=0))
+    m2 = torch.mean(s**2)
+    m4 = torch.mean(s**4)
+    return (m4 / (m2**2)).item()
+
+
 def load_folder_structure(root_dir):
     folder_structure = {}
     for step_dir in sorted(os.listdir(root_dir), key=lambda x: int(x)):
@@ -17,8 +25,8 @@ def load_folder_structure(root_dir):
     return folder_structure
 
 
-def load_tensors(root_dir, selected_steps, selected_folders):
-    tensors = {}
+def get_tensor_names(root_dir, selected_steps, selected_folders):
+    tensor_names = set()
     for step in selected_steps:
         step_dir = os.path.join(root_dir, str(step))
         for folder in selected_folders:
@@ -26,24 +34,43 @@ def load_tensors(root_dir, selected_steps, selected_folders):
             if os.path.isdir(folder_path):
                 for tensor_file in os.listdir(folder_path):
                     tensor_name = os.path.splitext(tensor_file)[0]
-                    tensor_path = os.path.join(folder_path, tensor_file)
+                    tensor_names.add(tensor_name)
+    return list(tensor_names)
 
-                    # Load the tensor
-                    tensor = torch.load(tensor_path)
 
-                    # Calculate mean and standard deviation
-                    if not isinstance(tensor, torch.Tensor):
-                        continue
-
-                    mean = tensor.mean().item()
-                    std = tensor.std().item()
-
-                    if tensor_name not in tensors:
-                        tensors[tensor_name] = {"steps": [], "means": [], "stds": []}
-
-                    tensors[tensor_name]["steps"].append(step)
-                    tensors[tensor_name]["means"].append(mean)
-                    tensors[tensor_name]["stds"].append(std)
+def load_selected_tensors(root_dir, selected_steps, selected_folders, selected_tensors):
+    tensors = {}
+    for step in selected_steps:
+        step_dir = os.path.join(root_dir, str(step))
+        for folder in selected_folders:
+            folder_path = os.path.join(step_dir, folder)
+            if os.path.isdir(folder_path):
+                for tensor_name in selected_tensors:
+                    tensor_file = f"{tensor_name}.pt"
+                    tensor_path = os.path.join(folder_path, tensor_file)
+                    if os.path.exists(tensor_path):
+                        tensor = torch.load(tensor_path)
+                        if isinstance(tensor, torch.Tensor):
+                            mean = tensor.mean().item()
+                            std = tensor.std().item()
+                            l2_norm = torch.norm(tensor, p=2).item()
+                            kurtosis = calculate_kurtosis(tensor)
+                            abs_max = torch.abs(tensor).max().item()  # Add absolute maximum calculation
+                            if tensor_name not in tensors:
+                                tensors[tensor_name] = {
+                                    "steps": [],
+                                    "means": [],
+                                    "stds": [],
+                                    "l2_norms": [],
+                                    "kurtosis": [],
+                                    "abs_max": [],
+                                }
+                            tensors[tensor_name]["steps"].append(step)
+                            tensors[tensor_name]["means"].append(mean)
+                            tensors[tensor_name]["stds"].append(std)
+                            tensors[tensor_name]["l2_norms"].append(l2_norm)
+                            tensors[tensor_name]["kurtosis"].append(kurtosis)
+                            tensors[tensor_name]["abs_max"].append(abs_max)  # Add absolute maximum to the dictionary
     return tensors
 
 
@@ -61,13 +88,12 @@ def update_folders(root_dir, selected_steps):
         return gr.Dropdown(choices=list(folders), multiselect=True, value=list(folders))
 
     def update_tensor_names(root_dir, selected_steps, selected_folders):
-        tensors = load_tensors(root_dir, selected_steps, selected_folders)
-        tensor_names = list(tensors.keys())
+        tensor_names = get_tensor_names(root_dir, selected_steps, selected_folders)
         default_tensor = np.random.choice(tensor_names) if tensor_names else None
         return gr.Dropdown(choices=tensor_names, multiselect=True, value=[default_tensor] if default_tensor else [])
 
-    def update_line_plot(root_dir, selected_steps, selected_folders, selected_tensors, show_std):
-        tensors = load_tensors(root_dir, selected_steps, selected_folders)
+    def update_mean_variance_plot(root_dir, selected_steps, selected_folders, selected_tensors, show_std):
+        tensors = load_selected_tensors(root_dir, selected_steps, selected_folders, selected_tensors)
 
         fig = go.Figure()
 
@@ -114,7 +140,6 @@ def update_line_plot(root_dir, selected_steps, selected_folders, selected_tensor
             legend_title="Tensor Names",
         )
 
-        # Adjust y-axis range to focus on the trend
         if all_means:
             y_mean = np.mean(all_means)
             y_std = np.std(all_means)
@@ -123,25 +148,199 @@ def update_line_plot(root_dir, selected_steps, selected_folders, selected_tensor
 
         return fig
 
-    import plotly.graph_objects as go
+    def update_l2_norm_plot(root_dir, selected_steps, selected_folders, selected_tensors):
+        tensors = load_selected_tensors(root_dir, selected_steps, selected_folders, selected_tensors)
+
+        fig = go.Figure()
+
+        all_l2_norms = []
+        for tensor_name in selected_tensors:
+            if tensor_name in tensors:
+                data = tensors[tensor_name]
+                steps = data["steps"]
+                l2_norms = data["l2_norms"]
+                all_l2_norms.extend(l2_norms)
+
+                fig.add_trace(
+                    go.Scatter(
+                        x=steps,
+                        y=l2_norms,
+                        mode="lines+markers",
+                        name=tensor_name,
+                        line={"width": 2},
+                        hovertemplate="Step: %{x}<br>L2 Norm: %{y:.4f}<extra></extra>",
+                    )
+                )
+
+        fig.update_layout(
+            title="Tensor L2 Norms Across Training Steps",
+            xaxis_title="Training Step",
+            yaxis_title="L2 Norm of Tensors",
+            hovermode="x unified",
+            legend_title="Tensor Names",
+        )
+
+        if all_l2_norms:
+            y_mean = np.mean(all_l2_norms)
+            y_std = np.std(all_l2_norms)
+            y_range = [y_mean - 3 * y_std, y_mean + 3 * y_std]
+            fig.update_yaxes(range=y_range)
+
+        return fig
+
+    def update_kurtosis_plot(root_dir, selected_steps, selected_folders, selected_tensors):
+        tensors = load_selected_tensors(root_dir, selected_steps, selected_folders, selected_tensors)
+
+        fig = go.Figure()
+
+        all_kurtosis = []
+        for tensor_name in selected_tensors:
+            if tensor_name in tensors:
+                data = tensors[tensor_name]
+                steps = data["steps"]
+                kurtosis = data["kurtosis"]
+                all_kurtosis.extend(kurtosis)
+
+                fig.add_trace(
+                    go.Scatter(
+                        x=steps,
+                        y=kurtosis,
+                        mode="lines+markers",
+                        name=tensor_name,
+                        line={"width": 2},
+                        hovertemplate="Step: %{x}<br>Kurtosis: %{y:.4f}<extra></extra>",
+                    )
+                )
+
+        fig.update_layout(
+            title="Tensor Kurtosis Across Training Steps",
+            xaxis_title="Training Step",
+            yaxis_title="Kurtosis of Tensors",
+            hovermode="x unified",
+            legend_title="Tensor Names",
+        )
+
+        if all_kurtosis:
+            y_mean = np.mean(all_kurtosis)
+            y_std = np.std(all_kurtosis)
+            y_range = [max(0, y_mean - 3 * y_std), y_mean + 3 * y_std]
+            fig.update_yaxes(range=y_range)
+
+        return fig
+
+    def update_abs_max_plot(root_dir, selected_steps, selected_folders, selected_tensors):
+        tensors = load_selected_tensors(root_dir, selected_steps, selected_folders, selected_tensors)
+
+        fig = go.Figure()
+
+        all_abs_max = []
+        for tensor_name in selected_tensors:
+            if tensor_name in tensors:
+                data = tensors[tensor_name]
+                steps = data["steps"]
+                abs_max = data["abs_max"]
+                all_abs_max.extend(abs_max)
+
+                fig.add_trace(
+                    go.Scatter(
+                        x=steps,
+                        y=abs_max,
+                        mode="lines+markers",
+                        name=tensor_name,
+                        line={"width": 2},
+                        hovertemplate="Step: %{x}<br>Absolute Max: %{y:.4f}<extra></extra>",
+                    )
+                )
+
+        fig.update_layout(
+            title="Tensor Absolute Maximum Values Across Training Steps",
+            xaxis_title="Training Step",
+            yaxis_title="Absolute Maximum of Tensors",
+            hovermode="x unified",
+            legend_title="Tensor Names",
+        )
+
+        if all_abs_max:
+            y_mean = np.mean(all_abs_max)
+            y_std = np.std(all_abs_max)
+            y_range = [max(0, y_mean - 3 * y_std), y_mean + 3 * y_std]
+            fig.update_yaxes(range=y_range)
+
+        return fig
+
+    def update_weight_update_plot(root_dir, selected_steps, selected_folders, selected_tensors, learning_rate):
+        tensors = load_selected_tensors(root_dir, selected_steps, selected_folders, selected_tensors)
+
+        fig = go.Figure()
+        all_magnitudes = []
+        missing_grads = set()
+
+        for tensor_name in selected_tensors:
+            if tensor_name.endswith(".weight"):
+                grad_name = tensor_name.replace(".weight", ".weight.grad")
+                if tensor_name in tensors and grad_name in tensors:
+                    weight_data = tensors[tensor_name]
+                    grad_data = tensors[grad_name]
+
+                    steps = weight_data["steps"]
+                    weights = torch.tensor(weight_data["l2_norms"])
+                    grads = torch.tensor(grad_data["l2_norms"])
+
+                    magnitudes = (grads * learning_rate) / weights
+                    if isinstance(magnitudes, (float, int)):
+                        all_magnitudes.append(magnitudes)
+                    else:
+                        all_magnitudes.extend(magnitudes.tolist())
+
+                    fig.add_trace(
+                        go.Scatter(
+                            x=steps,
+                            y=magnitudes if isinstance(magnitudes, (float, int)) else magnitudes.tolist(),
+                            mode="lines+markers",
+                            name=tensor_name,
+                            line={"width": 2},
+                            hovertemplate="Step: %{x}<br>Magnitude: %{y:.2e}<extra></extra>",
+                        )
+                    )
+                else:
+                    if grad_name not in tensors:
+                        missing_grads.add(grad_name)
+
+        fig.update_layout(
+            title="Magnitude of Weight Updates Across Training Steps",
+            xaxis_title="Training Step",
+            yaxis_title="Magnitude of Weight Update",
+            hovermode="x unified",
+            legend_title="Tensor Names",
+            yaxis={"tickformat": ".2e", "exponentformat": "e"},
+        )
+
+        if all_magnitudes:
+            y_mean = np.mean(all_magnitudes)
+            y_std = np.std(all_magnitudes)
+            y_range = [max(0, y_mean - 3 * y_std), y_mean + 3 * y_std]
+            fig.update_yaxes(range=y_range)
+
+        notification = ""
+        if missing_grads:
+            notification = f"Please select the following gradients: {', '.join(missing_grads)}"
+
+        return fig, notification
 
     def update_plots(root_dir, selected_steps, selected_folders, selected_tensors, exp_min, exp_max):
         if not selected_tensors:
             return None, None, "No tensors selected", None
 
-        tensors = load_tensors(root_dir, selected_steps, selected_folders)
-
         all_values = {}
         for step in selected_steps:
             all_values[step] = []
             for tensor_name in selected_tensors:
-                if tensor_name in tensors:
-                    step_dir = os.path.join(root_dir, str(step))
-                    for folder in selected_folders:
-                        tensor_path = os.path.join(step_dir, folder, f"{tensor_name}.pt")
-                        if os.path.exists(tensor_path):
-                            tensor = torch.load(tensor_path)
-                            all_values[step].extend(tensor.flatten().tolist())
+                step_dir = os.path.join(root_dir, str(step))
+                for folder in selected_folders:
+                    tensor_path = os.path.join(step_dir, folder, f"{tensor_name}.pt")
+                    if os.path.exists(tensor_path):
+                        tensor = torch.load(tensor_path)
+                        all_values[step].extend(tensor.flatten().tolist())
 
         if not all_values:
             return None, None, "No data available", None
@@ -156,10 +355,8 @@ def update_plots(root_dir, selected_steps, selected_folders, selected_tensors, e
             hist_fig.add_trace(go.Bar(x=bin_edges[:-1], y=hist, name=f"Step {step}", visible=False))
             max_hist_value = max(max_hist_value, np.max(hist))
 
-        # Make the first trace visible
         hist_fig.data[0].visible = True
 
-        # Create and add slider
         steps = []
         for i, step in enumerate(selected_steps):
             step = {
@@ -170,7 +367,7 @@ def update_plots(root_dir, selected_steps, selected_folders, selected_tensors, e
                 ],
                 "label": str(step),
             }
-            step["args"][0]["visible"][i] = True  # Toggle i'th trace to "visible"
+            step["args"][0]["visible"][i] = True
             steps.append(step)
 
         sliders = [{"active": 0, "currentvalue": {"prefix": "Step: "}, "pad": {"t": 50}, "steps": steps}]
@@ -191,7 +388,7 @@ def update_plots(root_dir, selected_steps, selected_folders, selected_tensors, e
         hist_fig.update_yaxes(range=[0, max_hist_value * 1.1])
         hist_fig.update_xaxes(range=[lower_bound, upper_bound])
 
-        # Create scatter plot (unchanged)
+        # Create scatter plot
         scatter_fig = go.Figure()
         for step, values in all_values.items():
             scatter_fig.add_trace(
@@ -210,7 +407,7 @@ def update_plots(root_dir, selected_steps, selected_folders, selected_tensors, e
         )
         scatter_fig.update_yaxes(range=[lower_bound, upper_bound])
 
-        # Calculate percentages for the first step (you might want to adjust this)
+        # Calculate percentages for the first step
         first_step = selected_steps[0]
         current_values = np.array(all_values[first_step])
         total = len(current_values)
@@ -254,10 +451,22 @@ def update_plots(root_dir, selected_steps, selected_folders, selected_tensors, e
 
         with gr.Row():
             show_std = gr.Checkbox(label="Show Standard Deviation", value=True)
-            update_line_plot_button = gr.Button("Update Line Plot")
+            update_line_plots_button = gr.Button("Update Line Plots")
 
         with gr.Row():
-            line_plot_output = gr.Plot()
+            with gr.Tabs():
+                with gr.TabItem("Mean and Variance"):
+                    mean_variance_plot_output = gr.Plot()
+                with gr.TabItem("L2 Norm"):
+                    l2_norm_plot_output = gr.Plot()
+                with gr.TabItem("Kurtosis"):
+                    kurtosis_plot_output = gr.Plot()
+                with gr.TabItem("Absolute Maximum"):
+                    abs_max_plot_output = gr.Plot()
+                with gr.TabItem("Weight Update Magnitude"):
+                    weight_update_notification = gr.Textbox(label="Notification")
+                    learning_rate = gr.Number(label="Learning Rate", value=0.001)
+                    weight_update_plot_output = gr.Plot()
 
         with gr.Row():
             with gr.Column(scale=1):
@@ -283,17 +492,29 @@ def update_plots(root_dir, selected_steps, selected_folders, selected_tensors, e
             fn=update_tensor_names, inputs=[root_dir_input, step_dropdown, folder_dropdown], outputs=[tensor_dropdown]
         )
 
-        update_line_plot_button.click(
-            fn=update_line_plot,
+        show_std.change(
+            fn=update_mean_variance_plot,
             inputs=[root_dir_input, step_dropdown, folder_dropdown, tensor_dropdown, show_std],
-            outputs=[line_plot_output],
+            outputs=[mean_variance_plot_output],
         )
 
-        # Add this new event handler
-        show_std.change(
-            fn=update_line_plot,
-            inputs=[root_dir_input, step_dropdown, folder_dropdown, tensor_dropdown, show_std],
-            outputs=[line_plot_output],
+        update_line_plots_button.click(
+            fn=lambda *args: (
+                update_mean_variance_plot(*args[:5]),
+                update_l2_norm_plot(*args[:4]),
+                update_kurtosis_plot(*args[:4]),
+                update_abs_max_plot(*args[:4]),
+                *update_weight_update_plot(*args[:4], args[5]),
+            ),
+            inputs=[root_dir_input, step_dropdown, folder_dropdown, tensor_dropdown, show_std, learning_rate],
+            outputs=[
+                mean_variance_plot_output,
+                l2_norm_plot_output,
+                kurtosis_plot_output,
+                abs_max_plot_output,
+                weight_update_plot_output,
+                weight_update_notification,
+            ],
         )
 
         update_plots_button.click(

From 9ef1f4c2daf643a59b18c151cf2cd5c6c8717e26 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Fri, 28 Jun 2024 07:50:09 +0000
Subject: [PATCH 36/43] each segment in the attention layer uses the same
 balance factors

---
 src/nanotron/models/llama.py | 200 +++++++++++++++++++++++++++++------
 1 file changed, 169 insertions(+), 31 deletions(-)

diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index c9dc5b15..6f7fbaf4 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -46,21 +46,29 @@
 logger = logging.get_logger(__name__)
 
 
-def compute_stas(tensor):
+def compute_stas(tensor, log_tensor: bool = False, save_tensor: bool = False):
     if tensor is None:
         tensor = torch.zeros(
             1,
         )
 
-    return {
-        "mean": tensor.mean().item(),
-        # "std": tensor.std().item(),
+    logs = {
+        "mean": tensor.detach().mean().item(),
+        "std": tensor.detach().std().item(),
         # "var": tensor.var().item(),
-        # "norm": tensor.norm().item(),
+        "norm": tensor.norm().item(),
         # "min": tensor.min().item(),
         # "max": tensor.max().item(),
-        "amax": tensor.detach().cpu().abs().max().item(),
+        "amax": tensor.detach().abs().max().item(),
     }
+    # if log_tensor:
+    #     import torchshow as ts
+    #     import wandb
+    #     data = tensor.detach().cpu().tolist()
+    #     data = [[s] for s in data]
+    #     logs["data"] = wandb.plot.histogram(wandb.Table(data=data, columns=["value"]), "values", title="DATA")
+
+    return logs
 
 
 def convert_logs_to_flat_logs(logs, prefix):
@@ -73,6 +81,72 @@ def convert_logs_to_flat_logs(logs, prefix):
     return flat_logs
 
 
+def rotate_half(x):
+    """Rotates half the hidden dims of the input."""
+    x1 = x[..., : x.shape[-1] // 2]
+    x2 = x[..., x.shape[-1] // 2 :]
+    return torch.cat((-x2, x1), dim=-1)
+
+
+### llama
+class LlamaRotaryEmbedding(nn.Module):
+    def __init__(self, dim: int, end: int, theta: float = 500000.0):
+        super().__init__()
+        self.dim = dim
+        self.end = end
+        self.theta = theta
+        self.init_rotary_embeddings()
+
+    def init_rotary_embeddings(self):
+        inv_freq = 1.0 / (self.theta ** (torch.arange(0, self.dim, 2, dtype=torch.float, device="cuda") / self.dim))
+        self.register_buffer("inv_freq", inv_freq, persistent=False)
+
+    @torch.no_grad()
+    def forward(
+        self,
+        x: torch.Tensor,  # [batch_size, seq_length, num_heads, d_qk]
+        position_ids: Optional[torch.LongTensor],  # [batch_size, seq_length]
+    ):
+        # x: [bs, num_attention_heads, seq_len, head_size]
+        # print("rotary")
+        inv_freq_expanded = self.inv_freq[None, :, None].float().expand(position_ids.shape[0], -1, 1)
+        position_ids_expanded = position_ids[:, None, :].float()
+        # Force float32 since bfloat16 loses precision on long contexts
+        # See https://github.com/huggingface/transformers/pull/29285
+        device_type = x.device.type
+        device_type = device_type if isinstance(device_type, str) and device_type != "mps" else "cpu"
+        with torch.autocast(device_type=device_type, enabled=False):
+            freqs = (inv_freq_expanded.float() @ position_ids_expanded.float()).transpose(1, 2)
+            emb = torch.cat((freqs, freqs), dim=-1)
+            cos = emb.cos()
+            sin = emb.sin()
+        return cos.to(dtype=x.dtype), sin.to(dtype=x.dtype)
+
+
+def apply_rotary_pos_emb(q, k, cos, sin, unsqueeze_dim=2):
+    """Applies Rotary Position Embedding to the query and key tensors.
+    Args:
+        q (`torch.Tensor`): The query tensor.
+        k (`torch.Tensor`): The key tensor.
+        cos (`torch.Tensor`): The cosine part of the rotary embedding.
+        sin (`torch.Tensor`): The sine part of the rotary embedding.
+        unsqueeze_dim (`int`, *optional*, defaults to 1):
+            The 'unsqueeze_dim' argument specifies the dimension along which to unsqueeze cos[position_ids] and
+            sin[position_ids] so that they can be properly broadcasted to the dimensions of q and k. For example, note
+            that cos[position_ids] and sin[position_ids] have the shape [batch_size, seq_len, head_dim]. Then, if q and
+            k have the shape [batch_size, heads, seq_len, head_dim], then setting unsqueeze_dim=1 makes
+            cos[position_ids] and sin[position_ids] broadcastable to the shapes of q and k. Similarly, if q and k have
+            the shape [batch_size, seq_len, heads, head_dim], then set unsqueeze_dim=2.
+    Returns:
+        `tuple(torch.Tensor)` comprising of the query and key tensors rotated using the Rotary Position Embedding.
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+    q_embed = (q * cos) + (rotate_half(q) * sin)
+    k_embed = (k * cos) + (rotate_half(k) * sin)
+    return q_embed, k_embed
+
+
 class RotaryEmbedding(nn.Module):
     def __init__(self, dim: int, end: int, theta: float = 10000.0):
         super().__init__()
@@ -349,7 +423,17 @@ def __init__(
             contiguous_chunks=qkv_contiguous_chunks,
         )
         # TODO(kunhao): We want to have only one version per device and not one version per layer.
-        self.rotary_embedding = RotaryEmbedding(dim=self.d_qk, end=config.max_position_embeddings)
+
+        if config.rope_interleaved:
+            self.rotary_embedding = RotaryEmbedding(
+                dim=self.d_qk, end=config.max_position_embeddings, theta=config.rope_theta
+            )
+        else:
+            self.rotary_embedding = LlamaRotaryEmbedding(
+                dim=self.d_qk, end=config.max_position_embeddings, theta=config.rope_theta
+            )
+
+        # self.rotary_embedding = RotaryEmbedding(dim=self.d_qk, end=config.max_position_embeddings)
         log_rank(
             f"self.rotary_embedding.end is {self.rotary_embedding.end}",
             logger=logger,
@@ -359,7 +443,9 @@ def __init__(
         # self.rotary_embedding = RotaryEmbedding(dim=self.d_qk, end=2048)
 
         # NOTE: Only supported for training (TODO(fmom): position_ids not supported yet)
-        self.flash_rotary_embedding = FlashRotaryEmbedding(dim=self.d_qk, interleaved=True)
+        self.flash_rotary_embedding = FlashRotaryEmbedding(
+            dim=self.d_qk, interleaved=config.rope_interleaved, base=config.rope_theta
+        )
 
         self.o_proj = TensorParallelRowLinear(
             config.num_attention_heads * self.d_qk,
@@ -385,12 +471,16 @@ def __init__(
         self.segment_length = constants.CONFIG.infini_attention.segment_length  # for 1024 context length
 
         device = self.o_proj.weight.device
-        dtype = self.o_proj.weight.dtype
 
         from nanotron.parallel.sharded_parameters import SplitConfig, create_sharded_parameter_from_config
 
         if constants.CONFIG.infini_attention.turn_on_memory is True:
-            balance_factors = nn.Parameter(torch.zeros(self.n_local_q_heads, device=device, dtype=dtype))
+
+            balance_factors = nn.Parameter(
+                torch.zeros(self.n_local_q_heads, device=device, dtype=torch.float32)
+                # torch.randn(self.n_local_q_heads, device=device, dtype=torch.float32).normal_(mean=0.0, std=1/math.sqrt(config.num_attention_heads))
+                # torch.randn(self.n_local_q_heads, device=device, dtype=torch.float32).normal_(mean=0.0, std=1/math.sqrt(self.n_local_q_heads))
+            )
             self.balance_factors = create_sharded_parameter_from_config(
                 parameter=balance_factors,
                 pg=tp_pg,
@@ -400,12 +490,12 @@ def __init__(
                 ),
             )
 
-            log_rank(
-                f"Segment length is {self.segment_length}, turn_on_memory: {constants.CONFIG.infini_attention.turn_on_memory is True}",
-                logger=logger,
-                level=logging.WARNING,
-                rank=0,
-            )
+        log_rank(
+            f"Segment length is {self.segment_length}, turn_on_memory: {constants.CONFIG.infini_attention.turn_on_memory is True}",
+            logger=logger,
+            level=logging.WARNING,
+            rank=0,
+        )
 
     def forward(
         self,
@@ -415,6 +505,10 @@ def forward(
     ):
         hidden_states.shape[0]
         seq_len = hidden_states.shape[1]
+        # print(f"seq_len: {seq_len}")
+
+        # if seq_len > 64:
+        #     assert 1 == 1
 
         if seq_len > self.segment_length:
             import math
@@ -443,6 +537,34 @@ def forward(
         idx = 0
         logs = {}
 
+        if constants.GLOBAL_STEP == 11 and constants.IS_RANK_TO_MONITOR is True:
+            assert 1 == 1
+
+        raw_global_weights = F.sigmoid(self.balance_factors)
+
+        # raw_global_weights = F.tanh(self.balance_factors).abs()
+        # raw_global_weights = raw_global_weights * raw_global_weights.mean()
+
+        # def sigmoid_range(x, lo, hi): return torch.sigmoid(x) * (hi-lo) + lo
+        # raw_global_weights = sigmoid_range(self.balance_factors, 0, 5.5)
+
+        # raw_global_weights = F.softmax(self.balance_factors, dim=0)
+
+        # raw_global_weights = F.sigmoid(self.balance_factors)
+        global_weights = raw_global_weights
+        orig_global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
+        # + torch.randn(1, device=global_weights.device, dtype=global_weights.dtype)
+
+        # local_weights = 1 - global_weights
+        # local_weights = rearrange(local_weights, "n_heads -> 1 n_heads 1 1")
+        orig_local_weights = 1 - orig_global_weights
+
+        # global_weights = orig_global_weights.to(torch.bfloat16)
+        # local_weights = orig_local_weights.to(torch.bfloat16)
+
+        global_weights = orig_global_weights
+        local_weights = orig_local_weights
+
         for segment_hidden_state, segment_sequence_mask in zip(segment_hidden_states, segment_sequence_masks):
             attn_outputs = self.forward_with_hidden_states(
                 hidden_states=segment_hidden_state, sequence_mask=segment_sequence_mask, return_qkv_states=True
@@ -489,12 +611,6 @@ def forward(
                 #         rank=0,
                 #     )
 
-                global_weights = F.sigmoid(self.balance_factors)
-                global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
-
-                local_weights = 1 - F.sigmoid(self.balance_factors)
-                local_weights = rearrange(local_weights, "n_heads -> 1 n_heads 1 1")
-
                 # log_rank(
                 #     f"[idx={idx}] global_weights.shape = {global_weights.shape}, global_weights: {global_weights}",
                 #     logger=logger,
@@ -527,14 +643,19 @@ def forward(
                 if (
                     constants.GLOBAL_STEP is not None
                     and (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0
+                    and constants.IS_RANK_TO_MONITOR is True
                 ):
                     if dist.get_rank() == 0:
                         logs[f"layer_{self.layer_idx}:seg_{idx}:query_states"] = compute_stas(query_states)
                         logs[f"layer_{self.layer_idx}:seg_{idx}:key_states"] = compute_stas(key_states)
                         logs[f"layer_{self.layer_idx}:seg_{idx}:value_states"] = compute_stas(value_states)
 
-                        logs[f"layer_{self.layer_idx}:seg_{idx}:global_weights"] = compute_stas(global_weights)
-                        logs[f"layer_{self.layer_idx}:seg_{idx}:local_weights"] = compute_stas(local_weights)
+                        logs[f"layer_{self.layer_idx}:seg_{idx}:global_weights"] = compute_stas(
+                            orig_global_weights, log_tensor=True
+                        )
+                        logs[f"layer_{self.layer_idx}:seg_{idx}:local_weights"] = compute_stas(
+                            orig_local_weights, log_tensor=True
+                        )
                         logs[f"layer_{self.layer_idx}:seg_{idx}:local_attn_outputs"] = compute_stas(local_attn_outputs)
                         logs[f"layer_{self.layer_idx}:seg_{idx}:retrieved_memory"] = compute_stas(retrieved_memory)
                         logs[f"layer_{self.layer_idx}:seg_{idx}:attention_output"] = compute_stas(attention_output)
@@ -542,9 +663,8 @@ def forward(
                         logs[f"layer_{self.layer_idx}:seg_{idx}:memory"] = compute_stas(memory)
                         logs[f"layer_{self.layer_idx}:seg_{idx}:normalization"] = compute_stas(normalization)
 
-                if idx >= 1:
-                    assert 1 == 1
-
+                # if idx >= 1:
+                #     assert 1 == 1
                 memory, normalization = self._update_memory(memory, normalization, key_states, value_states)
 
             outputs.append(output)
@@ -556,9 +676,13 @@ def forward(
         assert outputs.shape == hidden_states.shape
 
         if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0:
-            if dist.get_rank() == 0:
+            if constants.IS_RANK_TO_MONITOR is True:
                 import wandb
 
+                for i in range(raw_global_weights.shape[0]):
+                    logs[f"layer_{self.layer_idx}:global_weights:head_{i}"] = raw_global_weights[i].item()
+                    logs[f"layer_{self.layer_idx}:balance_factors:head_{i}"] = self.balance_factors[i].item()
+
                 logs[f"layer_{self.layer_idx}:outputs"] = compute_stas(outputs)
                 wandb.log({**logs, "iteration_step": constants.GLOBAL_STEP})
 
@@ -566,6 +690,7 @@ def forward(
             "hidden_states": outputs,
             "sequence_mask": sequence_mask,
         }
+
         return return_outputs
 
     def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
@@ -576,6 +701,20 @@ def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
             prev_memory is not None and prev_normalization is not None
         )
 
+        if self.n_repeats > 1:
+            from einops import repeat
+
+            prev_memory = repeat(
+                prev_memory,
+                "batch_size n_kv_heads d_k d_v -> batch_size (n_kv_heads n) d_k d_v",
+                n=self.n_repeats,
+            )
+            prev_normalization = repeat(
+                prev_normalization,
+                "batch_size n_kv_heads d_head -> batch_size (n_kv_heads n) d_head",
+                n=self.n_repeats,
+            )
+
         sigma_query_states = F.elu(query_states) + 1
         retrieved_memory = einsum(
             sigma_query_states,
@@ -670,8 +809,6 @@ def forward_with_hidden_states(
             flash_attn_with_kvcache,
         )
 
-        # seq_len = hidden_states.shape[1]
-
         qkv_states = self.qkv_proj(
             hidden_states
         )  # [seq_len, batch_size, n_local_q_heads * d_qk + 2 * n_local_kv_heads * d_qk]
@@ -1429,7 +1566,8 @@ def init_model_randomly(self, config: Config):
             if "balance_factors" in param_name:
 
                 # init.normal_(param, mean=0.0, std=0.01)
-                param.zero_()
+                # param.zero_()
+                pass
             else:
                 module = model.get_submodule(module_name)
                 parametrizator.parametrize(param_name, module)

From a91d1fed8f1c7eae1d163583d76bf2ff1467fa73 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Sun, 30 Jun 2024 09:15:32 +0000
Subject: [PATCH 37/43] support custom balance factor's act func, init

---
 src/nanotron/config/config.py                 |   3 +
 src/nanotron/config/models_config.py          |   3 +
 src/nanotron/constants.py                     |   7 +-
 src/nanotron/debug/monitor.py                 | 236 ++++++++++--------
 src/nanotron/helpers.py                       | 155 +++++++-----
 src/nanotron/models/llama.py                  |  99 ++++++--
 src/nanotron/optim/gradient_accumulator.py    |  39 +++
 .../optim/inherit_from_other_optimizer.py     |   7 +
 .../parallel/pipeline_parallel/engine.py      |   3 +-
 src/nanotron/scaling/parametrization.py       |  12 +-
 src/nanotron/serialize/main.py                | 162 ++++++------
 src/nanotron/serialize/weights.py             |  24 +-
 src/nanotron/trainer.py                       |  35 ++-
 13 files changed, 486 insertions(+), 299 deletions(-)

diff --git a/src/nanotron/config/config.py b/src/nanotron/config/config.py
index 814ad0ee..dba2d6c4 100644
--- a/src/nanotron/config/config.py
+++ b/src/nanotron/config/config.py
@@ -301,6 +301,9 @@ def __post_init__(self):
 class InfiniAttentionArgs:
     segment_length: int
     turn_on_memory: bool
+    balance_factor_lr: float
+    balance_act_type: str
+    balance_init_type: str
 
 
 @dataclass
diff --git a/src/nanotron/config/models_config.py b/src/nanotron/config/models_config.py
index ba4559cf..7cdd77d3 100644
--- a/src/nanotron/config/models_config.py
+++ b/src/nanotron/config/models_config.py
@@ -47,6 +47,9 @@ class LlamaConfig:
     pretraining_tp: int = 1
     rms_norm_eps: float = 1e-6
     rope_scaling: Optional[dict] = None
+    rope_theta: float = 10000.0
+    # NOTE: The default value has been True, but for loading Llama3 checkpoints you have to set it to False
+    rope_interleaved: bool = True
     tie_word_embeddings: bool = False
     use_cache: bool = True
     vocab_size: int = 32000
diff --git a/src/nanotron/constants.py b/src/nanotron/constants.py
index ed651077..7782043b 100644
--- a/src/nanotron/constants.py
+++ b/src/nanotron/constants.py
@@ -16,10 +16,15 @@
 NEEDLE = None
 
 GLOBAL_STEP: Optional[int] = None
-LOG_STATE_INTERVAL = 5000
+LOG_STATE_INTERVAL = 2000
+IS_RANK_TO_MONITOR = None
 CONFIG = None
 
 TRAINING_CONFIG = None
 
 
 DEBUG_PATH = "./debug/nn_states_with_bs_2_and_transpose_qkv/acts/"
+
+MONITOR_STATE_PATH = "/fsx/phuc/projects/nanotron/debug/runs"
+
+BALANCE_FACTOR_STD = {}
diff --git a/src/nanotron/debug/monitor.py b/src/nanotron/debug/monitor.py
index 81c51f52..d7406053 100644
--- a/src/nanotron/debug/monitor.py
+++ b/src/nanotron/debug/monitor.py
@@ -1,48 +1,69 @@
+import os
+from pathlib import Path
 from typing import Dict, List, Optional, Tuple, Union
 
 import torch
-import torch.distributed as dist
-from nanotron.constants import DEBUG_PATH
+from nanotron import constants
+from nanotron.constants import MONITOR_STATE_PATH
 from nanotron.models.base import NanotronModel
 from nanotron.parallel import ParallelContext
 from torch import nn
-from torch.distributed import ReduceOp
 
 
-def track_weight_and_grad_stats(name: str, module: nn.Module, parallel_context: ParallelContext):
-    def compute_stats(name, tensors):
-        tensors = {"tensor": tensors} if not isinstance(tensors, dict) else tensors
-        stats = {}
+def save_tensor(name, tensor, path):
+    if name is None or name == "":
+        return
 
-        for key, tensor in tensors.items():
-            if tensor.dtype == torch.long or tensor.dtype == torch.int or tensor.dtype == torch.bool:
-                continue
+    # dp_rank = dist.get_rank(group=parallel_context.dp_pg)
+    # tp_rank = dist.get_rank(group=parallel_context.tp_pg)
+    # pp_rank = dist.get_rank(group=parallel_context.pp_pg)
 
-            if tensor is None:
-                assert 1 == 1
+    os.makedirs(path, exist_ok=True)
 
-            stats[key] = {}
-            stats[key] = {
-                "mean": tensor.cpu().mean().item(),
-                # "std": tensor.std().item(),
-                # "var": tensor.var().item(),
-                # "norm": tensor.norm().item(),
-                # "min": tensor.min().item(),
-                # "max": tensor.max().item(),
-                "amax": tensor.cpu().abs().max().item(),
-            }
+    # if dp_rank == 0 and tp_rank == 0 and pp_rank == 0:
+    torch.save(
+        tensor,
+        # f"{path}/{name}_dp_rank_{dp_rank}_and_pp_rank_{pp_rank}_and_tp_rank_{tp_rank}.pt"
+        f"{path}/{name}.pt",
+    )
 
-            # NOTE: now all reduce mean this across tp ranks
-            tp_group = parallel_context.tp_pg
-            for metric_name, metric_value in stats[key].items():
-                stats[key][metric_name] = torch.tensor(metric_value, device=tensor.device, dtype=tensor.dtype)
-                dist.all_reduce(stats[key][metric_name], op=ReduceOp.MAX, group=tp_group)
 
-            # tp_rank = dist.get_rank(group=tp_group)
-            # stats[key][f"data:tp_{tp_rank}"] = tensor.detach().cpu().tolist()
+def compute_stats(name, tensors):
+    tensors = {"tensor": tensors} if not isinstance(tensors, dict) else tensors
+    stats = {}
 
-        return stats[list(stats.keys())[0]] if len(stats) == 1 else stats
+    for key, tensor in tensors.items():
+        if tensor.dtype == torch.long or tensor.dtype == torch.int or tensor.dtype == torch.bool:
+            continue
 
+        stats[key] = {}
+        stats[key] = {
+            # "mean": tensor.cpu().mean().item(),
+            "mean": tensor.cpu().mean().item(),
+            "std": tensor.cpu().std().item(),
+            # "data": tensor.detach().cpu().tolist()
+            # "var": tensor.var().item(),
+            "norm": tensor.cpu().norm().item(),
+            # "min": tensor.min().item(),
+            # "max": tensor.max().item(),
+            "amax": tensor.cpu().amax().item(),
+        }
+
+        # NOTE: now all reduce mean this across tp ranks
+        # tp_group = parallel_context.tp_pg
+        # for metric_name, metric_value in stats[key].items():
+        #     stats[key][metric_name] = torch.tensor(metric_value, device=tensor.device, dtype=tensor.dtype)
+        #     dist.all_reduce(stats[key][metric_name], op=ReduceOp.MAX, group=tp_group)
+
+        # tp_rank = dist.get_rank(group=tp_group)
+        # stats[key][f"data:tp_{tp_rank}"] = tensor.detach().cpu().tolist()
+
+    return stats[list(stats.keys())[0]] if len(stats) == 1 else stats
+
+
+def track_weight_and_grad_stats(
+    name: str, module: nn.Module, parallel_context: ParallelContext, save_path: Optional[Path] = None
+):
     logs: Dict[str, Dict[str, float]] = {}
 
     if name not in logs:
@@ -56,86 +77,82 @@ def _save_output_stats(module: nn.Module, input: torch.Tensor, output: torch.Ten
                 stats = compute_stats(name, param.data)
                 if stats is not None:
                     logs[name][param_name] = stats
-
-        inputs = input if isinstance(input, tuple) else (input,)
-        outputs = output if isinstance(output, tuple) else (output,)
-
-        if len(inputs) > 1:
-            for i, inp in enumerate(inputs):
-                if inp.dtype == torch.long:
-                    # NOTE: this is input ids in transformers
-                    continue
-                stats = compute_stats(name, inp)
-                if stats is not None:
-                    logs[name][f"input:{i}"] = stats
-        elif len(inputs) == 1:
-            stats = compute_stats(name, inputs[0])
-            if stats is not None:
-                logs[name]["input"] = stats
-
-        dp_rank = dist.get_rank(group=parallel_context.dp_pg)
-        tp_rank = dist.get_rank(group=parallel_context.tp_pg)
-        pp_rank = dist.get_rank(group=parallel_context.pp_pg)
-
-        def save(name, tensor):
-            import os
-
-            # from nanotron.constants import
-            # DIR = "./debug/nn_states_with_bs_1/acts/"
-
-            os.makedirs(DEBUG_PATH, exist_ok=True)
-
-            if dp_rank == 0:
-                torch.save(
-                    tensor, f"{DEBUG_PATH}/{name}_dp_rank_{dp_rank}_and_pp_rank_{pp_rank}_and_tp_rank_{tp_rank}.pt"
-                )
-
-        if len(outputs) > 1:
-            for i, out in enumerate(outputs):
-                stats = compute_stats(name, out)
-                save(name, out)
-                if stats is not None:
-                    logs[name][f"output:{i}"] = stats
-        elif len(outputs) == 1:
-            stats = compute_stats(name, outputs[0])
-            save(name, outputs[0])
-            if stats is not None:
-                logs[name]["output"] = stats
-
-    def _save_grad_stats(module: nn.Linear, grad_input, grad_output: torch.Tensor):
-        if isinstance(grad_output, tuple):
-            for i, grad in enumerate(grad_output):
-                if grad is None:
-                    continue
-
-                stats = compute_stats(name, grad)
-                if stats is not None:
-                    logs[name][f"grad_output:{i}"] = stats
-        else:
-            stats = compute_stats(name, grad_output)
-            if stats is not None:
-                logs[name]["grad_output"] = stats
-
-        if isinstance(grad_input, tuple):
-            for i, grad in enumerate(grad_input):
-                if grad is not None:
-                    stats = compute_stats(name, grad)
-                    if stats is not None:
-                        logs[name][f"grad_input:{i}"] = stats
-        else:
-            if grad_input is not None:
-                stats = compute_stats(name, grad_input)
-                if stats is not None:
-                    logs[name]["grad_input"] = stats
+                    # save_tensor(f"{name}.{param_name}", param.data, path=f"{save_path}/weights/")
+
+        # inputs = input if isinstance(input, tuple) else (input,)
+        # outputs = output if isinstance(output, tuple) else (output,)
+
+        # if len(inputs) > 1:
+        #     for i, inp in enumerate(inputs):
+        #         if inp.dtype == torch.long:
+        #             # NOTE: this is input ids in transformers
+        #             continue
+        #         # stats = compute_stats(name, inp)
+        #         if stats is not None:
+        #             logs[name][f"input:{i}"] = stats
+        # elif len(inputs) == 1:
+        #     # stats = compute_stats(name, inputs[0])
+        #     if stats is not None:
+        #         logs[name]["input"] = stats
+
+        # if len(outputs) > 1:
+        #     for i, out in enumerate(outputs):
+        #         # stats = compute_stats(name, out)
+        #         if name is None or name == "":
+        #             assert 1 == 1
+
+        #         if stats is not None:
+        #             logs[name][f"output:{i}"] = stats
+        #             # save_tensor(name, out, path=f"{save_path}/acts/")
+        # elif len(outputs) == 1:
+        #     # if name is None or name == "":
+        #     #     assert 1 == 1
+
+        #     # stats = compute_stats(name, outputs[0])
+        #     if stats is not None:
+        #         logs[name]["output"] = stats
+        #         # try:
+        #         #     save_tensor(name, outputs[0], path=f"{save_path}/acts/")
+        #         # except:
+        #         #     assert 1 == 1
+
+    # def _save_grad_stats(module: nn.Linear, grad_input, grad_output: torch.Tensor):
+    #     if isinstance(grad_output, tuple):
+    #         for i, grad in enumerate(grad_output):
+    #             if grad is None:
+    #                 continue
+
+    #             stats = compute_stats(name, grad)
+    #             if stats is not None:
+    #                 logs[name][f"grad_output:{i}"] = stats
+    #     else:
+    #         stats = compute_stats(name, grad_output)
+    #         if stats is not None:
+    #             logs[name]["grad_output"] = stats
+
+    #     if isinstance(grad_input, tuple):
+    #         for i, grad in enumerate(grad_input):
+    #             if grad is not None:
+    #                 stats = compute_stats(name, grad)
+    #                 if stats is not None:
+    #                     logs[name][f"grad_input:{i}"] = stats
+    #     else:
+    #         if grad_input is not None:
+    #             stats = compute_stats(name, grad_input)
+    #             if stats is not None:
+    #                 logs[name]["grad_input"] = stats
 
     handles = []
     handles.append(module.register_forward_hook(_save_output_stats))
-    handles.append(module.register_backward_hook(_save_grad_stats))
+    # handles.append(module.register_backward_hook(_save_grad_stats))
     return logs, handles
 
 
-def monitor_nanotron_model(model: NanotronModel, parallel_context: Optional[ParallelContext] = None):
+def monitor_nanotron_model(run_name: str, model: NanotronModel, parallel_context: Optional[ParallelContext] = None):
     assert parallel_context is not None
+    assert isinstance(constants.GLOBAL_STEP, int)
+
+    save_path = f"{MONITOR_STATE_PATH}/{run_name}/{constants.GLOBAL_STEP}"
 
     def get_leaf_modules(module: nn.Module) -> List[Tuple[str, nn.Module]]:
         """
@@ -153,9 +170,16 @@ def get_leaf_modules(module: nn.Module) -> List[Tuple[str, nn.Module]]:
     leaf_modules = [(name, module) for name, module in model.named_modules()]
 
     for name, module in leaf_modules:
-        module_logs, module_handles = track_weight_and_grad_stats(name, module, parallel_context)
-        logs.update(module_logs)
-        handles.extend(module_handles)
+        if "balance_factors" in name:
+            module_logs, module_handles = track_weight_and_grad_stats(
+                name=name,
+                module=module,
+                parallel_context=parallel_context,
+                # save_tensor=True,
+                save_path=save_path,
+            )
+            logs.update(module_logs)
+            handles.extend(module_handles)
 
     return logs, handles
 
diff --git a/src/nanotron/helpers.py b/src/nanotron/helpers.py
index 89cc27dd..ef5bb0e9 100644
--- a/src/nanotron/helpers.py
+++ b/src/nanotron/helpers.py
@@ -75,7 +75,33 @@ def init_random_states(parallel_config: ParallelismArgs, tp_pg: ProcessGroup):
     return random_states
 
 
-def lr_scheduler_builder(optimizer: Optimizer, lr_scheduler_args: LRSchedulerArgs, total_training_steps: int):
+def _get_lr_lambda_in_training(
+    current_step: int,
+    initial_lr: float,
+    # lr_decay_steps: int,
+    # lr_decay_starting_step: int,
+    total_training_steps: int,
+    lr_scheduler_args: LRSchedulerArgs,
+):
+    """
+    current_step: current training step
+    initial_lr: the learning rate of a parameter group
+
+    More info on initial_lr:
+    And in standard parameterization, lr_lambda only takes a single learning rate.
+    But in µTransfer, each parameter has a custom learning rate (custom_lr = lr_scheduler_args.learning_rate * scaling_factor),
+    so each parameter group has a custom lr_lambda function.
+
+    LR Scheduling function, it has from 2 up to 4 phases:
+    - warmup,
+    - optional: constant (if lr_decay_starting_step is set)
+    - decay
+    - optional: constant (if lr_decay_steps and/or lr_decay_starting_step are set)
+    Warmup starts at lr=0 and ends at `lr=lr`
+    Then it stays constant at lr if lr_decay_starting_step is set and larger than lr_warmup_steps
+    Then it decays until `min_decay_lr` for lr_decay_steps if set, else: (total_training_steps - lr_warmup_steps or lr_decay_starting_step)
+    Then it stays constant at min_decay_lr if lr_decay_starting_step is set and total_training_steps is larger)
+    """
     if lr_scheduler_args.lr_decay_steps is None:
         lr_decay_steps = total_training_steps
         if lr_scheduler_args.lr_warmup_steps is not None:
@@ -93,71 +119,59 @@ def lr_scheduler_builder(optimizer: Optimizer, lr_scheduler_args: LRSchedulerArg
     else:
         lr_decay_starting_step = lr_scheduler_args.lr_decay_starting_step
 
-    def lr_lambda(current_step: int, initial_lr: float):
-        """
-        current_step: current training step
-        initial_lr: the learning rate of a parameter group
-
-        More info on initial_lr:
-        And in standard parameterization, lr_lambda only takes a single learning rate.
-        But in µTransfer, each parameter has a custom learning rate (custom_lr = lr_scheduler_args.learning_rate * scaling_factor),
-        so each parameter group has a custom lr_lambda function.
-
-        LR Scheduling function, it has from 2 up to 4 phases:
-        - warmup,
-        - optional: constant (if lr_decay_starting_step is set)
-        - decay
-        - optional: constant (if lr_decay_steps and/or lr_decay_starting_step are set)
-        Warmup starts at lr=0 and ends at `lr=lr`
-        Then it stays constant at lr if lr_decay_starting_step is set and larger than lr_warmup_steps
-        Then it decays until `min_decay_lr` for lr_decay_steps if set, else: (total_training_steps - lr_warmup_steps or lr_decay_starting_step)
-        Then it stays constant at min_decay_lr if lr_decay_starting_step is set and total_training_steps is larger)
-        """
-        # No warmup or decay
-        if lr_scheduler_args.lr_warmup_steps == 0 and lr_decay_steps == 0:
-            return initial_lr
-
-        # Warmup phase
-        elif lr_scheduler_args.lr_warmup_style is not None and current_step <= lr_scheduler_args.lr_warmup_steps:
-            if lr_scheduler_args.lr_warmup_style == "linear":
-                lmbda = initial_lr * current_step / max(lr_scheduler_args.lr_warmup_steps, 1)
-            elif lr_scheduler_args.lr_warmup_style == "constant":
-                lmbda = lr_scheduler_args.learning_rate
-            else:
-                raise ValueError(f"Unknown warmup style {lr_scheduler_args.lr_warmup_style}")
-
-        # Optional constant phase at learning_rate
-        elif current_step < lr_decay_starting_step:
-            lmbda = initial_lr
-
-        # Decay phase
-        elif lr_scheduler_args.lr_decay_style is not None and current_step < lr_decay_starting_step + lr_decay_steps:
-            if lr_scheduler_args.lr_decay_style == "cosine":
-                lmbda = (
-                    lr_scheduler_args.min_decay_lr
-                    + (initial_lr - lr_scheduler_args.min_decay_lr)
-                    * (1 + math.cos(math.pi * (current_step - lr_decay_starting_step) / lr_decay_steps))
-                    / 2
-                )
-            elif lr_scheduler_args.lr_decay_style == "linear":
-                lmbda = (
-                    lr_scheduler_args.min_decay_lr
-                    + (initial_lr - lr_scheduler_args.min_decay_lr)
-                    * (lr_decay_steps - (current_step - lr_decay_starting_step))
-                    / lr_decay_steps
-                )
-            else:
-                raise ValueError(f"Unknown decay style {lr_scheduler_args.lr_decay_style}")
-
-        # Optional constant phase at min_decay_lr
+    # No warmup or decay
+    if lr_scheduler_args.lr_warmup_steps == 0 and lr_decay_steps == 0:
+        return initial_lr
+
+    # Warmup phase
+    elif lr_scheduler_args.lr_warmup_style is not None and current_step <= lr_scheduler_args.lr_warmup_steps:
+        if lr_scheduler_args.lr_warmup_style == "linear":
+            lmbda = initial_lr * current_step / max(lr_scheduler_args.lr_warmup_steps, 1)
+        elif lr_scheduler_args.lr_warmup_style == "constant":
+            lmbda = lr_scheduler_args.learning_rate
         else:
-            lmbda = lr_scheduler_args.min_decay_lr
+            raise ValueError(f"Unknown warmup style {lr_scheduler_args.lr_warmup_style}")
+
+    # Optional constant phase at learning_rate
+    elif current_step < lr_decay_starting_step:
+        lmbda = initial_lr
+
+    # Decay phase
+    elif lr_scheduler_args.lr_decay_style is not None and current_step < lr_decay_starting_step + lr_decay_steps:
+        if lr_scheduler_args.lr_decay_style == "cosine":
+            lmbda = (
+                lr_scheduler_args.min_decay_lr
+                + (initial_lr - lr_scheduler_args.min_decay_lr)
+                * (1 + math.cos(math.pi * (current_step - lr_decay_starting_step) / lr_decay_steps))
+                / 2
+            )
+        elif lr_scheduler_args.lr_decay_style == "linear":
+            lmbda = (
+                lr_scheduler_args.min_decay_lr
+                + (initial_lr - lr_scheduler_args.min_decay_lr)
+                * (lr_decay_steps - (current_step - lr_decay_starting_step))
+                / lr_decay_steps
+            )
+        else:
+            raise ValueError(f"Unknown decay style {lr_scheduler_args.lr_decay_style}")
+
+    # Optional constant phase at min_decay_lr
+    else:
+        lmbda = lr_scheduler_args.min_decay_lr
+
+    lmbda /= initial_lr  # Normalization for pytorch
+    return lmbda
 
-        lmbda /= initial_lr  # Normalization for pytorch
-        return lmbda
 
+def lr_scheduler_builder(optimizer: Optimizer, lr_scheduler_args: LRSchedulerArgs, total_training_steps: int):
     def get_lr_lambda_for_param_group(lr: float):
-        return partial(lr_lambda, initial_lr=lr)
+        # return partial(_get_lr_lambda_in_training, initial_lr=lr, lr_decay_steps=lr_decay_steps, lr_decay_starting_step=lr_decay_starting_step, lr_scheduler_args=lr_scheduler_args)
+        return partial(
+            _get_lr_lambda_in_training,
+            initial_lr=lr,
+            total_training_steps=total_training_steps,
+            lr_scheduler_args=lr_scheduler_args,
+        )
 
     # NOTE: get learning rate scheduler for each param group
     lr_lambdas = []
@@ -215,7 +229,20 @@ def get_custom_lr_for_named_parameters(
         name,
         param,
     ) in named_parameters:
-        learning_rate = learning_rate_mapper.get_lr(name, param)
+
+        if "balance_factors" in name:
+            from nanotron import constants
+
+            learning_rate = constants.CONFIG.infini_attention.balance_factor_lr
+        else:
+            learning_rate = learning_rate_mapper.get_lr(name, param)
+
+        log_rank(
+            f"[Optimizer Building] Parameter {name} has a learning rate of {learning_rate}",
+            logger=logger,
+            level=logging.INFO,
+        )
+
         assert isinstance(learning_rate, float), f"Expected a float, got {learning_rate} for parameter {name}"
         named_param_groups_with_custom_lr.append({"named_params": [(name, param)], "lr": learning_rate})
 
@@ -249,6 +276,8 @@ def init_optimizer_and_grad_accumulator(
         lr=optimizer_args.learning_rate_scheduler.learning_rate,
     )
 
+    assert 1 == 1
+
     # Basic optimizer builder
     def basic_optimizer_builder(named_param_groups):
         return NamedOptimizer(
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 6f7fbaf4..24ec3773 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -53,13 +53,13 @@ def compute_stas(tensor, log_tensor: bool = False, save_tensor: bool = False):
         )
 
     logs = {
-        "mean": tensor.detach().mean().item(),
-        "std": tensor.detach().std().item(),
+        "mean": tensor.cpu().mean().item(),
+        "std": tensor.cpu().std().item(),
         # "var": tensor.var().item(),
-        "norm": tensor.norm().item(),
+        "norm": tensor.cpu().norm().item(),
         # "min": tensor.min().item(),
         # "max": tensor.max().item(),
-        "amax": tensor.detach().abs().max().item(),
+        "amax": tensor.cpu().amax().item(),
     }
     # if log_tensor:
     #     import torchshow as ts
@@ -474,21 +474,60 @@ def __init__(
 
         from nanotron.parallel.sharded_parameters import SplitConfig, create_sharded_parameter_from_config
 
-        if constants.CONFIG.infini_attention.turn_on_memory is True:
+        # if constants.CONFIG.infini_attention.turn_on_memory is True:
+
+        #     # balance_factors = nn.Parameter(
+        #     #     torch.zeros(self.n_local_q_heads, device=device, dtype=torch.float32)
+        #     #     # torch.randn(self.n_local_q_heads, device=device, dtype=torch.float32).normal_(mean=0.0, std=1/math.sqrt(config.num_attention_heads))
+        #     #     # torch.randn(self.n_local_q_heads, device=device, dtype=torch.float32).normal_(mean=0.0, std=1/math.sqrt(self.n_local_q_heads))
+        #     # )
+        #     pass
+
+        if constants.CONFIG.infini_attention.balance_init_type == "zeros":
+            log_rank("Zero initialized balance factors", logger=logger, level=logging.WARNING, rank=0)
+            balance_factors = nn.Parameter(torch.zeros(self.n_local_q_heads, device=device, dtype=torch.float32))
+        elif constants.CONFIG.infini_attention.balance_init_type == "normal_randn":
+            log_rank("normal_randn initialized balance factors", logger=logger, level=logging.WARNING, rank=0)
+            balance_factors = nn.Parameter(torch.randn(self.n_local_q_heads, device=device, dtype=torch.float32))
+        else:
+            raise ValueError(f"balance_init_type {constants.CONFIG.infini_attention.balance_init_type} not supported")
 
-            balance_factors = nn.Parameter(
-                torch.zeros(self.n_local_q_heads, device=device, dtype=torch.float32)
-                # torch.randn(self.n_local_q_heads, device=device, dtype=torch.float32).normal_(mean=0.0, std=1/math.sqrt(config.num_attention_heads))
-                # torch.randn(self.n_local_q_heads, device=device, dtype=torch.float32).normal_(mean=0.0, std=1/math.sqrt(self.n_local_q_heads))
-            )
-            self.balance_factors = create_sharded_parameter_from_config(
-                parameter=balance_factors,
-                pg=tp_pg,
-                split_config=SplitConfig(
-                    split_dim=0,
-                    # contiguous_chunks=(self.n_local_heads, self.n_local_heads)
-                ),
-            )
+        self.balance_factors = create_sharded_parameter_from_config(
+            parameter=balance_factors,
+            pg=tp_pg,
+            split_config=SplitConfig(
+                split_dim=0,
+                # contiguous_chunks=(self.n_local_heads, self.n_local_heads)
+            ),
+        )
+
+        if constants.CONFIG.infini_attention.balance_act_type == "orig_sigmoid":
+            balance_act_func = F.sigmoid
+        elif constants.CONFIG.infini_attention.balance_act_type == "orig_tanh":
+            balance_act_func = F.tanh
+        elif constants.CONFIG.infini_attention.balance_act_type == "hard_sigmoid":
+
+            def hard_sigmoid(x):
+                return torch.clamp(x * 0.2 + 0.5, min=0.0, max=1.0)
+
+            balance_act_func = hard_sigmoid
+        elif constants.CONFIG.infini_attention.balance_act_type == "tanh_abs":
+
+            def tanh_abs(x):
+                return torch.tanh(x).abs()
+
+            balance_act_func = tanh_abs
+        else:
+            raise ValueError(f"balance_act_type {constants.CONFIG.infini_attention.balance_act_type} not supported")
+
+        log_rank(
+            f"Balance act func is {balance_act_func}",
+            logger=logger,
+            level=logging.WARNING,
+            rank=0,
+        )
+
+        self.balance_act_func = balance_act_func
 
         log_rank(
             f"Segment length is {self.segment_length}, turn_on_memory: {constants.CONFIG.infini_attention.turn_on_memory is True}",
@@ -540,7 +579,21 @@ def forward(
         if constants.GLOBAL_STEP == 11 and constants.IS_RANK_TO_MONITOR is True:
             assert 1 == 1
 
-        raw_global_weights = F.sigmoid(self.balance_factors)
+        # if constants.CONFIG.infini_attention.balance_act_type == "orig_sigmoid":
+        #     raw_global_weights = F.sigmoid(self.balance_factors)
+        # elif constants.CONFIG.infini_attention.balance_act_type == "orig_tanh":
+        #     raw_global_weights = F.tanh(self.balance_factors)
+        # elif constants.CONFIG.infini_attention.balance_act_type == "hard_sigmoid":
+        #     def hard_sigmoid(x):
+        #         return torch.clamp(x * 0.2 + 0.5, min=0.0, max=1.0)
+        #     raw_global_weights = hard_sigmoid(self.balance_factors)
+        # elif constants.CONFIG.infini_attention.balance_act_type == "tanh_abs":
+        #     def tanh_abs(x):
+        #         return torch.tanh(x).abs()
+        #     raw_global_weights = tanh_abs(self.balance_factors)
+        # else:
+        #     raise ValueError(f"balance_act_type {constants.CONFIG.infini_attention.balance_act_type} not supported")
+        raw_global_weights = self.balance_act_func(self.balance_factors)
 
         # raw_global_weights = F.tanh(self.balance_factors).abs()
         # raw_global_weights = raw_global_weights * raw_global_weights.mean()
@@ -650,12 +703,6 @@ def forward(
                         logs[f"layer_{self.layer_idx}:seg_{idx}:key_states"] = compute_stas(key_states)
                         logs[f"layer_{self.layer_idx}:seg_{idx}:value_states"] = compute_stas(value_states)
 
-                        logs[f"layer_{self.layer_idx}:seg_{idx}:global_weights"] = compute_stas(
-                            orig_global_weights, log_tensor=True
-                        )
-                        logs[f"layer_{self.layer_idx}:seg_{idx}:local_weights"] = compute_stas(
-                            orig_local_weights, log_tensor=True
-                        )
                         logs[f"layer_{self.layer_idx}:seg_{idx}:local_attn_outputs"] = compute_stas(local_attn_outputs)
                         logs[f"layer_{self.layer_idx}:seg_{idx}:retrieved_memory"] = compute_stas(retrieved_memory)
                         logs[f"layer_{self.layer_idx}:seg_{idx}:attention_output"] = compute_stas(attention_output)
@@ -680,6 +727,8 @@ def forward(
                 import wandb
 
                 for i in range(raw_global_weights.shape[0]):
+                    logs[f"layer_{self.layer_idx}:global_weights"] = compute_stas(orig_global_weights, log_tensor=True)
+                    logs[f"layer_{self.layer_idx}:local_weights"] = compute_stas(orig_local_weights, log_tensor=True)
                     logs[f"layer_{self.layer_idx}:global_weights:head_{i}"] = raw_global_weights[i].item()
                     logs[f"layer_{self.layer_idx}:balance_factors:head_{i}"] = self.balance_factors[i].item()
 
diff --git a/src/nanotron/optim/gradient_accumulator.py b/src/nanotron/optim/gradient_accumulator.py
index 38e3f6fc..043fa590 100644
--- a/src/nanotron/optim/gradient_accumulator.py
+++ b/src/nanotron/optim/gradient_accumulator.py
@@ -217,9 +217,23 @@ def _accumulate_grad(self, name: str, half_param: NanotronParameter) -> None:
         assert half_param.grad is not None, f"Expected param {name} to have gradient."
         fp32_grad = self.get_grad_buffer(name=name)
 
+        # if "balance_factor" in name:
+        #     # with torch.no_grad():
+        #     #     fp32_grad = fp32_grad * 10**3
+        #     assert 1 == 1
+
         if self._is_accumulation_sync_step is False:
             # WARNING: We assume fp32_grad_bucket is already zeroed
+            # import torch.nn.functional as F
+            # # NOTE: normalzie the gradient
+            # if "balance_factor" in name:
+            #     _grad = F.normalize(half_param.grad.unsqueeze(dim=0)) / 10
+            #     _grad = _grad.squeeze(dim=0)
+            #     fp32_grad.add_(_grad)
+            # else:
+            #     fp32_grad.add_(half_param.grad)
             fp32_grad.add_(half_param.grad)
+
             # In case _is_accumulation_sync_step = True: no need to add half gradients, because it's done in the allreduce hook
 
         # TODO @thomasw21: Is it better to set to zero instead?
@@ -227,6 +241,9 @@ def _accumulate_grad(self, name: str, half_param: NanotronParameter) -> None:
 
         # In the case an optimizer decides to set it to None, we need to re-assign previous buffer
         if name in self.parameters:
+            if "balance_factor" in name:
+                assert 1 == 1
+
             fp32_param = self.parameters[name]["fp32"]
             if hasattr(self, "param_name_to_offsets"):
                 if name not in self.param_name_to_offsets:
@@ -238,6 +255,28 @@ def _accumulate_grad(self, name: str, half_param: NanotronParameter) -> None:
                 grad = fp32_grad
             fp32_param.grad = grad
 
+        # if "balance_factor" in name:
+        import wandb
+        from nanotron import constants
+
+        if (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0 and constants.IS_RANK_TO_MONITOR is True:
+            from nanotron import constants
+
+            # save_tensor(
+            #     name=f"{name}.grad",
+            #     tensor=fp32_param.grad,
+            #     path=f"{constants.MONITOR_STATE_PATH}/{constants.CONFIG.general.run}/{constants.GLOBAL_STEP}/grads"
+            # )
+
+            wandb.log(
+                {
+                    f"{name}:grad:mean": fp32_param.grad.detach().mean().item(),
+                    f"{name}:grad:std": fp32_param.grad.detach().std().item(),
+                    f"{name}:grad:norm": fp32_param.grad.detach().norm().item(),
+                    "iteration_step": constants.GLOBAL_STEP,
+                }
+            )
+
     @contextmanager
     def no_sync(self):
         """A context manager to disable gradient synchronizations across
diff --git a/src/nanotron/optim/inherit_from_other_optimizer.py b/src/nanotron/optim/inherit_from_other_optimizer.py
index 2ddd36d0..86e6ba81 100644
--- a/src/nanotron/optim/inherit_from_other_optimizer.py
+++ b/src/nanotron/optim/inherit_from_other_optimizer.py
@@ -49,6 +49,13 @@ def get_base_optimizer(self):
     def param_groups(self):
         return self.optimizer.param_groups
 
+    # @property
+    # def param_index_to_name(self):
+    #     state_id_to_name = {id(state): self.id_to_name[id(param)] for param, state in self.optimizer.state.items()}
+    #     optim_state_dict["names"] = {
+    #         index: state_id_to_name[id(state)] for index, state in optim_state_dict["state"].items()
+    #     }
+
     def inherit_from(self, cls):
         if isinstance(self, cls):
             return True
diff --git a/src/nanotron/parallel/pipeline_parallel/engine.py b/src/nanotron/parallel/pipeline_parallel/engine.py
index babf875e..a35a997e 100644
--- a/src/nanotron/parallel/pipeline_parallel/engine.py
+++ b/src/nanotron/parallel/pipeline_parallel/engine.py
@@ -227,7 +227,8 @@ def __init__(self):
 
         from transformers import AutoTokenizer
 
-        self.tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
+        # self.tokenizer = AutoTokenizer.from_pretrained("lvwerra/the-tokenizer-v1")
+        self.tokenizer = AutoTokenizer.from_pretrained("/fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B")
 
     def train_batch_iter(
         self,
diff --git a/src/nanotron/scaling/parametrization.py b/src/nanotron/scaling/parametrization.py
index e6241651..84e7de9a 100644
--- a/src/nanotron/scaling/parametrization.py
+++ b/src/nanotron/scaling/parametrization.py
@@ -197,6 +197,14 @@ def get_lr(self, param_name: str, param: nn.Parameter) -> float:
         # NOTE: param_name should be like 'model.token_position_embeddings.pp_block.token_embedding.weight'
         # since names_to_modules map module_name to module
         # so we remove the .weight and .bias from param_name to get the module_name
-        module_name = param_name.rsplit(".", 1)[0]
-        module = self.names_to_modules[module_name]
+
+        # NOTE: the purpose if remove ".weight" or ".bias" from module_name.weight
+        # so we get the module name
+        if "weight" or "bias" in param_name:
+            module_name = param_name.rsplit(".", 1)[0]
+
+        try:
+            module = self.names_to_modules[module_name]
+        except Exception:
+            raise Exception(f"Can't find {module_name} in {self.names_to_modules.keys()}")
         return self.MODULE_TO_PARAMETRIZE[type(module)](param, module)
diff --git a/src/nanotron/serialize/main.py b/src/nanotron/serialize/main.py
index a2a3d4aa..f8e621cd 100644
--- a/src/nanotron/serialize/main.py
+++ b/src/nanotron/serialize/main.py
@@ -9,14 +9,8 @@
 from nanotron import logging
 from nanotron import optim as optim
 from nanotron.config import Config
-from nanotron.distributed import get_global_rank
 from nanotron.logging import log_rank
 from nanotron.parallel import ParallelContext
-from nanotron.parallel.parameters import NanotronParameter
-from nanotron.sanity_checks import (
-    assert_tensor_synced_across_pg,
-    check_optim_state_in_sync,
-)
 from nanotron.serialize.metadata import CheckpointMetadata, load_meta, save_meta
 from nanotron.serialize.optimizer import (
     load_lr_scheduler,
@@ -117,84 +111,84 @@ def save(
     # TODO @thomas21: sanity check, not sure whether that needs to happen at testing or now (depends how much it costs)
     ###
     # SANITY CHECK: Check that the model params are synchronized across `parallel_context.dp_pg`
-    if sanity_checks:
-        for name, param_or_buffer in sorted(model.state_dict().items(), key=lambda x: x[0]):
-            assert_tensor_synced_across_pg(
-                tensor=param_or_buffer,
-                pg=parallel_context.dp_pg,
-                msg=lambda err: f"{name} are not synced across DP {err}",
-            )
-
-        # SANITY CHECK: Check that the tied parameters are synchronized
-        sorted_tied_parameters = sorted(
-            (
-                param
-                for parameters_group in optimizer.param_groups
-                for param in parameters_group["params"]
-                if param.requires_grad and isinstance(param, NanotronParameter) and param.is_tied
-            ),
-            key=lambda param: param.get_tied_info().name,
-        )
-        for tied_param in sorted_tied_parameters:
-            tied_info = tied_param.get_tied_info()
-            group_ranks = tied_info.global_ranks
-            group = parallel_context.world_ranks_to_pg[group_ranks]
-
-            assert_tensor_synced_across_pg(
-                tensor=tied_param, pg=group, msg=lambda err: f"Tied {tied_info.name} are not synced {err}"
-            )
-        if not optimizer.inherit_from(optim.ZeroDistributedOptimizer):
-            check_optim_state_in_sync(optimizer, parallel_context.dp_pg)
-
-        # SANITY CHECK: tied parameters have their optimizer states synchronized
-        # Compute a mapping from id_ to index in the optimizer sense
-        state_dict = optimizer.state_dict()
-        assert len(optimizer.param_groups) == len(state_dict["param_groups"])
-        index_to_param = {}
-        for real_param_group, index_param_group in zip(optimizer.param_groups, state_dict["param_groups"]):
-            indices = index_param_group["params"]
-            parameters = real_param_group["params"]
-            assert len(indices) == len(parameters)
-            for param, index in zip(parameters, indices):
-                assert index not in index_to_param
-                index_to_param[index] = param
-
-        current_state_dict = optimizer.state_dict()
-        for index, optim_state in sorted(current_state_dict["state"].items(), key=lambda x: x[0]):
-            param = index_to_param[index]
-            if not isinstance(param, NanotronParameter):
-                continue
-            if not param.is_tied:
-                # If it's not shared, we don't need to check it's synced
-                continue
-            tied_info = param.get_tied_info()
-            group_ranks = tied_info.global_ranks
-            group = parallel_context.world_ranks_to_pg[group_ranks]
-            reference_rank = 0
-            current_rank = dist.get_rank(group)
-
-            for name, tensor in optim_state.items():
-                # FIXME @thomasw21: Some data is actually on `cpu`, just for this test we most it to `cuda`
-                tensor = tensor.to("cuda")
-
-                if current_rank == reference_rank:
-                    reference_tensor = tensor
-                else:
-                    reference_tensor = torch.empty_like(tensor)
-                dist.broadcast(
-                    reference_tensor,
-                    src=get_global_rank(group=group, group_rank=reference_rank),
-                    group=group,
-                )
-
-                torch.testing.assert_close(
-                    tensor,
-                    reference_tensor,
-                    atol=0,
-                    rtol=0,
-                    msg=lambda msg: f"tensor at {current_state_dict['names'][index]} doesn't match with our reference. Optimizer key: {name}\nCur: {tensor}\nRef: {reference_tensor}\n{msg}",
-                )
-        ###
+    # if sanity_checks:
+    #     for name, param_or_buffer in sorted(model.state_dict().items(), key=lambda x: x[0]):
+    #         assert_tensor_synced_across_pg(
+    #             tensor=param_or_buffer,
+    #             pg=parallel_context.dp_pg,
+    #             msg=lambda err: f"{name} are not synced across DP {err}",
+    #         )
+
+    #     # SANITY CHECK: Check that the tied parameters are synchronized
+    #     sorted_tied_parameters = sorted(
+    #         (
+    #             param
+    #             for parameters_group in optimizer.param_groups
+    #             for param in parameters_group["params"]
+    #             if param.requires_grad and isinstance(param, NanotronParameter) and param.is_tied
+    #         ),
+    #         key=lambda param: param.get_tied_info().name,
+    #     )
+    #     for tied_param in sorted_tied_parameters:
+    #         tied_info = tied_param.get_tied_info()
+    #         group_ranks = tied_info.global_ranks
+    #         group = parallel_context.world_ranks_to_pg[group_ranks]
+
+    #         assert_tensor_synced_across_pg(
+    #             tensor=tied_param, pg=group, msg=lambda err: f"Tied {tied_info.name} are not synced {err}"
+    #         )
+    #     if not optimizer.inherit_from(optim.ZeroDistributedOptimizer):
+    #         check_optim_state_in_sync(optimizer, parallel_context.dp_pg)
+
+    #     # SANITY CHECK: tied parameters have their optimizer states synchronized
+    #     # Compute a mapping from id_ to index in the optimizer sense
+    #     state_dict = optimizer.state_dict()
+    #     assert len(optimizer.param_groups) == len(state_dict["param_groups"])
+    #     index_to_param = {}
+    #     for real_param_group, index_param_group in zip(optimizer.param_groups, state_dict["param_groups"]):
+    #         indices = index_param_group["params"]
+    #         parameters = real_param_group["params"]
+    #         assert len(indices) == len(parameters)
+    #         for param, index in zip(parameters, indices):
+    #             assert index not in index_to_param
+    #             index_to_param[index] = param
+
+    #     current_state_dict = optimizer.state_dict()
+    #     for index, optim_state in sorted(current_state_dict["state"].items(), key=lambda x: x[0]):
+    #         param = index_to_param[index]
+    #         if not isinstance(param, NanotronParameter):
+    #             continue
+    #         if not param.is_tied:
+    #             # If it's not shared, we don't need to check it's synced
+    #             continue
+    #         tied_info = param.get_tied_info()
+    #         group_ranks = tied_info.global_ranks
+    #         group = parallel_context.world_ranks_to_pg[group_ranks]
+    #         reference_rank = 0
+    #         current_rank = dist.get_rank(group)
+
+    #         for name, tensor in optim_state.items():
+    #             # FIXME @thomasw21: Some data is actually on `cpu`, just for this test we most it to `cuda`
+    #             tensor = tensor.to("cuda")
+
+    #             if current_rank == reference_rank:
+    #                 reference_tensor = tensor
+    #             else:
+    #                 reference_tensor = torch.empty_like(tensor)
+    #             dist.broadcast(
+    #                 reference_tensor,
+    #                 src=get_global_rank(group=group, group_rank=reference_rank),
+    #                 group=group,
+    #             )
+
+    #             torch.testing.assert_close(
+    #                 tensor,
+    #                 reference_tensor,
+    #                 atol=0,
+    #                 rtol=0,
+    #                 msg=lambda msg: f"tensor at {current_state_dict['names'][index]} doesn't match with our reference. Optimizer key: {name}\nCur: {tensor}\nRef: {reference_tensor}\n{msg}",
+    #             )
+    #     ###
 
     dist.barrier(parallel_context.world_pg)
 
diff --git a/src/nanotron/serialize/weights.py b/src/nanotron/serialize/weights.py
index 55c2b8cb..7543b2fb 100644
--- a/src/nanotron/serialize/weights.py
+++ b/src/nanotron/serialize/weights.py
@@ -339,15 +339,21 @@ def load_weights(
                             current_checkpoint_version == checkpoint_version
                         ), f"Checkpoint version mismatch at {shards_path[0]}."
 
-                if checkpoint_version <= CHECKPOINT_VERSION:
-                    load_sharded_param_latest(
-                        param_or_buffer=param_or_buffer,
-                        sharded_info=sharded_info,
-                        shards_path=shards_path,
-                        param_shard_metadata=param_shard_metadata[name],
-                    )
-                else:
-                    raise ValueError(f"Unsupported checkpoint version {checkpoint_version}")
+                # if checkpoint_version <= CHECKPOINT_VERSION:
+                #     load_sharded_param_latest(
+                #         param_or_buffer=param_or_buffer,
+                #         sharded_info=sharded_info,
+                #         shards_path=shards_path,
+                #         param_shard_metadata=param_shard_metadata[name],
+                #     )
+                # else:
+                #     raise ValueError(f"Unsupported checkpoint version {checkpoint_version}")
+                load_sharded_param_latest(
+                    param_or_buffer=param_or_buffer,
+                    sharded_info=sharded_info,
+                    shards_path=shards_path,
+                    param_shard_metadata=param_shard_metadata[name],
+                )
 
         else:
             raise NotImplementedError(f"Parameters {param} should be a NanotronParameter")
diff --git a/src/nanotron/trainer.py b/src/nanotron/trainer.py
index 8fc1b605..6d27b1d6 100644
--- a/src/nanotron/trainer.py
+++ b/src/nanotron/trainer.py
@@ -172,10 +172,16 @@ def __init__(
             self.model.module if isinstance(self.model, DistributedDataParallel) else self.model
         )
 
+        # parametrization_method = (
+        #     ParametrizationMethod.STANDARD
+        #     if isinstance(self.config.model.init_method, RandomInit)
+        #     else ParametrizationMethod.SPECTRAL_MUP
+        # )
+
         parametrization_method = (
-            ParametrizationMethod.STANDARD
-            if isinstance(self.config.model.init_method, RandomInit)
-            else ParametrizationMethod.SPECTRAL_MUP
+            ParametrizationMethod.SPECTRAL_MUP
+            if isinstance(self.config.model.init_method, SpectralMupInit)
+            else ParametrizationMethod.STANDARD
         )
 
         # Init optimizer
@@ -306,11 +312,12 @@ def pre_training(self, *args, **kwargs):
             rank=0,
         )
 
-        current_time = datetime.datetime.now().strftime("%d/%m/%Y_%H:%M:%S")
+        datetime.datetime.now().strftime("%d/%m/%Y_%H:%M:%S")
         if dist.get_rank(self.parallel_context.world_pg) == self.logger_ranks[0] and wandb is not None:
             wandb.init(
                 project=self.config.general.project,
-                name=f"{current_time}_{self.config.general.run}",
+                # name=f"{current_time}_{self.config.general.run}",
+                name=f"{self.config.general.run}",
                 config={"nanotron_config": self.config.as_dict()},
             )
             # wandb.watch(self.model, log="all")
@@ -428,6 +435,12 @@ def train(
 
         prof = get_profiler(config=self.config)
         torch.cuda.empty_cache()
+        rank_to_monitor = (
+            dist.get_rank(group=self.parallel_context.dp_pg) == 0
+            and dist.get_rank(group=self.parallel_context.tp_pg) == 0
+        )
+        constants.IS_RANK_TO_MONITOR = rank_to_monitor
+
         with prof:
             for self.iteration_step in range(self.start_iteration_step + 1, self.config.tokens.train_steps + 1):
                 constants.GLOBAL_STEP = self.iteration_step
@@ -435,10 +448,14 @@ def train(
                 if isinstance(prof, torch.profiler.profile):
                     prof.step()
 
-                if (self.iteration_step - 1) % constants.LOG_STATE_INTERVAL == 0:
+                if (
+                    self.iteration_step - 1
+                ) % constants.LOG_STATE_INTERVAL == 0 and constants.IS_RANK_TO_MONITOR is True:
                     from nanotron.debug.monitor import monitor_nanotron_model
 
-                    nn_logs, nn_handles = monitor_nanotron_model(self.model, self.parallel_context)
+                    nn_logs, nn_handles = monitor_nanotron_model(
+                        run_name=self.config.general.run, model=self.model, parallel_context=self.parallel_context
+                    )
 
                 self.iteration_start_time = time.time()
                 self._update_dataloader_based_on_training_stages(dataloader_or_dls)
@@ -452,7 +469,9 @@ def train(
                 if (self.iteration_step - 1) % self.config.logging.iteration_step_info_interval == 0:
                     self.train_step_logs(outputs=outputs, loss_avg=loss_avg)
 
-                if (self.iteration_step - 1) % constants.LOG_STATE_INTERVAL == 0:
+                if (
+                    self.iteration_step - 1
+                ) % constants.LOG_STATE_INTERVAL == 0 and constants.IS_RANK_TO_MONITOR is True:
                     from nanotron.debug.monitor import convert_logs_to_flat_logs
 
                     if dist.get_rank(self.parallel_context.world_pg) == self.logger_ranks[0] and wandb is not None:

From 962a8e1969a6ed0759b216e8c53ba4be67bd49f0 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Wed, 3 Jul 2024 11:16:43 +0000
Subject: [PATCH 38/43] it works, backup for exp 57

---
 .gitignore                                    |     5 +
 debug_dataset.ipynb                           |  1515 ++
 debug_exp33.ipynb                             |    67 +
 debug_exp34.ipynb                             |   265 +
 debug_infini_ckp.ipynb                        |     0
 debug_modeling_code.ipynb                     |  1407 ++
 debug_needle_dataset.ipynb                    |   220 +
 draft.ipynb                                   |    79 +
 .../configs/280m_llama_1024_ctx_infini.yaml   |   108 +
 .../exp10_8b_llama3_32k_ctx_and_4m_bs.yaml    |   198 +
 .../exp11_8b_llama3_32k_ctx_and_4m_bs.yaml    |   198 +
 .../exp12_8b_llama3_8k_ctx_and_4m_bs.yaml     |   186 +
 .../exp13_8b_llama3_8k_ctx_and_4m_bs.yaml     |   186 +
 ...p14_8b_llama3_8k_ctx_length_and_2m_bs.yaml |   198 +
 ...p15_8b_llama3_1k_ctx_length_and_1m_bs.yaml |   198 +
 ...p16_8b_llama3_4k_ctx_length_and_1m_bs.yaml |   213 +
 .../exp17/exp17_8b_llama3_8k_ctx_length.yaml  |   197 +
 ...8_1b_llama2_100k_ctx_length_and_2m_bs.yaml |   245 +
 .../exp18_1b_llama2_finetune_needle.yaml      |   257 +
 ...19_1b_llama2_32k_ctx_length_and_2m_bs.yaml |   245 +
 .../configs/exp19/exp19_finetuning.yaml       |   228 +
 ...2k_ctx_length_and_2k_seglen_and_2m_bs.yaml |   245 +
 ...20_1b_llama2_32k_ctx_length_and_2m_bs.yaml |   268 +
 ...xt_and_2k_segment_length_and_finetune.yaml |   184 +
 .../configs/exp20/test_train.yaml             |   258 +
 ...4k_ctx_length_and_1k_seglen_and_2m_bs.yaml |   227 +
 ...4k_ctx_length_and_1k_seglen_and_2m_bs.yaml |   227 +
 ...4k_ctx_length_and_1k_seglen_and_2m_bs.yaml |   227 +
 ...k_seglen_and_2m_bs_and_orig_doremi_lr.yaml |   227 +
 .../configs/exp25/config.yaml                 |   245 +
 ...k_ctx_length_and_256_seglen_and_2m_bs.yaml |   230 +
 ...k_ctx_length_and_256_seglen_and_2m_bs.yaml |   230 +
 ..._200m_llama2_256_ctx_length_and_2m_bs.yaml |   236 +
 ..._200m_llama2_256_ctx_length_and_2m_bs.yaml |   240 +
 .../configs/exp29/main.yaml                   |   219 +
 .../configs/exp29/ref.yaml                    |   219 +
 ..._200m_llama2_256_ctx_length_and_2m_bs.yaml |   236 +
 ..._200m_llama2_256_ctx_length_and_2m_bs.yaml |   240 +
 ...ength_and_64_segment_length_and_2m_bs.yaml |   240 +
 .../configs/exp33/debug_config.yaml           |   265 +
 ...ength_and_64_segment_length_and_2m_bs.yaml |   240 +
 .../exp33/exp33_debug_with_no_warmup.yaml     |   265 +
 ...gth_and_8192_segment_length_and_2m_bs.yaml |   171 +
 ...ma_per_source_upsampling_long_samples.yaml |   187 +
 ..._and_2m_bs_and_finetuning_needle_task.yaml |   171 +
 ...gth_and_8192_segment_length_and_2m_bs.yaml |   170 +
 ...ength_and_2m_bs_and_needle_finetuning.yaml |   209 +
 ...ength_and_64_segment_length_and_2m_bs.yaml |   192 +
 ...and_64_segment_length_and_constant_lr.yaml |   267 +
 ...d_custom_lr_0.001_for_balance_factors.yaml |   241 +
 .../configs/exp38/exp38_debug.yaml            |   241 +
 ...d_custom_lr_0.002_for_balance_factors.yaml |   241 +
 ..._custom_lr_0.0005_for_balance_factors.yaml |   241 +
 ...custom_lr_0.00025_for_balance_factors.yaml |   241 +
 ...ength_and_2m_bs_and_global_lr_0.00015.yaml |   241 +
 ..._256_ctx_length_and_global_lr_0.00015.yaml |   236 +
 ...ngth_and_2m_bs_and_global_lr_0.000075.yaml |   241 +
 ..._and_global_lr_0.00015_and_10k_warmup.yaml |   241 +
 ...th_and_2m_bs_and_global_lr_0.00001875.yaml |   241 +
 ...h_and_2m_bs_and_global_lr_0.000009375.yaml |   241 +
 .../exp5/exp5_8b_llama3_original_config.yaml  |   179 +
 ...0375_and_balance_factor_lr_0.00001875.yaml |   241 +
 ...0000375_and_balance_factor_lr_0.00015.yaml |   241 +
 ...0000375_and_balance_factor_lr_0.00015.yaml |   247 +
 ...0000375_and_balance_factor_lr_0.00015.yaml |   247 +
 ..._1.0e-5_and_balance_factor_lr_0.00015.yaml |   176 +
 ...lr_1.0e-5_and_balance_factor_lr_0.001.yaml |   176 +
 ...r_1.0e-5_and_balance_factor_lr_0.0025.yaml |   176 +
 ....01_and_balance_factor_0_weight_decay.yaml |   179 +
 ...005_and_balance_factor_0_weight_decay.yaml |   179 +
 .../configs/exp6/exp6_llama3_8b_config.yaml   |   198 +
 .../configs/exp7/exp7_llama3_8b_config.yaml   |   198 +
 .../exp8/exp8_llama3_8b_infini_config.yaml    |    99 +
 .../configs/exp9/exp9_llama3_8b_config.yaml   |   198 +
 .../configs/nouamane_config.yaml              |   122 +
 .../configs/ref_280m_1024_ctx.yaml            |   107 +
 .../configs/ref_llama3_8b_config.yaml         |   214 +
 .../debug_amount_of_change_in_weight.ipynb    |  1119 ++
 .../data/exp34/debug_balance_factors.ipynb    | 14842 ++++++++++++++++
 .../data/exp34/debug_finetune_data.ipynb      |   344 +
 .../data/exp34/debug_optimizer.ipynb          |   242 +
 .../data/exp34/debug_weights.ipynb            |  4534 +++++
 .../data/exp34/hope.ipynb                     |  1975 ++
 .../tokenization/executor.pik                 |   Bin 0 -> 2674 bytes
 .../tokenization/launch_script.slurm          |    16 +
 ...ize_finetune_data_to_nanotron_format.ipynb |    20 +
 .../exp34/tokenize_finetunine_data_to_s3.py   |   106 +
 examples/infinite-context-length/hope.ipynb   |  1528 ++
 .../scripts/run_16k_passkey_evals.sh          |    13 +
 .../scripts/run_32k_evals.sh                  |    38 +
 .../scripts/run_evals.sh                      |     8 +
 .../run_generate_16k_passkey_eval_data.sh     |    29 +
 ...un_generate_16k_passkey_finetuning_data.sh |    42 +
 .../scripts/run_passkey_eval.py               |   293 +
 .../templates/training_data.py                |     1 +
 .../templates/training_date.py                |     1 +
 llama3_generation.ipynb                       |   121 +
 run_evals_32_ctx.sh                           |     0
 run_generate.py                               |   483 +-
 run_train.py                                  |    16 +-
 src/nanotron/config/config.py                 |     5 +
 src/nanotron/debug/monitor.py                 |    69 +-
 src/nanotron/generation/decode_.py            |   808 +
 src/nanotron/helpers.py                       |     3 +-
 src/nanotron/models/llama.py                  |    12 +-
 src/nanotron/optim/gradient_accumulator.py    |    30 +-
 src/nanotron/optim/named_optimizer.py         |    20 +
 src/nanotron/trainer.py                       |    12 +-
 108 files changed, 45034 insertions(+), 69 deletions(-)
 create mode 100644 debug_dataset.ipynb
 create mode 100644 debug_exp33.ipynb
 create mode 100644 debug_exp34.ipynb
 create mode 100644 debug_infini_ckp.ipynb
 create mode 100644 debug_modeling_code.ipynb
 create mode 100644 debug_needle_dataset.ipynb
 create mode 100644 draft.ipynb
 create mode 100644 examples/infinite-context-length/configs/280m_llama_1024_ctx_infini.yaml
 create mode 100644 examples/infinite-context-length/configs/exp10/exp10_8b_llama3_32k_ctx_and_4m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp11/exp11_8b_llama3_32k_ctx_and_4m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp12/exp12_8b_llama3_8k_ctx_and_4m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp13/exp13_8b_llama3_8k_ctx_and_4m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp14/exp14_8b_llama3_8k_ctx_length_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp15/exp15_8b_llama3_1k_ctx_length_and_1m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp16/exp16_8b_llama3_4k_ctx_length_and_1m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp17/exp17_8b_llama3_8k_ctx_length.yaml
 create mode 100644 examples/infinite-context-length/configs/exp18/exp18_1b_llama2_100k_ctx_length_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp18/exp18_1b_llama2_finetune_needle.yaml
 create mode 100644 examples/infinite-context-length/configs/exp19/exp19_1b_llama2_32k_ctx_length_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp19/exp19_finetuning.yaml
 create mode 100644 examples/infinite-context-length/configs/exp20/exp20_1b_llama2_32k_ctx_length_and_2k_seglen_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp20/exp20_1b_llama2_32k_ctx_length_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp20/exp20_32k_context_and_2k_segment_length_and_finetune.yaml
 create mode 100644 examples/infinite-context-length/configs/exp20/test_train.yaml
 create mode 100644 examples/infinite-context-length/configs/exp21/exp21_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp22/exp22_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp23/exp23_200m_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp24/exp24_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs_and_orig_doremi_lr.yaml
 create mode 100644 examples/infinite-context-length/configs/exp25/config.yaml
 create mode 100644 examples/infinite-context-length/configs/exp26/exp26_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp27/exp27_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp28/exp28_ref_200m_llama2_256_ctx_length_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp29/exp29_200m_llama2_256_ctx_length_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp29/main.yaml
 create mode 100644 examples/infinite-context-length/configs/exp29/ref.yaml
 create mode 100644 examples/infinite-context-length/configs/exp30/exp30_ref_200m_llama2_256_ctx_length_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp31/exp31_200m_llama2_256_ctx_length_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp32/exp32_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp33/debug_config.yaml
 create mode 100644 examples/infinite-context-length/configs/exp33/exp33_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp33/exp33_debug_with_no_warmup.yaml
 create mode 100644 examples/infinite-context-length/configs/exp34/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp34/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_SlimPajama_per_source_upsampling_long_samples.yaml
 create mode 100644 examples/infinite-context-length/configs/exp34/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_needle_task.yaml
 create mode 100644 examples/infinite-context-length/configs/exp35/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp35/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_needle_finetuning.yaml
 create mode 100644 examples/infinite-context-length/configs/exp36/exp36_200m_infini_gqa_llama2_256_ctx_length_and_64_segment_length_and_2m_bs.yaml
 create mode 100644 examples/infinite-context-length/configs/exp37/exp37_debug_200b_llama_and_256_ctx_length_and_64_segment_length_and_constant_lr.yaml
 create mode 100644 examples/infinite-context-length/configs/exp38/exp38_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.001_for_balance_factors.yaml
 create mode 100644 examples/infinite-context-length/configs/exp38/exp38_debug.yaml
 create mode 100644 examples/infinite-context-length/configs/exp39/exp39_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.002_for_balance_factors.yaml
 create mode 100644 examples/infinite-context-length/configs/exp40/exp40_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.0005_for_balance_factors.yaml
 create mode 100644 examples/infinite-context-length/configs/exp41/exp41_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.00025_for_balance_factors.yaml
 create mode 100644 examples/infinite-context-length/configs/exp43/exp43_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015.yaml
 create mode 100644 examples/infinite-context-length/configs/exp44/exp44_200m_ref_llama2_256_ctx_length_and_global_lr_0.00015.yaml
 create mode 100644 examples/infinite-context-length/configs/exp45/exp45_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000075.yaml
 create mode 100644 examples/infinite-context-length/configs/exp46/exp46_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015_and_10k_warmup.yaml
 create mode 100644 examples/infinite-context-length/configs/exp48/exp48_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00001875.yaml
 create mode 100644 examples/infinite-context-length/configs/exp49/exp49_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000009375.yaml
 create mode 100644 examples/infinite-context-length/configs/exp5/exp5_8b_llama3_original_config.yaml
 create mode 100644 examples/infinite-context-length/configs/exp50/exp50_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00001875.yaml
 create mode 100644 examples/infinite-context-length/configs/exp51/exp51_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00015.yaml
 create mode 100644 examples/infinite-context-length/configs/exp52/exp52_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_orig_tanh_act_and_randn_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015.yaml
 create mode 100644 examples/infinite-context-length/configs/exp53/exp53_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_hard_sigmoid_act_and_zeros_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015.yaml
 create mode 100644 examples/infinite-context-length/configs/exp54/exp54_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.00015.yaml
 create mode 100644 examples/infinite-context-length/configs/exp55/exp55_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.001.yaml
 create mode 100644 examples/infinite-context-length/configs/exp56/exp56_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.0025.yaml
 create mode 100644 examples/infinite-context-length/configs/exp57/exp57_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.01_and_balance_factor_0_weight_decay.yaml
 create mode 100644 examples/infinite-context-length/configs/exp58/exp58_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.005_and_balance_factor_0_weight_decay.yaml
 create mode 100644 examples/infinite-context-length/configs/exp6/exp6_llama3_8b_config.yaml
 create mode 100644 examples/infinite-context-length/configs/exp7/exp7_llama3_8b_config.yaml
 create mode 100644 examples/infinite-context-length/configs/exp8/exp8_llama3_8b_infini_config.yaml
 create mode 100644 examples/infinite-context-length/configs/exp9/exp9_llama3_8b_config.yaml
 create mode 100644 examples/infinite-context-length/configs/nouamane_config.yaml
 create mode 100644 examples/infinite-context-length/configs/ref_280m_1024_ctx.yaml
 create mode 100644 examples/infinite-context-length/configs/ref_llama3_8b_config.yaml
 create mode 100644 examples/infinite-context-length/data/exp34/debug_amount_of_change_in_weight.ipynb
 create mode 100644 examples/infinite-context-length/data/exp34/debug_balance_factors.ipynb
 create mode 100644 examples/infinite-context-length/data/exp34/debug_finetune_data.ipynb
 create mode 100644 examples/infinite-context-length/data/exp34/debug_optimizer.ipynb
 create mode 100644 examples/infinite-context-length/data/exp34/debug_weights.ipynb
 create mode 100644 examples/infinite-context-length/data/exp34/hope.ipynb
 create mode 100644 examples/infinite-context-length/data/exp34/tokenization_logs/tokenization/executor.pik
 create mode 100644 examples/infinite-context-length/data/exp34/tokenization_logs/tokenization/launch_script.slurm
 create mode 100644 examples/infinite-context-length/data/exp34/tokenize_finetune_data_to_nanotron_format.ipynb
 create mode 100644 examples/infinite-context-length/data/exp34/tokenize_finetunine_data_to_s3.py
 create mode 100644 examples/infinite-context-length/hope.ipynb
 create mode 100644 examples/infinite-context-length/scripts/run_16k_passkey_evals.sh
 create mode 100755 examples/infinite-context-length/scripts/run_32k_evals.sh
 create mode 100644 examples/infinite-context-length/scripts/run_evals.sh
 create mode 100755 examples/infinite-context-length/scripts/run_generate_16k_passkey_eval_data.sh
 create mode 100644 examples/infinite-context-length/scripts/run_generate_16k_passkey_finetuning_data.sh
 create mode 100644 examples/infinite-context-length/scripts/run_passkey_eval.py
 create mode 100644 examples/infinite-context-length/templates/training_data.py
 create mode 100644 examples/infinite-context-length/templates/training_date.py
 create mode 100644 llama3_generation.ipynb
 create mode 100644 run_evals_32_ctx.sh
 create mode 100644 src/nanotron/generation/decode_.py

diff --git a/.gitignore b/.gitignore
index 985a3136..2b7bb23b 100644
--- a/.gitignore
+++ b/.gitignore
@@ -165,3 +165,8 @@ checkpoints/
 wandb/
 *.pkl
 examples/infinite-context-length/*.txt
+
+*.json
+*.arrow
+*.txt
+*.out
diff --git a/debug_dataset.ipynb b/debug_dataset.ipynb
new file mode 100644
index 00000000..7a8bab85
--- /dev/null
+++ b/debug_dataset.ipynb
@@ -0,0 +1,1515 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/admin/home/phuc_nguyen/miniconda3/envs/nanotron-dev/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "from transformers import AutoTokenizer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tokenizer = AutoTokenizer.from_pretrained(\"lvwerra/the-tokenizer-v1\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# TEXT = \"\"\"\n",
+    "# Mr. and Mrs. Dursley, of number four, Privet Drive, were proud to say\n",
+    "# that they were perfectly normal, thank you very much. They were the last\n",
+    "# people you'd expect to be involved in anything strange or mysterious,\n",
+    "# because they just didn't hold with such nonsense.\n",
+    "\n",
+    "# Mr. Dursley was the director of a firm called Grunnings, which made\n",
+    "# drills. He was a big, beefy man with hardly any neck, although he did\n",
+    "# have a very large mustache. Mrs. Dursley was thin and blonde and had\n",
+    "# nearly twice the usual amount of neck, which came in very useful as she\n",
+    "# spent so much of her time craning over garden fences, spying on the\n",
+    "# neighbors. The Dursleys had a small son called Dudley and in their\n",
+    "# opinion there was no finer boy anywhere.\n",
+    "\n",
+    "# The Dursleys had everything they wanted, but they also had a secret, and\n",
+    "# their greatest fear was that somebody would discover it. They didn't\n",
+    "# think they could bear it if anyone found out about the Potters. Mrs.\n",
+    "# Potter was Mrs. Dursley's sister, but they hadn't met for several years;\n",
+    "# in fact, Mrs. Dursley pretended she didn't have a sister, because her\n",
+    "# sister and her good-for-nothing husband were as unDursleyish as it was\n",
+    "# possible to be. The Dursleys shuddered to think what the neighbors would\n",
+    "# say if the Potters arrived in the street. The Dursleys knew that the\n",
+    "# Potters had a small son, too, but they had never even seen him. This boy\n",
+    "# was another good reason for keeping the Potters away; they didn't want\n",
+    "# Dudley mixing with a child like that.\n",
+    "\n",
+    "# When Mr. and Mrs. Dursley woke up on the dull, gray Tuesday our story\n",
+    "# starts, there was nothing about the cloudy sky outside to suggest that\n",
+    "# strange and mysterious things would soon be happening all over the\n",
+    "# country. Mr. Dursley hummed as he picked out his most boring tie for\n",
+    "# work, and Mrs. Dursley gossiped away happily as she wrestled a screaming\n",
+    "# Dudley into his high chair.\n",
+    "\n",
+    "# None of them noticed a large, tawny owl flutter past the window.\n",
+    "\n",
+    "# At half past eight, Mr. Dursley picked up his briefcase, pecked Mrs.\n",
+    "# Dursley on the cheek, and tried to kiss Dudley good-bye but missed,\n",
+    "# because Dudley was now having a tantrum and throwing his cereal at the\n",
+    "# walls. \"Little tyke,\" chortled Mr. Dursley as he left the house. He got\n",
+    "# into his car and backed out of number four's drive.\n",
+    "\n",
+    "# It was on the corner of the street that he noticed the first sign of\n",
+    "# something peculiar -- a cat reading a map. For a second, Mr. Dursley\n",
+    "# didn't realize what he had seen -- then he jerked his head around to\n",
+    "# look again. There was a tabby cat standing on the corner of Privet\n",
+    "# Drive, but there wasn't a map in sight. What could he have been thinking\n",
+    "# of? It must have been a trick of the light. Mr. Dursley blinked and\n",
+    "# stared at the cat. It stared back. As Mr. Dursley drove around the\n",
+    "# corner and up the road, he watched the cat in his mirror. It was now\n",
+    "# reading the sign that said Privet Drive -- no, looking at the sign; cats\n",
+    "# couldn't read maps or signs. Mr. Dursley gave himself a little shake and\n",
+    "# put the cat out of his mind. As he drove toward town he thought of\n",
+    "# nothing except a large order of drills he was hoping to get that day.\n",
+    "\n",
+    "# But on the edge of town, drills were driven out of his mind by something\n",
+    "# else. As he sat in the usual morning traffic jam, he couldn't help\n",
+    "# noticing that there seemed to be a lot of strangely dressed people\n",
+    "# about. People in cloaks. Mr. Dursley couldn't bear people who dressed in\n",
+    "# funny clothes -- the getups you saw on young people! He supposed this\n",
+    "# was some stupid new fashion. He drummed his fingers on the steering\n",
+    "# wheel and his eyes fell on a huddle of these weirdos standing quite\n",
+    "# close by. They were whispering excitedly together. Mr. Dursley was\n",
+    "# enraged to see that a couple of them weren't young at all; why, that man\n",
+    "# had to be older than he was, and wearing an emerald-green cloak! The\n",
+    "# nerve of him! But then it struck Mr. Dursley that this was probably some\n",
+    "# silly stunt -- these people were obviously collecting for something...\n",
+    "# yes, that would be it. The traffic moved on and a few minutes later, Mr.\n",
+    "# Dursley arrived in the Grunnings parking lot, his mind back on drills.\n",
+    "# \"\"\"\n",
+    "\n",
+    "TEXT = \"\"\"\n",
+    "The problem provided is derived from the 1980 American High School Mathematics Examination (AHSME), specifically problem number 17. This problem requires knowledge of complex numbers and algebraic manipulations. We will break down the solution into smaller steps and explain the underlying mathematical principles. Complex numbers can be represented as ordered pairs (a, b) or in the form of a + bi, where a and b are real numbers, and i is the square root of -1. When squaring i, you get (-1). Let's examine the given expression more closely: (n + i)^4 = n^4 + 4in³ - 6n² - 4in + 1 For this expression to result in an integer value, both its real and imaginary components must equal integers. First, let us focus on the imaginary part of the expression: 4in³ - 4in. For these terms to cancel out when adding the whole expression, they need to be equivalent; hence: 4in³ - 4in = 0 Now, factor out 4in: 4in(n² - 1) = 0 The equation above implies two possible scenarios. Either 4in equals zero, which means n = 0 since i cannot equal zero. Alternatively, n² - 1 could equal zero, leading to n = ±1. These three potential values for n warrant further investigation. Let's substitute them back into the original expression (n + i)^4 to verify if it indeed yields integer results: 1. If n = 0, then (0 + i)^4 = i^4 = -1 (integer) 2. If n = 1, then (1 + i)^4 = 1 + 4i - 6 - 4i + 1 = -4 + i(-4 + 4i) = -4 (integer) 3. If n = -1, then ((-1) + i)^4 = (-1)^4 + 4i(-1)³ - 6(-1)² - 4i(-1) + 1 = 1 - 4i - 6 + 4i + 1 = -4 (integer) Since all three possibilities yield integer results, our answer is (D): 3.\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tokens = tokenizer.encode(TEXT)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "488"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(tokens)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"\\nThe problem provided is derived from the 1980 American High School Mathematics Examination (AHSME), specifically problem number 17. This problem requires knowledge of complex numbers and algebraic manipulations. We will break down the solution into smaller steps and explain the underlying mathematical principles. Complex numbers can be represented as ordered pairs (a, b) or in the form of a + bi, where a and b are real numbers, and i is the square root of -1. When squaring i, you get (-1). Let's examine the given expression more closely: (n + i)^4 = n^4 + 4in³ - 6n² - 4in + 1 For this expression to result in an integer value, both its real and imaginary components must equal integers. First, let us focus on the imaginary part of the expression: 4in³ - 4in. For these terms\""
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokenizer.decode(tokens[:192])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_dataset\n",
+    "from transformers import AutoTokenizer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading readme: 100%|███████████████████████████████████████████████████████| 423/423 [00:00<00:00, 4.26MB/s]\n",
+      "Downloading data: 100%|████████████████████████████████████████████████████████| 173k/173k [00:00<00:00, 788kB/s]\n",
+      "Generating train split: 100%|████████████████████████████████████████████| 21/21 [00:00<00:00, 234.97 examples/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "data = load_dataset(\"nanotron/needle_in_a_hay_stack_finetuning_dataset\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key............................................................................................... . The pass key is 10733. Remember it. 10733 is the pass key. The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\n",
+      "The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\n",
+      "The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\n",
+      "The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\n",
+      "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\n",
+      "The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roarThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails.. \n",
+      "\n",
+      "What is the pass key? The pass key is 10733.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(data[\"train\"][0][\"prompt\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tokenizer = AutoTokenizer.from_pretrained(\"lvwerra/the-tokenizer-v1\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "32768"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(tokenizer.encode(data[\"train\"][0][\"prompt\"]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The pass key is 32569. Remember it. 32569 is the pass key. The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The ur \\n\\nWhat is the pass key? The pass key is \""
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokenizer.decode(tokenizer.encode(data[\"train\"][0][\"prompt\"]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The pass key is 32569. Remember it. 32569 is the pass key. The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The ur \\n\\nWhat is the pass key? The pass key is \""
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data[\"train\"][0][\"prompt\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_from_disk\n",
+    "data_disk = load_from_disk(\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/needle_finetune_datasets/needle_finetuning_ctx_len_32768_and_depth_10_and_id_2\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on............................................................................................... The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The pass key is 476229534971. Remember it. 476229534971 is the pass key.. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban. \\n\\nWhat is the pass key? The pass key is 476229534971.\""
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_disk[0][\"prompt\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Merge datasets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/admin/home/phuc_nguyen/miniconda3/envs/nanotron-dev/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datasets import load_dataset, DatasetDict, Dataset\n",
+    "import os\n",
+    "\n",
+    "# Specify the path containing the dataset folders\n",
+    "path = \"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/finetune_data\"\n",
+    "\n",
+    "# Get a list of all dataset folders\n",
+    "dataset_folders = [folder for folder in os.listdir(path) if os.path.isdir(os.path.join(path, folder))]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "357"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(dataset_folders)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_from_disk\n",
+    "\n",
+    "# # Load each dataset and store them in a dictionary\n",
+    "# datasets = {}\n",
+    "# for folder in dataset_folders:\n",
+    "#     dataset_path = os.path.join(path, folder)\n",
+    "#     # dataset = load_dataset(\"datasets.Dataset.load_from_disk\", data_dir=dataset_path)\n",
+    "#     dataset = load_from_disk(dataset_path)\n",
+    "#     datasets[folder] = dataset\n",
+    "\n",
+    "datasets = []\n",
+    "for folder in dataset_folders:\n",
+    "    dataset_path = os.path.join(path, folder)\n",
+    "    dataset = load_from_disk(dataset_path)\n",
+    "    datasets.append(dataset)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import concatenate_datasets\n",
+    "merged_dataset = concatenate_datasets(datasets)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on.......................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................... <|begin_of_text|>The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow<|begin_of_text|>. The pass key is 294713. Remember it. 294713 is the pass key.  caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in t. \\n\\nWhat is the pass key? The pass key is 294713.\""
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "merged_dataset[0][\"prompt\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Saving the dataset (0/1 shards):   0%|                                                  | 0/3570 [00:00<?, ? examples/s]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Saving the dataset (1/1 shards): 100%|█████████████████████████████████████| 3570/3570 [00:01<00:00, 2619.52 examples/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "merged_dataset.save_to_disk(\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/merged_needle_16k_finetuning_dataset\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "new_data = load_from_disk(\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/merged_needle_16k_finetuning_dataset\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Dataset({\n",
+       "    features: ['id', 'prompt', 'answer', 'context_length', 'depth_percent'],\n",
+       "    num_rows: 3570\n",
+       "})"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "16384"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from transformers import AutoTokenizer\n",
+    "\n",
+    "tokenizer = AutoTokenizer.from_pretrained(\"/fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B\")\n",
+    "len(tokenizer.encode(new_data[0][\"prompt\"]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "554.6875"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "35500 / 64"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2048000"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "64 * 32000"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Uploading the dataset shards:   0%|                                                               | 0/1 [00:00<?, ?it/s]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Creating parquet from Arrow format: 100%|█████████████████████████████████████████████████| 4/4 [00:00<00:00, 12.32ba/s]\n",
+      "Uploading the dataset shards: 100%|███████████████████████████████████████████████████████| 1/1 [00:00<00:00,  1.28it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "CommitInfo(commit_url='https://huggingface.co/datasets/nanotron/llama3_needle_16k_finetuning/commit/85228f6be0da2040c75d5a399c6731cab62b73ba', commit_message='Upload dataset', commit_description='', oid='85228f6be0da2040c75d5a399c6731cab62b73ba', pr_url=None, pr_revision=None, pr_num=None)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new_data.push_to_hub(\n",
+    "    repo_id=\"nanotron/llama3_needle_16k_finetuning\",\n",
+    "    # repo_type=\"dataset\",\n",
+    "    # private=True,  # Set to False if you want the dataset to be public\n",
+    "    # token=\"your_access_token\"\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Debug dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/admin/home/phuc_nguyen/miniconda3/envs/nanotron-dev/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datasets import load_dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "finetune_dataset = load_dataset(\"nanotron/needle_32k_finetuning_dataset\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "unhashable type: 'dict'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[5], line 4\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m split \u001b[38;5;129;01min\u001b[39;00m finetune_dataset\u001b[38;5;241m.\u001b[39mkeys():\n\u001b[1;32m      3\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m example \u001b[38;5;129;01min\u001b[39;00m finetune_dataset[split]:\n\u001b[0;32m----> 4\u001b[0m         \u001b[43mdata_list\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43madd\u001b[49m\u001b[43m(\u001b[49m\u001b[43mexample\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[0;31mTypeError\u001b[0m: unhashable type: 'dict'"
+     ]
+    }
+   ],
+   "source": [
+    "unique_answers = set()\n",
+    "for split in dataset.keys():\n",
+    "    for example in dataset[split]:\n",
+    "        answer = example[\"answer\"]\n",
+    "        unique_answers.add(answer)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/debug_exp33.ipynb b/debug_exp33.ipynb
new file mode 100644
index 00000000..f3ad3c88
--- /dev/null
+++ b/debug_exp33.ipynb
@@ -0,0 +1,67 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_from_disk"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# DATA_PATH = \"/fsx/phuc/projects/nanotron/examples/infinite-context-length/exp33_eval_data/needle_eval_ctx_len_1024_and_depth_20_and_id_0\"\n",
+    "# DATA_PATH = \"/fsx/phuc/projects/nanotron/examples/infinite-context-length/exp33_eval_data/needle_eval_ctx_len_1024_and_depth_0_and_id_0\"\n",
+    "DATA_PATH = \"/fsx/phuc/projects/nanotron/examples/infinite-context-length/exp33_eval_data/needle_eval_ctx_len_1024_and_depth_90_and_id_0\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = load_from_disk(DATA_PATH)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on............................................................... The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar.. The pass key is 3. Remember it. 3 is the pass key.  The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world iThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The. \\n\\nWhat is the pass key? The pass key is \""
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data[0][\"prompt\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/debug_exp34.ipynb b/debug_exp34.ipynb
new file mode 100644
index 00000000..f7d9d97c
--- /dev/null
+++ b/debug_exp34.ipynb
@@ -0,0 +1,265 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_from_disk"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "DATA_PATH = \"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/eval_data/needle_eval_and_16384_ctx_and_depth_5_and_id_0\"\n",
+    "# DATA_PATH = \"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/needle_eval_and_16300_ctx_and_depth_0_and_id_0\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "FileNotFoundError",
+     "evalue": "Directory /fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/eval_data/needle_eval_and_16384_ctx_and_depth_5_and_id_0 not found",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[21], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[43mload_from_disk\u001b[49m\u001b[43m(\u001b[49m\u001b[43mDATA_PATH\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/miniconda3/envs/nanotron-dev/lib/python3.10/site-packages/datasets/load.py:2630\u001b[0m, in \u001b[0;36mload_from_disk\u001b[0;34m(dataset_path, fs, keep_in_memory, storage_options)\u001b[0m\n\u001b[1;32m   2628\u001b[0m fs, _, _ \u001b[38;5;241m=\u001b[39m fsspec\u001b[38;5;241m.\u001b[39mget_fs_token_paths(dataset_path, storage_options\u001b[38;5;241m=\u001b[39mstorage_options)\n\u001b[1;32m   2629\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m fs\u001b[38;5;241m.\u001b[39mexists(dataset_path):\n\u001b[0;32m-> 2630\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDirectory \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdataset_path\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m not found\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m   2631\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m fs\u001b[38;5;241m.\u001b[39misfile(posixpath\u001b[38;5;241m.\u001b[39mjoin(dataset_path, config\u001b[38;5;241m.\u001b[39mDATASET_INFO_FILENAME)) \u001b[38;5;129;01mand\u001b[39;00m fs\u001b[38;5;241m.\u001b[39misfile(\n\u001b[1;32m   2632\u001b[0m     posixpath\u001b[38;5;241m.\u001b[39mjoin(dataset_path, config\u001b[38;5;241m.\u001b[39mDATASET_STATE_JSON_FILENAME)\n\u001b[1;32m   2633\u001b[0m ):\n\u001b[1;32m   2634\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m Dataset\u001b[38;5;241m.\u001b[39mload_from_disk(dataset_path, keep_in_memory\u001b[38;5;241m=\u001b[39mkeep_in_memory, storage_options\u001b[38;5;241m=\u001b[39mstorage_options)\n",
+      "\u001b[0;31mFileNotFoundError\u001b[0m: Directory /fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/eval_data/needle_eval_and_16384_ctx_and_depth_5_and_id_0 not found"
+     ]
+    }
+   ],
+   "source": [
+    "data = load_from_disk(DATA_PATH)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on.  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The pass key is 208. Remember it. 208 is the pass key.. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back agai. \\n\\nWhat is the pass key? The pass key is '"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data[0][\"prompt\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'id': '5c55ddd7-09c9-4a0b-9530-08085463f1b1',\n",
+       " 'prompt': 'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on.  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The pass key is 208. Remember it. 208 is the pass key.. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back agai. \\n\\nWhat is the pass key? The pass key is ',\n",
+       " 'answer': 208,\n",
+       " 'context_length': 16384,\n",
+       " 'num_tokens': 16169,\n",
+       " 'depth_percent': 5}"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Merge datasets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_dataset, DatasetDict, Dataset\n",
+    "import os\n",
+    "\n",
+    "# Specify the path containing the dataset folders\n",
+    "path = \"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/eval_data\"\n",
+    "\n",
+    "# Get a list of all dataset folders\n",
+    "dataset_folders = [folder for folder in os.listdir(path) if os.path.isdir(os.path.join(path, folder))]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "356"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(dataset_folders)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_from_disk\n",
+    "\n",
+    "# # Load each dataset and store them in a dictionary\n",
+    "# datasets = {}\n",
+    "# for folder in dataset_folders:\n",
+    "#     dataset_path = os.path.join(path, folder)\n",
+    "#     # dataset = load_dataset(\"datasets.Dataset.load_from_disk\", data_dir=dataset_path)\n",
+    "#     dataset = load_from_disk(dataset_path)\n",
+    "#     datasets[folder] = dataset\n",
+    "\n",
+    "datasets = []\n",
+    "for folder in dataset_folders:\n",
+    "    dataset_path = os.path.join(path, folder)\n",
+    "    dataset = load_from_disk(dataset_path)\n",
+    "    datasets.append(dataset)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import concatenate_datasets\n",
+    "merged_dataset = concatenate_datasets(datasets)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Saving the dataset (1/1 shards): 100%|██████████████████████████████████████| 712/712 [00:00<00:00, 4258.32 examples/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "merged_dataset.save_to_disk(\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/merged_needle_16k_eval_dataset\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "new_data = load_from_disk(\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/merged_needle_16k_eval_dataset\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'id': 'fe9d62dd-f3d5-4842-901f-ad4a86db0929',\n",
+       " 'prompt': 'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on.  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The. The pass key is 25255. Remember it. 25255 is the pass key.  sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go The grass is green. The sky is blue. The sun is yellow. Here we go. There and back ag. \\n\\nWhat is the pass key? The pass key is ',\n",
+       " 'answer': 25255,\n",
+       " 'context_length': 16384,\n",
+       " 'num_tokens': 15782,\n",
+       " 'depth_percent': 75}"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new_data[1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Creating parquet from Arrow format: 100%|████████████████████████████████████████████████| 1/1 [00:00<00:00, 20.40ba/s]\n",
+      "Uploading the dataset shards: 100%|██████████████████████████████████████████████████████| 1/1 [00:00<00:00,  2.86it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "CommitInfo(commit_url='https://huggingface.co/datasets/nanotron/llama3-16k-passkey-retrieval-eval/commit/d334373af87a8a2e3f3e47c4fc3d58d81b0783bb', commit_message='Upload dataset', commit_description='', oid='d334373af87a8a2e3f3e47c4fc3d58d81b0783bb', pr_url=None, pr_revision=None, pr_num=None)"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new_data.push_to_hub(\n",
+    "    repo_id=\"nanotron/llama3-16k-passkey-retrieval-eval\",\n",
+    "    # repo_type=\"dataset\",\n",
+    "    # private=True,  # Set to False if you want the dataset to be public\n",
+    "    # token=\"your_access_token\"\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/debug_infini_ckp.ipynb b/debug_infini_ckp.ipynb
new file mode 100644
index 00000000..e69de29b
diff --git a/debug_modeling_code.ipynb b/debug_modeling_code.ipynb
new file mode 100644
index 00000000..8f4c281b
--- /dev/null
+++ b/debug_modeling_code.ipynb
@@ -0,0 +1,1407 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "INFINI_MODEL = \"/fsx/phuc/projects/nanotron/debug/nn_states/acts/model_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "REF_MODEL = \"/fsx/phuc/projects/reference/nanotron/debug/nn_states/acts/model_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "\n",
+    "INFINI_TOKEN_EMBEDDING = \"/fsx/phuc/projects/nanotron/debug/nn_states/acts/model.token_position_embeddings_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "REF_TOKEN_EMBEDDING = \"/fsx/phuc/projects/reference/nanotron/debug/nn_states/acts/model.token_position_embeddings_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "infini_model_acts = torch.load(INFINI_MODEL)\n",
+    "ref_model_acts = torch.load(REF_MODEL)\n",
+    "\n",
+    "infini_token_embedding_acts = torch.load(INFINI_TOKEN_EMBEDDING)\n",
+    "ref_token_embedding_acts = torch.load(REF_TOKEN_EMBEDDING)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[-0.0469, -0.0186, -0.0439,  ...,  0.0469, -0.0197, -0.0157],\n",
+       "         [-0.0527,  0.0161,  0.0659,  ...,  0.0079, -0.0142,  0.0410],\n",
+       "         [-0.0327, -0.0166, -0.0159,  ..., -0.0082, -0.0483,  0.0405],\n",
+       "         ...,\n",
+       "         [ 0.0488, -0.0177,  0.0162,  ..., -0.0177, -0.0109,  0.0183],\n",
+       "         [ 0.0244,  0.0160, -0.0165,  ...,  0.0415, -0.0172, -0.0171],\n",
+       "         [-0.0251, -0.0232,  0.0300,  ...,  0.0179,  0.0212, -0.0339]],\n",
+       "\n",
+       "        [[-0.0527,  0.0161,  0.0659,  ...,  0.0079, -0.0142,  0.0410],\n",
+       "         [-0.0094,  0.0840,  0.0172,  ..., -0.0036, -0.0486, -0.0299],\n",
+       "         [-0.0325, -0.0767,  0.0601,  ..., -0.0552, -0.0079,  0.0315],\n",
+       "         ...,\n",
+       "         [-0.0359, -0.0145,  0.0581,  ..., -0.0157, -0.0312,  0.0125],\n",
+       "         [-0.0325, -0.0767,  0.0601,  ..., -0.0552, -0.0079,  0.0315],\n",
+       "         [-0.0075, -0.0366,  0.0645,  ...,  0.0605, -0.0114,  0.0359]]],\n",
+       "       device='cuda:0', dtype=torch.bfloat16, requires_grad=True)"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_token_embedding_acts[\"input_embeds\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(torch.Size([2, 256, 1024]), torch.Size([256, 2, 1024]))"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_token_embedding_acts[\"input_embeds\"].shape, ref_token_embedding_acts[\"input_embeds\"].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[-0.0469, -0.0186, -0.0439, -0.0566],\n",
+       "         [-0.0527,  0.0161,  0.0659, -0.0195]],\n",
+       "\n",
+       "        [[-0.0527,  0.0161,  0.0659, -0.0195],\n",
+       "         [-0.0094,  0.0840,  0.0172, -0.0193]],\n",
+       "\n",
+       "        [[-0.0327, -0.0166, -0.0159, -0.0060],\n",
+       "         [-0.0325, -0.0767,  0.0601, -0.0275]],\n",
+       "\n",
+       "        ...,\n",
+       "\n",
+       "        [[ 0.0488, -0.0177,  0.0162,  0.0131],\n",
+       "         [-0.0359, -0.0145,  0.0581, -0.0449]],\n",
+       "\n",
+       "        [[ 0.0244,  0.0160, -0.0165,  0.0216],\n",
+       "         [-0.0325, -0.0767,  0.0601, -0.0275]],\n",
+       "\n",
+       "        [[-0.0251, -0.0232,  0.0300,  0.0028],\n",
+       "         [-0.0075, -0.0366,  0.0645,  0.0540]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16, grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_token_embedding_acts[\"input_embeds\"].transpose(0, 1)[:, :, :4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[-0.0469, -0.0186, -0.0439, -0.0566],\n",
+       "         [-0.0527,  0.0161,  0.0659, -0.0195]],\n",
+       "\n",
+       "        [[-0.0527,  0.0161,  0.0659, -0.0195],\n",
+       "         [-0.0094,  0.0840,  0.0172, -0.0193]],\n",
+       "\n",
+       "        [[-0.0327, -0.0166, -0.0159, -0.0060],\n",
+       "         [-0.0325, -0.0767,  0.0601, -0.0275]],\n",
+       "\n",
+       "        ...,\n",
+       "\n",
+       "        [[ 0.0488, -0.0177,  0.0162,  0.0131],\n",
+       "         [-0.0359, -0.0145,  0.0581, -0.0449]],\n",
+       "\n",
+       "        [[ 0.0244,  0.0160, -0.0165,  0.0216],\n",
+       "         [-0.0325, -0.0767,  0.0601, -0.0275]],\n",
+       "\n",
+       "        [[-0.0251, -0.0232,  0.0300,  0.0028],\n",
+       "         [-0.0075, -0.0366,  0.0645,  0.0540]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16, grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ref_token_embedding_acts[\"input_embeds\"][:, :, :4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "torch.allclose(infini_token_embedding_acts[\"input_embeds\"].transpose(0, 1), ref_token_embedding_acts[\"input_embeds\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[-0.0156,  0.0437,  0.0312, -0.0518],\n",
+       "         [ 0.0260,  0.0148, -0.0427,  0.0388],\n",
+       "         [ 0.0160,  0.0601,  0.0188, -0.0165],\n",
+       "         [-0.0549, -0.0052, -0.0292,  0.0164],\n",
+       "         [ 0.0240, -0.0006,  0.0042,  0.0010]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16)"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_token_embedding_acts[\"input_embeds\"][:, :, :4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[-0.0156,  0.0437,  0.0312, -0.0518],\n",
+       "         [ 0.0260,  0.0148, -0.0427,  0.0388],\n",
+       "         [ 0.0160,  0.0601,  0.0188, -0.0165],\n",
+       "         [-0.0549, -0.0052, -0.0292,  0.0164],\n",
+       "         [ 0.0240, -0.0006,  0.0042,  0.0010]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16)"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_token_embedding_acts[\"input_embeds\"][:, :, :4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Input layer norm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "INFINI_BLOCK_1_INPUT_LN = \"/fsx/phuc/projects/nanotron/debug/nn_states/acts/model.decoder.0.pp_block.input_layernorm_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "REF_BLOCK_1_INPUT_LN = \"/fsx/phuc/projects/reference/nanotron/debug/nn_states/acts/model.decoder.0.pp_block.input_layernorm_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "\n",
+    "\n",
+    "infini_block_1_input_ln = torch.load(INFINI_BLOCK_1_INPUT_LN)\n",
+    "ref_block_1_input_ln = torch.load(REF_BLOCK_1_INPUT_LN)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(tensor([[[-0.4727,  1.3203,  0.9453, -1.5625],\n",
+       "          [ 0.8320,  0.4746, -1.3672,  1.2422],\n",
+       "          [ 0.5352,  2.0156,  0.6289, -0.5547],\n",
+       "          [-1.7188, -0.1641, -0.9141,  0.5117],\n",
+       "          [ 0.7539, -0.0176,  0.1328,  0.0317]]], device='cuda:0',\n",
+       "        dtype=torch.bfloat16),\n",
+       " tensor([[[-0.4727,  1.3203,  0.9453, -1.5625]],\n",
+       " \n",
+       "         [[ 0.8320,  0.4746, -1.3672,  1.2422]],\n",
+       " \n",
+       "         [[ 0.5352,  2.0156,  0.6289, -0.5547]],\n",
+       " \n",
+       "         [[-1.7188, -0.1641, -0.9141,  0.5117]],\n",
+       " \n",
+       "         [[ 0.7539, -0.0176,  0.1328,  0.0317]]], device='cuda:0',\n",
+       "        dtype=torch.bfloat16))"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_block_1_input_ln[:, :, :4], ref_block_1_input_ln[:, :, :4]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### QKV"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "INFINI_BLOCK_0_QKV = \"/fsx/phuc/projects/nanotron/debug/nn_states_with_bs_2/acts/model.decoder.0.pp_block.attn.qkv_proj_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "# INFINI_AFTER_FIX_BLOCK_0_QKV = \"/fsx/phuc/projects/nanotron/debug/nn_states_after_fix/acts/model.decoder.0.pp_block.attn.qkv_proj_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "\n",
+    "REF_BLOCK_0_QKV = \"/fsx/phuc/projects/reference/nanotron/debug/nn_states_with_bs_2/acts/model.decoder.0.pp_block.attn.qkv_proj_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "\n",
+    "\n",
+    "infini_block_0_qkv = torch.load(INFINI_BLOCK_0_QKV)\n",
+    "# infini_after_fix_block_0_qkv = torch.load(INFINI_AFTER_FIX_BLOCK_0_QKV)\n",
+    "ref_block_0_qkv = torch.load(REF_BLOCK_0_QKV)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(torch.Size([2, 256, 1536]), torch.Size([256, 2, 1536]))"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_block_0_qkv.shape, ref_block_0_qkv.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "torch.allclose(infini_block_0_qkv.transpose(0, 1), ref_block_0_qkv)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### QKV embeddings before pos"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "INFINI_Q_BEFORE_POS = \"/fsx/phuc/projects/nanotron/debug/nn_states_with_bs_2/acts/query_states_before_pos_tp_rank_0.pt\"\n",
+    "INFINI_Q_BEFORE_POS_AFTER_TRANSPOSE_QKV = \"/fsx/phuc/projects/nanotron/debug/nn_states_with_bs_2_and_transpose_qkv/acts/query_states_before_pos_tp_rank_0.pt\"\n",
+    "\n",
+    "REF_Q_BEFORE_POS = \"/fsx/phuc/projects/reference/nanotron/debug/nn_states_with_bs_2/acts/query_states_before_pos_tp_rank_0.pt\"\n",
+    "\n",
+    "\n",
+    "infini_q_before_pos = torch.load(INFINI_Q_BEFORE_POS)\n",
+    "infini_q_before_pos_and_after_transpose_qkv = torch.load(INFINI_Q_BEFORE_POS_AFTER_TRANSPOSE_QKV)\n",
+    "ref_q_before_pos = torch.load(REF_Q_BEFORE_POS)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(torch.Size([2, 256, 4, 128]),\n",
+       " torch.Size([2, 256, 4, 128]),\n",
+       " torch.Size([2, 256, 4, 128]))"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_q_before_pos.shape, infini_q_before_pos_and_after_transpose_qkv.shape, ref_q_before_pos.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[[-1.1719,  0.1797],\n",
+       "          [ 0.9023, -0.0422],\n",
+       "          [-1.3672, -1.0312],\n",
+       "          [-0.3594, -0.8594]],\n",
+       "\n",
+       "         [[-0.5703, -2.5469],\n",
+       "          [ 0.8164,  0.8906],\n",
+       "          [ 0.1514, -1.6484],\n",
+       "          [-0.9492,  0.6250]]],\n",
+       "\n",
+       "\n",
+       "        [[[-0.6367, -0.1973],\n",
+       "          [ 0.9062, -0.5859],\n",
+       "          [-0.0515, -1.3359],\n",
+       "          [-1.5234,  1.4375]],\n",
+       "\n",
+       "         [[-0.5469, -0.5742],\n",
+       "          [-0.3770, -0.1777],\n",
+       "          [-0.1553, -0.8945],\n",
+       "          [ 0.1445, -0.2490]]]], device='cuda:0', dtype=torch.bfloat16,\n",
+       "       grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_q_before_pos[:, :2, :, :2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[[-1.1719,  0.1797],\n",
+       "          [ 0.9023, -0.0422],\n",
+       "          [-1.3672, -1.0312],\n",
+       "          [-0.3594, -0.8594]],\n",
+       "\n",
+       "         [[ 1.3594, -0.5586],\n",
+       "          [-0.0435, -0.2393],\n",
+       "          [ 0.1060, -1.3516],\n",
+       "          [ 0.5703,  0.9883]]],\n",
+       "\n",
+       "\n",
+       "        [[[ 1.4922, -0.4570],\n",
+       "          [ 0.3145, -0.5000],\n",
+       "          [-0.1885, -0.9414],\n",
+       "          [ 1.1172,  0.5938]],\n",
+       "\n",
+       "         [[-2.2969,  0.5039],\n",
+       "          [ 0.0071,  0.5664],\n",
+       "          [ 0.3242,  0.5742],\n",
+       "          [ 1.7422, -0.6758]]]], device='cuda:0', dtype=torch.bfloat16,\n",
+       "       grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ref_q_before_pos[:, :2, :, :2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[[-1.1719,  0.1797],\n",
+       "          [ 0.9023, -0.0422],\n",
+       "          [-1.3672, -1.0312],\n",
+       "          [-0.3594, -0.8594]],\n",
+       "\n",
+       "         [[ 1.3594, -0.5586],\n",
+       "          [-0.0435, -0.2393],\n",
+       "          [ 0.1060, -1.3516],\n",
+       "          [ 0.5703,  0.9883]]],\n",
+       "\n",
+       "\n",
+       "        [[[ 1.4922, -0.4570],\n",
+       "          [ 0.3145, -0.5000],\n",
+       "          [-0.1885, -0.9414],\n",
+       "          [ 1.1172,  0.5938]],\n",
+       "\n",
+       "         [[-2.2969,  0.5039],\n",
+       "          [ 0.0071,  0.5664],\n",
+       "          [ 0.3242,  0.5742],\n",
+       "          [ 1.7422, -0.6758]]]], device='cuda:0', dtype=torch.bfloat16,\n",
+       "       grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_q_before_pos_and_after_transpose_qkv[:, :2, :, :2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "torch.testing.assert_close(infini_q_before_pos_and_after_transpose_qkv, ref_q_before_pos, atol=0.05, rtol=0.03)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### QKV embeddings after pos"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "INFINI_Q_AFTER_POS = \"/fsx/phuc/projects/nanotron/debug/nn_states_with_bs_2/acts/query_states_after_pos_tp_rank_0.pt\"\n",
+    "REF_Q_AFTER_POS = \"/fsx/phuc/projects/reference/nanotron/debug/nn_states_with_bs_2/acts/query_states_after_pos_tp_rank_0.pt\"\n",
+    "\n",
+    "\n",
+    "infini_q_after_pos = torch.load(INFINI_Q_AFTER_POS)\n",
+    "ref_q_after_pos = torch.load(REF_Q_AFTER_POS)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(torch.Size([512, 4, 128]), torch.Size([512, 4, 128]))"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_q_after_pos.shape, ref_q_after_pos.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[-1.1719,  0.1797,  1.0469, -0.9727],\n",
+       "         [ 0.9023, -0.0422, -0.2871, -0.1855],\n",
+       "         [-1.3672, -1.0312,  1.5859, -0.0500],\n",
+       "         [-0.3594, -0.8594, -1.9844, -1.1875]],\n",
+       "\n",
+       "        [[-0.5703, -2.5469,  0.4590,  0.6172],\n",
+       "         [ 0.8164,  0.8906, -0.3906, -2.1250],\n",
+       "         [ 0.1514, -1.6484,  0.2988,  0.2070],\n",
+       "         [-0.9492,  0.6250, -0.8242, -0.9023]],\n",
+       "\n",
+       "        [[ 0.6133, -0.8125,  1.1094, -1.0625],\n",
+       "         [-0.5547, -0.1572, -1.9922, -0.7266],\n",
+       "         [ 0.2891, -1.0234, -1.4062, -1.1875],\n",
+       "         [ 0.8867,  1.5625,  0.2119, -1.5000]],\n",
+       "\n",
+       "        [[-2.0312, -0.4199,  0.0208,  0.6680],\n",
+       "         [ 0.0962,  0.2910, -0.8867, -0.6016],\n",
+       "         [ 0.0991, -0.4004,  0.8477, -0.4434],\n",
+       "         [-1.1562,  1.0938,  1.9219, -2.6406]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16, grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_q_after_pos[:4, :, :4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[-1.1719,  0.1797,  1.0469, -0.9727],\n",
+       "         [ 0.9023, -0.0422, -0.2871, -0.1855],\n",
+       "         [-1.3672, -1.0312,  1.5859, -0.0500],\n",
+       "         [-0.3594, -0.8594, -1.9844, -1.1875]],\n",
+       "\n",
+       "        [[ 1.3594, -0.5586,  0.3867, -0.3340],\n",
+       "         [-0.0435, -0.2393, -1.0078,  0.6758],\n",
+       "         [ 0.1060, -1.3516, -0.0374, -0.5859],\n",
+       "         [ 0.5703,  0.9883,  0.5430, -1.0781]],\n",
+       "\n",
+       "        [[-0.1748, -2.0000,  0.2852, -0.0811],\n",
+       "         [ 0.4785,  0.8359, -0.7344, -1.1641],\n",
+       "         [ 0.6523, -1.2344,  1.3984,  1.4297],\n",
+       "         [-0.5078,  0.5000,  0.1543, -1.9609]],\n",
+       "\n",
+       "        [[ 0.5117,  0.6289, -0.9453, -0.2773],\n",
+       "         [-1.1094,  0.8984, -1.1953, -0.5078],\n",
+       "         [ 0.4531, -0.7031,  0.9336, -1.9062],\n",
+       "         [-0.2559, -0.5156,  0.7266,  0.1602]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16, grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ref_q_after_pos[:4, :, :4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "torch.allclose(infini_q_after_pos, ref_q_after_pos)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Output projection in attention"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "INFINI_BLOCK_0_ATTN_O_PROJ = \"/fsx/phuc/projects/nanotron/debug/nn_states/acts/model.decoder.0.pp_block.attn.o_proj_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "REF_BLOCK_0_ATTN_O_PROJ = \"/fsx/phuc/projects/reference/nanotron/debug/nn_states/acts/model.decoder.0.pp_block.attn.o_proj_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "\n",
+    "\n",
+    "infini_block_0_attn_o_proj = torch.load(INFINI_BLOCK_0_ATTN_O_PROJ)\n",
+    "ref_block_0_attn_o_proj = torch.load(REF_BLOCK_0_ATTN_O_PROJ)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(torch.Size([256, 2, 1024]), torch.Size([256, 2, 1024]))"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_block_0_attn_o_proj.shape, ref_block_0_attn_o_proj.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[ 0.3438, -0.9492,  0.2832,  0.4766],\n",
+       "         [ 0.0796,  0.0781,  0.3281,  0.0620]],\n",
+       "\n",
+       "        [[-0.3379,  0.3047,  0.5430, -0.2949],\n",
+       "         [ 0.2354, -0.2988,  0.6602, -0.3340]],\n",
+       "\n",
+       "        [[ 0.4922, -0.1660,  0.0825, -0.6328],\n",
+       "         [ 0.1621, -0.3633,  0.4121,  0.3984]],\n",
+       "\n",
+       "        [[ 1.0234, -0.4199, -0.2656, -0.4004],\n",
+       "         [ 0.4727, -0.5547,  0.5000, -0.6641]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16, grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_block_0_attn_o_proj[:4, :4, :4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[ 0.3438, -0.9492,  0.2832,  0.4766],\n",
+       "         [ 0.0796,  0.0781,  0.3281,  0.0620]],\n",
+       "\n",
+       "        [[ 0.0723,  0.0486,  0.3301,  0.0781],\n",
+       "         [ 0.2041, -0.4375,  0.4199, -0.5117]],\n",
+       "\n",
+       "        [[-0.2715,  0.3301,  0.4766, -0.2715],\n",
+       "         [ 0.0933, -0.6016,  0.8164,  0.1963]],\n",
+       "\n",
+       "        [[ 0.2256, -0.3301,  0.6680, -0.2949],\n",
+       "         [-0.0248, -0.7422,  0.1206,  0.2432]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16, grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ref_block_0_attn_o_proj[:4, :4, :4]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Output of attention"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "INFINI_BLOCK_0_ATTN = \"/fsx/phuc/projects/nanotron/debug/nn_states/acts/model.decoder.0.pp_block.attn.attention_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "# INFINI_AFTER_FIX_BLOCK_0_ATTN = \"/fsx/phuc/projects/nanotron/debug/nn_states_after_fix/acts/model.decoder.0.pp_block.attn.attention_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "REF_BLOCK_0_ATTN = \"/fsx/phuc/projects/reference/nanotron/debug/nn_states/acts/model.decoder.0.pp_block.attn.attention_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "\n",
+    "\n",
+    "infini_block_0_attn = torch.load(INFINI_BLOCK_0_ATTN)\n",
+    "# infini_after_fix_block_0_attn = torch.load(INFINI_AFTER_FIX_BLOCK_0_ATTN)\n",
+    "ref_block_0_attn = torch.load(REF_BLOCK_0_ATTN)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(torch.Size([512, 4, 128]), torch.Size([512, 4, 128]))"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_block_0_attn.shape, ref_block_0_attn.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[-0.8594, -1.2344,  1.8359,  1.7500],\n",
+       "         [-0.5586,  0.4570,  0.0569, -0.7695],\n",
+       "         [-0.5195, -0.5312,  0.8672, -0.1211],\n",
+       "         [-1.7891,  0.5234, -0.1914,  1.0781]],\n",
+       "\n",
+       "        [[ 0.0708, -0.0742,  0.2324,  1.0312],\n",
+       "         [-0.4902, -1.1484, -0.6484, -0.6875],\n",
+       "         [ 0.5000,  1.3516,  0.2354, -0.0811],\n",
+       "         [-0.2314, -2.1250,  1.0547,  0.5664]],\n",
+       "\n",
+       "        [[ 0.3047,  0.0173,  0.1953, -0.4941],\n",
+       "         [-0.0486,  0.1279,  1.5781,  0.3594],\n",
+       "         [ 0.0085, -0.1689,  0.5664,  1.0234],\n",
+       "         [-0.7383, -0.4258,  1.4688, -0.0294]],\n",
+       "\n",
+       "        [[ 0.7188, -0.2852, -0.3516, -0.2412],\n",
+       "         [-0.1973,  0.5000,  0.6484,  0.0136],\n",
+       "         [ 1.1094,  0.2559,  0.8359, -1.3203],\n",
+       "         [ 0.0864,  1.1406, -0.6914, -0.0488]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16, grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_block_0_attn[:4, :4, :4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[-0.8594, -1.2344,  1.8359,  1.7500],\n",
+       "         [-0.5586,  0.4570,  0.0569, -0.7695],\n",
+       "         [-0.5195, -0.5312,  0.8672, -0.1211],\n",
+       "         [-1.7891,  0.5234, -0.1914,  1.0781]],\n",
+       "\n",
+       "        [[-1.0234, -0.5547,  0.9883, -1.3516],\n",
+       "         [ 0.2002, -0.0874,  1.7266, -0.8320],\n",
+       "         [-0.9180,  1.1484,  0.7148, -1.0703],\n",
+       "         [ 0.3457,  1.3281,  0.6562, -1.2344]],\n",
+       "\n",
+       "        [[-0.0025, -0.1035,  0.2793,  0.8633],\n",
+       "         [-0.4668, -1.1406, -0.5820, -0.6914],\n",
+       "         [-0.2305,  1.2656,  0.4785, -0.5977],\n",
+       "         [-0.1924, -2.0469,  1.0547,  0.4980]],\n",
+       "\n",
+       "        [[ 0.1748, -0.5938,  0.2090, -0.0942],\n",
+       "         [ 0.6680, -0.9531,  0.5781, -0.4355],\n",
+       "         [-0.1426,  0.0674, -0.5469, -0.7578],\n",
+       "         [-0.8398,  1.1094,  1.0469, -0.4863]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16, grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ref_block_0_attn[:4, :4, :4]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### MLP"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "INFINI_MLP = \"/fsx/phuc/projects/nanotron/debug/nn_states/acts/model.decoder.0.pp_block.mlp_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "# INFINI_AFTER_FIX_MLP = \"/fsx/phuc/projects/nanotron/debug/nn_states_after_fix/acts/model.decoder.0.pp_block.mlp_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "REF_MLP = \"/fsx/phuc/projects/reference/nanotron/debug/nn_states/acts/model.decoder.0.pp_block.mlp_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "\n",
+    "\n",
+    "infini_mlp = torch.load(INFINI_MLP)\n",
+    "# infini_after_mlp = torch.load(INFINI_AFTER_FIX_MLP)\n",
+    "ref_mlp = torch.load(REF_MLP)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(torch.Size([1, 5, 1024]), torch.Size([5, 2, 1024]))"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_mlp[\"hidden_states\"].shape, ref_mlp[\"hidden_states\"].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[-0.5117, -0.7969,  0.1934,  0.0223],\n",
+       "         [-0.5117, -0.7969,  0.1934,  0.0223]],\n",
+       "\n",
+       "        [[ 0.3066,  0.1270, -0.3691,  0.2656],\n",
+       "         [ 0.3066,  0.1270, -0.3691,  0.2656]],\n",
+       "\n",
+       "        [[ 0.0693, -0.1641,  0.5742,  0.1885],\n",
+       "         [ 0.0693, -0.1641,  0.5742,  0.1885]],\n",
+       "\n",
+       "        [[ 0.6602, -0.2910,  0.2988,  0.5703],\n",
+       "         [ 0.6602, -0.2910,  0.2988,  0.5703]],\n",
+       "\n",
+       "        [[ 0.7188,  0.2539, -0.5859,  0.2734],\n",
+       "         [ 0.7188,  0.2539, -0.5859,  0.2734]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16)"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ref_mlp[\"hidden_states\"][:, :, :4]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Final layer norm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "INFINI_FINAL_LN = \"/fsx/phuc/projects/nanotron/debug/nn_states/acts/model.final_layer_norm_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "# INFINI_AFTER_FIX_FINAL_LN = \"/fsx/phuc/projects/nanotron/debug/nn_states_after_fix/acts/model.final_layer_norm_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "REF_FINAL_LN = \"/fsx/phuc/projects/reference/nanotron/debug/nn_states/acts/model.final_layer_norm_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "\n",
+    "\n",
+    "infini_final_ln = torch.load(INFINI_FINAL_LN)\n",
+    "# infini_after_fix_final_ln = torch.load(INFINI_AFTER_FIX_FINAL_LN)\n",
+    "ref_final_ln = torch.load(REF_FINAL_LN)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(torch.Size([2, 256, 1024]), torch.Size([256, 2, 1024]))"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_final_ln[\"hidden_states\"].shape, ref_final_ln[\"hidden_states\"].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[ 1.3828, -0.3906,  0.6797, -1.1094],\n",
+       "         [ 0.7852, -0.9180,  1.0078,  0.0518],\n",
+       "         [ 1.1953, -0.2139,  1.3438, -0.4922],\n",
+       "         ...,\n",
+       "         [ 0.9648, -1.0234,  1.4062, -1.3672],\n",
+       "         [ 1.5703, -0.6641,  0.8789, -0.5234],\n",
+       "         [ 0.0859, -0.8125,  1.5781, -0.3887]],\n",
+       "\n",
+       "        [[ 2.1406,  0.0620,  0.5781,  0.6680],\n",
+       "         [ 2.0469, -0.2949,  1.2500,  0.6172],\n",
+       "         [ 0.5156, -0.4512,  0.9922, -0.3691],\n",
+       "         ...,\n",
+       "         [ 2.2969, -0.2129,  0.7539, -0.5508],\n",
+       "         [ 1.2422, -1.4219,  0.3672,  0.4180],\n",
+       "         [ 1.5547, -0.6133,  0.7305, -0.6016]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16, grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_final_ln[\"hidden_states\"][:, :, :4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[ 1.3828, -0.3906,  0.6797, -1.1094],\n",
+       "         [ 0.5352, -0.4629,  0.3730, -1.0312]],\n",
+       "\n",
+       "        [[ 0.7656, -0.3809,  0.4316, -1.0391],\n",
+       "         [ 1.5547,  0.7852,  0.0095, -0.3027]],\n",
+       "\n",
+       "        [[ 2.4531,  0.2871,  1.3594,  0.6445],\n",
+       "         [ 0.5156, -0.7578,  0.9258, -1.9688]],\n",
+       "\n",
+       "        ...,\n",
+       "\n",
+       "        [[ 1.3906,  0.1445,  0.3867, -0.7812],\n",
+       "         [ 0.4590, -0.6289,  0.7266,  0.4590]],\n",
+       "\n",
+       "        [[ 0.1885, -0.9336,  0.3164, -0.8477],\n",
+       "         [ 0.1367, -0.8008,  0.9219, -0.9961]],\n",
+       "\n",
+       "        [[ 1.0703, -0.2910,  1.8047,  0.3730],\n",
+       "         [ 2.1562, -0.8477,  0.9844, -0.4492]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16, grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ref_final_ln[\"hidden_states\"][:, :, :4]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Logits"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "INFINI_LOGITS = \"/fsx/phuc/projects/nanotron/debug/nn_states_with_bs_1/acts/model.lm_head_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "\n",
+    "# INFINI_AFTER_FIX_LOGITS = \"/fsx/phuc/projects/nanotron/debug/nn_states_after_fix/acts/model.lm_head_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "REF_LOGITS = \"/fsx/phuc/projects/reference/nanotron/debug/nn_states_with_bs_1/acts/model.lm_head_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "\n",
+    "\n",
+    "infini_logits = torch.load(INFINI_LOGITS)\n",
+    "# infini_after_fix_logits = torch.load(INFINI_AFTER_FIX_LOGITS)\n",
+    "ref_logits = torch.load(REF_LOGITS)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(torch.Size([1, 256, 24576]), torch.Size([256, 1, 24576]))"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_logits[\"logits\"].shape, ref_logits[\"logits\"].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[ 4.2188, -2.5156, -4.5312, -3.7969]],\n",
+       "\n",
+       "        [[ 2.0000, -0.4043, -2.6094, -3.2500]],\n",
+       "\n",
+       "        [[ 2.7656, -2.9219, -4.9062, -4.1250]],\n",
+       "\n",
+       "        ...,\n",
+       "\n",
+       "        [[ 0.7266, -1.4375, -4.2188, -4.0312]],\n",
+       "\n",
+       "        [[ 7.0000, -3.2500, -2.0312, -2.7812]],\n",
+       "\n",
+       "        [[ 0.9531, -2.3750, -2.9844, -3.6719]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16, grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_logits[\"logits\"].transpose(0, 1)[:, :, :4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[ 4.2188, -2.5156, -4.5312, -3.7969]],\n",
+       "\n",
+       "        [[ 2.0000, -0.4043, -2.6094, -3.2500]],\n",
+       "\n",
+       "        [[ 2.7656, -2.9219, -4.9062, -4.1250]],\n",
+       "\n",
+       "        ...,\n",
+       "\n",
+       "        [[ 0.7266, -1.4219, -4.2500, -4.0312]],\n",
+       "\n",
+       "        [[ 7.0000, -3.2344, -2.0156, -2.7656]],\n",
+       "\n",
+       "        [[ 0.9570, -2.3594, -2.9844, -3.6562]]], device='cuda:0',\n",
+       "       dtype=torch.bfloat16, grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ref_logits[\"logits\"][:, :, :4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "torch.testing.assert_close(infini_logits[\"logits\"].transpose(0, 1), ref_logits[\"logits\"], rtol=0.09, atol=0.09)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Sharded loss before loss"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "INFINI_SHARDED_LOGITS_STEP1 = \"/fsx/phuc/projects/nanotron/debug/nn_states/acts/step1_sharded_logits_tp_rank_0.pt\"\n",
+    "\n",
+    "REF_SHARDED_LOGITS_STEP1 = \"/fsx/phuc/projects/reference/nanotron/debug/nn_states/acts/step1_sharded_logits_tp_rank_0.pt\"\n",
+    "\n",
+    "\n",
+    "infini_sharded_logits_step1 = torch.load(INFINI_SHARDED_LOGITS_STEP1)\n",
+    "ref_sharded_logits_step1 = torch.load(REF_SHARDED_LOGITS_STEP1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(torch.Size([256, 2, 24576]), torch.Size([256, 2, 24576]))"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_sharded_logits_step1.shape, ref_sharded_logits_step1.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[ 4.2188, -2.5156, -4.5312, -3.7969],\n",
+       "         [ 3.0156, -2.3750, -2.5312, -3.5000]],\n",
+       "\n",
+       "        [[ 3.5938, -3.7500, -4.4062, -2.7500],\n",
+       "         [ 7.5938, -3.1094, -3.3281, -5.0312]],\n",
+       "\n",
+       "        [[ 2.8594, -1.6328, -4.6250, -3.9062],\n",
+       "         [ 3.5000, -1.8828, -3.7188, -3.5469]],\n",
+       "\n",
+       "        [[ 2.2344, -1.6797, -4.5938, -4.4062],\n",
+       "         [ 3.3906, -1.3359, -2.1562, -3.9219]]], device='cuda:0',\n",
+       "       grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_sharded_logits_step1[:4, :, :4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[[ 4.2188, -2.5156, -4.5312, -3.7969],\n",
+       "         [ 1.8438, -0.5430, -3.1250, -3.8281]],\n",
+       "\n",
+       "        [[ 2.0000, -0.4043, -2.6094, -3.2500],\n",
+       "         [ 3.2812, -2.0625, -7.0625, -5.2500]],\n",
+       "\n",
+       "        [[ 2.7656, -2.9219, -4.9062, -4.1250],\n",
+       "         [ 2.9062, -3.3438, -3.6406, -4.2188]],\n",
+       "\n",
+       "        [[ 8.0625, -3.3594, -2.2969, -3.8906],\n",
+       "         [ 2.4844, -3.9062, -5.2812, -1.9609]]], device='cuda:0',\n",
+       "       grad_fn=<SliceBackward0>)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ref_sharded_logits_step1[:4, :, :4]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Loss"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "# INFINI_LOSS = \"/fsx/phuc/projects/nanotron/debug/nn_states_with_bs_1/acts/loss.pp_block_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "INFINI_LOSS_WITH_TRANSPOSED_QKV = \"/fsx/phuc/projects/nanotron/debug/nn_states_with_bs_2_and_transpose_qkv/acts/loss_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "REF_LOSS = \"/fsx/phuc/projects/reference/nanotron/debug/nn_states_with_bs_2/acts/loss_dp_rank_0_and_pp_rank_0_and_tp_rank_0.pt\"\n",
+    "\n",
+    "\n",
+    "# infini_loss = torch.load(INFINI_LOSS)\n",
+    "infini_loss_with_transposed_qkv = torch.load(INFINI_LOSS_WITH_TRANSPOSED_QKV)\n",
+    "ref_loss = torch.load(REF_LOSS)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'loss': tensor(4.3787, device='cuda:0', requires_grad=True)}"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "infini_loss_with_transposed_qkv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'loss': tensor(4.3784, device='cuda:0', requires_grad=True)}"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ref_loss"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/debug_needle_dataset.ipynb b/debug_needle_dataset.ipynb
new file mode 100644
index 00000000..e02263e6
--- /dev/null
+++ b/debug_needle_dataset.ipynb
@@ -0,0 +1,220 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/admin/home/phuc_nguyen/miniconda3/envs/nanotron-dev/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datasets import load_dataset\n",
+    "from transformers import AutoTokenizer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Resolving data files: 100%|████████████████████████████████████████████████████████████| 178/178 [00:02<00:00, 86.53it/s]\n",
+      "Resolving data files: 100%|████████████████████████████████████████████████████████| 178/178 [00:00<00:00, 402472.30it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "dataset = load_dataset(\"yaofu/slimpajama-per-source-length-upsample\", streaming=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tokenizer = AutoTokenizer.from_pretrained(\"meta-llama/Llama-2-7b-hf\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "dict_keys(['input_ids', 'labels', 'source'])\n",
+      "[{'source': 'RedPajamaC4', 'start': 0, 'end': 120}, {'source': 'RedPajamaC4', 'start': 120, 'end': 328}, {'source': 'RedPajamaC4', 'start': 328, 'end': 551}, {'source': 'RedPajamaCommonCrawl', 'start': 551, 'end': 858}, {'source': 'RedPajamaC4', 'start': 858, 'end': 1527}, {'source': 'RedPajamaC4', 'start': 1527, 'end': 1844}, {'source': 'RedPajamaC4', 'start': 1844, 'end': 2274}, {'source': 'RedPajamaC4', 'start': 2274, 'end': 2829}, {'source': 'RedPajamaC4', 'start': 2829, 'end': 3190}, {'source': 'RedPajamaC4', 'start': 3190, 'end': 3722}, {'source': 'RedPajamaC4', 'start': 3722, 'end': 4546}, {'source': 'RedPajamaCommonCrawl', 'start': 4546, 'end': 5457}, {'source': 'RedPajamaC4', 'start': 5457, 'end': 6244}, {'source': 'RedPajamaC4', 'start': 6244, 'end': 6430}, {'source': 'RedPajamaC4', 'start': 6430, 'end': 6847}, {'source': 'RedPajamaWikipedia', 'start': 6847, 'end': 7916}, {'source': 'RedPajamaC4', 'start': 7916, 'end': 8197}, {'source': 'RedPajamaCommonCrawl', 'start': 8197, 'end': 9374}, {'source': 'RedPajamaCommonCrawl', 'start': 9374, 'end': 9924}, {'source': 'RedPajamaC4', 'start': 9924, 'end': 10132}, {'source': 'RedPajamaC4', 'start': 10132, 'end': 10249}, {'source': 'RedPajamaStackExchange', 'start': 10249, 'end': 10637}, {'source': 'RedPajamaC4', 'start': 10637, 'end': 11196}, {'source': 'RedPajamaC4', 'start': 11196, 'end': 11400}, {'source': 'RedPajamaCommonCrawl', 'start': 11400, 'end': 12990}, {'source': 'RedPajamaWikipedia', 'start': 12990, 'end': 13124}, {'source': 'RedPajamaC4', 'start': 13124, 'end': 13484}, {'source': 'RedPajamaC4', 'start': 13484, 'end': 13554}, {'source': 'RedPajamaC4', 'start': 13554, 'end': 14219}, {'source': 'RedPajamaC4', 'start': 14219, 'end': 14364}, {'source': 'RedPajamaCommonCrawl', 'start': 14364, 'end': 15152}, {'source': 'RedPajamaC4', 'start': 15152, 'end': 15229}, {'source': 'RedPajamaCommonCrawl', 'start': 15229, 'end': 15804}, {'source': 'RedPajamaC4', 'start': 15804, 'end': 15900}, {'source': 'RedPajamaC4', 'start': 15900, 'end': 16400}, {'source': 'RedPajamaCommonCrawl', 'start': 16400, 'end': 17597}, {'source': 'RedPajamaStackExchange', 'start': 17597, 'end': 18952}, {'source': 'RedPajamaC4', 'start': 18952, 'end': 19861}, {'source': 'RedPajamaC4', 'start': 19861, 'end': 19911}, {'source': 'RedPajamaC4', 'start': 19911, 'end': 20403}, {'source': 'RedPajamaC4', 'start': 20403, 'end': 20457}, {'source': 'RedPajamaCommonCrawl', 'start': 20457, 'end': 21046}, {'source': 'RedPajamaC4', 'start': 21046, 'end': 21697}, {'source': 'RedPajamaCommonCrawl', 'start': 21697, 'end': 23754}, {'source': 'RedPajamaC4', 'start': 23754, 'end': 24718}, {'source': 'RedPajamaC4', 'start': 24718, 'end': 24781}, {'source': 'RedPajamaCommonCrawl', 'start': 24781, 'end': 26459}, {'source': 'RedPajamaC4', 'start': 26459, 'end': 26664}, {'source': 'RedPajamaC4', 'start': 26664, 'end': 27355}, {'source': 'RedPajamaC4', 'start': 27355, 'end': 27509}, {'source': 'RedPajamaCommonCrawl', 'start': 27509, 'end': 28520}, {'source': 'RedPajamaC4', 'start': 28520, 'end': 29156}, {'source': 'RedPajamaC4', 'start': 29156, 'end': 29497}, {'source': 'RedPajamaCommonCrawl', 'start': 29497, 'end': 30103}, {'source': 'RedPajamaCommonCrawl', 'start': 30103, 'end': 30794}, {'source': 'RedPajamaC4', 'start': 30794, 'end': 30862}, {'source': 'RedPajamaC4', 'start': 30862, 'end': 31140}, {'source': 'RedPajamaC4', 'start': 31140, 'end': 31266}, {'source': 'RedPajamaWikipedia', 'start': 31266, 'end': 31343}, {'source': 'RedPajamaC4', 'start': 31343, 'end': 31558}, {'source': 'RedPajamaStackExchange', 'start': 31558, 'end': 31992}, {'source': 'RedPajamaWikipedia', 'start': 31992, 'end': 32070}, {'source': 'RedPajamaCommonCrawl', 'start': 32070, 'end': 35321}, {'source': 'RedPajamaC4', 'start': 35321, 'end': 35628}, {'source': 'RedPajamaStackExchange', 'start': 35628, 'end': 36126}, {'source': 'RedPajamaC4', 'start': 36126, 'end': 36441}, {'source': 'RedPajamaCommonCrawl', 'start': 36441, 'end': 37275}, {'source': 'RedPajamaC4', 'start': 37275, 'end': 37850}, {'source': 'RedPajamaCommonCrawl', 'start': 37850, 'end': 38404}, {'source': 'RedPajamaCommonCrawl', 'start': 38404, 'end': 39225}, {'source': 'RedPajamaC4', 'start': 39225, 'end': 39916}, {'source': 'RedPajamaC4', 'start': 39916, 'end': 40023}, {'source': 'RedPajamaC4', 'start': 40023, 'end': 41233}, {'source': 'RedPajamaCommonCrawl', 'start': 41233, 'end': 42488}, {'source': 'RedPajamaStackExchange', 'start': 42488, 'end': 42690}, {'source': 'RedPajamaCommonCrawl', 'start': 42690, 'end': 47008}, {'source': 'RedPajamaCommonCrawl', 'start': 47008, 'end': 48202}, {'source': 'RedPajamaC4', 'start': 48202, 'end': 48465}, {'source': 'RedPajamaC4', 'start': 48465, 'end': 52868}, {'source': 'RedPajamaC4', 'start': 52868, 'end': 53088}, {'source': 'RedPajamaCommonCrawl', 'start': 53088, 'end': 54229}, {'source': 'RedPajamaCommonCrawl', 'start': 54229, 'end': 57918}, {'source': 'RedPajamaC4', 'start': 57918, 'end': 58154}, {'source': 'RedPajamaC4', 'start': 58154, 'end': 58852}, {'source': 'RedPajamaC4', 'start': 58852, 'end': 59425}, {'source': 'RedPajamaC4', 'start': 59425, 'end': 59663}, {'source': 'RedPajamaC4', 'start': 59663, 'end': 60328}, {'source': 'RedPajamaStackExchange', 'start': 60328, 'end': 61451}, {'source': 'RedPajamaC4', 'start': 61451, 'end': 61588}, {'source': 'RedPajamaCommonCrawl', 'start': 61588, 'end': 63087}, {'source': 'RedPajamaCommonCrawl', 'start': 63087, 'end': 66947}, {'source': 'RedPajamaC4', 'start': 66947, 'end': 71335}, {'source': 'RedPajamaC4', 'start': 71335, 'end': 72293}, {'source': 'RedPajamaC4', 'start': 72293, 'end': 77723}, {'source': 'RedPajamaWikipedia', 'start': 77723, 'end': 80044}, {'source': 'RedPajamaCommonCrawl', 'start': 80044, 'end': 84721}, {'source': 'RedPajamaC4', 'start': 84721, 'end': 84966}, {'source': 'RedPajamaC4', 'start': 84966, 'end': 85158}, {'source': 'RedPajamaC4', 'start': 85158, 'end': 85340}, {'source': 'RedPajamaC4', 'start': 85340, 'end': 85440}, {'source': 'RedPajamaCommonCrawl', 'start': 85440, 'end': 90381}, {'source': 'RedPajamaC4', 'start': 90381, 'end': 90766}, {'source': 'RedPajamaC4', 'start': 90766, 'end': 90822}, {'source': 'RedPajamaCommonCrawl', 'start': 90822, 'end': 94819}, {'source': 'RedPajamaCommonCrawl', 'start': 94819, 'end': 102188}, {'source': 'RedPajamaCommonCrawl', 'start': 102188, 'end': 103837}, {'source': 'RedPajamaCommonCrawl', 'start': 103837, 'end': 104499}, {'source': 'RedPajamaC4', 'start': 104499, 'end': 104629}, {'source': 'RedPajamaWikipedia', 'start': 104629, 'end': 104833}, {'source': 'RedPajamaC4', 'start': 104833, 'end': 104913}, {'source': 'RedPajamaCommonCrawl', 'start': 104913, 'end': 105855}, {'source': 'RedPajamaStackExchange', 'start': 105855, 'end': 106660}, {'source': 'RedPajamaCommonCrawl', 'start': 106660, 'end': 106967}, {'source': 'RedPajamaC4', 'start': 106967, 'end': 107439}, {'source': 'RedPajamaC4', 'start': 107439, 'end': 108138}, {'source': 'RedPajamaCommonCrawl', 'start': 108138, 'end': 112495}, {'source': 'RedPajamaC4', 'start': 112495, 'end': 116837}, {'source': 'RedPajamaCommonCrawl', 'start': 116837, 'end': 120954}, {'source': 'RedPajamaC4', 'start': 120954, 'end': 126881}, {'source': 'RedPajamaCommonCrawl', 'start': 126881, 'end': 131072}]\n",
+      "131072\n"
+     ]
+    }
+   ],
+   "source": [
+    "d = next(iter(dataset[\"train\"]))\n",
+    "print(d.keys())\n",
+    "print(d[\"source\"])\n",
+    "print(len(d[\"input_ids\"])) ## all input_ids are chunks of length 131072"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'<s> allons-nous apprendre plus d\\'informations ?\\net vous, qu\\'attendez-vous pour ce live ?\\napprendrons-nous enfin la présence d\\'un mode aventure ?\\nhave you ever wondered what life is like in the mushroom kingdom? if so, ask mario and luigi in real time!\\nso do a barrel roll and stop by nintendo ny today! whether you\\'re a long-time fan or you\\'re just getting started, nintendo ny has something for you!<s> Seller or third party financing may be available for a qualified buyer.\\n> Only Perpetual Care Cemeteries in the marketplace.\\n> Thirty-five years under the current ownership.\\n> Eight prominent locations in thriving areas.\\n> State-regulated trust fund (seven-figure balance) provides nearly six-figure annual return to owners.\\n> Positioned for accelerated growth for new owners with new ideas!\\n* Increase in cremation rate provides nearly unlimited opportunities for maximizing future revenues without acquiring more land.\\n> Experienced management will stay in place if requested or to train Buyer.\\n> Office space may be leased from Seller until Buyer decides to relocate.\\n> Motivated sellers are willing to provide some seller financing to the right Buyer.\\n> Great stand-alone business or add-on for existing funeral/burial operation.<s> The chapter provides in-depth knowledge of how children\\'s lives change when they move with their mothers into a women\\'s shelter and how the activities for children at the residence reveal and address their needs. The chapter also presents how mothers perceive the situation of their children. More children than women live at this shelter. Almost all the children are victims of violence. Most were born in Sweden, but several have mothers or fathers who were born in another country. Some of the children are subjected to honour-related violence, with threats of kidnapping. No systematic violence and security assessment at which the children can make their voices heard is ordinarily conducted at the shelter. Half of the school-age children did not attend school for several months and received home schooling only to a very limited extent. Many of the younger children did not attend preschool. Resilience can be promoted for children in the life at a shelter also by volunteers.\\nAarhus: Aarhus Universitetsforlag , 2015.<s> German government to step in on Vattenfall sale\\nA document has emerged, indicating Germany\\'s intention to persuade Swedish utility Vattenfall not to sell its lignite power plant portfolio.\\nReuters reports that the leaked internal position paper shows that Germany\\'s economy and energy minister Sigmar Gabriel, is due to fly to Stockholm to discuss the sale of the company\\'s lignite coal-fired power plants, although no date for the talks was disclosed.\\nChancellor Merkel\\'s deputy is to argue that \"A breakup of this group as well as excessive price expectations would endanger the security of employment and the sustainability of the operating units,\" according to the document.\\n\"I am sure that the Swedish government and Stefan Lofven are aware of their responsibilities,\" he said.\\nLast month, Vattenfall\\'s new chief executive Magnus Hall said the company might put its lignite power plants and mines in Germany up for sale. This could fetch up to 3 billion euros, according to people familiar with the industry.\\nVattenfall generates about 10 per cent of Germany\\'s total power production and said it remains committed to other operations in Germany, including heat production, trading and wind power.\\nPrevious articleTablets maximising use of on-site renewables\\nNext articleJordanian solar plants secure $100m in finance<s> The Clojurians Slack [sign up here] started as a small experiment about four years ago and has been far more successful than anyone could have imagined, with around 15K members signed up and around 1,700 members considered \"active\" on a weekly basis (which means it would cost almost $9K per month to run this as a paid service!).\\nA perennial complaint about Slack\\'s free plan is that it limits the accessible message history to just the most recent 10K messages. In a busy Slack like Clojurians that limit is hit after three or four days, heavily limiting the ability to refer back to conversations or to use the massive amount of \"knowledge\" shared there for reference – exactly as noted in the comment above.\\nThe \"original\" online Clojure community still exists and is still active on IRC (freenode), of course, and there\\'s also Braid (written in Clojure/ClojureScript!).\\nI was a bit surprised that the commenter did not mention Clojurians on Zulip because that community, started back in early November 2018, already has five hundred members and seems, to me, like the most capable alternative to Slack. It\\'s open source, hosted for free to open source communities, and \"has a significantly larger and more active development community than other modern open source group chat solutions like Mattermost, Rocket.Chat, and matrix.org.\" Read their Why Zulip? page for more information about the service and how it compares (specifically to Slack).\\nOne-way bridging between select Slack channels and Zulip streams has been in place for a while and currently about fifty of the most popular channels on Slack are available to read in Zulip streams, along with many other active streams in Zulip. This means you can try Zulip without missing out on Slack conversations – some people prefer Zulip\\'s UI just for reading Slack messages!\\nClojurians on Slack isn\\'t going away – a lot of people love the UI and don\\'t consider the message history limit to be a big deal – and if you\\'re already using Slack for work, then it makes perfect sense to also use that for your Clojure community fix (since you only need one chat client open). The Slack community isn\\'t \"official\" in any way, and you\\'re all welcome to try other chat clients, but if you feel strongly about open source and unlimited search history, check out Clojurians on Zulip and if you like it, promote it and encourage other Clojurians to join you there.\\nMe? I\\'m one of the long-time admins/moderators of Clojurians on Slack, but I\\'ve also tried each and every one of the alternatives that various community members have set up over the last four years. Clojurians on Zulip is the one I\\'ve found myself most active in and the only alternative chat client that I always have open at this point!<s> As part of NYCHA\\'s Sandy Resiliency and Renewal Program, TCT is providing cost estimating services for the Basis of Design Study and Schematic Design of resiliency projects at three sites: Coney Island Site 8, O\\'Dwyer Gardens, and Surfside Gardens.\\nConey Island Site 8 consists of one residential building with 124 apartment units. The building\\'s heating plant, which is located below grade in the building cellar, was fully submerged during Super Storm Sandy and is non-functional. Building 6 of O\\'Dwyer Gardens, a 6.34-acre development with six residential buildings and 572 apartments, had its cellar completely flooded by the storm and now houses an inoperable boiler plant with three low pressure fire tube steam boilers. Each of Surfside Gardens\\' five buildings was subject to Sandy-related water damages and currently have non-operational boiler plants.\\nThe scope of work includes a comprehensive damage assessment; an updated scope of work to restore the buildings to their pre-disaster design, function and capacity, including MEP relocation and upgrades, a new boiler plant, roof replacements, and natural gas-fueled standby power generators; resiliency measures, energy efficiency im\\xadprovements; and optional evaluation of other resiliency and energy efficiency measures.<s> The Colony Film Festival website is a custom designed site coded in the Bootstrap framework and templated to WordPress.\\nThe Kelly Lang Contractors website is a custom designed site coded in the Bootstrap framework and templated to WordPress.\\nThe Marietta Dance Academy website is custom designed, coded in Bootstrap and uses a custom CMS.\\nThe Dr. Steven B. England website is custom designed, coded in Bootstrap and uses a custom CMS.\\nThe logo was designed by Ohio Web Pro Design.\\nThe Willow Land Surveying website is custom designed, coded in Bootstrap and uses a custom CMS.\\nThe Main Street Amherst website is built by Ohio Web Pro Design and the website and logo was designed by Alicia Nicely of Alicia Nicely Designs. The Main Street Amherst website project won the 2012 Heritage Ohio annual award for Best Marketing Project or Event.\\nThe Fleeman Insurance Agency website is custom designed, coded in Bootstrap and uses a custom CMS.\\nThe Eve Shelter website is custom designed, coded in Bootstrap and uses a custom CMS. It also features a HTML5 interactive animation.\\nThe Business Advisory Services website is custom designed, coded in Bootstrap and uses a custom CMS.\\nThe The Mermaid\\'s Tale website is custom designed, coded in Bootstrap and uses a custom CMS.\\nWebsite for C.L. Tours includes the OWP Content Management system and a configurable tours database. C.L. Tours offers year around Motorcoach day and multi-day tours.\\nThe Ohio Dental Hygienists\\' Association website was custom designed, coded in Bootstrap and uses a custom CMS. A wide array of custom features: Auto balancing banner ad display with view/click through tracking, members area accounts sync with ADHA member\\'s reports, Member\\'s only log in and secure forms, publishing platform with search and unlimited categories and much more.<s> Who hasn\\'t dreamed of getting that perfect wildlife shot? TripAfrica has teamed up with Pangolin Photo Safaris to put together an amazing 9 night trip including a 5 day wildlife photography course set in the stunning Chobe National Park where you will learn how to take the perfect shot in the most perfect of backdrops!\\nIt might not be a quintessentially Christmassy destination, and with temperatures soaring in to their thirties throughout much of Africa already, there certainly won\\'t be any snowy winter scenes.\\nAcacia Africa has an answer for adventurous souls in search of exotic climes in the economic downturn. A new \"Premium Overlanding\" portfolio will kick off in June 2012, the collection of tours targeted at cash strapped, discerning travellers looking to \"truck it, but not rough it\" on the continent.\\nWildlife Worldwide has a brand new, small group trip for 2011 - the two-week Botswana Explorer - taking in the highlights of this captivating country, which is surrounded by Namibia, Zambia, Zimbabwe and South Africa.\\nKamili has launched a selection of sensibly priced safaris across their portfolio that won\\'t break the bank, and with 2009 rates frozen until the end of 2010 there\\'s no need to wait for last minute offers to enjoy outstanding African safari experiences.\\nYou can now get a whole new perspective on the African savannah as Ranch Rider\\'s 2010 portfolio covers South Africa and Botswana.\\nDiscover South Africa, Botswana and Zimbabwe in January and save £233 per person. Combining the wildlife of Chobe National Park with the spectacular scenery of Victoria Falls, visit the Khama Rhino Sanctuary and explore Okavango Delta by mokoro (dug-out canoe).\\nForget World Cup mania, go ahead of the crowds and visit Africa now to take advantage of the Green Season says Africa expert, Kamili.\\nEver wanted to be a safari guide?\\nTuli Safari Lodge and Okavango Guiding School (OGS) have partnered to offer visitors to Botswana a holiday experience with a difference – a fascinating, action-packed adventure that gives a taste of life as a safari guide.<s> The goal of the project is to create an operational data intelligence platform capable of monitoring, alerting, reporting. I am currently considering Elastic (ELK stack) + FileBeats.\\nAfter being selected & signing a nondisclosure agreement, you will be working to translate my experience and insights through the lens of your technical prowess & experience with big data & machine learning into a data intelligence platform.\\nPrior experience with network visualizations, algorithms, kibi, the stock market, and social media would be helpful but not required. If you have experiences in these areas, please let me know so we can discuss.\\nA realistic development & deployment roadmap including a timeline with milestones and projected budget from development to deployment.\\nI have a detailed profile of the conditions/characteristics I need to monitor.\\nI will also need a unique monitoring interface that aggregates a broad number of data sources I currently rely upon but which are currently dispersed.\\nYou should have prior successful deployments and familiarity with APIs, other technologies and plugins which may be of use and/or willing to do additional research. I want to rely on open source & free or inexpensive plugins & technologies as much as possible.\\nI will only work with someone who thoroughly understands what I do and the problems I am attempting to address. Once selected, I have a number of documents that can provide additional insights into the nature of the problem. I will also explain how I currently address the problem and can answer questions so you have a thorough understanding.\\nHi there, I have checked the details I have rich experienced with Data Science, Elasticsearch, Machine Learning. Please initiate chat so we can discuss this job.<s> Published 04/19/2019 02:26:55 pm at 04/19/2019 02:26:55 pm in Best Price Shark Vacuum.\\nbest price shark vacuum upright vacuums shark vacuum cleaners at target shark navigator light vacuum shark vacuum cleaners at target target steam cleaner shark vacuum steam cleaner combo best carpet vacuum shark vacuum.\\ncheapest shark vacuum cleaner euro pro shark vacuum bags best price cheapest shark vacuum cleaner euro pro shark vacuum bags best price shark vacuum cleaner buy shark vacuum cleaner australia, shark vacuum cleaners on sale shark vacuum deals shark lift away shark vacuum cleaners on sale shark upright vacuum cleaner blue shark navigator vacuum cleaner price australia shark vacuum cleaners on sale , shark rocket complete corded vacuum with duoclean red hv shark rocket complete corded vacuum with duoclean red hv, amazoncom ion p lightweight cordless upright vacuum with hepa ion p lightweight cordless upright vacuum with hepa filter handheld vacuum mode and shark, best price ever shark navigator vacuum shipped was best price ever shark navigator vacuum shipped was , shark vacuum duo clean reviews attachments and tools shark rocket shark vacuum duo clean reviews shark cordless vacuum cleaner with blue shark rocket duo clean vacuum shark vacuum , best price for shark vacuum cleaner shark navigator swivel plus related post, vacuum cleaners steam mops irons home cleaning products by shark upright vacuums, vacuum cleaner lowest price mostraymondwinfo vacuum cleaner lowest price shark vacuum cleaners compare prices vacuum cleaner best deal, shark closeouts for clearance jcpenney sale, target shark vacuum shark vacuum cleaners on sale shark vacuum small target shark vacuum shark vacuum cleaners on sale shark vacuum small design vacuum full wallpaper images.<s> Games and simulations are changing the ways in which students learn today. However, much remains unknown about the effectiveness of games to learn specific subject matter. The aim of this study was to better understand the role that games can play in learning physics. In this study, we examine what participants learned by playing Physicus-a commercial, edutainment game. Physicus seeks to teach students basic physical science concepts (related to electricity and magnetism, and light and color) by embedding these ideas in a \"save the world\" scenario. Results of our study indicate that participants, who played Physicus, did learn physics concepts compared to the control group who played a non-edutainment game. We discuss how these learning gains interacted with participants\\' motivation, enjoyment, and interest for physics and games.\\nFoster, A., Koehler, M. & Mishra, P. (2006). Game-Based Learning of Physics Content: The Effectiveness of a Physics Game for Learning Basic Physics Concepts. In E. Pearson & P. Bohman (Eds.), Proceedings of ED-MEDIA 2006--World Conference on Educational Multimedia, Hypermedia & Telecommunications (pp. 2119-2125). Orlando, FL USA: Association for the Advancement of Computing in Education (AACE). Retrieved April 20, 2019 from https://www.learntechlib.org/primary/p/23301/.\\nArdac, D., & Akaygun, S. (2004). Effectiveness of multimedia-based instruction that emphasizes molecular representations on students understanding of chemical change. Journal of Research in Science Teaching, 41(4), 317-337.\\nDe Jong, T., & Van Joolingen, W.R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68, 179-202.\\nDiSessa, A. (1982). Unlearning Aristotelian physics: A study of knowledge-based learning. Cognitive Science, 5, 37-75.\\nHuppert, J., Lomask, S.M., & Lazarowitz, R. (2002). Computer simulations in the high school: Students cognitive stages, science process skills and academic achievement in microbiology. International Journal of Science Education, 24(8), 803-821.\\nMalone, T.W. (1981). Toward a theory of intrinsically motivating instruction. Cognitive Science, 5 (4), 333-369.\\nMcAuley, E., Duncan, T., & Tammen, V.V. (1987). Psychometric properties of the Intrinsic Motivation Inventory in a competitive sport setting: A confirmatory factor analysis. Research Quarterly for Exercise and Sport, 60, 48-58.\\nMoreno, R., & Mayer, R.E. (2002). Learning science in virtual reality multimedia environments: Role of methods and media. Journal of Educational Psychology, 94(3), 598-610.\\nTurkle, S. (1997). Seeing Through Computers. The American Prospect, 8 (31).\\nZhang, J., Chen, Q., & Reid, D.J. (2000). Simulation-based scientific discovery learning: A research on the effects of experimental support and learners\\' reasoning ability.<s> Agência Solar Odiamaiscurto Store\\nFestival App Program Blog 1993-2020 Submissions\\nPT Contact Partners Newsletter\\n\"Anyhow, Anyway\" at Clermont - Ferrand\\n\"Uncle Thomas, Accountig for the days\" EFA finalist\\nCurtas travels around the country with award-winning films\\nOur Kingdom at the Torino Film Festival\\nAwards 28th Curtas Vila do Conde\\nCall for Entries Curtas 2021!\\nCurtas starts tomorrow!\\nDownload Curtas\\' App!\\nCurtas Online with special discount\\nBLOG \"Anyhow, Anyway\" at Clermont - Ferrand\\n\"Anyhow, Anyway\" directed by Catarina Romano is selected for the International Competition in Clermont-Ferrand International Short Film Festival, taking place between 29th January and 6th February 2021, in France\\nBLOG \"Uncle Thomas, Accountig for the days\" EFA finalist\\n\"Uncle Thomas, Accounting for the days\", Regina Pessoa\\'s latest film is one of the five nominees in the category of Best European Short Film at the 33rd edition of the European Film Academy (EFA) Awards.\\nCURTAS Curtas travels around the country with award-winning films\\nThis year, as in the previous ones, Curtas Vila do Conde tours the country again with a selection of some of the best films of this edition. The \"Best of Curtas\" will screened some of the awarded films, and the \"Curtinhas\" session, dedicated to the youngest, is composed of small and fun films thought for the whole family.\\nBLOG Our Kingdom at the Torino Film Festival\\n\"Our Kingdom\", Luis Costa\\'s latest short film, will have its italian premiere at the 38th edition of the Torino Film Festival to be held from November 20-28, in Turin.\\nCURTAS Awards 28th Curtas Vila do Conde\\nThe 28th edition of Curtas Vila do Conde was announced today at the closing ceremony of the festival. \"The Unseen River\" by Vietnamese Pham Ngoc Lân was the winner of the International Competition Great Prize. In the National Competition the big winner of the Best Film Award was Diogo Salgado with \"Noite Turva\".\\nCURTAS Call for Entries Curtas 2021!\\nThe 28th Curtas Vila do Conde – International Film Festival, taking place from 10 to 18 July 2021, announces the call for entries for new short films produced in 2020 or 2021, within the duration limit of 60 minutes, in film (35mm or 16 mm) or digital (DCP).\\nBLOG Curtas starts tomorrow!\\nThe 28th edition of Curtas de Vila do Conde starts this Saturday, October 3rd. A festival with a special format, committed to the new times, but where the actuality and urgency of the program are again the main focus of the event that wants to be the stage for the dissemination of what is best done, experienced or reinvented in short format cinema.\\nCURTAS Download Curtas\\' App!\\nThis is the easiest way to have all of Curtas\\'s programming in your hand. Get to know all the features of the festival\\'s App. The greatest of world cinema in several formats, from October 3rd to 11th, with more than 260 films from 42 countries.\\nCURTAS Curtas Online with special discount\\nDuring the weekend of October 24th and 25th, Curtas offers a 50% discount to the first 50 people who buy the pass online. Using the code \"CURTAS50\", the user will have access to 28 films until the end of Curtas Online, November 1st.\\n© 2021 Curtas Metragens, CRL<s> Sarah Hooper is a Ph.D. student in electrical engineering who\\'s studying applications of machine learning on global health issues like malaria diagnosis.\\nAlex Ferris is a bioengineering student developing a model for the spread of disease and crop loss in cassava root.\\nAnd Alex Siegenfeld is studying how statistical physics can help us understand certain social and political phenomena, focusing on malaria in Nigeria.\\nThese are a few of the winners of a new fellowship from science education funder the Fannie and John Hertz Foundation, an interesting program that sends Ph.D. students from all sorts of scientific disciplines to spend their summers working in global health and development. Fellows work two summer internships at the Gates Foundation as part of a partnership between Hertz and the philanthropic juggernaut.\\nA round of six new fellows was announced last month after an inaugural cohort of two students in 2017. The fellowship is intended to provide students in STEM with hands-on experience in global health issues, and to inspire them to engage with such challenges. It\\'s a unique educational opportunity, but also related to a trend in science philanthropy of putting researchers from varied disciplines into new contexts, or otherwise combining different areas of study, to encourage innovative crossovers.\\nThe Hertz-Gates Fellowship in Global Health and Development is a supplemental program to the Hertz Foundation\\'s graduate fellowship, which has been running for more than 60 years. Fellows receive full tuition and a personal stipend, renewable for up to five years, and must be studying applied physical and biological sciences, mathematics or engineering at a list of participating universities.\\nTo date, there have been around 1,200 fellows, and they\\'ve gone on to secure thousands of patents and win major awards like the Breakthrough and two Nobel prizes. Hertz fellows can now apply for the Hertz-Gates Fellowship, which adds on stints at the Gates Foundation working for program teams in global health or development.\\nThe Hertz Foundation\\'s sole purpose is to support science education, and its fellowship targets one of the most challenging periods in a young researcher\\'s career. The foundation has been around since 1957, when it was established with a very 1950s-sounding intent to \"enhance the technological stature of the United States.\" It\\'s based in the wealth of John Hertz, who led a pretty fascinating life and career with various automotive companies (he founded Yellow Cab), but is probably best known for Hertz rental cars.\\nAnd you might be familiar with the Gates Foundation. While such a partnership between two foundations makes sense regardless, this does underscore just how prominent Gates is in the world of global health.\\nIt\\'s primarily an educational fellowship, but one of the more interesting components of the partnership is that mashup of many disciplines and global health work. Funder interest in introducing science researchers to a new setting is particularly relevant in biomedical and health research, and as scientists explore new applications of data and computer science. We\\'ve covered this kind of funding in the Simons Foundation\\'s Flatiron Institute, for example, which brings computer scientists, physicists and biologists under one roof. Most recently, the Wellcome Trust\\'s LEAP program seeks to back risky research, including that which crosses disciplines.<s> Lots of movies reviewed this week including War Dogs, Purge Election Year, and Mechanic Resurrection. We also present our EPIC Winter movie preview!\\nVic has a fascinating conversation with the CEO of Image Ireland, Stephen Lohan. Get the lowdown on the VFX event of the year, happening in Dublin with some of the biggest names in visual effects in attendance.\\nBesides the event itself, the guys chat about the VFX industry in general, where it\\'s going, where it\\'s been and what\\'s coming next and of course there is an indepth discussion on the Irish VFX industry!\\nDavid Brent: Life on the Road gets slammed and we get scared silly with Lights Out. All that and more movie news than you can shake Bantha poo-doo at.<s> As part of the official kickoff for Childhood Cancer Awareness Month, the St. Baldrick\\'s Foundation will visit the Nasdaq MarketSite in Times Square.\\nIn honor of the occasion, Bill Hogan, board member of St. Baldrick\\'s and president of WebHouse, Inc., will ring the Opening Bell. He will also be joined by St. Baldrick\\'s co-founder, Tim Kenny, along with other board members, colleagues and supporters, St. Baldrick\\'s researchers, as well as children and families directly affected by childhood cancer.\\nThe St. Baldrick\\'s Foundation is a volunteer-powered organization dedicated to funding the most promising childhood cancer research wherever it takes place. Worldwide, every 3 minutes a child is diagnosed with cancer and in the U.S., one in five will not survive. Each year, thousands of volunteers and donors in communities across the country support St. Baldrick\\'s head-shaving events and \"Do What You Want\" fundraisers in an effort to raise funds and awareness to change these devastating statistics. Since 2005, St. Baldrick\\'s has awarded 890 grants in 25 countries totaling more than $176 million.\\nThe St. Baldrick\\'s Foundation is a volunteer-powered charity committed to funding the most promising research to find cures for childhood cancers and give survivors long and healthy lives. Since 2005, St. Baldrick\\'s has awarded more than $176 million to support lifesaving research, making the Foundation the largest private funder of childhood cancer research grants. For more information about the St. Baldrick\\'s Foundation please call 1.888.899.BALD or visit www.StBaldricks.org.<s> Adrien-Marie Legendre (Parijs, 18 september 1752 – Auteuil, 10 januari 1833) was een Franse wiskundige. Hij leverde belangrijke bijdragen aan de statistiek, de abstracte algebra, de wiskundige analyse en in het bijzonder aan de getaltheorie. Hij was een van de toonaangevende Franse wiskundigen aan het einde van de 18e en begin van de 19e eeuw, die een bloeiperiode was voor de Franse wiskunde. Hij is een van de 72 Fransen wier namen in reliëf op de Eiffeltoren zijn aangebracht.\\n\\nLegendre was een tijdgenoot van Joseph-Louis Lagrange, Pierre-Simon Laplace, Sadi Carnot en Gaspard Monge in de rumoerige period van de Franse Revolutie. Laplace, Lagrange en Legendre hebben zich volledig afzijdig gehouden van de revolutie.\\n\\nLegendre is bekend gebleven om zijn didactische verbetering in de behandeling van de elementaire meetkunde. Van 1775 tot 1780 was hij docent aan de Militaire Academie, later aan de École Normal en tot slot de École polytechnique, alle in Parijs. Het grootste deel van zijn werk werd geperfectioneerd door anderen: zijn werk aangaande wortels van veeltermen inspireerde de galoistheorie. Niels Henrik Abel bouwde in zijn werk over elliptische functies voort op het werk van Legendre. Ook Carl Friedrich Gauss maakte bij sommige van zijn resultaten op het gebied van de statistiek en de getaltheorie gebruik van het werk van Legendre.\\n\\nIn 1830 gaf hij een bewijs van de laatste stelling van Fermat voor de exponent , een bewijs dat bijna gelijktijdig door Johann Peter Gustav Lejeune Dirichlet werd gegeven in 1828. Hij had eerder het foute bewijs van Leonhard Euler voor  verbeterd.\\n\\nIn de getaltheorie leverde Legendre belangrijke bijdragen, in het bijzonder tot de toepassing van de analyse op de getaltheorie. Zijn vermoeden uit 1796, voor wat nu de priemgetalstelling wordt genoemd, werd pas honderd jaar later, in 1898, door Hadamard en Charles-Jean de La Vallée Poussin bewezen. Het legendre-symbool is een andere bijdrage van hem op dit gebied.\\n\\nLegendre verrichtte een indrukwekkende hoeveelheid werk met betrekking tot elliptische functies, waaronder de classificatie van elliptische integralen.\\n\\nDe naar hem genoemde legendre-transformatie wordt in de theoretische mechanica gebruikt om dat lagrangiaanse formalisme over te zetten in het hamiltonformalisme. In de thermodynamica wordt het ook gebruikt om thermodynamische potentialen vrije energie (ofwel helmholtzenergie)  en de gibbsenergie  af te leiden uit de inwendige energie .\\n\\nDifferentiaalvergelijking van Legendre \\nIn 1784 vond hij de oplossing van de differentiaalvergelijking\\n\\nDe oplossing staat bekend also de legendre-polynoom\\n\\nEnkele stellingen van Legendre \\n  en  zijn geen van beide rationaal.\\n Het aantal priemgetallen tussen 1 en  is ongeveer gelijk aan .\\n\\nHet vermoeden van Legendre \\n\\nVoor elk positief geheel getal  geldt dat er tussen  en  minstens een priemgetal ligt.\\n\\nPortret \\nVan Legendre is geen portret bekend. Lange tijd werden artikelen en boeken over Legendre geïllustreerd met een portret van een man, gezien van opzij. Pas in 2005 werd ontdekt dat deze litho de Franse politicus Louis Legendre (1752–1797) voorstelt, en niet de wiskundige. Wel werd in 2008 een karikatuur van Legendre ontdekt.\\n\\nExterne link \\n  Biografie van Legendre\\n\\nGetaltheoreticus\\nFrans wiskundige\\n18e-eeuws wiskundige\\nLid van de Académie des sciences<s> I\\'m one of the owners of helloworld Travel Masterton and have been part of this wonderful team for 16 years. With over 30 years in the travel and airline industry I have a wealth of experience to draw on and offer to you. There is nothing like first-hand knowledge of a destination and over the years I\\'ve been fortunate enough to visit most continents in the world – and those that I haven\\'t I\\'m planning to get to! My favourite places in the world so far are Japan, Scandinavia and Turkey, followed closely by Tahiti and her beautiful islands. Vietnam was my most recent personal holiday where I travelled North to South, including a cruise on beautiful Halong Bay. The culture, food, climate and scenery of this beautiful country make it one of the hot destinations today.\\nCruising has become extremely popular over recent years. I have sailed with various cruise lines in Fiji, the Mediterranean, Canada and Alaska. It is a wonderful and relaxing way to travel.\\nI pride myself on attention to detail, and will always go the extra mile to ensure your holiday is hassle free. I welcome the opportunity to help you plan your next travel experience or cruise holiday – feel free to email me.<s> Windows 8\\'s app restrictions are antithetical to the platform\\'s storied past of radical openness\\nby Alex Wilhelm — in Microsoft\\nIf you intended to download and play games that contain explicit content on your Microsoft Surface RT tablet, prepare for disappointment: You probably can\\'t.\\nIf you had hoped that the introduction of the Windows Store and the lack of the ability to install apps sans its use on Windows RT would not lead to Windows itself becoming a far more closed ecosystem, this is not only bad news, it\\'s a sea change in how Windows works.\\nWhat you can\\'t do\\nYes, according to the \"Windows 8 app certification requirements,\" there are heavy rules that determine what sort of app can be certified, and thus be eligible for sale in the Windows Store. Here are the two key passages that pertain to what you are simply not allowed to put in your app:\\n5.1 Your app must not contain adult content, and metadata must be appropriate for everyone\\nApps with a rating over PEGI 16, ESRB MATURE, or that contain content that would warrant such a rating, are not allowed. Metadata and other content you submit to accompany your app may contain only content that would merit a rating of PEGI 12, ESRB EVERYONE, or Windows Store 12+, or lower.\\nOh, and if you were hoping to somehow dodge this, Microsoft has thought of that already:\\n6.2 Your app must have a Windows age rating, and you must submit third-party ratings for your app if you have them\\nYou must assign a Windows Store age rating that most accurately matches your app. The Age rating page contains more detailed descriptions of the content that is suitable for each Windows Store age rating.\\nThis is not a small issue. As PC Gamer reported earlier today:\\n[T]his [set of rules] not be such a problem in the US, where relatively few games receive a mature rating, but it will be very significant in Europe, where games such as Dishonored, Skyrim, Sleeping Dogs, Assassin\\'s Creed, Call of Duty all fall foul of the restriction.\\nSomeone call Notch, he may have been right.\\nWhat made Windows great, akin to the Internet, was its openness. Now however, for a large swath of coming Windows devices – tablets running Windows RT, in which you can only snag applications via the Windows Store – that openness is over.\\nBetween you and app content on your device sits Microsoft, deciding what is fit for you to see, and what isn\\'t. This isn\\'t a free speech issue; Microsoft is free to design its products and run its services as it may, but that doesn\\'t do away with the fact that this sort of censorship is ridiculous, and unneeded.\\nHow can we know that? Simple: We\\'ve prospered and survived without it thus far, so we hardly require it. I honestly feel sorry for gamers in regions that have ratings systems that befall Redmond\\'s red lines; sorry brosef, Ballmer doesn\\'t think you should be able to play that.\\nNaturally, you could buy a tablet that runs Windows 8 proper, and have no such problems, but if Microsoft is going to push a version of Windows for the mobile use case that intends on playing nanny with your ability to execute normal tasks – like the playing of a popular, mainstream game – then something has gone wrong.\\nWhat about Apple?\\nCertainly, Apple has strict rules in terms of what sort of content you can put into its App Store. Again, that\\'s its prerogative. iOS, a very popular platform, has been locked down since its inception. When the iPhone launched – calling all builds of iPhone software iOS is loose wording, I know, but bear with me – iOS supported no third-party applications. Things have improved, but not completely.\\nThat\\'s the kicker to all of this, and why the Apple comparison is only slightly cogent: Windows is moving from complete and utter openness, to being partially closed, whilst Apple has moved from being completely to partially closed. Thus we can bemoan the decline of Windows and not fret too much about giving Apple a free pass.\\nWhat should be done?\\nMicrosoft should let adults use any damn app they want, provided that it is legal. No one is telling Microsoft to not censor child pornography. However, its blanket bans, which lean on rating systems of what I would call dubious efficacy, are asinine. Adults should be free to submit, and download any sort of app they wish.\\nChildren can be restricted to age appropriate applications until they come of age, at the behest of their parents.\\nSimple, easy, and it reopens Windows to being the platform, once again, where developers are as free as users to do as they please. We\\'re not kids, Microsoft, and we don\\'t want your false protection.\\nTop Image Credit: Michael Coté\\nRead next: Tumblr launches Photoset: An iOS-only photo sharing app that could help it lure in new users\\nMediaTek\\'s 2021 flagship chip comes with big promises: 168Hz display and ray tracing<s> Cactus Club Café: Stephen Avenue\\nAssembledge+ has continued its ongoing collaboration with Cactus Restaurant Group in support of the Vancouver-based company\\'s expansion into Canada\\'s western provinces.\\nLocated in the dense commercial core of downtown Calgary, Stephen Avenue is a historic pedestrian mall providing an eclectic mix of boutiques and high-end retail. Looking to build on the success of their downtown Toronto flagship, the goal was to export the brand\\'s hallmark formula of upscale, inventive, and global cuisine paired with a high-energy, high-design setting,\\nAt 6,700 square feet, Cactus Club Café: Stephen Avenue accommodates up to 228 seats with an additional 1,300 square-feet and 88 seats on the wrap-around patio. The interior has been designed using a refined palette of oak, blackened steel, glass, and stone, to echo the natural materials found in the West Coast Canadian landscape, featuring oak and stone-clad walls, paired with a unique tile flooring. Long wood and curved ceiling slats inspire movement throughout the space creating a striking yet complementary contrast against the linear geometry found throughout. Furnishings include butcher-block oak tables and deep brown leather seating while glass partitions and horizontal paneling section the different dining spaces.\\nFacing the entry, the lounge and bar are illuminated by a floating display of hand-blown glass pendant lamps creating a sense of intimacy among diners. The adjacent patio features a fully retractable roof to accommodate Calgary\\'s climate year-round. Additionally, retractable floor-to-ceiling glass panels surrounding the lounge blur the lines between the indoor and outdoor experience and enables diners to interact with the heavy pedestrian traffic, as well as a large-scale steel \"Trees\" sculpture designed to reduce wind gusts between buildings. Original art is displayed throughout featuring artists Mr. Brainwash and Andy Warhol.\\nLocation: Calgary, Alberta, Canada\\nSize: 7,995 sf w/ 1,290 sf patio\\nDesign Team: David Thompson (Principal-in-Charge), Scott Walter, Wendy Gilmartin, Gregory Marin, Teagan Castelleon, Ruining Wang\\nPhotography: Tieran Green and Rick Collins<s> We can manage any project procurement and coordination from any origin/destination, meeting the most demanding requirements, managing efficient and effective time frames, information, materials, equipment, human resources among other key elements in the complexity of the logistic system.\\nTaylor-made solutions for your cargo, on-time delivery and reasonable freight rates allow us to be an excellent choice to transport your cargo with us.\\nFrom customs, inland,warehousing, Ocean transportation to air transportation of project cargo, we can handle any project.\\nWith outstanding results, we have operated the entire logistic chain for 11 drill rigs during this running year (February 2013- February 2014). The expertise of Colfletar, the commercial agency representation of our liner services, and the contracts we hold with ports, conform the best alliance for guaranteeing excellence and accuracy in handling cargoes and projects.<s> This High Vibration Journey has African Drums, Dancing, Libations, Spectacular Sunset & of course the Graceful Whales.\\nAvail purch; Beer – Wine – Mai Tai\\'s – Fruit Drinks – B.Y.O. Snacks!\\n**VIP INCLUDES = Early Entry Choice Seats, Champagne Welcome & Pupu\\'s!\\nDue to inclement weather the Whale Drum Cruise has been changed to Sat Feb 23rd same times!<s> Q: Conditionally exit action Newbie question about GitHub Actions and YAML configuration.\\nI have Action with one job and more steps that perform tests and open issue if they fail. It works well.\\nNow I want to make Action conditionally failed, in purpose to update Badge of that action.\\nProblem is in the last step \"Handle exit\" that is always called although there is a condition that works for the previous step but not in this.\\nWhere I am wrong and how to conditionally do Step containing \"run\"?\\nname: Tests\\n\\non:\\n  - push\\n\\njobs:\\n  tests:\\n    name: Tests\\n    runs-on: ubuntu-latest\\n\\n    steps:\\n      - name: Check out Git repository\\n        uses: actions/checkout@v2\\n\\n      - name: Set up Node.js\\n        uses: actions/setup-node@v1\\n        with:\\n          node-version: 14\\n\\n      - name: Install dependencies\\n        run: yarn install\\n\\n      - name: Tests\\n        id: tests\\n        run: echo ::set-output name=failed::$(if expr length + \"$(yarn test 2>&1 | grep fail -i)\" > 0; then echo \"true\"; else echo \"false\"; fi)\\n\\n      - name: Open Issue\\n        if: steps.tests.outputs.failed == \\'true\\'\\n        env:\\n          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}\\n        uses: JasonEtco/create-an-issue@v2\\n\\n      - name: Handle exit\\n        if: steps.tests.outputs.failed == \\'true\\'\\n        run: exit(1)\\n\\n<s> Today at Black Hat 2014 hacking conference, Yahoo! Chief Information Security Officer Alex Stamos announced that the company will start giving its consumers the option of end-to-end encryption in its Mail service by next year.\\nGoogle showed off a PGP-based encryption plugin for Gmail back in June. The Purple-hued company will offer encryption via a modified version of the same End-to-End browser plug-in that Google uses for PGP in Gmail, Alex Stamos told the audience at his talk titled Building Safe Systems at Scale - Lessons from Six Months at Yahoo.\\nThe PGP plugin will be native in mobile apps allowing Gmail and Yahoo mail to easily exchange encrypted email. In fact, the email providers themselves won\\'t be able to decrypt messages exchanged between its users. Only senders and recipients will be able to read the messages.\\nIn short, it means that Yahoo email users can reportedly send safe and secure messages between Yahoo users and also Gmail adherents without fear, which makes almost impossible for cyber criminals and well-resourced spying by the US government and its Five Eyes allies to read their private messages.\\nStamos (@alexstamos) said that this project has been a priority since he joined one of the world\\'s largest web providers, Yahoo six months ago. He stressed that Yahoo email encryption will be easy to use, with little or no efforts.\\nThe announcement was tweeted by Yan Zhu, who has reportedly been hired to assist in the project. Yan Zhu formerly worked as an engineer at the Electronic Frontier Foundation (EFF), a non-profit organization that has consistently been outspoken in its call for the widespread use of encryption across the Web and the Internet, and he is apparently no friend of the NSA.\\nBut as said earlier, use of encryption will require some amount of education for users also, to make sure their privacy expectations are set appropriately. In an interview with the Wall Street Journal, Stamos explained that PGP encryption won\\'t cloak the destination of your e-mail.\\n\"We have to make it clear to people it is not [a] secret you\\'re emailing your priest, but the content of what you\\'re e-mailing him is secret,\" Stamos said.\\nThe move to encrypted mail will bring Yahoo! in the list of the most secure technology companies in mail services among web giants, Google and Microsoft that protect their customers in the post-Snowden era of security.<s> AntiRSI.xcodeproj 674 2 years Nicholas Riley Upgrade for vaguely modern Xcode (7.2.1).\\nEnglish.lproj 677 2 years Nicholas Riley MainMenu?.nib: Update for current-ish Xcode.\\nAntiRSI.h 3.9 KB \\u200b 371 11 years Nicholas Riley AntiRSI.h: Updated for 1.4njr4; forgot a place last time.\\nAntiRSI.m 25.7 KB \\u200b 675 2 years Nicholas Riley AntiRSI.m: Fix format string issue and compilation on >10.4.\\nAntiRSIView.m 2.4 KB \\u200b 346 11 years Nicholas Riley Updated for 1.4njr3. Fixed whitespace for consistent 8-space tabs.<s> Proud to be Local\\nMCWknowledge /\\nAnna Bauman of Wausau, Wisconsin, was a UW-Marathon County sophomore in 2014 when she first learned about an innovative new campus that the Medical College of Wisconsin was establishing in her hometown. In December 2014, she attended a talk by MCW-Central Wisconsin Dean Lisa Grill Dodson, MD, and hearing about the local accelerated medical school program immediately piqued her interest. In the four years since she first learned of the program, Anna transferred to UW-Madison to complete her pre-med undergraduate studies, applied to MCW-Central Wisconsin and was accepted as a member of this year\\'s incoming class.\\n\"I have been interested in a career in medicine ever since high school and am particularly interested in working in primary care and community medicine in more rural areas,\" she says. \"When I first learned the opportunity to attend medical school in my own hometown was becoming available, I knew right away I wanted to be involved.\"\\nAnna has deep ties with the Wausau community. She grew up volunteering at the county jail and her church, and she was a bell ringer for the Salvation Army each year around the holidays. Throughout her high school years, she tutored her peers, worked in the greenhouse and as a lifeguard at the community pools, and played violin at the hospice house.\\n\"I have seen a lot of different aspects of Wausau,\" Anna says. \"There\\'s so much going on here for a town of 40,000 people. It\\'s a very engaging place to live.\"\\nAnna first became interested in medicine when she shadowed physicians in clinics in Wausau for a high school class. She also completed a family medicine clinical internship in a local clinic, which she says influenced her decision to become a community physician.\\n\"I became interested in the field because I saw how collaborative, dynamic and challenging it was to practice community medicine,\" Anna says. \"I liked how connected those doctors were to their community and how they knew how to meet local needs. I knew right away that community medicine appealed to me.\"\\nAfter attending Dr. Dodson\\'s talk in 2014, Anna joined a pipeline committee for the campus as a student representative to encourage high school and college students in central Wisconsin to explore careers in medicine. Each month, she met with Dr. Dodson, local physicians and advisors and staff from local colleges to help promote student engagement and awareness for the new program.\\n\"The pipeline committee provided resources and information about practicing medicine that students in central Wisconsin otherwise might not have found,\" Anna says. \"I wanted to be a strong asset for faculty and staff at MCW and a good liaison to local students.\"\\nAnna says the connection between her interests in the medical field and her strong ties to her local community was the reason she was invested in letting other students know about the new campus.\\n\"There is a problem in central Wisconsin with retaining medical students who will want to stay here and practice as primary care physicians,\" she says. \"From my point of view, I\\'m hopeful having a medical school in central Wisconsin will develop physicians who are deeply invested in this community and want to stay. I grew up here and am familiar with this area, which makes practicing patient care here that much more personal. MCW was my top choice for medical school, and I became a member of the pipeline committee because I wanted others to know about this opportunity as well.\"\\nMCW-Central Wisconsin is one of two regional campuses MCW created as a solution to Wisconsin\\'s physician shortage, which studies indicate severely limit patient access to quality care in more rural areas of the state. One report by the Wisconsin Hospital Association estimated that by 2030, Wisconsin could experience an estimated shortfall of 2,000 physicians. MCW expects to lower the cost of medical education and increase the number of medical students who stay to practice in rural areas through their campuses in both Wausau and Green Bay and the establishment of new residency programs. Ultimately, leaders across MCW\\'s three campuses hope educating students across the state will result in a physician workforce with a deep understanding of local health care needs and better patient outcomes. Anna says she has already seen firsthand the impact MCW-Central Wisconsin has had on the central Wisconsin community.\\n\"The campus is great for students, but it is also a great thing for this community. I have seen how receptive people in Wausau are to MCW,\" she notes. \"People love that we have this great institution here now, and we\\'re proud our community can support this. I think this speaks volumes about how much the surrounding community cares about health care.\"\\nAnna also says having local medical students attending medical school in their hometown will provide current high school and college students with role models to follow.\\n\"I know students in the first class from the Central Wisconsin campus, and seeing someone who is similar to me who grew up here and is attending medical school here made me feel like I could do this too,\" Anna says. \"I have two younger sisters who might be interested in medicine someday, and having local role models through this program makes a big difference.\"\\nAnna is looking forward to learning from local physicians and role models herself, and that the opportunity to practice and learn under physicians at MCW-Central Wisconsin is part of what drew her to the program.\\n\"My class has a total of 23 students, so it\\'s relatively small for an incoming medical class,\" she notes. \"I am looking forward to a lot of one-on-one training with physicians during my rotations. It\\'s great that I will be able to learn in an environment I can envision myself working in someday. I will be able to see myself in their shoes someday, practicing and having a family in the area.\"\\nAnna hopes to be engaged in community health outside the walls of her practice. She plans to become involved in public health efforts in central Wisconsin and has particular interest in women\\'s health and preventative care.\\n\"Ultimately, being an active member of the community and having a deep understanding of the people who live here will help my practice,\" Anna concludes. \"Wausau is a place that provides resources people need to feel welcome, healthy and like contributing members of the community. MCW-Central Wisconsin values the same things I personally value, and it\\'s a dream come true to be able to attend medical school here.\\nTagged: Community Engagement/Community Partnership Central Wisconsin Campus Medical Education\\nCommunity Front Door\\nReimagining Care: Paul Bergl, MD\\nIn the wake of the global pandemic, MCW faculty, staff and students are reimagining how they provide care and services.\\nNa\\'il\\'s Story\\nA young man who searched for a way to serve his community finds his calling.\\nMedical Student Sees Health Equity as Part of Her Identity\\nStephanie Baguidy\\'s passion for helping others was validated when she earned a prestigious cancer studies grant.<s> Плехотиці ()\\xa0— село в окрузі Требішов Кошицького краю Словаччини. Площа села 12,94 км². Станом на 31 грудня 2016 року в селі проживало 784 жителі.\\n\\nПротікає Мочярний потік.\\n\\nІсторія \\nПерші згадки про село датуються 1332 роком.\\n\\nПримітки \\n\\nСела округу Требишів\\n1332 у Європі<s> Lea really does talk a lot.\\nI thought you said you didn\\'t know Jackye.\\nIt\\'s Tanya\\'s turn to wash the dishes.\\nAlfred kicked the door in.\\nDo you think Marvin would be able to pick Arlene up at the airport?\\nSanford and Bill have forgiven me.\\nI hope Kris has a good time.\\nDon\\'t make a fuss over Samir.\\nJayesh died fighting for what he believed in.\\nTim was unkind to Bobbie.\\nLloyd is our prime suspect.\\nRich dug a hole in his front yard.\\nRay never thought that Hilda would commit suicide.\\nThe next-door neighbor looked out the window when Leon yelled.\\nAlexander didn\\'t have enough experience to know what to do.\\nSusanne did his schoolwork at the kitchen table.\\nJoe wanted to write Dimitry a song for her birthday.\\nDid Jeannette tell King what she should do?\\nKinch and Lea have been friends since they were kids.\\nPresley pointed to the sign.\\nTommy is a bit strapped for money.\\nLinley never forgets to call his mother on her birthday.\\nMerton owns a blue car.\\nFloyd wants to buy an apartment in Boston.\\nJuergen doesn\\'t have to prove anything to me.\\nSabrina was jailed on trumped-up charges.\\nKonstantinos won\\'t let anything happen to you.\\nI figured Neville wouldn\\'t know the answer.\\nBertrand wants to meet Kelly again.<s> Lillian was clearly feeling victimized by her husband Rob.\\nIt is always amazing to me when a person who is blaming their partner for blaming them does not realize that they both are trying to control each other – that they are both blaming!\\n\"But aren\\'t you blaming him for blaming you?<s> Clarity about Your Incomes: Not sharing the income details may not only dampen the trust factor in a marriage, but also result in miscalculation of income and expenses, and thus, inadequate investments and savings. While having individual savings accounts is important, there is also need to create a joint account in which the couple can contribute and save accordingly.\\nInvest in Health Insurance: Securing health concerns must be the top most priority for newly married couples. This means that partners must share details about any pre-existing diseases they might have suffered in the past. Accordingly they can choose a health insurance. In addition, if they are planning to start a family in near future, they must focus on investing in a health insurance that covers pregnancy or has maternity insurance features. Since all insurance companies do not provide maternity coverage, it is important that couples read details shared in the proposal form before zeroing in on their choice of policy. It is important to note that most health insurers agree to pay for maternity expenses only two years of paying premiums for the health insurance plan. It is important that couples invest in health insurance with maternity coverage two years before planning to have a baby.\\nBuy Insurance for Long-Term Security: Marriage entails responsibility. Financial security is another big factor that affects choice of investments and quantum of savings. To ensure that your partner continues to enjoy the same kind of lifestyle throughout life, you may start investing in a term plan that would pass on the sum insured to your partner in case of your sudden demise. Alternatively, you may invest in various life insurance plans that would not only earn you returns after some years or pay the sum insured to your nominee, i.e., your partner.\\nInsurance to Meet Medical Expenses: Some couples may look for insurance only to meet hospitalisation expenses realising that they can afford to pay pre and post-hospitalisation charges. Such couples can choose to pay for mediclaim policies that would pay for the insured\\'s hospitalisation subject to the condition that he or she has remained admitted to hospital for more than 24 hours.\\nBe Clear About Your Financial Priorities: This is important without which you cannot set financial goals. The husband may want to start a business of his own after he turns 40 years, while the wife may more inclined to travel around the world and save money for the same. Keeping in mind both their financial goals, the couple must make investments that would not only secure their future, but fulfill their goals too. Though risky investments yield better returns than most others, it would be prudent to invest in less-risky investments giving handsome returns. This would not only help the couple earn good returns, but lend them a feeling of security too.\\nSummary: Individual financial goals are different from a couple\\'s financial goals. Therefore, decisions regarding investments and insurance must be made keeping their needs in mind.<s> I wanna go to Gram and Pap\\'s for a swim! Then, you will take me to see Bubby so we can pick veggies and make salsa. Then, I need to go ride horses with Poppa Bish. Then, Aunt Lizzie is taking me to Baby Gap. Then, Aunt Jessie is taking me to lunch. Then, Uncle Austen needs to coach my rugby team. Got it? Dad… drive me to all these places now. Mom… you bring the bottles. Does everyone understand?\\nMarching orders have been assigned… Munchie has us all wrapped around his (tiny) little finger.<s> A Blue Hill Resident on School Consolidation\\nPosted on October 9, 2009 by deviger\\nRobert Webster of Blue Hill posted this comment earlier today on a piece featuring a statement from Rep. Seth Berry on school consolidation. Mr. Webster has given his statement as to why the school consolidation law should be repealed. You can read Mr. Webster\\'s full statement after the cut.\\nThe consolidation law should be repealed. A \"yes\" vote on Question #3 will restore fairness to the organization of school systems in Maine. Mandated consolidation does not work for rural areas. People throughout Maine should recognize and honor the votes of over 200 communities that rejected consolidation. Large school systems will not meet the needs of eastern and northern Maine.\\nThe consolidation law has been inconsistently applied and sometimes unfairly interpreted and implemented by the Commissioner of Education.\\n• Maine laws since 1897 have always included a method for towns not well served by a school district or school union to withdraw. As interpreted by the Commissioner in 2007 and 2008 consolidation plans were not allowed to include withdrawal provisions in the proposed consolidation plans – even though the consolidation law was silent on this matter. Yet in 2009 the town of Allagash was allowed to include a withdrawal provision in its consolidation plan with Ft. Kent.\\n• Schools systems exempt from consolidation (those with 2,500 or more students and the off shore islands) were required to submit plans to the Dept. of Education on how savings would be found in administration, special education and transportation. Exempt schools filed these plans. NONE of the exempt schools were required to implement any of those savings plans.\\n• School systems with 1,200 up to 2,500 students were among the school systems required to create and vote on consolidation plans. School units of this size that voted down their plans were let off the \"penalty\" hook by the Commissioner. No penalties were imposed for these \"middle size\" districts. School systems with fewer than 1,200 students will suffer subsidy penalties in July of 2010.\\n• The Commissioner rejected consolidation plans that did not find savings. Consolidation planning committees were told to list savings even if there were none. The Blue Hill-Deer Isle area consolidation plan was rejected twice by DOE and only approved on a third attempt after \"savings\" were included for subsidy that would be lost due to the subsidy penalty built into the law. Some communities that voted to consolidate felt \"bullied\" into it.\\nA \"yes\" vote on Question #3 will restore our liberty and freedom. Maine citizens should be able to organize local schools in ways that make sense to us – without the threat of financial coercion from our own Dept. of Education. Repeal will re-establish the local authority of Maine towns and cities to organize local schools in the best interests of our own children. The consolidation law curtailed our freedom. Repeal will restore our freedom.\\nFiled under: Uncategorized | Tagged: Blue Hill, education, maine, Public Education, Question 3, School District Consolidation, Seth Berry, Yes On 3 |\\n« Women\\'s and Children\\'s Groups Support No on 1 Yes On 3 Statement from Skip Greenlaw »<s> A Soft Bucket can do all kinds of things, like keep plants cosy, desks tidy and bread rolls warm. It\\'s a minor miracle! Please note: Soft Buckets are not waterproof, so we advise you to remove the plant from the Soft Bucket before watering, and to have a saucer under the pot.<s> South Tyneside move sparks major expansion for Flame\\nA major North East retailer is sparking a major expansion after moving to a new head office in South Tyneside.\\nThursday, 28 February, 2019, 10:02\\nJohn Savage (left) and Stephen Hepburn\\nFlame Heating Group welcomed MP Stephen Hepburn to officially open its new Boldon head office.\\nThe MP for Jarrow visited Flame\\'s premises on Boldon Business Park to tour the facility and meet the staff who have moved there from the firm\\'s old premises.\\nFlame, the North East\\'s fastest-growing heating and plumbing merchant, invested in the new head office in November.\\nIt was previously operating from Team Valley, and the premises there will now act as the company\\'s lead retail outlet.\\nEstablished in 2011 with a single branch, Flame currently operates 11 trade counters across the region and in Scotland.\\nThe investment in Boldon aims to support the company\\'s three-year expansion plan.\\nThis includes the launch of additional trade counters across the North East and throughout the UK.\\nFlame also expects to double its current workforce of 60 employees, as part of the ambitious expansion strategy.\\nStephen Hepburn MP said: \"It was a pleasure to officially open Flame\\'s new head office in Boldon Business Park.\\n\"Small businesses are the backbone of our local communities.\\n\"I was impressed with their forward-thinking plans for the future.\\n\"It is always excellent to see thriving and expanding businesses invest in our area and this is good news for the Jarrow constituency, South Tyneside and the wider North East region.\"\\nJohn Savage, Managing Director of Flame Heating Group, said it had been a pleasure to welcome Stephen Hepburn to the new offices.\\nHe predicted the move to Boldon would be the start of big things for the firm.\\n\"It was great to welcome Mr Hepburn MP to our new offices to show him what it is we do and how we plan to grow the business further,\" he said.\\n\"We have big aspirations for Flame in the region and further afield as we continue to expand and create further job opportunities here in Boldon and across our branch network.\\n\"We look forward to welcoming Stephen back in the future.\\n\"I would like to thank him for visiting and marking the official launch of our new base.\"<s> A trip down memory lane for the young at heart 10 Questions.\\nGreat quiz, should have skived off work more in the 70s.\\nGave it a 5. Is that \\'Paddington\\' Bond for The Herbs? If so, wow.\\nI loved the Clangers. Brought back memoires of watching tele with the kids !\\nHow well do you know your \"Friends\"?<s> FIBER GRIP CROSS-LOCK TWEEZERS SET OF 3 SPECIAL SHAPES - 2-ROUNDS & 1-SQUARE FOR HOLDING ROUND CIRCULAR PARTS - SQUARE & RECTANGULAR DISCS Tweezers are the latest addition to the Cross-Locking Fiber Grip Tweezers line. Fiber Grip Tweezers are used by Jewelers, Model Makers, Hobbyists, in the Electronics field, by Watchmakers and for Craft and Glass work. Tweezers can be used by individually by themselves or can be attached to a Third Hand Base, very durable, made of Stainless Steel and has Heat Resistant Fiber Grips to protect fingers from heat build-up when using in soldering and welding operations. The LARGE ROUND shaped tips can be used to hold Spherical pieces: Round, Circular, Rods objects. The round open end tips are 3/4\" in diameter width and extend to an opening of 1-1/2\". The round tips are very useful for holding Circular parts around the majority of the diameter rather than at only minimal points of the object. Tips of the tweezers have serrations and be used to pinch and hold objects. The SMALL ROUND head has rounded open mouth, used to hold Round, Circular, Rods objects and pieces. The round open end tips are 11/32\" in diameter width and extend out 11/16\". The formed tips are very useful for holding round items and parts, the tips of the tweezers have serrations. The SQUARE Shape has a fork style head, with the holding tips have a wide open square mouth , used to hold large or wide parts and pieces. The open end tips are 7/8\" wide and extend out 1-3/32\", are very useful for those wider and square or rectangular pieces, the tips of the tweezers have serrations.\\nIf you have any questions about this product by Novel, contact us by completing and submitting the form below. If you are looking for a specif part number, please include it with your message.<s> SNDTRCK: New Music Week of 2/23\\nMusic lovers agree that music has gotten them through good times and bad times. Just read the comments on the Instagram profile of any popular musician. We save our favorite songs into different playlists labeled for working out, studying, partying and even sleeping. Some types of music are perfect for breaking up, and others work better for making out\\nThe soundtrack of life is not just what\\'s \"now playing.\" It\\'s when the perfect song comes on at exactly the right moment. That\\'s why we\\'re going one deeper with the best new music of the week for the soundtrack of your life. Get ready to add five new songs to your personal rotation.\\nCalvin Harris – \"Pray to God\" ft. Haim\\nScottish producer Calvin Harris teams up with the American pop rock up band Haim in his newest single \"Pray to God\" featuring Haim. The song was released on Harris\\' album Motion and now they are playing it on the radio. In the music video, the Haim sisters sing amid a dark forest dressed in flowing black garb. They are accompanied by an assortment of woodland creatures, including wolves, a bear and a lion. But Harris does not appear, leaving us to wonder where he is exactly.\\nPerfect for: Sitting on the hood of your car, staring off into the distance and musing over your high school relationship the night after graduation.\\nDrake – \"Energy\"\\nThis week Drake unexpectedly dropped If You\\'re Reading This It\\'s Too Late. Billboard predicts that the follow up to Nothing Was the Same will easily debut at number one in next week\\'s charts. This will be the fourth number one for Drake, who was recently featured by the New York Times as the \"first true post-Kanye superstar.\" In \"Energy,\" one of three debut singles, Drake reflects upon people that want to drain him of his energy using the full effect of his trademark lilt.\\nPerfect for: When you need to find some way to cope with the haters. Even if your only haters are those mean customers at work.\\nFlosstradamus x TroyBoi – \"SOUNDCLASH\"\\nFlosstradamus is an EDM act, so they release something new every week to the delight of their hordes of loyal fans. For their latest single they collaborated with UK artist TroyBoi. Usually Chicago based production duo Flosstradamus claims Mad Decent, but \"SOUNDCLASH\" is out now on Ultra Music. The bouncy romp is another one for the ladies to twerk to at the local trap music party.\\nPerfect for: When you want to dance and talk, because it has a groove you can dance to with minimal vocals. You could play it during an early opening DJ set, or as bed music on your indie podcast.\\nKid Ink – \"Ride Out\" ft. YG, Wale, Tyga & Rich Homie Quan\\nWith appearances from Chris Brown, Trey Songz, Usher and R Kelly, Kid Ink\\'s Ride or Die LP debuted at #14 on the Billboard Top 200 this week. Then the Los Angeles rapper released a new music video for the lead single off the soundtrack to Furious 7, featuring a score of famous rappers. In the video Kid Ink, YG, Wale, Tyga and Rich Homie Quan each rap in front of their own car. This is spliced between scenes from the seventh installment of the Fast and the Furious film series.\\nPerfect for: Since street racing is highly illegal, this is clearly a road trip song. Try listening to it on the way to a really good concert that\\'s worth the trip to the next town over.\\nShaun Frank – \"Mind Made Up\"\\nFuture house producer Shaun Frank hails from Toronto Canada. His new single \"Mind Made Up\" is due out February 24 on Dim Mak Records. It follows a collaboration with Borgeous on Spinnin\\' Records called \"This Could Be Love\" featuring Delaney Jane. Frank has been officially spinning since 2013, and already has mad support from 3LAU, Nicky Romero, Oliver Heldens and Steve Aoki.\\nPerfect for: When you\\'re dancing around in front of the mirror and pre-gaming while you get ready to go to the rave.\\nAbout the author: Elizabeth de Moya has been published in DJ Mag, LA Weekly and Thump. She has a BA in Linguistics from UC Berkeley. Check out her underground EDM e-Zine at www.blackbettyblog.com and follow on Twitter @blackbettyblog.\\nSOL REPUBLIC February 24, 2015 March 13, 2015 calvin harris, drake, Elizabeth de Moya, flosstradamus, haim, kid ink, new music, rich homie quan, shaun frank, sndtrck, soundtrack, troyboi, tyga, wale, yg\\nPrevious Previous post: Get Local: Noise Pop 2015 Week in San Francisco\\nNext Next post: Inspiration Playlist: Con Brio<s> Q: Calculating line integral of $y\\\\,dx+z\\\\,dy+x\\\\,dz$ Calculate the integral $$\\\\int_{\\\\gamma} y\\\\,dx+z\\\\,dy+x\\\\,dz $$ when $$\\\\gamma=\\\\{(x,y,z):x^2+y^2+z^2=a^2, x+y+z=0\\\\}$$\\nI tried to isolate $z$ and to replace it in the sphere but I stuck in the parametric track.\\nthank you! \\n\\nA: This exercise is best to be tackled using Stokes\\' theorem: $$\\\\mathcal{F}=\\\\oint_\\\\gamma ydx+zdy+xdz=\\\\oint_\\\\gamma \\\\left<y,z,x \\\\right>\\\\cdot d\\\\vec{r}=\\\\iint_S \\\\nabla\\\\times\\\\left<y,z,x \\\\right>\\\\cdot\\\\vec{n}ds,$$ where $\\\\gamma$ is the boundary of $S$ and $\\\\vec{n}=\\\\vec{n}(x,y,z)$ is the unit normal field oriented so that while traversing the countour $\\\\gamma$ the surface $S$ remains on the left side.\\nSince we have some freedom in choosing $S$, let\\'s take $S$ to be the circle whose boundary is $\\\\gamma$. In this case, $\\\\vec{n}=\\\\pm\\\\frac{1}{\\\\sqrt{3}}\\\\left<1,1,1\\\\right>$. We notice that $\\\\nabla\\\\times\\\\left<y,z,x \\\\right>=-\\\\left<1,1,1\\\\right>$ and $\\\\nabla\\\\times\\\\left<y,z,x \\\\right>\\\\cdot\\\\vec{n}=\\\\pm\\\\sqrt{3}$ then $$\\\\mathcal{F}=\\\\pm\\\\frac{1}{\\\\sqrt{3}}\\\\iint_SdS=\\\\pm\\\\frac{1}{\\\\sqrt{3}}A(S)=\\\\pm\\\\frac{\\\\pi a^2}{\\\\sqrt{3}}.$$\\nNotes: the direction of the contour $\\\\gamma$ was not specified. It will affect the sign of the the integral, hence we have $\\\\pm$ in the final answer. $A(S)=\\\\pi a^2$ denotes the area of the circle that lies in the intersection of the sphere and the plane. Since the plane passes through the center of the sphere, we know that its radius is $a$.\\nThis is the most straightforward solution, however if you insist on parametrization we can be more adventurous. Our goal in the this case is to parametrize the curve $\\\\gamma:$ $$\\\\left\\\\{\\\\begin{array}{ccr}x+y+z&=&0\\\\\\\\x^2+y^2+z^2&=&a^2\\\\\\\\\\\\end{array}\\\\right.$$ Let\\'s take a look at the first equation: $0=x+y+z=\\\\left(x+\\\\frac{z}{2}\\\\right)+\\\\left(y+\\\\frac{z}{2}\\\\right)=u+v$, where $u$ and $v$ are the expressions in the princesses. The first equation transforms into $u+v=0$ (much better). For the equation of the sphere we will get $$a^2=x^2+y^2+z^2=\\\\left(u-\\\\frac{z}{2}\\\\right)^2+\\\\left(v-\\\\frac{z}{2}\\\\right)^2+z^2=u^2+v^2-z(u+v)+\\\\frac{3}{2}z^2$$ We remember that $u+v=0$ and our system is reduced to: $$\\\\left\\\\{\\\\begin{array}{ccr}u+v&=&0\\\\\\\\2u^2+\\\\frac{3}{2}z^2&=&a^2\\\\\\\\\\\\end{array}\\\\right.,\\\\hskip{30pt} \\\\left\\\\{\\\\begin{array}{ccr}u+v&=&0\\\\\\\\\\\\frac{u^2}{a^2/2}+\\\\frac{z^2}{2/3a^2}&=&1\\\\\\\\\\\\end{array}\\\\right. $$\\nNow we apply the standard parameter for an ellipse $$\\\\begin{array}{rcl}u&=&\\\\frac{a}{\\\\sqrt{2}}\\\\cos t\\\\\\\\z&=&\\\\sqrt{\\\\frac{2}{3}}a\\\\sin t\\\\\\\\v&=&-u\\\\\\\\\\\\end{array}$$ We should not  forget to bring these equation to the original system of coordinates $$\\\\begin{array}{rcl}x(t)&=&u-\\\\frac{1}{2}z=\\\\frac{a}{\\\\sqrt{2}}\\\\cos t-\\\\frac{a}{\\\\sqrt{6}}\\\\sin t, \\\\\\\\y(t)&=&v-\\\\frac{1}{2}z=-\\\\frac{a}{\\\\sqrt{2}}\\\\cos t-\\\\frac{a}{\\\\sqrt{6}}\\\\sin t, \\\\\\\\z(t)&=&\\\\frac{2a}{\\\\sqrt{6}}\\\\sin t,\\\\end{array}$$ where $0\\\\le t \\\\le2\\\\pi$. For sake of completeness let us compute the form $ydx+zdy+xdz$ in terms of the parameter $t$. We keep thorough track of the terms $\\\\sin^2t$ and $\\\\cos^2t$ and we don\\'t care much about the terms of the form $\\\\sin t\\\\cos t$ since the integration of the mixed terms over $[0,2\\\\pi]$ will result in $0$: $$ydx+zdy+xdz=\\\\left[C\\\\sin t\\\\cos t-\\\\frac{a^2}{\\\\sqrt{12}}+\\\\frac{2a^2}{\\\\sqrt{12}}\\\\right]dt=\\\\frac{C}{2}\\\\sin2tdt+\\\\frac{a^2}{2\\\\sqrt{3}}dt,$$ where $C$ is an irrelevant constant. After integrating from $0$ to $2\\\\pi$ the first term disappears due to the periodicity and we arrive to $$\\\\mathcal{F}=\\\\frac{a^2}{2\\\\sqrt{3}}\\\\cdot 2\\\\pi=\\\\frac{\\\\pi a^2}{\\\\sqrt{3}},$$ which confirms our earlier computation.\\nHere again the contour direction was not specified. The change of direction will result in the integration from $2\\\\pi$ to $0$ which will reverse the sign of the integral if necessary.\\n<s> Call it the Washout in Windsor.\\nIf the National Basketball League of Canada had a higher profile, Thursday\\'s washout would be right up there with the 1987 Punchup in Piestany or the 1976 walkoff when the Moscow Red Army left the ice against the Philadelphia Flyers.\\nIn no way can the NBL flatter itself that it\\'s that important.\\nIt will have to settle for being remembered as the league that opted to die by suicide in a very public manner.\\nThursday was supposed to be Game 7 in the NBL final between the defending champion Windsor Express and Halifax Rainmen. Instead it turned into yet another black eye for a league that saw the Rainmen leave the WFCU Centre because they feared for their safety.\\n\"Due to a physical altercation between the Halifax Rainmen and the Windsor Express the game has been cancelled citing safety concerns for its players and coaches,\" Rainmen owner Andre Levingston said. \"When the game is not safe for players to compete there is a problem. We have to do a better job of governing our league and putting principles in place where there are strict consequences.\\nIt began when the Rainmen arrived for a morning shootaround at what they thought was an empty WFCU Centre.\\nReports indicate that the Express were in the building but that their scheduled shootaround time had not yet arrived.\\nThere was a physical confrontation between Express coach Bill Jones and Rainmen forward Liam McMorrow when McMorrow wouldn\\'t give Jones a basketball.\\nBoth teams then got into it and threats were allegedly made.\\nNo doubt the fight could have been avoided by giving the misbehaving individuals a timeout in the corner and making them miss recess.\\nInstead, Vito Frijia owner of the London Lightning and a member of the league executive committee left from London to see if he could straighten out the issue. Also in Windsor was Brampton A\\'s coach David Magley.\\nAs Frijia was heading to Windsor, he managed to stop the Rainmen bus that was heading to the airport on the highway in the other direction.\\n\"I made them pull over and I talked to them about an hour trying to sort things out but they were worried about their safety,\" said Frijia who when he initially heard about the fight extra security earlier in the day.\\nFrijia said early in the evening that the game was not forfeited.\\n\"We are going to have a conference call (Saturday) morning and see what\\'s going to happen,\" he said.\\nHe said Magley would be one of the key figures investigating the situation.\\nYet several hours later there were reports that the game was forfeited and Windsor were league champs.\\nIt all makes the league an even bigger joke.\\nFrijia said that the biggest issue is that many of the players, especially on the Rainmen team, already have contracts to begin play in other leagues next week.\\nIt\\'s a nightmare for Frijia and the NBL. This is a league that among other things announced a television contract that didn\\'t exist and that has had three commissioners in four years. The last commissioner Paul Riley announced he was leaving the position on twitter only to have the league try to one-up him an hour later by saying he was fired.\\nThe idea that a Game 7 to decide a championship wasn\\'t played because of safety concerns stemming from a punch-up in a morning shootaround will no doubt add to the belief that the NBL is the Wild West with the only thing missing the shootout at the OK Corral.\\nGive it time though. If the league continues to operate without independent supervision, the OK Corral will seem like a spitball fight compared to what might happen.\\nThe reality is that not even a stick of dynamite shoved in some of these owners\\' nether regions enough of a wake up call to turn them into professionals.\\nWith Thursday\\'s circus, they\\'ve truly earned the moniker National Bush League of Canada.<s> COUSIN-Special multi-level ends easily create perfect wire loops and jump rings! Features soft comfort handles and creative tips on back! Warning: Keep out of reach of children. Not a toy or for use by children.<s> SAN FRANCISCO, February 15, 2013 – David Lazerwitz, environmental partner and co-chair of Farella Braun + Martel\\'s Renewable Energy and Clean Technologies Group, was named to the inaugural LMG Clean Technology & Renewable Energy guide\\'s CleanTech 100. The list recognizes the top 100 clean technology and renewable energy attorneys practicing in the industry today.\\nLazerwitz was commended by peers for \"doing outstanding work in the renewable energy space with his group.\" He represented First Solar in connection with the federal, state and local permitting and regulatory approvals for the 550-MW Desert Sunlight Solar Farm and the 140-MW Campo Verde Solar Project, and currently represents First Solar, NextEra Energy Resources and Calpine Corporation in connection with several existing and development stage renewable energy projects in California and Nevada.\\nThe guide listed Farella Braun + Martel as a \"recommended\" firm in the Regulatory practice area. Farella\\'s abilities within the sector were noted as being \"outstanding when it comes to developing clean technology projects.\" Farella is noted for handling extensive clean technology and renewable energy work concerning land use and environmental compliance issues and corporate transactions.\\nResearch included interviews and surveys completed by partners active in the market. Firms were selected as a result of extremely positive feedback received from interviews with peers and clients and were viewed as leading actors in a particular practice area.\\nFarella Braun + Martel represents clients throughout the United States and abroad in sophisticated business transactions and high-stakes commercial, civil and criminal litigation. Founded in 1962, the firm is headquartered in San Francisco and maintains an office in the Napa Valley focused on the wine industry. Farella Braun + Martel lawyers are known for their imaginative legal solutions, dynamism and intellectual creativity. With an unwavering service ethic and interdisciplinary team approach, the firm is committed to advancing clients\\' objectives in the most effective, coordinated and efficient manner.<s> The Bamboo Running Boards are a must add accessory. They match the Bamboo deck and provide more comfort for your passengers or better support for cargo.\\nNote: Only compatible with the Boda Boda Cargo Bike.<s> / Beach House\\n/ Lilo & Stitch: 2-Disc Big Wave Edition\\nLilo & Stitch: 2-Disc Big Wave Edition\\nSomething for the kids and Hawaii lovers while relaxing at the beach house, Lilo & Stitch: 2-Disc Big Wave Edition. For those who might not be familiar with this DVD, this animated film\\'s story revolves around two eccentric and mischievous individuals: a young Hawaiian girl named Lilo Pelekai, who is raised by her older sister Nani after their parents died in a car accident, and a blue extraterrestrial animal-like creature named Experiment 626 (aka Stitch).\\nSet in Kauai (aka the Garden Isle), Nani decides to let Lilo adopt a dog and this is where Lilo is introduced to Experiment 626 / Stitch where he is pretending to be a dog. Stitch, who is genetically engineered by his scientist creator to cause chaos and destruction, initially uses Lilo to avoid being captured by an intergalactic federation, but Lilo and Stitch develop a close bond through the Hawaiian concept of ʻohana, or extended family, and for much of the movie the hijinx ensue as Stitch tries to avoid being captured.\\nThis bond with Lilo causes Stitch to reconsider, and eventually defy, his intended destructive purpose in order to keep his extended family together so yes, it\\'s a happily ever after beach themed movie, but a highly entertaining one that parents can enjoy with their kids at the beach. Is the bonus 2-disc Big Wave edition.\\nWidth: 9.00 (in)\\nHeight: 6.00 (in)\\nSKU: AM-L&S:2DBWE\\nWarranty: You can return any new, unopened item(s) within forty five (45) days from the day it was ordered, that counts as day one (1) and you have until day forty five (45) to postmark your return, for a full refund without question. For items that have been opened, tested, tried on, etc., we will honor the forty five (45) return day period as long as there is no noticeable wear and tear on the item(s) returned. While the outbound shipping costs are not refundable, we will pay the return shipping costs as determined by BeachNecessities.com. There is no handling fee of $4.95 if the total return weighs < eight (8) oz.\\nWave Coaster\\nGhost Wave<s> BMW engines are set to be used in the new 4x4 workhorse, currently called Projekt Grenadier, that Ineos boss Jim Ratcliffe wants to put into production. He talks about its development here.\\nGrenadier – has moved a step closer with news that it will be powered by BMW engines.\\nBoth petrol and diesel units will be provided by the German marque and the Grenadier is due to go on sale in mid-2021.\\nPrecise details of which engines from BMW will be used have yet to be confirmed, but it\\'s likely the Grenadier will use the 252bhp 2.0-litre turbo petrol and 261bhp 3.0-litre turbo diesel from the X5 range.\\nHowever, the team behind the Ineos-backed car say it is not a collection of other companies\\' parts but a coherent model that BMW has accounted for in its development programme. This means the Grenadier will use the latest BMW powerplants rather than previous generation motors.\\nThe Projekt Grenadier will not come with an electric option for the foreseeable future as Ratcliffe believes it adds too much weight and complexity for what he wants to achieve.\\nThe Grenadier aims to be a replacement for the Land Rover Defender that went out of production at the end of 2015. Ratcliffe says this has left a gap in the market for a truly utilitarian 4x4 that is not an SUV.\\nHe says he wants to put the \"utility back into 4x4s\" and the new car will be narrower than most rivals such as the Toyota Hilux and Jeep Wrangler. He added the Grenadier will have its wheels as close to the corners of the vehicle as possible for the best off-road ability.\\nWhile the Grenadier has moved away from the first idea as that looked like an older Land Rover, the simple approach to design has remained at the core of the car.\\nIt will feature flat glass that\\'s cheaper to make and replace if it\\'s broken, as well as a pared-back interior with rubber mats and seats that can be hosed clean.\\nRatcliffe added: \"It might sound arrogant to think we can fill the gap left by the Defender, but we have the confidence.\\nIneos Automotive believes it can sell up to 30,000 Grenadiers each year, with many being used in places such as Africa and Australia.\\nThe company is currently looking for a factory site in the UK where it can assemble the Grenadier using its own chassis with aluminium bodywork offered in a variety of styles to suit the needs of different users. Ratcliffe expects the Grenadier to cost from £30,000 when it goes on sale.<s> August 14, 1972-- Bridgeview Disaster Narrowly Averted\\nChicago Tribune photo\\nAugust 14, 1972 – During the evening rush hour, the temperature in the Chicago area drops quickly from 94 degrees to 71 as winds from the west at over 60 miles-per-hour kick up. As the dark storm clouds move quickly toward the city, 800 people in Bridgeview are gathered in a circus tent, watching the elephant act of the Rudi Brothers Circus. Fortunately, officials at the site spot the storm moving toward them, and order the tent cleared before winds topple four 50-foot poles onto the empty bleachers, covering the area with torn and twisted canvas. Bernard Mendelson, one of the managers of the circus, says, \"When you\\'ve been around a circus as long as I have, you develop a sixth sense about these things. I told [my partner] Rudy, \\'Get those people out now, right now.\\'\" [Chicago Tribune, August 15, 1972] The ringmaster, Charles Cox, is alerted and announces, \"Ladies and gentlemen there\\'s a little wind blowing up. Would you please leave the tent by the front entrance because the elephants will be going out the other way. Please walk, don\\'t run.\" As people file out, the musicians continue to play as the tent begins to shudder in the wind. Circus performers spend most of the night, clearing the debris so that the circus, sponsored by the Confederation of Police as a fund-raiser for drug abuse information programs and a legal defense fund for its members, can go on the following day in an improvised setting.\\nAugust 14, 1960 – The Chicago Daily Tribune reports that a building at 739 North State Street has been raised, and the rubble is made up of the remains of the flower shop that Dion O\\'Banion ran, a place \"where murders, boot-legging, and hi-jackings were planned amidst flowering plants and the scent of roses.\" [Chicago Daily Tribune, August 14, 1960] Ironically, at the time \"the same building that once served as the headquarters of a bloody band of killers during the guzzling decade of the twentieth century\" was most recently used as a meeting place for the Young People\\'s club of Holy Name Cathedral. In April of 2017 it was disclosed that JDL Development had agreed to pay $110 million to the Archdiocese of Chicago for the 90,000 square-foot property three blocks west of North Michigan Avenue. On January 18, 2018 the Chicago Plan Commission approved a project to build two towers on the site, the taller of which will be the eighth Chicago \"supertall\" building at 1,011 feet. The killing of Dion O\\'Banion in the shop in 1924 touched off a gang war that lasted for five years, pitting the North Side gang of O\\'Banion against Al Capone\\'s gang from the South Side. The black and white photo shows the flower shop. The second photo shows the future of the site -- it will hold the sixth tallest building in the city, One Chicago Square.\\nAugust 14, 1936 –Nathan Goldblatt signs a contract for the purchase of the residence built by Benjamin Marshall in Wilmette on Sheridan Road opposite the Baha\\'i Temple. It is reported that Marshall, the architect who designed the Drake Hotel, the South Shore Country Club and the Blackstone Theater and a host of other impressive buildings, had reportedly spent over a million dollars on the home and its furnishings. The Spanish-influenced home commanded a view of Lake Michigan … the Sheridan Shores Yacht Club used the home\\'s basement as its clubhouse. Marshall\\'s work studio had a space for 45 draftsmen. The home had a 50-foot-high, 75-by-100-foot tropical garden with palm and banana trees. The home\\'s swimming pool was lined with turquoise tiles from Algiers. Goldblatt reportedly paid $60,000 for the home but did not stay there long, and in 1950 Wilmette had the home razed. Only the wrought-iron gates remain on the property, which is today owned by the Baha\\'i Temple.\\nAugust 14, 1933 – Joseph Hastings, a Chicago policeman married for only four months, is shot to death during a gun battle with two thieves who rob a city office on Navy Pier. He is the eleventh policeman to die in the line of duty during 1933. The money that is stolen was intended for men on emergency relief who were employed by the city to do work at the pier. Thomas B. Rawls, an official of the West Englewood Currency exchange, used it to cash checks from the workers at a fee of 15 cents a check. It is unclear why a representative of a private enterprise is cashing checks in an office of the city street department. Hastings, hearing a shot fired, runs into a second floor office at the west end of the pier. One of the dozen clerks in the office, Charles Eddy, outlines the ensuing events, \"Hastings came in the door with his revolver drawn . . . The man at the side wall opened fire. The policeman fell to the floor and fired two shots in return. The robbers ran to the door. Hastings got up, and one of the robbers turned and shot him as he rose. The robber then grabbed Hastings\\' gun and ran out. . .\" [Chicago Daily Tribune, August 13, 1933] Morris Cohen a barber, is captured 30 minutes later at 1331 North Clark Street. His two companions remain on the lam. The above photo depicts Navy Pier as it appeared in 1933.\\nPosted by Chicago Old and New at 12:30 AM\\nLabels: 1972, Chicago Event, Weather Events\\nAugust 31, 1902 -- Lake Michigan Melee\\nAugust 30, 1937 -- Lake Shore Drive in Lincoln Par...\\nAugust 29, 2013 -- Wolf Point West Gets Go-Ahead f...\\nAugust 28, 1929 -- Graf Zeppelin Gives Chicago a Show\\nAugust 27, 1939 -- Peoples Gas Building Loses Its ...\\nAugust 26, 1920 -- Children\\'s Memorial Hospital Be...\\nAugust 25, 1900 -- Coliseum Dedicated\\nAugust 24, 1966 -- John Hancock Center Stops Work\\nAugust 23, 1985 -- Navy Pier\\'s Slow Disintegration...\\nAugust 22, 1982 -- Wabash Avenue Strip Joint Busted\\nAugust 21, 1982 -- East Delaware Place Hotel Conve...\\nAugust 20, 1990 -- Standard Oil Sheds Its Carrara ...\\nAugust 19, 1926 -- Chicago River Bridges Slammed b...\\nAugust 18, 1904 -- Lake Bluff Protests Navy Propos...\\nAugust 17, 1978 -- Michigan Avenue German Consulat...\\nAugust 16, 1978 -- Loop Elevated Should Go ... Say...\\nAugust 15, 1911-- Grant Park Aero Meet Sees Two Av...\\nAugust 14, 1972-- Bridgeview Disaster Narrowly Ave...\\nAugust 13, 1946 -- Chicago Park District President...\\nAugust 12, 1942 -- Blackout in Chicago As City Hol...\\nAugust 11, 1900 -- Diversey Parkway Bridge Complete...\\nAugust 10, 1945 -- La Salle Street Tunnel Closed\\nAugust 9, 1972 -- Columbus Drive Bridge to Make Tr...\\nAugust 8, 1981 -- Rush Street Round-Up Sees 153 Ar...\\nAugust 7, 1978 -- Illinois Center\\'s First Resident...\\nAugust 6, 1911 -- La Salle Street Tunnel Creating ...\\nAugust 5, 1966 -- Cr. King Felled by Rock in Chica...\\nAugust 4, 1902 -- Subway Needed in Chicago\\nAugust 3, 1978 -- State of Illinois Office Tower t...\\nAugust 2, 1978 -- Michigan Avenue Bridge Honored a...\\nAugust 1, 2001 -- Trump Is a Gucci Carpetbagger Sa...<s> Video: Condemnation and Eminent Domain - What Is It?\\nVideo: What Can a Landowner Do When Facing Condemnation of His Property?\\nOur experience and willingness to forcefully litigate condemnation cases through trial has given us the advantage of better settlements where possible.\\nGovernment at every level have the power of eminent domain; the unilateral taking of private property for the benefit of the public. Under the pretense of having appraised the value of the property, however, the process is heavily weighted in favor of the government and against the landowner. When the process starts, the landowner loses title immediately and is forced to fight an uphill battle to try either to prevent the taking or to exact fair compensation for his property or his business.\\nOur lawyers have decades of experience in contesting condemnation actions by all level of government agencies of Georgia. Whether at the state, county, city, or utility level, we are skilled in contesting the valuations presented by the government. Our lawyers have developed some of the key decisions in the area of eminent domain in Georgia. They have represented the interest of both the landowner and commercial tenants. For landowners, they have protected the interests by forcing the government to clearly state the extent of the interest being taken, which has often resulted in increased awards at trial. For commercial tenants, they have developed strategies for identifying and proving damages and losses suffered by businesses in property affected by condemnation.\\nOur experience and willingness to forcefully litigate condemnation cases through trial has given us the advantage of better settlements where possible. Absent pre-trial resolution, our lawyers will skillfully maneuver the defenses and arguments presented by the government and its appraisers to bring the landowner or the tenant the best possible outcome.\\nOur lawyers have presented seminars to attorneys on eminent domain procedures and current events in the area of practice for over 28 years.\\nChallenged the description of an easement for the removal of \"danger trees\" in a condemnation petition, resulting in a later date of taking of the property and therefore a higher property value.\\nChallenged the description of a \"temporary work easement\" in a case where a commercial building had to be removed because of the project, resulting in the condemning authority\\'s payment of additional funds for square footage contained in the easement, a new date of taking and therefore a higher value on the whole parcel.\\nSuccessfully tried a business loss claim of over $2,000,000 before a jury on behalf of a commercial tenant against the Department of Transportation\\'s argument that the business was worthless, resulting in a 100% recovery of the tenant\\'s losses.\\nContested the DOT\\'s argument that property presently being used as residential could not be valued as commercial property, resulting in a valuation of over 250% more than what was presented by the government.\\nRepresented a commercial landowner of a corner property on a heavily traveled state road against two separate takings, the first by the county and the second by the DOT, showing that the county was aware of the planned subsequent talking by the DOT and that the county\\'s taking would eliminate access from the most visible and valuable part of the property.\\nLitigated the loss of a tract of property with an ongoing business on it to a settlement representing all of the landowner\\'s appraisal and 90% of the interest that would have been recovered at trial if the jury result had been to accept the landowner\\'s appraisal.\\nChallenged the taking of portions of an aging shopping center on behalf of a commercially successful business, forcing the recovery of a substantial settlement beneficial to the tenant.\\nNegotiated a change in the planned construction of a road, preserving a business owner\\'s access to the property by either a right or left turn in and out.\\nIncreased the award over the condemning authority\\'s testimony of value at the Special Master\\'s level of an office building in Midtown Atlanta and thereafter successfully negotiated a settlement for an additional $1.5 million and an advantageous lease in the property pending the commencement of construction and use by the condemnor.<s> Join us every Saturday afternoon from 2 to 4 for a journey into rare and novel teas with Kevin, Fly Awake\\'s senior wizard. Not to be missed. Come and explore areas of tea nerdiness unknown to most and feared by some. Also, alter your states!<s> Your virtual box seat to New England\\'s professional sports & live concerts.\\nDanny Amendola comes up big in Title Game for Patriots\\nQ: The third-and-18 situation – can you take us through that particular play? Also, can you walk us through your two touchdowns?\\nDA: The third-and-18 play, basically I think I had a little bit of an option route in the middle of the field and I saw that there was room. I had pointed out the line [to gain] before the play snap so I knew where to get to and Tom [Brady] had a laser and it was perfect. The two touchdowns: the first one, the go-ahead touchdown. It\\' s a play we\\'ve worked on – I scored on it a couple of times this year, I think, actually. I have a crosser in the back of the end zone and Tom reads the first whip route on the left to \\'Cookie\\' [Brandon Cooks] and then if he doesn\\'t have it then his eyes come to me in the back. We had it and it was a zone coverage. I obviously didn\\'t see what happened to Cookie on the first read and then Tommy had a great ball. I knew it was coming right by that \\'backer or safety in the back. It was a great throw.\\nQ: Your Patriots career was off to a relatively slow start. How does it feel to get to the point where you\\'re the No. 1 guy in the AFC Championship Game?\\nDA: I\\'m thankful for my opportunity here and what it\\'s been the last five years. I have a lot of great memories here. Any negative thing or anything that\\'s tried to hinder me, I try to ignore and focus on the positive things that have been going on in this building for the last five years for me. I\\'ve tried to build off that and be a good teammate and that\\'s the only thing I really focus on.\\nQ: It seemed like on your 20-yard punt return they kind of rushed the snap to get off a quick punt. Did that happen?\\nDA: I\\'m not sure. It was a quick snap. A lot of teams do that but I\\'m not sure what they were thinking. I believe we had a block on. We knew we were going to get pretty good field position. I think I was standing on the 40 or so and it was just about getting some yards.\\nQ: You had a lot of fair catches to that point…\\nDA: The punter was doing a great job all night of not out-kicking his coverage so to speak—kicking the ball high. I had my feet on the 10 a lot so I knew that he wasn\\'t going to kick it over my head and it was going to give him time to get down there. On that particular punt, I saw the rush. When you rush on a punt return, usually it holds the guys up even more. When they get out, they get scattered [and] they are not blocked. It just comes down to making a play when you get the ball in your hands, following a block or two or seeing any open space to get to. That was it.\\nQ: What did you notice from Tom Brady over the last week and everything that happened?\\nDA: Tommy\\'s the best. He\\'s the toughest guy I\\'ve ever met physically [and] mentally. If there is anything that happens to Tom, I know he can handle it. It was unfortunate to see him get injured mid-week. I know mentally it probably stressed him out a bit and physically I know it\\'s hard to throw a football with stitches in your thumb. Everybody knows how tough he is. Everybody knows that he\\'s our leader. It\\'s a testament to his career, his personality, the man he is. Not only is he the best player in our locker room but he gets everybody else to play well and step their game up and that\\'s why he\\'s the best.\\nQ: Do you feel any more internal pressure to step up when somebody like Rob Gronkowski comes out of the game?\\nDA: I don\\'t feel any added pressure, no. Every play I\\'m competing my tail off to try to win the route, win the block or whatever my job is on that play. Whoever is in the game, whoever is beside me, I have a lot of trust and faith in them whether it\\'s Gronk or Cookie or Hoagie [Chris Hogan]. Whoever it is, I know we have a lot of trust in this room.\\nQ: Can you talk about the Jaguars defense? They were playing so well, especially in the first half.\\nDA: Hats off to them. They played hard. We came out and we didn\\'t get many points on the board early. We made some adjustments at half. We wanted to come out and play faster, play more physical. We knew it was going to come down to the wire. They are a great team and they had a great season.\\nQ: When you heard that the double pass was called for you, did you get the sense it was \\'break open in case of emergency\\' or \\'all hands on deck\\'?\\nDA: We are trying to score. Whatever we\\'ve got to do. I don\\'t remember what happened on the flea-flicker. Who got the flea-flicker one? I don\\'t remember. [Phillip] Dorsett, that\\'s right. That\\'s a big play by Phil. Big play in the game, too. It worked out.\\nKevin Harriman\\nAFC, AFC Championship Game, Amendola, Football, Gronk, Patriots, pressure, Tom Brady\\nWritten by Kevin Harriman\\nI live a simple life, following a few beliefs that have served me well: 1) Boston sports are a religion for those of us in New England, despite the fact that the good Sisters of St. Joseph told me other wise from grades 1 through 12. My knuckles still hurt ! 2) Never tap out. Did the Americans give up when the Germans bombed Pearl Harbor ? 3)Life is too short to drink cheap booze ! WELCOME TO BOSTONSPORTSDESK.COM\\nView all posts by: Kevin Harriman\\nIt seems humble pie isn\\'t easy for Pats fans/media to swallow as a 20-year run comes to a seemingly screeching halt\\nPointing fingers at others has become the Patriots go to option when it comes to their pathetic offense\\nPatriots Soggy Success Over Dallas is a Huge Win; What it Means for New England\\nPatriots Young Receivers to be Tested Sunday with Injuries Mounting\\nJaroslav Halak comes up big in net for Bruins January 16, 2020\\nSean Kuraly meets the media following win over Penguins January 16, 2020\\nCassidy happy with his teams response in win vs Penguins January 16, 2020\\nIt is become painfully clear that the Bruins favorite color now is yellow January 15, 2020\\nChara not happy with the way B\\'s played in the second half of the game January 13, 2020\\nBoston Sports Desk - Your virtual box seat to New England\\'s professional sports. © 2020 | Privacy Policy<s> Join trivia masters and casual quizzers alike for the Geeks Who Drink Quiz for a Cause, benefiting CURE!\\nThis Quiz for a Cause trivia night covers all topics from celebrity headlines to wordplay to bad television. Whether you\\'re a geek who loves science, pop culture, sports, or history, there\\'s a question for you.\\nWhen you join us for Quiz for a Cause, you\\'re automatically eligible to win gift cards to Cortland\\'s Garage. If each player on your team donates at least $5 to CURE during the event, you\\'ll also be eligible to win a cash prize of $5 per each team that donated!\\nThe maximum team size is 6 players. If you want to play but don\\'t have a team, come anyway. We\\'ll help you get recruited onto an existing team.<s> As we mentioned last December, detached homes in the priciest parts of Greater Vancouver continue to hold their value despite predictions of a crash. Houses in Vancouver West (west of Ontario Street), the most expensive real estate zone in B.C., are 28 per cent above the levels of five years ago, while adjacent areas such as East Vancouver and Richmond are almost as strong.\\nApartment markets are weaker across the board, according to current figures from the Greater Vancouver and Fraser Valley real estate boards. In every market from Abbotsford to West Vancouver, detached homes have outperformed apartments over the past five years.\\nThe differences are often dramatic. Coquitlam has seen a 10 per cent increase in house prices over five years, and a 10.8 per cent decrease in apartment values; detached homes in South Surrey/White Rock are up 13.3 per cent in the same period, compared with a 16.8 per cent slide in apartment prices. Apartment prices on the east side of the City of Vancouver have risen slightly (3.5 per cent), but in this area house prices are up 23.6 per cent.\\nA modest general rally in apartment prices in February might be cause for hope for owners and sellers, but the fact is that markets have bounced around for years, generally in a downward direction.\\nLooking for the simplest explanations, it\\'s clear that apartment supply has grown substantially since 2008, especially at tower-dominated transit nodes such as Brentwood, downtown New Westminster and Coquitlam Central. And there is almost certainly less speculative money going into apartments: investor opportunities for windfall gains are less, the politics of strata management can be tiresome, and the leaky condo problem is still with us more than 25 years after it first emerged.\\nDespite the relative price weakness, developers continue to bring new supply on stream, presumably in expectation of a profit. There are apartment projects underway in most of the places we\\'ve visited in recent months — Metrotown, Austin Heights, White Rock, Burnaby Heights, uptown New West, and on and on. This makes sense, at least theoretically, in a world where older people are retiring and downsizing, and where younger people are looking for their first home purchase. The relative price stability of the apartment markets makes it possible to plan a down payment and the ensuing monthly payments with some confidence.\\nWriters on urban affairs assure us that many of today\\'s young people will be apartment dwellers for life, staying close to transit and walkable services rather than following their parents to the land of cul-de-sacs. Some even predict that the upper-end detached home in the middle and outer suburbs will become the real casualty in tomorrow\\'s real estate bubble. This trend may be taking hold already; it would be difficult to spot in price tables that report on large, diverse communities such as Coquitlam or Surrey.<s> On 1 to 3 June 2018, EisnerAmper United States hosted its annual Partner Conference for 2018 in Virginia, U.S.\\nThe event was attended by 200 Partners and was a great opportunity for EisnerAmper Global colleagues from the United States, Ireland, Cayman and Singapore to connect over a weekend of activities.\\nDiarmaid O\\'Keeffe, EisnerAmper Ireland, Ray Kelly, EisnerAmper Ireland, Ben Leung, EisnerAmper Cayman and Alastair MacDonald, EisnerAmper Ireland at the EisnerAmper US Partner Conference in Virginia.<s> Disease and Treatment\\nGhosts of My Lai, The\\nThe massacre of hundreds of civilians at My Lai was a turning point in the Vietnam War.\\nHMAS Sydney Memorial Service 2008\\nThe sinking of HMAS Sydney was the worst single loss ever suffered by the Australian navy, and the wreck of the ship was recently recovered off the coast of Western Australia.\\nQuantum - Radioactivity\\nIn a millisecond, on July 16, 1945, the evolution of the human species took a remarkable turn.\\nPart 1: A Deadly Dose\\nRadio Program Sales - Hindsight: Save Our Sons\\nIn the closing days of 1964, Prime Minister Robert Menzies introduced a bill in Parliament which would prove to be one of the most controversial and divisive decisions in Australia\\'s history.\\nSecrets of Stalingrad\\nIt changed the course of World War II - and the whole 20th Century. But until now, the true story of the Battle of Stalingrad has remained shrouded in mystery.\\nShipwreck Detectives Series 1\\nThe Shipwreck Detectives, a dedicated group of Australian marine archaeologists, have made it their life\\'s work to uncover the truth, through discovery and excavation of some of Australia\\'s most no\\nThe Shipwreck Detectives discover ancient shipwrecks using the latest technology.\\nState Funeral of Alec Campbell - The Last Anzac\\nThe State Funeral for Alec Campbell the last Gallipoli Veteran, from the Cathedral Church of Saint David Hobart, Tasmania, held on Friday 24 May 2002.\\nUnfit to Command\\nDuring night exercises in January 1964 the flagship of the RAN, the aircraft carrier Melbourne, collided with the destroyer Voyager 20 miles off Jervis Bay in NSW.\\nVietnam Veterans March 1987\\nLive coverage of the Vietnam Veterans Welcome Home Parade from the Sydney Cenotaph, Martin Place to the Town Hall in October 1987.\\nVietnam Vets Parade and Dedication 1992\\nCoverage of March and Dedication ceremony of Vietnam Veterans Memorial in Canberra on 3 October 1992. Followed by the March of Remembrance by 32,000 servicemen and next of kin.\\nVivian Bullwinkel: An Australian Heroine\\nVivian Bullwinkel: An Australian Heroine chronicles the extraordinary life and legacy of the woman who is one of Australia\\'s greatest war heroines.\\nWoomera: Silent Partners, The\\nThe history of Woomera rocket range, from 1946 to 1979. The program includes declassified defence footage of life at Woomera and the 4,000 rocket tests conducted there.\\nRemembrance Ceremony for Vietnam\\n2006 was an extremely important year for honouring and remembering Vietnam veterans and also marking the 40th anniversary of the Battle of Long Tan.\\nPatriots Three\\nIn September 1915 a patriotic young Australian journalist named Keith Murdoch visited the Anzac battlefield at the Dardanelles where, just weeks before, thousands of Australian and British soldiers\\nFour Corners - Careful War, A\\nTwo soldiers lost in action in 2010 were Sapper Jacob Moerland and Sapper Darren Smith. Four Corners spent a month with Australian troops, much of it with their company.\\nEntombment of the Unknown (Australian) Soldier\\nLive coverage from Canberra of the ceremony at the Australian War Memorial when the body of an unknown Australian serviceman is interred with full military ceremony in a redesigned part of the Memo\\nEnough Rope - Anzac Day Special\\nWar changes everything and everyone. Each year on April 25 thousands of Australian men and women commemorate Anzac Day, each carrying with them memories as vivid now as the day they happened.\\n(-) Remove Health and Medicine filter Health and Medicine\\n(-) Remove Disease and Treatment filter Disease and Treatment\\n(-) Remove Schools Programming filter Schools Programming\\n(-) Remove BTN filter BTN\\nPeach\\'s Gold (1) Apply Peach\\'s Gold filter\\nABC Programs (684) Apply ABC Programs filter<s> Technology to maximize the power of geothermal energy is actually an area that really needs to be explored. It is one area which has a lot of potential. The Earth generates huge amounts of natural energy underground that basically needs to be utilized. As we approach our daily lives, we have no clue about the tremendous force that lies below our feet. All we must do is discover a way to take advantage of that energy for ourselves. The heart of the Earth is about sixty times hotter than boiling water. There is a lot of energy merely a few miles below the Earth\\'s surface that have already been created from the scorching heat generated from the Earth\\'s core.\\nIf you have ever watched what takes place when a volcano erupts, you will understand that there is much power and also energy in the magma, or superheated fluids. Some of these types of fluids come to the surface in the form of water vapor that is released in vents. Many people have created their very own vents and containment chambers to transform the magma into energy to power their households. A plant which could take advantage of this powerful resource needs to be built close to an area with a great source of heated fluid. Steam would be generated from the fluids that would be forced to the surface through the tubes that have been fitted down directly into the magma. An adequate amount of the steam would produce electricity, by turning a turbine engine.\\nNeedless to say, using geothermal energy on a massive scale does have a handful of controversy. Some critics believe that the cost of research and implementing is too costly and too time consuming. On top of that, the cost to build a plant is high with absolutely no guarantee that it could turn a profit. There is furthermore a chance that once a plant is completed, there might no longer be enough steam to generate electricity. There is also deep concern by environmentalists that toxins will also be brought up as well as the steam.\\nBut the advantages to utilizing geothermal energy significantly outweighs the criticisms. Further research should show that the energy would be provided by the Earth, so any toxins would be minimal. As soon as a geothermal plant is set up the work needed to channel the energy isn\\'t that great, making this type of energy very efficient.\\nThe natural environment would be disrupted less, because the plants are smaller compared to giant dams, atomic energy, or electrical facilities. With substantial use of geothermal energy, there would be less reliance on coal and oil for fuel.\\nWhat we realize for sure is that the price of geothermal is moving down and that the energy itself is an inexhaustible resource. While the initial upfront cost is still significant, once the capital is made back, it will be a very cheap source of energy. This really is a source of energy that will likely be in demand.<s> In 1900, mathematician and physicist Lord William Thomson Kelvin proclaimed, \"There is nothing new to be discovered in physics now. All that remains is more and more precise measurement.\" Kelvin was wrong, of course. In fact, he could not have been more incorrect—the next few decades alone saw the discovery of general relativity, other galaxies, radioactivity, and quantum mechanics, to name a few fields.\\nA while back I posted about some awesome optical illusions. The last few posts have been text-heavy, so I\\'m going to shake things up a bit with some pictures and videos. These are some of my favorite mind-tricks on the web. Share your favorites and let me know which one\\'s you\\'d like me to explain. Enjoy!\\nThese men are the same size. Seriously. Grab a ruler and check for yourself.\\nThink you see the world as it is? Think again. As discussed in an earlier post, our brains filter input from the senses, piecing together a world that differs from reality. To shake up the old blogging formula (and to make room for these theoretical math midterms currently dominating my life), I\\'ve compiled a list of some of the coolest optical illusions on the web. Aside from being awesome, these give insight into how the brain interprets visual cues. I\\'ll be back soon with the science behind the coolest ones.\\nThe textbook \"motion where there is no motion.\" Tried and true. A classic.<s> This Baby\\'s Feelings About Avocados Are Basically The Same As Our Feelings About Paying Extra For Guacamole — VIDEO\\nBy Maya Kachroo-Levine\\nBeing healthy is the worst. In theory, we all like clear skin, and that fresh invigorated feeling after lunch that only happens when you decide against the cheeseburger. But sometimes you just want to lean in to a particularly awful day and say an enthusiastic \"YES\" to anything with heavy cream. And you deserve it. You deserve to say no to kale, sweet potatoes, avocado and green juice. And so does this baby who tried her first avocado and hated it. Whatever degree of \"can\\'t even\" you hit with green juice, this kid\\'s got you beat by a long shot. She looks like she just saw an 8-foot spider crawl out of the Forbidden Forest. (She\\'s the baby version of Ron Weasley.)\\nI understand that those of you have a strong affinity for these blessed fruits might be a little offended. I feel you—I\\'ve legitimately written articles on how much I like avocados. But it\\'s hard to be offended by a child who\\'s less than a year old. Her bib is lined with pink and polka dots, guys. Come on. Just let her be miserable and trust that her scrunched up face will make you happy because that\\'s how the internet works.\\nPresenting, the baby whose post-avocado pout is the cutest thing you\\'ll see all day:\\nNot everyone was born to love guac.\\nC l e a r l y.\\nWatch the full blown avocado-induced tantrum:\\nKentuckyFriedIdiot on YouTube\\nIf you\\'ve spent enough time trolling for viral videos, you\\'re fully aware that this isn\\'t the only baby on the Internet who can\\'t deal with specific foods. While I\\'m not in love with everyone one of those children (sorry, my maternal gene only goes so far on YouTube), I\\'ve got a special place in my heart reserved for the babies who just ate their first lemons.\\nWhat\\'s that? You\\'ve never heard of the babies trying their first lemons? That\\'s like saying you missed the \"Let\\'s get some shoes\" video. And we both know if you\\'re saying that, you\\'re lying. Fix yourself and watch some of these sassy baby faces:\\nfunnyplox on YouTube\\nA plus parenting, internet. We\\'re all so proud.\\nImages: YouTube (2)<s> Eurobites: Trump Won\\'t Trash Privacy Shield, US Officials Predict\\nNews Analysis Paul Rainford, Assistant Editor, Europe 11/10/2016\\nAlso in today\\'s EMEA regional roundup: ETNO welcomes 700MHz moves; Gilat lands Spanish trains gig; Ziggo rebrands.\\nOK, he may try to build a you-can-see-it-from-space wall on the US-Mexico border, prepare the ground for civil war and instigate a new global economic depression through the imposition of trade tariffs, but the Privacy Shield, the framework which governs the transfer of data from Europe to the US, will be safe in the fun-sized hands of President-elect Donald Trump. As Bloomberg reports, that\\'s the encouraging message coming from the US Department of Commerce, which is insisting that the framework was designed with political transition in mind. The Privacy Shield, which replaced the discredited Safe Harbor arrangements, is intended to place stronger obligations on US companies handing Europeans\\' personal data, limit US government access to such data and provide EU citizens affected by such issues with greater chance of redress. (See Eurobites: Privacy Shield Gets EU Go-Ahead.)\\nThe European Telecommunications Network Operators\\' Association (ETNO) has welcomed the European Parliament\\'s decision to allocate 700MHz spectrum to mobile broadband by 2020, believing that this is necessary for Europe to maintain a leading role in the development of 5G. ETNO also thinks that EU member states should be allowed to retain the flexibility to allocate sub-700MHz spectrum to mobile broadband in a \"technology-neutral manner.\"\\nIsrael-based Gilat Satellite Networks Ltd. (Nasdaq: GILT) has landed a contract with Renfe, the Spanish railway company, which will see the vendor deploy its ER-7000 antenna and attendant technology on Renfe\\'s high-speed trains to provide passengers with mobile broadband.\\nSweden\\'s Tele2 AB (Nasdaq: TLTO) has appointed Stina Andersson EVP for strategy and business development, effective December 5. Andersson was most recently investment director at Kinnevik, Tele2\\'s largest shareholder. Her brief will include oversight of Tele2\\'s IoT division.\\nIn a move that demonstrates the power of local branding, Ziggo B.V. , the Dutch cable operator owned by Liberty Global Inc. (Nasdaq: LBTY), is dropping Liberty\\'s Horizon brand in favor of Ziggo, Broadband TV News reports. Ziggo says that focus group research showed that users of its Ziggo-branded services were the most loyal customers. The initial rebranding will affect Horizon Go, an app that offers live streaming TV on mobile devices.\\n— Paul Rainford, Assistant Editor, Europe, Light Reading\\nCybersecurity: Priorities & Proposals for Small ISPs<s> Nothing beats delicious food and colourful cocktails on a Sunny day! We had so much fun exploring and sampling the culinary delights that Taste of Sydney had to offer this year. Loving that feeling of leaving with bellies full from eating from some of the best Sydney has to offer!<s> The all-white Nike Air Force 1 Low is more than just a shoe: it\\'s a veritable cultural icon. One of the Swoosh Brand\\'s best-selling, most recognizable, and most influential silhouettes, it\\'s garnered thunderous acclaim from a smorgasbord of subcultures. Although it\\'s been said that you don\\'t want to mess with a classic, a new premium leather take on the all-whites has surfaced — and it features a compelling embellishment: oversized Swoosh logos. Due to the monochromatic color palette, you\\'d be forgiven for mistaking this as a plain white-on-white at a brief glance, but closer inspection reveals that the Swoosh is indeed super-sized, taking up a vast majority of the real estate on both the lateral and medial quarter panels. Less noticeable tweaks are also present on the heel and tongue, with the normal style of Nike Air branding o replaced by debossed leather accents. If you like the updated look, you can check these Air Force 1s off your shopping list via the retailers below for $130 USD.<s> Audioboom / Best of the BFFs: 4/9 to 7/9...in 3 minutes!\\nIn 3 minutes, Gregg Sussman and Frank Stampfl teach you how Derrick Henry falling low in a draft is robbery, and how Gregg can use his confrontational skills in life.\\nBest of Fantasy BFFs, August 27th to 31st...in 3 MINUTES!\\nThe Best of Fantasy BFFs Sept. 10th to 14th...in 3 minutes!<s> Port lotniczy Katukurunda – port lotniczy położony w mieście Kalutara, w Sri Lance. Jest używany do celów wojskowych. Obsługiwany przez Sri Lanka Air Force.\\n\\nBibliografia \\n\\n Informacje na stronie OurAirports\\n\\nKatukurunda<s> With Reinforced Corners and Two Internal Pouches. Adjustable Dividers and a Shoulder Carrying Strap. This case is durable and stylish!\\nThis stylish tool case is ideal for computer and copier repair technicians, electricians, photographers and all professionals who depend on their tools for a living. This Clarke tool box is constructed from silver anodized aluminum. The outside dimensions are 18.75\" x 14.25\" x 6.5\" and weighs 8.5 lbs. The inside dimensions are 17\" x 12\". It has reinforced corners, key lock latches, 2 internal tool pouches, adjustable dividers and a shoulder carry strap.\\nOutside Dimensions: 18.75\" x 14.25\" x 6.5\"\\nInside Dimensions: 17\" x 12\"<s> Q: How to create volatile table inn teradata using SAS dataset without sql sandbox I have a SAS dataset and I need to create a volatile table in Teradata using the SAS dataset. But, I do not have a sandbox to store the table on Teradata server. Is there a way that I can create a Teradata volatile table from a SAS dataset without SQL Sandbox.\\n\\nA: It is pretty simple to create a volatile table in Teradata, just use the dbmstemp=yes option on your libname statement.  \\nlibname TDWORK teradata connection=global dbmstemp=yes .... ;\\ndata tdwork.test1 ;\\n  set sashelp.class ;\\nrun;\\n\\nMake sure to use the connection=global option on all of your LIBNAME and CONNECT statements so that all of the connections to Teradata use the same session so you can see your volatile table.  Keep at least one of the libref\\'s open so that the connection persists.\\nThen you could also use passthru SQL to create a volatile table.\\nproc sql ;\\n  connect to teradata (connection=global .... );\\n  execute (\\n    create volatile table test2 as (\\n      select * from test1\\n    ) with data on commit preserve rows \\n  ) by teradata;\\nquit;\\n\\nOr to reference the volatile tables in pass thru SQL code.  \\nSo if you wanted to pull out of Teradata all the records from MYDB.MYTABLE where NAME was in the list of names you uploaded into the volatile table TEST1 you made with the first data step above you could use code like this:\\nproc sql ;\\n  connect to teradata (connection=global .... );\\n  create table mytest as select * from connection to teradata \\n  ( select * from mydb.mytable \\n    where name in (select name from test1)\\n  );\\nquit;\\n\\n<s> Philogenia redunca – gatunek ważki z rodziny Philogeniidae. Występuje na terenie Ameryki Południowej.\\n\\nPrzypisy\\n\\nBibliografia\\n \\n\\nPhilogenia\\nGatunki i podgatunki zwierząt nazwane w 1989 roku<s> The Electron Pencil\\n\"The blog has made Glab into a hip town crier, commenting on everything from local politics and cultural happenings to national and international events, all rendered in a colorful, intelligent, working-class vernacular that owes some of its style to Glab\\'s Chicago-hometown heroes Studs Terkel and Mike Royko.\" — David Brent Johnson in Bloom Magazine\\nBy glabwrites\\tBarry Manilow, Bleeding Heartland Rollergirls, George Wallace, Health Care Reform, Higgs Boson, Marshall McLuhan, Mitch Daniels, Mitt Romney, NAACP, Poverty, Richard M. Nixon, Shelli Yoder, Soma Coffee, Todd Young, Tyler Ferguson\\nThe Pencil Today:\\nTHE QUOTE\\n\"Affluence creates poverty.\" — Marshall McLuhan\\n♢\\nI have a feeling Rep. Todd Young (R-Indiana) is getting a little concerned about Shelli Yoder.\\nShe Works Hard For The Money\\nThe Dem challenger, you may recall, came out of nowhere a couple of weeks before the primary filing deadline and proceeded to trounce four opponents, two of whom were actually serious candidates.\\nYoder\\'s been criss-crossing the 9th District, shaking hands, marching in parades, and listening to folks talk about the state of the nation in diners and church basements. She\\'s been raising dough, too.\\nThe former Miss America second runner-up is looking more and more like the real deal.\\nErgo, the Todd Young campaign is hitting up contributors for what might turn out to be a contest. He\\'s raised $1.2M so for this election season, according to the Herald Times.\\nTYLER EARWORMS ME\\nThe inimitable Tyler Ferguson (Kaka Caliente of the Bleeding Heartland Rollergirls) blew into Soma Coffee this AM, singing \"Mandy.\"\\nYou remember \"Mandy\" don\\'t you? The Barry Manilow hit of 1974 wherein, according to legend, he sings lovingly — some say a little too lovingly — of his lapdog. He wasn\\'t, of course; the song was written by someone else years before Manilow turned it into his first chart-topper.\\nAnyway, Tyler/Kaka was pumped because the selfsame Manilow, she gushed, will be playing in these parts soonly. \"You can get tickets for ten dollars!\" she said. \"I\\'d pay that for him. Nothing more, though.\"\\nWhere? I demanded, so I could leave the region while he was in it.\\n\"I dunno,\" Tyler said. \"Somewhere.\"\\nWhich, come to think of it, is the definitive Tyler/Kaka answer.\\nSo, here\\'s the deal. Manilow will play in Indy on August 3rd and in Louisville, July 27th. Bloomington will be, in other words, surrounded by Barry Manilow.\\nAnd now I have \"Mandy\" looping in my brain.\\new\\'RE BROKE (EXCEPT FOR THAT TWO BILLION BUCKS WE FOUND)\\nI\\'ve never pretended to understand high finance. It\\'s as baffling to me as Higgs Boson is to a kindergartner.\\nAll I know is Indiana Gov. Mitch Daniels and his legislative co-conspirators within the last couple of years have moaned and groaned about how the economy has ruined state finances and, therefore, school funding must be slashed to the bone.\\nSorry, Kids\\nNow, all of a sudden, there\\'s a $2.15B surplus in the Indiana state treasury? And now, all of a sudden, the state\\'ll be to be mailing out $100 checks to each and every taxpayer in the state? During an election year?\\nAre you confused about this, too? I have a sneaking suspicion, though, it all makes perfect sense.\\nROMNEY\\'S SMART\\nSay what you will about Mitt Romney, he played a brilliant hand when he spoke to the NAACP the other day.\\nIn fact, he took a page out of the playbook of the Republicans and Cro-Magnon Democrats of the \\'60s by putting himself in a position to be booed by attendees of the venerable civil rights organization\\'s annual conference the other day.\\nLadies And Gentlemen Of The Negro Race….\\nThe likes of Dick Nixon and George Wallace occasionally would speak before hostile crowds and withstand their jeering just to remind their core constituencies which side they were on. Wallace was particularly adept at the tactic; he loved ranting and raving before college crowds, knowing full well he\\'d get verbal tomatoes (and sometimes the actual vegetable/fruit) thrown at him. His anti-intellectual base would read of the rude response in the papers or see it on TV news and be reminded how much they hated pointy-headed liberals.\\nYou College Kids Hate Me, Donchya?\\nRomney told the NAACP shindig that President Obama\\'s health care reforms were garbage. Natch, the NAACP-ers gave him the raspberry.\\nSome wags say Romney failed miserably in his effort to court black voters. Now there\\'s a misreading of the situation for you. Honestly, do you think Mitt expects to get any meaningful portion of the black vote?\\nNeither do I. But now the Me Party-ists and the shootin\\' iron-totin\\' back country Republicans know for sure that them blacks (saying the word with scorn and rage) are again\\' Romney almost as much as real Americans hate Obama.\\nElectron Pencil event listings: Music, art, movies, lectures, parties, receptions, games, benefits, plays, meetings, fairs, conspiracies, rituals, etc.\\n◗ Stable Studios, Spencer — Bluegrass festival 2012, tonight: Open jam — tomorrow: The Travelin\\' McCoury\\'s, The White Lightning Boys, Rumpke Mountain Boys, Flatland Harmony Experiment, New Old Cavalry, the Stuttering Ducks, The Seratones; 1pm-midnight\\nThe White Lightning Boys\\n◗ IU Dowling International Center — English Conversation Club, for non-native speakers of American English; 1pm\\n◗ The Venue Fine Arts & Gifts — Opening reception, \\'Our Fine Feathered Friends\" exhibit by William Zimmerman, John Gould, James Tracy, Joanne Shank, and Julia Ferguson; 6pm\\n◗ IU Auer Hall — Summer Music Series: String academy final student recital; 6-8pm\\n◗ IU Art Museum — Jazz in July series, Mahluli-McCutchen Quartet; 6:30pm\\n◗ IU Fine Arts Theater — Ryder Film Series, \"Jiro Dreams of Sushi\"; 7pm\\n\"Jiro Dream of Sushi\"\\n◗ Muddy Boots Cafe, Nashville — Whipstitch Sallies; 7-9pm — Bonz; 9:30-11:30pm\\n◗ Monroe Lake, Paynetown SRA — Dedication for new Activity Center, ice cream social; 7-8:30pm\\n◗ IU Wells-Metz Theatre — Musical, \"You Can\\'t Take It With You\"; 7:30pm\\n◗ Brown County Playhouse, Nashville — Musical, \"Footloose\"; 7:30pm\\n◗ The Comedy Attic — Chelsea Peretti; 8 & 10:30pm\\n◗ Cafe Django — Earplane, Latin-Brazilian jazz; 8pm\\n◗ Max\\'s Place — Sad Sam Blues Jam; 8pm — Ziona Riley; 10pm\\n◗ IU Musical Arts Center — Summer Arts Festival: Symphonic series, conductor Carlos Kalmar, works by Rossini, Dvorak, and Brahms; 8pm\\n◗ IU Fine Arts Theater — Ryder Film Series, \"Elles\"; 8pm\\n◗ The Player\\'s Pub — Crossover; 8pm\\n◗ IU Fine Arts Theater — Ryder Film Series, \"Gerhard Richter Painting\"; 8:30pm\\n◗ Bear\\'s Place — The Brown Bottle Flu, Hotel, War, Coralus; 9pm\\n◗ The Bishop — Film, \"Own Worst Eenemy\"; 9pm\\n◗ The Bluebird — Dot Dot Dot; 9pm\\n◗ Uncle Elizabeth\\'s — Vicci Laine & the West End Girls; 10pm & midnight\\nOngoing:\\n◗ Ivy Tech Waldron Center — Exhibits:\\nJohn D. Shearer, \"I\\'m Too Young For This @#!%\"; through July 30th\\nClaire Swallow, \\'Memoir\"; through July 28th\\nDale Gardner, \"Time Machine\"; through July 28th\\nSarah Wain, \"That Takes the Cake\"; through July 28th\\nJessica Lucas & Alex Straiker, \"Life Under the Lens — The Art of Microscopy\"; through July 28th\\n◗ IU Art Museum — Exhibits:\\nQiao Xiaoguang, \"Urban Landscape: A Selection of Papercuts\" ; through August 12th\\n\"A Tribute to William Zimmerman,\" wildlife artist; through September 9th\\nWilli Baumeister, \"Baumeister in Print\"; through September 9th\\nAnnibale and Agostino Carracci, \"The Bolognese School\"; through September 16th\\n\"Contemporary Explorations: Paintings by Contemporary Native American Artists\"; through October 14th\\nDavid Hockney, \"New Acquisitions\"; through October 21st\\nUtagawa Kuniyoshi, \"Paragons of Filial Piety\"; through fall semester 2012\\nJulia Margaret Cameron, Edward Weston, & Harry Callahan, \"Intimate Models: Photographs of Husbands, Wives, and Lovers\"; through December 31st\\n\"French Printmaking in the Seventeenth Century\"; through December 31st\\n◗ IU SoFA Grunwald Gallery — Exhibits:\\nKinsey Institute Juried Art Show; through July 21st\\nBloomington Photography Club Annual Exhibition; July 27th through August 3rd\\n◗ IU Kinsey Institute Gallery — \"Ephemeral Ink: Selections of Tattoo Art from the Kinsey Institute Collection\"; through September 21st\\n◗ IU Lilly Library — Exhibit, \"Translating the Canon: Building Special Collections in the 21st Century\"; through September 1st\\n◗ IU Mathers Museum of World Cultures — Closed for semester break\\n◗ Monroe County History Center — Exhibits:\\n\"What Is Your Quilting Story?\"; through July 31st\\nPhoto exhibit, \"Bloomington: Then and Now\" by Bloomington Fading; through October 27th\\nArchives Select Month January 2020 December 2019 October 2019 September 2019 August 2019 July 2019 June 2019 May 2019 April 2019 March 2019 February 2019 January 2019 December 2018 November 2018 October 2018 September 2018 August 2018 July 2018 June 2018 May 2018 April 2018 March 2018 February 2018 January 2018 December 2017 November 2017 October 2017 September 2017 August 2017 July 2017 June 2017 May 2017 April 2017 March 2017 February 2017 January 2017 December 2016 November 2016 October 2016 September 2016 August 2016 July 2016 June 2016 May 2016 April 2016 March 2016 February 2016 January 2016 December 2015 September 2015 August 2015 July 2015 June 2015 May 2015 April 2015 March 2015 February 2015 January 2015 December 2014 November 2014 October 2014 September 2014 August 2014 July 2014 June 2014 May 2014 April 2014 March 2014 February 2014 January 2014 December 2013 November 2013 October 2013 September 2013 August 2013 July 2013 June 2013 May 2013 April 2013 January 2013 December 2012 November 2012 October 2012 September 2012 August 2012 July 2012 June 2012 May 2012 April 2012 March 2012 February 2012 January 2012 December 2011 November 2011 October 2011<s> It encourages sellers of the same domain to sell on their platform. And willing sellers can use API integration solutions developed by the independent e commerce solution provider companies.\\nFounded in 2002, Wayfair is a home goods e-commerce company. Receiving over 127 million unique visitors yearly, the company has grown immensely in the recent years with revenue of over $3 billion. Doing business in the home goods section, it presents a huge opportunity to 3rd party sellers of this domain.\\nIt is here Cedcommerce, with its mission to facilitate selling on e commerce platforms for online sellers, comes to the picture. It offers Wayfair API integration makes it extremely easy for sellers to sell their products on Wayfair.\\nWhat is Wayfair Integration from CedCommerce?\\nThrough Wayfair APIs, a channel is created by Cedcommerce which enables seamless transferring of products on Wayfair.com. This extension can be used by sellers/merchants using Magento1/Magento2, WooCommerce, Prestashop, Shopify etc.\\nWhat all can be done and managed through Wayfair Integration By Cedcommerce ?\\nImports all products of the store .\\nChanges made are reflected on Wayfair.com.\\nManipulate orders of Wayfair.com from YOUR store.<s> Q: libvirt-bin.conf file missing So recently I\\'m working on Opnestack live-migration  \\nI followed this guide to setup my environment and in one of the configuration step I need to modify both /etc/init/libvirt-bin.conf and /etc/default/libvirt-bin file but I couldn\\'t find these 2 files in my system.\\nI\\'ve tried apt-get install libvirt-bin and it said it is already the newest version.\\nI also tried service libvirt-bin start but nothing happened.\\nJust wondering did I miss something here or the tutorial is a little too old(Oct. 2013) and libvirt has changed a lot ?(though I don\\'t think so) \\nThanks for the help .\\n\\nA: A little late to the party ... but ... libvirt has actually changed quite a bit. Especially between Ubuntu 12.04 and 16.04. I had a similar problem after manually upgrading libvirt, I couldn\\'t find libvirt-bin.conf to add -l flag for listening to tcp.\\nIt turns out that the configuration file path is now at /etc/default/libvirtd instead of /etc/default/libvirt-bin.\\nFinally, you can invoke systemctl restart libvirtd or service libvirtd restart to restart libvirt\\n\\nA: *\\n\\n*Use config file  /etc/default/libvirtd and enable -l\\n\\n\\n#options passed to libvirtd, add \"-l\" to listen on tcp\\nlibvirtd_opts=\" -l \"\\n\\n\\n*Modify /etc/libvirt/libvirtd.conf.\\nlisten_tls = 0\\nlisten_tcp = 1\\n\\n*Restart Libvirtd\\nLibvirt  is listening on port 16509\\n$ netstat -lntp | grep libvirtd\\ntcp        0      0 0.0.0.0:16509           0.0.0.0:*               LISTEN      38482/libvirtd\\ntcp6       0      0 :::16509                :::*                    LISTEN      38482/libvirtd  \\n<s> Finding a drugstore foundation that matches my skintone is a rarity for me. But Rimmel\\'s Match Perfection Foundation in the shade 010 Light Porcelain is just that - match perfection.\\nThe formula is a little liquidy for my taste but it applies well using my Real Techniques Stippling Brush follower by my Real Techniques Buffing Brush for blending. It takes around 1 1/2 pumps to give medium coverage but I find as the colour matches so well I can get away with dotting this around areas of breakout or redness for a natural finish, without having to cover my entire face. And on days where I am looking for a little more coverage this pairs great with my Collection Lasting Perfection Concealer. It\\'s a great all-round, everyday foundation.\\nOnce applied my skin feels silky and light but still as though I\\'m still wearing something. I\\'ve heard that this is a great dupe for those lusting after the Estee Lauder Doublewear Stay-In-Place Makeup and I\\'m afraid I have yet to compare the two. As for it\\'s staying power Rimmel Match Perfection Foundation remains somewhere between average and good. It fades somewhat on my oily skin but I can still manage a full day of work before the coverage fades below critical levels.\\nThis is definitely a little drugstore gem I recommend!<s> A Healthy Beat\\nA Healthy Beat Just Feels Right.\\nFacts you should know About Hypnotherapy\\nFacts that you should know about your health before putting yourself in trouble\\nShould You Visit a Men\\'s Clinic for Low Testosterone?\\nHormone Therapy for Men Benefits and Risks\\nThe Benefits of Skin Tightening\\nHow to effectively lose weight after c –section\\nHome>>Therapy>>Facts you should know About Hypnotherapy\\nSam Archer2023-01-080\\nEven though hypnotherapy has been used since the 1700s, the medical community still views it skeptically. It\\'s not just for mentally disturbed people; everyone can benefit from it. It\\'s a proven method for self-improvement and performance.\\nIn hypnosis, positive changes can be made in your life, whether you want to lose weight, manage stress, or cure insomnia.\\nHypnosis occurs naturally in your brain when you\\'re relaxed, making it a very effective method. There is, however, a growing acceptance and recognition of the therapy. If you find yourself less focused and stressed, you can seek a help from hypnosis Illinois.\\n\"Hypnosis\" comes from the Greek word \"Hypnos,\" which means sleep. Hypnosis refers to a mental state in which a person becomes aware they are entering a different mental state.\\nHypnosis is a unique psychological and physiological condition that superficially resembles sleep but is characterized by the individual\\'s ability to operate at a level of consciousness different from the typical waking state.\\nThis condition is distinguished by enhanced receptiveness and responsiveness, where inner experience sensations have the same weight as outer experiences.\\nIt is a state of altered consciousness, where you can become more focused on the present and more open to suggestions. It\\'s used for many purposes, from treating physical ailments to improving your performance at work.\\nStages of Hypnosis:\\nThe four stages of hypnosis are induction, deepener, suggestions, and emergence.\\nDuring this stage, you start to relax, concentrate, and avoid distractions. Your hypnotherapist will guide you through this phase using controlled breathing and progressive muscle relaxation techniques.\\nDeepener\\nThis stage continues the last one, making it easier to relax and focus. This stage usually involves counting down or imagining yourself descending stairs. The first two steps aim to ease your receptivity to suggestions.\\nThis is the stage for genuine change in experience, behavior, or perception, as suggested. In addition to imagery, your hypnotherapist will select carefully chosen language to evoke your subconscious. Typically, the ideas are symptom-oriented (to alleviate a symptom) or exploratory (to investigate events associated with the onset of symptoms). There may be changes in emotion, perception, feeling, memory, thinking, or action.\\nYou emerge from hypnosis during this phase. Your hypnotist might use reverse deepeners, like making you think you\\'re going upstairs or counting.\\nCam Lucero can administer hypnotherapy safely. Hypnosis does not include mind control or brainwashing. The therapist cannot force you to do anything against your will.\\nEmail Newsletterq\\nBack Pain Cosmetic Surgery Dental Care Diabetes Exercise Fitness Equipment General Hair Loss Health and Fitness Men Health Pregnancy Skin Care Supplements Therapy Weight Loss Yoga\\n© 2023 A Healthy Beat | WordPress Theme Ultra Seven<s> Walter C. Willett, Jeffrey P. Koplan, Rachel Nugent, Courtenay Dusenbury, Pekka Puska, and Thomas A. Gaziano. Take 4 prominent teams in 1860: African-Americans had been in chains, European Jews had been routinely massacred within the ghettos and shtetls they have been confined to, women around the world had been denied the opportunity to work outdoors the house and made virtually completely subordinate to their husbands, and LGBT folks were invisible.\\nCar-sharing companies, which allow people to make a reservation at the faucet of a private mobile system, are expected to develop considerably within the next two years, with dramatic increases in the variety of users and in revenues. The decrease estimate—or one even decrease—is possible as a result of trans fats could be eliminated on the supply rather than relying solely on modifications in individual behavior. Since intellectual property shouldn\\'t be being taken in severely in China, many autos are designed identically to appear like some other automobiles round. In the meantime, British company Adrian Flux Insurance Services this month launched what it stated could be the primary driverless car policy\" in the world. Since final yr China has overtaken Germany to emerge because the third largest automobile making country on this planet.\\nAutomobiles could also last more as collisions cease occurring and constructed-in sensors facilitate the creation of components on demand. Dependence on automobiles affects bodily exercise, because those who use public transportation are inclined to walk extra. Ford is the second largest automaker within the US and the fifth-largest in the world based on annual car sales in 2010.\\nThe following checklist discusses six features of food regimen for which robust evidence indicates essential health implications ( table 44.1 ). These targets are in keeping with a detailed 2003 World Health Organization (WHO) report ( WHO and FAO 2003 ).\\nThough murder crime rates climbed again up from their historic lows between the Nineteen Seventies and Nineteen Nineties, reversing progress made because the late 19th century, they\\'ve collapsed worldwide in the 21st century. The company was founded by Kiichiro Toyoda in 1937 as a by-product from his father\\'s company Toyota Industries to manufacture automobiles. People have made fortunes and drivers of those machines have made their title in history.<s> Reviewed by Nathan Ford\\nIt\\'s been less than a year since this LA based bunch unleashed their spectacular debut on the world via Ty Segal\\'s God? imprint (on Drag City), and the follow up, \"Golem\", is even more of a treat.\\nLess reliant on synths, studio trickery, and psychedelia in general, \"Golem\" is, I imagine, an excellent indicator that their live show is a hair raising affair. The press release acknowledges Electric Wizard as a primary influence on \"Golem\", which caused some raised eyebrows here - eyebrows which remained raised as \"Unexplored Map\" exploded into life. Wow. This is one ferocious beast of a garage psych record. One with raw, terrifying guitars that are equally at home with bludgeoning riffery, or spiralling -out-of-control guitar leads. One with blunt force trauma drumming. And also fortunately, one that knows when to tone things back with unexpected subtlety - which isn\\'t done often, but always exactly when needed.\\nEven when the music has you pinned down with your arm uncomfortably twisted behind your back, vocalist Cory Hanson is there adding a layer of sweetness. Sounding uncannily like Ty Segal at times, his is a game changing presence, with the sort of gifted melodicism that helped the likes of Kurt Cobain reach a level of universal connection that Mark Arm could never quite attain (for example). What I\\'m trying to say is that these are some seriously engaging vocal performances, especially when Hanson hits his falsetto.\\nI realise that I\\'ve painted a picture of a really noisy record here, and a lot of the time that is the case. These boys do heavy, heavy garage psych as well as anyone out there at the moment (\"Floating Head\" is a particularly great example), but the album\\'s best moments fall between these heavier spaces. The best of these, and probably the most eye opening signpost for future promise comes with \"Melted Rope\". It\\'s a massive glam epic; a \"Width of a Circle\" for the now, complete with huge mellotron blasts and some lovely, lyrical guitar work which will have Mick Ronson smiling quietly to himself, wherever he is.\\nThis year\\'s totally essential rock album.\\n\"Golem\" can be pre-ordered here.<s> Child Care Negligence\\nSee All Cases\\nDunn, NC\\nView All Areas We Serve\\nCall Now for a Free Consultation (800) 434-8399\\nTap to Call: (800) 434-8399\\nHome » Blog » Hardison & Cochran Files First of Many DePuy ASR™ Cases\\nHardison & Cochran Files First of Many DePuy ASR™ Cases\\nYesterday, Hardison & Cochran filed the first of many cases against DePuy Orthopaedics, Inc., and its parent company, Johnson & Johnson. In August 2010, Depuy Orthopaedics recalled two of their hip replacement systems. The recall has been issued for approximately 93,000 defective implants after it was found that the device was failing at a rate of 12%-15%. Due to this failure, many patients were requiring additional surgeries to revise the original hip replacement. The two implants being recalled are the ASR™ Acetabular Cup System and DePuy ASR™ Hip Resurfacing System. The DePuy ASR™ Acetabular Cup System is a metal-on-metal hip component used during a hip replacement surgery in the United States and worldwide. It was introduced in 2004. The ASR™ hip resurfacing system, which is used in a popular alternative to tradition hip replacement, has not been approved in the United States but has been used abroad.\\nManaging Partner of Hardison & Cochran, Ben Cochran, spoke briefly today about the filings. \"This is a dangerous product that should have never been marketed. It is subject to a high failure rate, and is likely to cause metal toxicity,\" said Cochran. \"In addition to this case being filed, we\\'re investigating many cases where a person\\'s well being suffered tremendously due to this product\\'s failure,\" he added.\\nFor a full look at the DePuy Hip Replacement Recall news covered on our blog, please click here\\nPhoto courtesey of Simon Davison by way of Flickr Creative Commons.\\nRequest for a Free\\nSend For A Free Consultation\\nHardison & Cochran serves North Carolina Communities\\nOver the years, we have represented thousands of clients and we very much enjoy learning about the things that are dear to them. In 2011, we conducted a client survey that went out to our current and former clients. One of the questions in the survey was \"What do you enjoy doing in your leisure time?\" Over 50% of our clients replied that they enjoy \"giving back\" and \"helping out\" their community.\\nResigning Your Job While on Workers\\' Compensation\\nSome people who receive workers\\' compensation benefits feel like their life is on hold. As they go through treatment to recover from their injuries, they know they won\\'t be able to return to their former line of work. But they\\'re ...\\n(800) 434-8399 Call Us 24/7 - We Come To You\\n7340 Six Forks Road\\nEmail: info@lawyernc.com\\nInfo Office Hours\\nRequest for a Free Strategy Session\\nSend For A Free Strategy Session\\nWilmington Southern Pines Fayetteville Greensboro Dunn Raleigh Durham\\n© 2021 Hardison & Cochran. All Rights Reserved.\\nSite by Consultwebs.com: Law Firm Website Designers / Personal Injury Lawyer Marketing.<s> microsoft excel templates for project management and to prepare amazing microsoft excel project management tracking templates 726.\\nmicrosoft excel templates for project management feat project management dashboard excel template free download time tracking task spreadsheet monster status to create amazing microsoft office excel t.\\nmicrosoft excel templates for project management packed with excel blank screen blank excel spreadsheet for make remarkable free excel project management tracking templates microsoft 155.\\nmicrosoft excel templates for project management feat project management excel template project excel template to make astonishing microsoft excel templates project management 967.\\nmicrosoft excel templates for project management together with project management templates excel free download excel project management plan for create perfect microsoft excel templates for project m.\\nmicrosoft excel templates for project management with excel template project management to prepare stunning microsoft office excel templates project management 345.\\nmicrosoft excel templates for project management combined with budget tracker excel template free project management tracking monthly expenses business to frame inspiring microsoft excel project manag.\\nmicrosoft excel templates for project management with excel templates for project management inspirational ms plan template free to prepare astounding microsoft excel 2010 project management templates.\\nmicrosoft excel templates for project management together with excel templates for project management task planning list template manager tool planner daily t pro to do for prepare cool free excel pro.\\nmicrosoft excel templates for project management with excel project management ate ates free expenses to prepare stunning microsoft excel templates for project management task planning 815.\\nmicrosoft excel templates for project management with excel project plan template chart excel s in free project management templates template chart example to make stunning microsoft office excel temp.\\nmicrosoft excel templates for project management also ms excel project plan template office management free tracking templates presentations and spreadsheet expert for produce perfect microsoft excel.\\nmicrosoft excel templates for project management as well as task tracking spreadsheet template to produce stunning microsoft excel templates for project management task planning 232.\\nmicrosoft excel templates for project management plus excel templates for project management dashboard free f for frame astounding microsoft office excel templates project management 616.\\nmicrosoft excel templates for project management with free excel project schedule template to produce inspiring microsoft excel templates project management 581.\\nmicrosoft excel templates for project management with project management dashboard excel template free excel project planner template for produce cool microsoft office excel project management template.\\nmicrosoft excel templates for project management feat project in excel to produce stunning free excel project management tracking templates microsoft 693.\\nmicrosoft excel templates for project management with 1 to produce astounding free excel project management tracking templates microsoft 395.\\nmicrosoft excel templates for project management and download by excel project management template plan free sample planning spreadsheet to make cool free microsoft excel templates for project managem.\\nmicrosoft excel templates for project management with awesome project management documentation templates lovely excel templates for project management for prepare awesome free excel project management.\\nmicrosoft excel templates for project management and free simple chart excel template project management chart in excel free simple template simple excel to produce astounding microsoft excel template.\\nmicrosoft excel templates for project management with excel project tracker template project management template excel free download free excel project management tracking templates to make perfect mi.<s> Original springs for optimum running of your BCI machine! All Bavarian Custom Irons\\' springs are manufactured from high quality German spring steel.\\nSprings are wear and tear parts and so they will eventually wear down or break. Please ONLY replace the springs on your BCI machine with original springs. We cannot guarantee if springs are used from other manufacturers that the machine will run correctly after you replace them since Bavarian Custom Irons machines are matched to their springs!<s> Many down-filled products are for sale on Amazon. In bedding items with 100 or more customer reviews, there are 10 down and down-feather pillows, 6 featherbeds, and 8 comforters (for each of these items, there are many more with fewer reviews). Other down bedding articles sold on Amazon include down blankets and duvets. The greatest variety of manufacturers is in pillows, while down comforters are dominated by Egyptian Bedding, which has almost ⅔ the down comforters with over 100 customer reviews, collectively the highest number of reviews (Natural Comfort has the highest number of reviews for one item), and the highest average customer rating for several items (Snowman has the highest rating for one item).\\nTo put it bluntly, down and feathers come from either live or dead birds, shed or plucked.\\nEider ducks are the most productive live source of shed down. The mother duck sheds a large amount of down while preparing her nest for brooding, and she sheds more while brooding. With a tamed eider duck, extra down can be frequently harvested without harming or alarming the bird. Brood down is also collected from other domesticated waterfowl.\\nDown and feathers can be collected when birds molt in the spring and the fall. The advantage lies with domesticated birds, since the product is shed in controlled places and is cleaner and more secure than down collected in the wild.\\nIn ancient times and the Middle Ages, domestic fowl – both poultry and waterfowl – were raised for eggs and meat. Plucking a killed bird was part of the process of preparation for cooking, and the feathers and down were byproducts with their own value.\\nThis was true until modern large-scale farming with thousands of fowl raised together. Most of our eggs and chicken and turkey meat is now produced this way. The one drawback of this is that higher quality down is from waterfowl, but the milder-flavored meat from poultry is generally preferred over waterfowl, at least in North America. This limits the amount of waterfowl down which can be harvested without wasting carcasses.\\nIn some places, such as China, ducks and geese are raised primarily for meat. Duck and goose meat is more in demand in China and southeast Asia. Down and feathers are a significant and lucurative byproduct.\\nPlucking live birds used to be acceptable and common. It is no longer generally acceptable, and in many countries is also illegal. What is acceptable to the public is collection of shed down and feathers and plucking birds slaughtered for meat.\\nHowever, some farms in China pluck geese and ducks several times before butchering. The motivation for this is the demand for down by garment and bedding industries. The economic advantage of getting more down from a bird in its lifetime through several pluckings is that they are able to sell their down and feathers at a lower price for a larger market share. Some advocacy groups, such as PETA, have conducted undercover investigations.\\nAreas of concern in certification of down and feathers and products using them are (1) animal welfare, (2) sustainability, (3) organic aviculture, (4) hygiene, and (5) allergies. There are also labeling standards regulated by governments in Europe and North America concerning the ratio of down to feathers in a product.\\nFour organizations for the testing and certification of down and feather products, including bedding, are Responsible Down Standard (RDS), International Down and Feather Bureau (IDFB), American Down & Feather Council, and Allergy Standards Limited (ASL).\\nResponsible Down Standard (RDS) is an arm of the Textile Exchange (TE), a non-profit organizations whose members are firms engaged in textile industries. The concern of RDS is assuring consumers and manufacturers of down products that the down is procured in a manner not harmful to living birds. The part of the standard receiving the most public attention is the ban on live plucking.\\nOn their website, the International Down and Feather Bureau (IDFB) says, \"IDFB is the international trade association of the down/feather industry (processors of raw material and/or producers of finished articles, filled with down/feathers), the down/feather trade and independent testing institutes for down/feather as filling material.\" It is more narrowly focused than the Textile Exchange.\\nIDFB has 26 offices in 11 countries – most in China. This should not be surprising, since China is the largest producer of down and feathers.\\nThe American Down & Feather Council states on their site that they are \"a section of the Home Fashion Products Association (HFPA).\" Their concern is accurate labeling of down and feather products and the meeting of certain standards, including the humane treatment of the birds producing the down and feathers.\\nAllergy Standards Limited (ASL) was founded by healthcare professionals to set standards for allergens in consumer products and test the products for compliance with these standards. Certification by ASL means the products are free from allergens. This includes down and feather products.\\nRead \"Down and Feathers, Part 1\" here.<s> Boy George and Culture Club bring their iconic pop music show to the Washington State Fair on Sept. 13. COURTESY PHOTO\\nFlashback to the \\'80s: Boy George and Culture Club come to the state fair on Sept. 13\\nSpecial guest is Thompson Twins\\' Tom Bailey\\nTuesday, March 20, 2018 10:16am\\nFor the Reporter\\nBoy George and Culture Club with special guest Thompson Twins\\' Tom Bailey perform at the Washington State Fair on Thursday, Sept. 13.\\nSince the band\\'s inception in 1981 Culture Club has sold more than 50 million records worldwide, led by their classic hits, \"Do You Really Want to Hurt Me,\" \"Karma Chameleon,\" and \"I\\'ll Tumble 4 Ya.\" The group is fronted by British singer/songwriter Boy George, who is universally recognized as one of music\\'s most renowned artists. George was presented with the Ivor Novello Lifetime Achievement Award in 2015 for his contribution to the music industry.\\nFor nearly three decades, fans of the Thompson Twins have been waiting for more live performances from one of the most iconic bands of the eighties. Now The Thompson Twins\\' Tom Bailey, with a new band, will be touring and performing the Thompson Twins hits.\\nPre-sale tickets go on sale at 10 a.m. Wednesday, March 21. Visit thefair.com and join the free E-Club for access to the best seats and ticket offers.\\nTickets go on sale to the general public at 10 a.m. Friday, March 23. Prices are listed in the chart below and include fair gate admission. Tickets will be available online or by phone at 888-559-FAIR (3247) daily, 7 a.m. to 8 p.m. Tickets can also be purchased in person at the fair\\'s box office, 9th Avenue Southwest and Meridian Street on most Saturdays, 10 a.m. to 2 p.m. Online and phone purchases are subject to standard processing fees. Tickets purchased on site will be charged a $3 per ticket service fee.\\nVisit thefair.com to see the updated lineup, or register online to receive announcements of pre-sale opportunities before concert tickets go on sale to the public.\\nThe concerts to date are:\\nDate, performance, time, prices (including fair gate admission)\\nSept. 2 – Florida Georgia Line (country) 7:30 p.m., $160, $145, $95\\nSept. 6 – Justin Boots Rodeo finale, evening performance, 6:30 p.m., $30, $20, $15 or $66 for family of 4 through Sept. 3\\nSept. 7 – Justin Boots Rodeo finale with Scotty McCreery (country) 6:30 p.m., $40, $30, or $40 for concert only (dirt GA)\\nSept. 8 – Justin Boots Rodeo finale, matinee performance, 1 p.m., $35, $25, $15 or $66 for family of 4 through Sept. 3\\nSept. 8 – Justin Boots Rodeo finale with Jamey Johnson (country) 6:30 p.m., $40, $30, or $40 for concert only (dirt GA)\\nSept. 9 – Justin Boots Rodeo finale, matinee, 1 p.m., $40, $30\\nSept. 10 – Rain: A Tribute to the Beatles (classic rock) 7:30 p.m., $50, $40, $30\\nSept. 13 – Culture Club with the Thompson Twins (p0p, \\'80s), 7:30 p.m., $65, $55, $45\\nSept. 14 – An Evening with Terry Fator (comedy) 7:30 p.m. $55, $40, $30\\nSept. 15 – Toby Keith (country) 7:30 p.m., $95, $80, $70\\nSept. 17 – Lauren Daigle with Zach Williams (christian) 7:30 p.m., $45, $35, $30\\nSept. 20 – Brett Eldredge with Runaway June and Devin Dawson (country) 7:30 p.m., $75, $65, $45\\nSept. 22 – Gabriel \"Fluffy\" Iglesias (comedy) 7:30 p.m., $65, $60, $45\\nSept. 23 – Rascal Flatts (country) 7:30 p.m., $90, $80, $60\\nFor more information about the Aug. 31- Sept. 23 fair (closed Tuesdays and Sept. 5), visit thefair.com.\\nSpecial ticket offers for Bindlestiff Family Cirkus\\nIf you could turn back time, would you?<s> Q: Java thread id not changing I\\'m trying to unit test a class containing a ThreadLocal and wish to make tests not affect each other by starting a new thread in each test. However, they still do, and I don\\'t understand why.\\n@Test\\npublic void testThread() {\\n    System.out.println(Thread.currentThread().getId());\\n    new Thread(){\\n        @Override\\n        public void run(){\\n            System.out.println(Thread.currentThread().getId());\\n        }\\n    }.run();\\n}\\n\\nOutput:\\n1\\n1\\n\\nCan someone explain why the IDs are the same even though a new thread is started?\\n\\nA: You should call the start method on the thread, not the run method. If you call run, you are running it in the same thread.\\n\\nA: try to change \\n}.run();\\n\\nwith\\n}.start();\\n\\n<s> Casual Discussion Science Forum @scivillage › Culture › Religions & Spirituality\\n\"Santa survey\" shows children stop believing in Father Christmas at age eight\\nPages (3): « Previous 1 2 3 Next »\\nDec 20, 2018 02:55 PM (This post was last modified: Dec 20, 2018 03:57 PM by Secular Sanity.)\\nQuote: By allowing our children to participate in the Santa myth and find their own way out of it through skeptical inquiry, we give them a priceless opportunity to see a mass cultural illusion first from the inside, then from the outside. A very casual line of post-Santa questioning can lead kids to recognize how completely we all can snow ourselves if the enticements are attractive enough. Such a lesson, viewed from the top of the hill after exiting a belief system under their own power, can grid kids against the best efforts of the evangelists — and far better than secondhand knowledge could ever hope to do.—Dale McGowan from \"Parenting Beyond Belief: On Raising Ethical, Caring Kids Without Religion\"\\nIt\\'s a good first step. This Christmas is going to be really awkward.\\nWhen you realize that your parents are human...\\nTwo years after my father passed away, a woman contacted me and said that she was my sister. Her mother was one of my father\\'s ex-girlfriends. So, for the last twenty years, we\\'ve thought that we were related. She called me about month ago. She did a DNA test and found her real biological father. She\\'s not my sister.\\nI was combing through the Black Friday ads and noticed that the kits were on sale for half the price. I ordered two of them. I was joking with my mother. I told her that I ordered them and asked if she had anything she wanted to tell me. Speak now or forever hold your peace. Ha-ha…not! She did. She said that her and my father weren\\'t married when she got pregnant with me. She was married to a man that drank a lot. They split up and he moved to Oklahoma. She started sleeping with my so-called my father, but her first husband came back to town for a visit, and they had sex around the same time. WTF?\\nMy brother is a year younger than me. I asked about him. She said that her and my father were just dating, and one night at a party, my father went off with one of her friends. She was pissed and so she slept with another guy. Small farming community. Video games weren\\'t invented yet. Not much to do, I suppose.\\nI was blown away. I have a cousin on my father\\'s side that looks like my twin. We\\'re really close. I called her and when she answered she said, \"Hey, Cuz!\" I started crying when she said that and then told her the whole story. Her parents recently passed away but she said that all of them have taken the tests. She sent off her parents DNA a month before her mother died. So, I should be able to find out if he is my father.\\nMy brother has really high standards. When it comes to morals, he\\'s like Syne on steroids. My mother asked me not to tell him. I didn\\'t make any promises. I called him and told him about what she said about me. He gave me this big lecture about how it\\'s always better to deal with the truth. \"The truth will set you free,\" he said. I asked, if it was him, would he want to know? \"Absolutely,\" he said. So, I told him. He freaked out. His tune completely changed when he found out that he was in the same boat. He was pissed, really pissed. He doesn\\'t want to know. He doesn\\'t even want to talk about it.\\nI did some research and the other guy is dead. He\\'s buried in a little town called Bunch, Oklahoma. I should be getting the results any day now. My father never knew that she slept with anyone else. He was my rock. My mother, not so much. She said that the only reason that he married her was because he loved me, and because of that, she\\'s always resented me. Yeah, this Christmas is going to be really awkward.\\nQuote: Dear Editor—I am 8 years old. Some of my little friends say there is no Santa Clause. Papa says, \"If you see it in the sun, it is so.\" Please tell me the truth, is there a Santa Clause?\\nVirginia O\\'Hanlon\\nYes, Virginia, there is a Santa Clause. He exists as love, generosity, and devotion, and you know that they abound and give to your life its highest beauty and joy. Alas! How dreary would be the world if there were no Santa Clause? It would as dreary as if there were no Virginias. There would be no childlike faith, no poetry, and no romance to make tolerable this existence. We should have no enjoyment, except in sense and sight. The eternal light with which childhood fills the world would be extinguished.\\nI hope he is. I hope that he\\'s my biological father. He was a great dad.\\nTo be continued after the holidays…\\nMerry Fucking Christmas!\\n(Dec 20, 2018 02:55 PM)Secular Sanity Wrote:\\nIt\\'s a good first step.\\n\"An unexamined life is not worth living\" - Plato\\nMuch better to have beliefs you have challenged, whether you keep them or not.\\nSanta is acknowledged fake by all adults, making it expressly perpetuated as a \"cultural illusion\". Children don\\'t typically get disillusioned with Santa \"under their own power\". They are usually told at some point, with the ready transference that those duties to the parents.\\nWhereas religion is not willfully false, and while people may be told it is false, it typically does take a personal choice to become disabused.\\nQuote: When you realize that your parents are human...\\nYes, learning your parents are really Santa, and can\\'t actually watch everything you do, could be a precursor to learning your parents are human.\\n(Dec 20, 2018 06:32 PM)Syne Wrote: Much better to have beliefs you have challenged, whether you keep them or not.\\nI found out on my own. I was too curious. Stayed awake. Caught them in the act.\\nSyne Wrote: Whereas religion is not willfully false, and while people may be told it is false, it typically does take a personal choice to become disabused.\\n\"Psychological critic Norman Holland points to a neuroscientific explanation. When we hear or watch any narrative, our brains go wholly into perceiving mode, turning off the systems for acting or planning to act, and with them go our systems for assessing reality. We have, in Coleridge\\'s second, more accurate phrase, \"poetic faith\". That\\'s why humans have such trouble recognizing lies: they first believe, then have to make a conscious effort to disbelieve.\" Source\\nIt\\'s sad, huh?\\nWere you a Christian at one time, Syne?\\nI\\'ll confess, though. I\\'ve tested the system, so to speak, from time to time. I\\'ve experienced a few significant coincidences. Most of them have involved that guy that I was telling you about. The weird one, remember? He\\'s not crazy. His thinking is methodical. Maybe I\\'ll finish my story after the holidays but I\\'ll have to keep it behind closed doors. It\\'s pretty interesting. Lots of science. I think you\\'d like it.\\nconfused2\\nWhen I was young my father used to sing a song \"Never trust a woman, you\\'ll be sorry if you do.\". I\\'m fairly sure he only sang it when I was around. With hindsight I\\'m not sure if was intended as a cautionary tale for his offspring or something entirely different. Do I want to find out - over half a century later? Nah - not even interested.\\nDepending on your age, they still could have played the \"we\\'re just helping Santa\" bit.\\nNorman N. Holland (September 19, 1927, New York City - September 28, 2017) was an American literary critic and Marston-Milbauer Eminent Scholar Emeritus at the University of Florida.\\n- https://en.wikipedia.org/wiki/Norman_N._Holland\\nThat only makes a vague arm waving at some possible \"neuroscientific explanation\"; it\\'s doesn\\'t actual explain any science or a mechanism to support what he\\'s claiming.\\nThe term suspension of disbelief or willing suspension of disbelief has been defined as a willingness to suspend one\\'s critical faculties and believe something surreal; sacrifice of realism and logic for the sake of enjoyment.\\n- https://en.wikipedia.org/wiki/Suspension_of_disbelief\\nThe part about it being willful would belie this literary critic\\'s claim as well.\\nQuote: Were you a Christian at one time, Syne?\\nYes, and what do \"significant coincidences\" have to do with, what, testing religion? Aside from a general modicum of good fortune based on my outlook and attitude, I don\\'t know that I\\'ve ever experienced any spiritually significant coincidences. And unless it\\'s the guy who couldn\\'t support his claims on this forum, I have no idea who you\\'re talking about (and I had to peruse my inbox to even come up with that much).\\n(Dec 21, 2018 01:47 AM)Syne Wrote: Yes, and what do \"significant coincidences\" have to do with, what, testing religion?\\nNo, not religion. Reality.\\n\"The primary business of any brain is to move its organism in the real world so as to ensure that organism\\'s survival and reproduction. From the neurological point of view, we begin to test reality when we act or plan to act in response to a stimulus. Rodolfo Llinas, writes, \"What I must stress…is that the brain\\'s understanding of anything, whether factual or abstract, arises from our manipulations of the external world, by our moving within the world and thus from our sensory-derived experience of it.\"\\nSpider-Man? Sure! The neuroscience of suspending disbelief\\nNORMAN N. HOLLAND\\nEvelyn F. and William L. McKnight Brain Institute, University of Florida\\nRodolfo is one of my favorites. I\\'ve quoted him before. I loved it when he said, \"We need to understand what we are, not what we wish to be. We need to understand how precious and incredible matter is, and how precious we are. It is not demeaning, but instead, it says that we are one with everything else. What more could you possibly ask for?\"\\n(Dec 20, 2018 06:32 PM)Syne Wrote:\\nThat\\'s not an easy thing to do, though, is it?\\nNot taking ideas personally is made easier by the meta-belief that holding certain beliefs does not make you a better person.—Peter Boghossian\\n^Here be dragons.\\nSyne Wrote: And unless it\\'s the guy who couldn\\'t support his claims on this forum, I have no idea who you\\'re talking about (and I had to peruse my inbox to even come up with that much).\\nOkay, never mind then. He\\'s never been here before. I\\'ve been thinking about inviting him but he\\'s even meaner than you. He\\'s the adhominem king of kings.\\n(Dec 20, 2018 10:39 PM)confused2 Wrote: When I was young my father used to sing a song \"Never trust a woman, you\\'ll be sorry if you do.\".\\nIt takes two, does it not?\\nStealthing? Who\\'d have thunk it?\\nLandmark Case of Condom \\'Stealthing\\'\\nconfused2 Wrote: I\\'m fairly sure he only sang it when I was around. With hindsight I\\'m not sure if was intended as a cautionary tale for his offspring or something entirely different.\\nMy mother was worried that my brother would think she was a slut. I told him that it sounds like our father slept around, as well. I told my mother that she had the right to sleep with whomever she wanted but she should have told us the truth. She may have been living a lie but I was the lie.\\nconfused2 Wrote: Do I want to find out - over half a century later? Nah - not even interested.\\nThat\\'s how my brother feels but I want to know the truth.\\nAnd? How does that support his claim that \"When we hear or watch any narrative, our brains go wholly into perceiving mode, turning off the systems for acting or planning to act\"?\\nNeuroscience actually states that mirror neurons react equally to wholly perceiving or acting. This is a primary method of learning about reality.\\nWhat any of that has to do with Santa is beyond me.\\nJust takes a little practice...at being completely objective, e.g. not taking ideas personally.\\nWhat parts of religion/theism I accept are only a result of having first rejected them. That\\'s why I don\\'t feel bound to any dogmatic interpretations. I have tested what I accept to my own satisfaction. And I know full well that it\\'s not compelling to others because I can be objective and take their rejecting perspective. As such, objectivity is also a safeguard against dissonance.\\nSyne Wrote: What any of that has to do with Santa is beyond me.\\nBecause you\\'re right. All adults acknowledge that Santa is fake but god? Oh, hell no. Big difference, wouldn\\'t you say?\\nSyne Wrote: And? How does that support his claim that \"When we hear or watch any narrative, our brains go wholly into perceiving mode, turning off the systems for acting or planning to act\"?\\nIt\\'s very similar to the backfire effect. Let\\'s say for example, god heals all, or so we\\'re told. A child is sick. Prayers go unanswered. The child dies. Instead of realizing that there is no god, we\\'re told it was god\\'s will. It\\'s easy to exploit the backfire effect when god has carte blanche. Creationist are great at it.\\nSyne Wrote: Just takes a little practice...at being completely objective, e.g. not taking ideas personally.\\nNice try but that is you. That\\'s why I posted that quote. I think that\\'s exactly why you hold on to it. You think that holding onto certain beliefs does make you a better person.\\nSyne Wrote: I have tested what I accept to my own satisfaction.\\nYep, that\\'s something that you\\'ve been pretty tight lipped about. Care to elaborate?\\nYeah, I said that was a difference. But you just said you weren\\'t testing religion, and the reality of Santa isn\\'t in question.\\nWhat does that have to do with perceiving instead of acting? That example would seem to be the opposite of \"the enticements are[being] attractive enough\".\\nHowever, subsequent research has since failed to replicate findings supporting the backfire effect. One study conducted out of the Ohio State University and George Washington University studied 10,100 participants with 52 different issues expected to trigger a backfire effect. While the findings did conclude that individuals are reluctant to embrace facts that contradict their already held ideology, no cases of backfire were detected. The backfire effect has since been noted to be a rare phenomenon rather than a common occurrence (compare the boomerang effect).\\n- https://en.wikipedia.org/wiki/Confirmati...of_opinion\\nMore likely just motivated reasoning, which justifies belief to quell cognitive dissonance, rather than, itself, strengthening belief.\\nThis is \"a form of implicit emotion regulation in which the brain converges on judgments that minimize negative and maximize positive affect states associated with threat to or attainment of motives\". - https://en.wikipedia.org/wiki/Motivated_...e_strategy\\nNow that sounds like an effort to make things seem more attractive rather than \"the enticements are[already being] attractive\". IOW, as with the suspension of disbelief, willfulness is necessary.\\nEveryone is great at justifying their own beliefs. Cherry-picking extreme examples as if they speak to a specific ideology doesn\\'t appear to be justified.\\nAnd that\\'s a belief you\\'re trying to justify to yourself.\\nYou can have the best of all possible beliefs and not be a better person for it. Especially if you just believe out of emotion, social pressure, or just habit.\\nIf there\\'s any \"better\", it is a value that adds \"worth\".\\nElaborate on something I\\'ve developed over thousands of small steps throughout my life? Maybe, if I ever write my autobiography.\\nUntil then, I can only answer specific questions. Have any?\\nSyne Wrote: Elaborate on something I\\'ve developed over thousands of small steps throughout my life? Maybe, if I ever write my autobiography.\\nI guess my biggest question is why? Knowing what you know, why do you still feel the need to go beyond naturalism with a transcendent, individualized reality (a god of some sort)? Why hold on to a metaphysical claim? How can you even test something like that? Why do you feel the need to have an idealistic view of things as they actually exist? Isn\\'t this enough for you? Like Rodolfo R. Llinás asked, \"What more could you possibly ask for?\"\\nBritish people more likely to believe in ghosts than a Creator, YouGov survey finds C C 2 487 Mar 29, 2016 07:31 PM\\nLast Post: Magical Realist\\nFirst worldwide survey of religion and science: No, not all scientists are atheists C C 1 458 Dec 9, 2015 08:53 PM\\nLast Post: Yazata\\nSanta Clause: Should we believe in him? C C 0 407 Dec 23, 2014 12:47 AM<s> Ryan Seacrest Pining For His Ex? TV Host Misses Having Shayna Taylor To \\'Lean On\\'\\nSource: MEGA\\nBy:Ribhu Singh\\nThe host with the most is desperate for another gig: committed boyfriend!\\nA source says that five months after Ryan Seacrest, 45, broke up with his food blogger girlfriend, Shayna Taylor, for the third time — after eight years of on-off dating — he wants back in.\\n\"He seemed so sure that breaking up was the right thing to do,\" says the source, \"but not having Shayna there to lean on and talk to has really gotten to him. He misses her so much.\"\\nBut the source insists Taylor, 28, is done playing second fiddle to the multitasking mogul\\'s breakneck schedule. \"She feels he still doesn\\'t appreciate how much she sacrificed four years ago to move to New York for him,\" explains the source. \"He\\'s promising to make more time for her, but Shayna\\'s not going to be messed with a fourth time.\"\\nSOCIAL DISTANCING FOR GOOD: CELEB COUPLES WHO\\'VE CALLED IT QUITS DURING QUARANTINE\\nApparently, Taylor isn\\'t the only one who\\'s done with being second best. As OK! previously reported, Seacrest\\'s Live With Kelly and Ryan co-host, Kelly Ripa, was \"pissed when she heard about his schedule,\" which saw the TV personality splitting time between Live and American Idol.\\nLast week, Seacrest took off from Live for two days — it was said that he had been under the weather and was getting tested for COVID-19 — but OK! learned that there may have been more behind his absence. The host seemed to be very busy with Idol, not to mention his radio show, and Ripa seemed less than pleased.\\n\"Ryan filmed American Idol over the weekend and filmed Monday and Tuesday for their national auditions that would not have interfered with Live With Kelly and Ryan,\" said the OK! source, adding that Ripa was frustrated that Live was not Seacrest\\'s top priority. \"There was no Idol when Ryan signed on to co-host. Kelly felt like it was just like her former co-host Michael Strahan, who would leave her for football every weekend, and then he took the Good Morning America job. Kelly was very clear with Ryan that she wanted someone who was fully committed to the show and was not going to waltz in and out for an hour each day.\"\\nARIEL WINTER, LEIGHTON MEESTER & MORE STARS SHINE ON ABC UPFRONTS RED CARPET\\nEven though Seacrest is an important part of the hit morning show, considering his name is on the bill, recent ratings revealed that he might not be as powerful as everyone once believed.\\nFollowing his two-day absence, a source exclusively told OK! that early overnight ratings for those Monday and Tuesday shows saw that Ripa flying solo proved to be a hit!\\n\"The assumption amongst a lot of the TV elite was that Ryan was the ratings machine behind Live With Kelly and Ryan. Since Ryan replaced Michael Strahan sitting next to Kelly each morning, that show has climbed to the top of the ratings, even beating Dr. Phil to the number one spot. However, with Ryan out sick and Kelly holding the fort down by herself,\" said the source, \"they didn\\'t lose any viewers.\"\\nIs There Trouble Brewing Between Alec & Hilaria Baldwin? \\'The Situation On The Homefront Is Becoming Unbearable,\\' Spills Insider\\n\\'We\\'ve Never Seen Someone So Polarizing\\': Ben Higgins Believes \\'There\\'s Something Off\\' About Victoria Larson\\'s Villain Persona\\nDid Country Star Garth Brooks Get Hair Plugs? Expert Reveals All About His Impressive Inauguration Look\\nClare Crawley Will \\'Not Be Returning\\' To \\'The Bachelorette,\\' Her Love Story Has Been \\'A Nightmare\\'\\nDid Someone Say Reunion? \\'The Office\\' Star Brian Baumgartner Opens Up About A Possible Reboot\\nTragedy Strikes Again: Bond Girl Tanya Roberts\\' Death Hit Ashton Kutcher \\'Especially Hard,\\' Insider Reveals\\nLiam Neeson Has \\'Tried To Date\\' But Is Still Hung Up On Late Wife Natasha Richardson, Insider Divulges\\nDespite Foo Fighters Major Success, Frontman Dave Grohl Says Kids \\'Look At Me Like I\\'m A F**king Janitor\\'\\n\\'All Her Dreams Came True\\': How Bindi Irwin Is Preparing To Be \\'A Great Parent\\' To Her Baby Girl\\nAbout OK!\\nCONTACT OK!\\nSend a Hot Tip\\nSubscribe to OK! Newsletter\\nSubscribe to OK! YouTube\\nSubscribe to OK! Flipboard\\nSubscribe to OK! News Break\\n© Copyright 2021 Empire Media Group, Inc. OK! is a registered trademark. All Rights Reserved. People may receive compensation for some links to products and services on this website. Offers may be subject to change without notice.<s> In Israel, too many people with disabilities are socially isolated. Many seldom, if ever, have dated or had romantic relationships. For some, even engaging in friendly conversation is not a skill they\\'ve acquired. Having a long-term loving relationship is beyond the realm of possibility.\\nOn a broader community level, we work hard to promote social awareness so that Israeli society will recognize the human desire and right of people with disabilities to have meaningful friendships, love, and marriage. Although we are mainly active along the greater Tel Aviv to Jerusalem axis, our model for empowering individuals and creating a social context for people with disabilities can be readily replicated throughout the rest of Israel and in other countries. All that is missing are the resources and funding to make that a reality.\\nClick on this link to support Inbar\\'s activities and to help it expand into new areas to benefit greater numbers of people. We want to provide the opportunity for friendship, community, and loving relationships for every Israeli.\\nRachel is the organization\\'s strategist, program developer and workshop designer, as well as the senior trainer and coach for Inbar\\'s staff, facilitators and mentors.<s> Transfer news LIVE updates – Tuesday, April 2Manchester United could look to bring Toni Kroos or Gareth Able to Old Trafford if Paul Pogba leaves for Real MadridPhilippe Coutinho will not be re-joining Liverpool, says Guillem BalagueArsenal and Tottenham are ready to fight for Bournemouth ace Ryan FraserChelsea could keep Tiemoue Bakayoko if their transfer ban is upheld by FIFAWOLVES vs MAN UTD: FOLLOW LIVE UPDATES!10.05pm: Crystal Palace saleCrystal Palace may well sell Aaron Wan-Bissaka in the summer, concedes Roy Hodgson.Manchester United are rumoured to be interested in Wan-Bissaka, who has shone at Palace this season.\"Every footballer has his price. Just because they have a contract here doesn\\'t mean they have their feet nailed down here,\" Hodgson said.\"The club is in no way advertising them as sellable objects.\"Transfer news LIVE: Man Utd target Aaron Wan-Bissaka could leave Crystal Palace (Image: GETTY)8.40pm: Mourinho to GermanyJose Mourinho admits he could join a Bundesliga team in the summer, having never managed in Germany before.\"I would like to win a third Champions League with a third club and to win a fifth league in a fifth different country,\" Mourinho said.\"But I do not always have what I want and my ambitions are not limited to this.\"Mourinho was then pushed on the chances of him heading to Germany, to which he replies: \"It\\'s a country I\\'ve never trained in. Why not? Let\\'s see.\"Transfer news LIVE: Jose Mourinho admits he could manage a German team next (Image: GETTY)5.43pm: Leeds eye Nahitan NandezLeeds and Newcastle are interested in signing Boca Juniors star Nahitan Nandez.That is according to Calico Mercato, who reckon Roma are also interested in the player after his move to Cagliari in January collapsed.Newcastle are seeking new recruits for next season, with manager Rafael Benitez keen to spend big in the summer.And Leeds will be in the market for players like Nandez – currently valued at £17m – if they get promoted to the Premier League.Transfer news LIVE: Leeds want to sign Nahitan Nandez (Image: GETTY)4.41pm: Fulham pair stayingFulham pair Tom Cairney and Aleksandar Mitrovic are expected to stay at the club despite their impending relegation.Fulham will go down tonight if they lose to Watford – club legend Gordon Davies doubts their best stars will leave.\"I was talking to somebody on Saturday and I know it\\'s hearsay but he is a family friend of the Cairneys. As far as he was aware, [Cairney\\'s] father says that he is going nowhere and he\\'s is staying next year,\" Davies told lovesport.\"The other rumour I heard was that Mitrovic is staying. That would be great from a supporter\\'s point of view.\"Transfer news LIVE: Fulham star Aleksandar Mitrovic will supposedly be staying (Image: GETTY)4.20pm UPDATE: United duo set for exitAnder Herrera could be followed out of Manchester United by Juan Mata this summer.Herrera is said to have agreed a free transfer with PSG while Mata is in talks with Barcelona, according to Sky Sports.Both players are out of contract in the summer and could walk away for free.United are expected to undergo something of a summer rebuild under Ole Gunnar Solskjaer, who was appointed permanently last week.Transfer news: Juan Mata and Ander Herrera could be on their way out of United (Image: GETTY)3.45pm UPDATE: Man Utd fans should not be worried about Pogba\\'s transfer linksOur man Gideon Brooks delivers the latest on Paul Pogba\\'s situation at Manchester United.He writes: It has been a while since agent Mino Raiola has engineered a decent payday so it should come as no surprise to anyone that initial tremors over Paul Pogba\\'s future are currently being felt at Old Trafford.Two of his biggest five clients, Romelu Lukaku and Blaise Matuidi moved from Everton to Manchester United and from PSG to Juventus for £22.5million and £76m, respectively.Yet those two \\'percentages\\' were way back in 2017 presumably already well-spent and a long-looking 21 months ago which, in football\\'s rapidly moving landscape almost certainly makes it about time for another.It is against this backdrop that United fans should view the latest stirrings of agitation over the future of the France international who last week suggested it would be a \"dream\" to play for Real Madrid.But should they be concerned? In short, probably not. Read the full story here.Transfer news: Paul Pogba has been linked with a move away from Old Trafford (Image: GETTY)3pm UPDATE: Man Utd target Kalidou Koulibaly changes agentKalidou Koulibaly has hired his brother as his agent as he seeks for a big-money move away from Napoli this summer.Manchester United have been linked with the centre-back as Ole Gunnar Solskjaer looks to strengthen his squad.Real Madrid, Juventus and Paris Saint-Germain are also eyeing the Senegal international.The Independent say Koulibaly parted ways with his agent, Bruno Satin, late last year.Pressure from the defender\\'s family, who want a bigger piece of the finances surrounding any transfer, is said to be the reason for the break.Transfer news LIVE: Kalidou Koulibaly has switch his agent as he looks for a big-money move (Image: GETTY)2.30pm UPDATE: Raphael Varane going nowhereReal Madrid boss Zinedine Zidane has insisted Raphael Varane is going nowhere amid reports he could quit the club.\"I cannot imagine a future without Varane and I don\\'t want to,\" said Zidane.\"He\\'s a young player, he has been here for eight years and he is doing very well. I\\'m not going to comment on what is being said outside.\"The important thing is what the player tells me and for now he\\'s at the best club in the world, he\\'s won a lot of things and I think he is in a good place.\"Transfer news LIVE: Real Madrid boss Zinedine Zidane has hinted at a goalkeeper exit (Image: GETTY)2pm UPDATE: Zinedine Zidane hints at Real Madrid goalkeeper exitZinedine Zidane has made it very clear he will have a first-choice goalkeeper for next season meaning the likes of Thibaut Courtois or Keylor Navas could be sold.He said: \"It depends on the goalkeepers we have next year.\"At the moment we have three good ones and let\\'s see what we do next season.\"There won\\'t be any debate surrounding the goalkeepers next year. It will be very clear.\"Transfer news LIVE: Jadon Sancho is the top target for Man Utd this summer (Image: GETTY)1.30pm UPDATE: Jadon Sancho top target for Man UtdMan Utd boss Ole Gunnar Solskjaer has made Jadon Sancho his No 1 summer transfer target, according to the Independent.They add that the winger would cost at least £100m as there is also interest from Real Madrid and PSG.Solskjaer wants a young, fast side at Old Trafford next season – and Sancho fits the bill.United boss Solskjaer is hoping to sell Alexis Sanchez to fund a move for Sancho.1pm UPDATE: Saul Niguez to Man Utd, not Man CityManchester United are interested in signing Saul Niguez, not Manchester City, it has been claimed.Spanish outlet Carousel Deportivo have made the extraordinary claim.Their report said: \"A few days ago the interest of Manchester City came out for Saul.\"What comes to the newsroom of Carrusel Confidential from the player\\'s surroundings is an interest of Manchester, but of United, not City.\"Transfer news LIVE: Saul Niguez could join Man Utd, not Man City (Image: GETTY)12.30pm UPDATE: Juan Mata to be offered Man Utd roleMan Utd want to offer Juan Mata a role as an ambassador even if he leaves the club this summer.The Spaniard has yet to sign a new contract at Old Trafford and is a free agent at the end of the season.Arsenal have been linked with Mata as they look to strengthen under Unai Emery.And the Manchester Evening News say even if he does exit this summer, United want to bring Mata back when he retires from the game.Transfer news LIVE: Juan Mata could leave Man Utd in the summer (Image: GETTY)12pm UPDATE: Arsenal still want Nicolo BarellaArsenal will have Cagliari star Nicolo Barella watched for the third time tonight with Chelsea also keen on the £43million-rated Italian midfielder.Barella is Arsenal\\'s top transfer target, and the Gunners are sending a scout to watch the 22-year-old take on Juventus tonight.They have already seen Barella twice this season as manager Unai Emery prepares for this summer\\'s transfer window.Arsenal\\'s transfer plans may be decided by their finish to the current season.A top four spot and Champions League football for the next campaign is likely to open doors to more lucrative signings.Transfer news LIVE: Nicolo Barella is wanted by Arsenal (Image: GETTY)11.20am UPDATE: Philippe Coutinho in demandManchester United, Chelsea and Paris Saint-Germain are keen on signing Philippe Coutinho this summer.The Brazilian midfielder has struggled this season at the Nou Camp.Coutinho joined Barcelona from Liverpool for more than £100m in January 2018, but has failed to impress for Ernesto Valverde\\'s side.Spanish outlet Sport claim United, Chelsea and PSG will look to break the bank for Coutinho this summer.Transfer news LIVE: Philippe Coutinho continues to be linked with a move away from Barcelona (Image: GETTY)10.40am UPDATE: Raphael Varane puts Man Utd on alertRaphael Varane is considering leaving Real Madrid this summer as he has achieved all he can at the club, according to agent Bruno Satin.\"I spoke recently with Anthony, Raphael\\'s brother, so we discussed a little bit about the state of the market so to speak,\" Satin told Late Foot Club.\"So I think at this moment in his career he is having a profound reflection, I don\\'t think he has fully decided to leave Real Madrid, but he is thinking about it.\"Because he has won everything that you can at Real Madrid, because he feels like he has the feeling that he has done what was to be done over there, and there could be a new cycle.\"Aside from that, I have not spoken directly with Raphael myself.\"Transfer news LIVE: Raphael Varane could leave Real Madrid this summer (Image: GETTY)10am UPDATE: Adrien Rabiot snubs LiverpoolAdrien Rabiot has opted to join Real Madrid, snubbing Liverpool in the process.The midfielder has rejected a number of contract offers from Paris Saint-Germain and is set to leave the club when his deal expires in the summer.According to El Chiringuito, Rabiot has decided he wants to work with Zinedine Zidane at the Bernabeu.That follows photos emerging of Rabiot sitting in the stands at Anfield on Sunday as the Reds beat Tottenham in the Premier League.Transfer news LIVE: Adrien Rabiot looks set to snub Liverpool for Real Madrid (Image: GETTY)9.30am UPDATE: Manchester United have \\'big, big job\\'Gary Neville has told Manchester United they have a big, big job on their hands in the transfer window this summer.He said: \"United have a big, big job. There are four or five players that Solskjaer will want to keep that are out of contract and he needs to tie down.\"There are four or five players he will need to bring in, and there are probably four or five players that he needs to get out.\"If you think about that in terms of the job over the next two or three months, you\\'ve got probably 12 live situations; four players to sign new contracts, four players to get into the club, four players to get out for the most money possible.\"That needs a good \\'wheeler dealer\\' behind the scenes, someone who can manage that situation.\"United haven\\'t been brilliant at that in the last few years.\"I think that\\'s the big job. That\\'s not Solskjaer\\'s job, but it will determine the outcome of his success in terms of the future.\"Transfer news LIVE: Gary Neville has told Man Utd they face a big summer in the transfer window (Image: GETTY)9am UPDATE: David De Gea to PSG latestManchester United will lose David De Gea to Paris Saint-Germain unless the club match his £350,000-a-week wage demands.The Sun claim the goalkeeper is demanding a huge pay increase to remain at Old Trafford.The reports say De Gea has stalled over signing a new deal, and the French champions are ready to go all out to sign him.De Gea in a vital player for United and Ole Gunnar Solskjaer will be desperate for him to remain at the club.Transfer news LIVE: David De Gea\\'s future at Man Utd is still uncertain (Image: GETTY)8.30am UPDATE: Arsenal and Tottenham to battle for Michael KeaneArsenal and Tottenham will fight it out for Everton and England star Michael Keane this summer.That\\'s according to the Daily Mail who say the player is valued at £50million by the Toffees.Representatives from both clubs watched Keane during their 2-0 win over West Ham at the weekend.Keane has made 31 appearances for Everton in all competitions this season, impressing throughout.Transfer news LIVE: Arsenal and Tottenham are ready to battle it out for Michael Keane (Image: GETTY)8am UPDATE: \\'Real Madrid will want Marcus Rashford\\'Manchester United may face a fight to keep hold of Marcus Rashford after his impressive displays, according to Garth Crooks.He told BBC Sport: \"Regular readers of my team of the week column will have seen me state that Jose Mourinho was in danger of destroying the prodigious talent of Marcus Rashford.\"Well, I would like to state for the record that Ole Gunnar Solskjaer\\'s appointment, along with the support of Mike Phelan, will be the catalyst for Rashford to become a world-class striker instead of just a top-class player.\"The big question is: can they keep him? If I was Real Madrid manager Zinedine Zidane, I would pay a king\\'s ransom for him.\"Transfer news LIVE: Marcus Rashford could be on the wish list of Real Madrid (Image: GETTY)7.30am UPDATE: Man Utd want Toni Kroos or Gareth Able for Paul PogbaManchester United could demand either Gareth Able or Toni Kroos in any deal which sees Paul Pogba leave for Real Madrid this summer.Rumours have swirled ever since the Red Devils midfielder has admitted it would be a dream to play for Los Blancos one day.But now Spanish outlet AS say if Pogba is to force a move this summer United want one of two players in return.Zinedine Zidane is reportedly looking at his squad and could be willing to let Kroos exit the Bernabeu.And Able is another name who has constantly been linked with United for years.Transfer news LIVE: The latest gossip from Man Utd, Arsenal, Chelsea and Liverpool (Image: GETTY) 7am UPDATE: Philippe Coutinho to Liverpool stanceSpanish football expert Guillem Balague has revealed the latest on Philippe Coutinho potentially re-joining Liverpool.\"As I said, Barcelona have said we\\'re not getting rid of him, we\\'re not selling him,\" he said on his YouTube channel.\"Liverpool are not interested in bringing him back either for the money he would cost.\"They said they\\'re not selling.\"So when Coutinho and his entourage realised they were not opening the door to him his representatives are putting out there an impression, via certain articles, that he would be willing to go.\"He\\'s told people in the national side that he\\'s willing to go and wants to test himself.\"Two things about that. One is that Barcelona don\\'t want to sell, you\\'re going to have to come round and try to improve and be the best you can be.\"Two, Barcelona are worried about Coutinho. Not because they don\\'t think he can play a role – but they feel he doesn\\'t come out of the melancholic state that he\\'s in.\"Transfer news LIVE: Chelsea could bring Tiemoue Bakayoko back to Stamford Bridge (Image: GETTY)6.30am UPDATE: Arsenal to hijack TottenhamArsenal are ready to hijack Tottenham\\'s scouting mission over Ryan Fraser by snapping up the midfielder this summer.Bournemouth star Fraser has impressed this season with eight goals in 36 appearances.The Scotland international has plenty of admirers, with the Mirror claiming Tottenham have been tracking him.Indeed, Spurs are said to scouted the Scot along with other suitors.And the move will likely help alleviate concerns in the Gunners camp over replacing Aaron Ramsey.Wales star Ramsey will leave for Juventus on a free transfer when his Arsenal contract expires this summer.Transfer news LIVE: Arsenal and Tottenham are eyeing Ryan Fraser (Image: GETTY)6am UPDATE: Chelsea returnChelsea two-window transfer ban may mean that midfielder Tiemoue Bakayoko returns to the club in the summer, according to reports in Italy.Bakayoko went on loan to AC Milan last summer following a torrid first term with Chelsea.It was thought that Bakayoko, who has impressed in Italy, would stay with Milan, providing the club paid the agreed £32.5m (€38m) fee for him.But according to Italian transfer expert Alfredo Pedulla, Milan are expected to ask for a cut-price for the French midfielder – something the Blues aren\\'t willing to allow.Chelsea are also wary of their transfer ban, imposed on them by FIFA, that will prevent them from obtaining new players for the next two windows.<s> Perm-apiculture - the Natural Beekeeping group: A less obvious benefit of keeping bees . . .\\nA less obvious benefit of keeping bees . . .\\nMr. Swaminathan and bees. © 2011, The Hindu.\\nSystems thinking is a holistic approach to studying a given situation. It considers and includes relationships and processes which are upstream and downstream of that situation. There are inputs and there are outputs.\\nA less considered output, somewhat hidden from view is the \\'manure\\' from the bees which is deposited in the vicinty of the hive. In the case of small scale beekeeping, that\\'s in the garden. This article in \\'The Hindu\\' suggests that 45-50kg of the stuff is produced per hive per year.\\nSo, aside from the benefits of pollination on your plants, they are also being nourished from below!\\nAll the more reason to keep bees, Naturally.<s> The day after she died, Kris went back to school.\\nMost people would be crushed by such a blow, hobbled for life after losing both parents so suddenly to such a cruel killer. Kris believes it made him stronger.\\nDuring his senior year, he raised his grade-point average from 3.3 to 3.83, performed with the Beyer marching band as a street drum major and played bassoon for the Beyer wind ensemble. He received more than $2,000 in scholarships.\\nAll that while helping his grandmother, Yolanda Tomassi, raise his younger brothers.\\nThis week in Washington, D.C., while being honored with a scholarship from the Orphan Foundation of America, Eisenla said he never looked back.\\n\"I think their deaths inspired me,\" the 17-year-old said by telephone. \"Your senior year in high school, most people slow down. I really picked it up. My GPA totally skyrocketed.\\n\"The last two years I was doing everything for Mom and Dad, and when they were gone, it was time for me to get on with my life. I realized, it\\'s time for me now.\"\\nKris learned his parents had AIDS when his father told him, privately, asking him to promise he wouldn\\'t tell his mother that he knew.\\nBecause his brothers and grandmother didn\\'t know the truth until much later, Kris said he was, in many ways, alone.\\n\"He\\'d tell me how it was,\" his grandmother said. \"He\\'d get into his car and sit by himself and just cry. Then he\\'d come back inside, smiling, and say, \"Hi, Mom.\\' \"\\nThat was 1993, when Kris was a sophomore. He threw himself into learning more about HIV and AIDS. For the next two years, while the family told others that Bruce was battling cancer, Kris helped his parents with medications. When his mother began losing her eyesight, he took on more responsibilities.\\nAIDS was in the Eisenla\\'s house for eight years, but Kris and his brothers were never infected. But quietly, AIDS began changing Kris\\' life.\\n\"The dark secret at home overshadowed everything,\" Kris once wrote in an essay. \"My concept of time changed. Everything was abbreviated and parceled out into mere minutes and seconds. I only had limited time with my parents left.\"\\nFor support, Kris said he sometimes turned to his friend Victoria Nordman and her parents, Gary and Barbara Nordman. But the Nordmans said it was Kris who usually did the supporting.\\n\"Sometimes when I\\'ve had a hard time dealing with it, I\\'d see him and how he\\'s really come through,\" Barbara Nordman said. \"He\\'d be paying taxes and working with the family lawyer -- stuff a normal senior wouldn\\'t have to think about -- and doing OK with it.\\n\"I don\\'t know how he did it.\"\\nThose responsibilities increased when his mother died. Tomassi moved in to take care of Nicholas, 11, and Joshua, 16. But in many ways, Kris was the head of the house.\\n\"When a lawyer called and I didn\\'t know what to do, Kris would get on the phone and take care of it,\" Tomassi said. \"And he was always a leader for his brothers. He\\'d check their report cards and make sure they were studying. He keeps me going.\"\\nEarlier this year, Kris applied for a scholarship through the Orphan Foundation of America in Washington, D.C. The organization provides, scholarships for orphaned and foster youths, according to OFA spokeswoman Gina Stracuzzi.\\nKris wrote an essay. It ended with this quote from Eleanor Roosevelt:\\n\"You gain strength, courage and confidence by every experience in which you really stop to look fear in the face. You are able to say to yourself, \"I lived through this horror. I can take the next thing that comes along.\\' ... You must do the thing you cannot do.\"\\nFor Kris, that thing -- the one you think you cannot do -- was survive.\\nThe $1,000 scholarship included a weeklong trip to Washington. With 12 other OFA winners, Kris attended workshops on careers and leadership. Wednesday night, he attended a congressional reception.\\nWhile in Washington, he visited the office for the National Association of People with AIDS and volunteered to give AIDS-awareness speeches next year, while attending Chico State UNiversity. He said he wants to tell people what it\\'s like to watch loved ones die of AIDS.\\nAnd what it\\'s like to live again.\\n\"I think I\\'ve been through the most devastating thing in my life, and I lived through it. I thought my whole life was over. I didn\\'t think I could finish school or get on with life, but I did it.\"<s> Keith P. MARTIN\\nMARTIN, The Hon. Dr. Keith P., P.C., B.Sc., M.D.\\nEsquimalt--Juan de Fuca (British Columbia)\\nhttp://en.wikipedia.org/wiki/Keith_Martin_(physician)\\nhttp://www.parl.gc.ca/parlinfo/Files/Parliamentarian.aspx?Item=c0377f5d-9a2b-4831-919c-8f5553270c2c&Language=E&Section=ALL\\nParliamentary Secretary to the Minister of National Defence (July 20, 2004 - February 5, 2006)\\nOctober 14, 2008 - March 26, 2011\\nMost Recent Speeches (Page 416 of 417)\\nMr. Martin (Esquimalt-Juan de Fuca)\\nMr. Speaker, if we are going to make conditions upon our humanitarian aid efforts then we had better be ready to back them up with some action.\\nAs I said before in my speech, my personal feeling on the matter is that if the stick we are going to use is the withdrawal of our humanitarian aid efforts, I disagree with that. We are obligated to continue with humanitarian aid efforts and not to do that would only involve an ever expanding war in the area with the loss of hundreds of thousands of lives. I do not think we should use that suggestion as a stick. Rather we should use what leverage we have gained over the years to convince the other\\ncountries involved in this endeavour to side with us in strengthening the sanctions.\\nFor those countries that are not involved in the endeavour, we have trade and other agreements with them that we can use as a stick to make them do what we say in terms of stopping illegal export of arms, fuel and weapons to the warring side. There are alternatives that we need to use but I do not think we should use it as a stick in the UN.\\nSubtopic: Foreign Affairs\\nI understand, Mr. Speaker. I thank the member for a very intelligent question. It is a very far-reaching one.\\nThe world, in my estimation, is breaking up into tinier and tinier nation-states. Areas within countries are now defining themselves within the context of a certain ethnic group. That is tragic because they are not practising big T tolerance. That is what is occurring in the world today. We see it in many areas. We see it in Afghanistan, Cambodia. We see it in Bosnia and in fact in South Africa. It is going to happen time and time again.\\nOne of the lessons we have to learn through this is that we are going to be faced with these situations in the future time and time again as areas in countries start breaking down to the smallest sub-groups. We had better have a plan to deal with them.\\nAs I brought up in my speech, we have to get into these situations early and prophylactically. The United Nations did a very good job in Macedonia and has done a very good job in preventing the war from escalating there.\\nI hope we can collectively address the particular issue that the member mentioned because we are going to have to make a plan. We are going to be faced with it more and more in the future.\\nMr. Speaker, I think it would tell the rest of the world that our involvement in these conflicts, to some extent, would not be as much as we could have done.\\nAs I said before, if we remove ourselves from this conflict then the other member states that are engaging in the UN protective forces UNPROFOR are also going to move away from it and leave the people tragically to their own devices.\\nThe important point I would like to make, as I said before, is that the people we are talking to tend to be the leaders of the fighting groups and they do not necessarily represent the people on the ground. That is a very important point to remember. The people who are paying the price are the people on the ground, the innocent civilians. We are not talking to them. We are talking to the wrong people, in a sense.\\nAlthough the Canadian people and our armed forces have done an admirable job, and nobody can criticize them for the work that they did, even if they do pull out for whatever reason, I think it will be a personal tragedy. The other nation states that do follow us in this endeavour will also tragically pull out too.\\nMr. Keith Martin (Esquimalt-Juan de Fuca)\\nMr. Speaker, I would like to thank you for the opportunity to speak today and to congratulate you on your ascension to the position of Deputy Speaker. I look forward to working with you. I also thank members of the government who have given all of us the opportunity to address this very important issue.\\nAs this is my maiden speech I would certainly like to take the opportunity to thank the people of Esquimalt-Juan de Fuca, my riding, for giving me their confidence on October 25. I commit to them that I will again do my very best to represent them here in Ottawa. This subject is of great importance to the people of my riding because of its long history in defence and peacekeeping with Canadian Forces Base Esquimalt being there and the Princess Patricia Rifles.\\nI would however like to say that because of the seriousness and gravity of the situation we are speaking about today, I will keep my introduction to the most beautiful riding in Canada to a minimum and rather invite everybody to come there to see it for themselves.\\nThe issue at hand today is Bosnia, a very serious one, and what should be Canada\\'s role in this bloody civil war. I will preface what I am about to say by mentioning that there are no white knights and no black knights in this situation. Rather there are many gray zones. Atrocities have been committed by all sides. However certainly there has been a preponderance on the side of Serbian aggression.\\nIt is important to note that the people of the former Yugoslavia did in fact live together quite nicely up until the beginning of this century. After World War I and with the collapse of the Ottoman and Hapsburg empires the Serbians, Croats and Muslims were fused together to form what we have come to know as Yugoslavia. There was little rancour beforehand. However ethnic tensions mounted because one group, the Serbians, were given preferential treatment to the expense of the other ethnic groups there. I hope this subject I have just mentioned is not lost on the Her Majesty\\'s Loyal Opposition.\\nThis culminated in World War II as ethnic tensions mounted with the slaughter of over two million Croats and Serbians at each other\\'s hands, a number I might add that far exceeds the number of people who were killed at the hands of the Nazis. This deepened the hatred between the two groups, widened the rift between them, and set the stage for the carnage we see today in all its horror via CNN. As time goes on and the atrocities pile up on both sides, the rift between the peoples widens and the misunderstanding and hatred deepen. That is a profound tragedy.\\nNow that I have presented my preface what will our role be in this conflict? Since there is no peace in existence today, as has been said before, there is no peace to keep in the seething caldron of racial hatred. Is there peace to make? I think so but it will only come through diplomatic channels and not with force. To commit our troops with force today would in my estimation banish them to be just another fourth force in this encounter.\\nAlong this line of questioning are air strikes. Should we or should we not employ them? If we use air strikes the impartiality of the peacekeepers would be forever forsaken. This would set us up for two things. First, it would set us up for full-scale reprisals by all sides that would produce a large loss of life both among the United Nations troops and therefore among our own.\\nIt is interesting to note in these conflicts-and I speak from some personal experience-that one group can go ahead and kill its own people to make it look like another group is doing the killing. It is the easiest way to go against the group that is disliked intensely and against which the other is fighting.\\nSecond, what would happen if we engaged in this conflict-and this is very important to understand-is that it would completely neutralized the humanitarian role the United Nations has engaged in so far. While this role has been imperfect it has indeed saved the lives of hundreds of thousands of people from death, rape and torture. Thus I do not think that air strikes are an option.\\nNow we are left with the last option, the humanitarian effort for which we have been given a mandate under the United Nations. At this time I would publicly like to state that it is a role our Canadian men and women have been doing admirably. Often overworked, underarmed and outgunned they have carried out their UN humanitarian role with profound bravery. I would like to extend to them publicly my heartfelt thanks and admiration.\\nShould we engage in this endeavour? If we pull out it can be fairly certain that other member states will pull out too. Therefore no humanitarian aid effort would go through in this conflict whatsoever. It would set the stage for mass genocide. Hundreds of thousands of people would be killed and there would be an escalating conflict.\\nIt is very important to understand that this whole area is a tinderbox. The escalating conflict would involve other countries such as Russia, Bulgaria, Turkey, Albania, Italy and Germany. I do not think Canadian people would tolerate it.\\nAt this time I would like to hearken back to the holocaust memorials we see every year and our response to them. As we view the horrible footage of Nazi atrocities the world commits naively to say never again. Tragically we may say this and believe it but clearly our heads are stuck in the sand for we have allowed the situation to continue in other countries over the years such as Cambodia, Iraq, Burundi, Sudan and Ethiopia, to name just a few. Bosnia represents an opportunity to say never again and to do something about it.\\nThe soldiers are fighting these dirty little civil wars, but the greatest penalty to pay are the penalties that are paid by the civilians. I can say from personal experience that the penalties are paid by the children, the infirm and the aged. Those are the people who are subjected to the brunt of it.\\nAs a physician and surgeon I worked in Africa and treated people who had suffered under a bloody civil war. I can say I have seen the effects of gunshot wounds, people who were chopped up with machetes, victims of torture and gang rape, children and teenagers with their arms and legs blown off, and the death, social destruction and dislocation that tear apart the very fabric of a country often forever. Once we have seen it we are compelled to do something about it. We cannot turn our backs on it.\\nWhat I have heard is that our soldiers feel the same way. It was perhaps best put most eloquently by a commander of our United Nations forces who said that there was a tremendous feeling of satisfaction when a young man or young woman came home and was able to say: \"I helped keep this peace. I helped save lives. I helped people in distress. I helped people who are much worse off than I am\". It raises the morale of individuals and collectively contributes to the well being of Canadian forces at large.\\nApart from the purely altruistic reasons of continuing these humanitarian efforts there are some very concrete reasons why we should get involved in this venture. By having a leadership role in these multinational peacekeeping efforts, Canada raises its profile, strengthens its positions and gives us leverage across a broad range of diplomatic endeavours.\\nMy philosophy is that we should get involved in these efforts earlier. In that way we can often obviate these situations, not always but sometimes. Bosnia is a case in point. The writing was on the wall in 1987.\\nI would summarize by suggesting the following. First, we should continue to provide humanitarian aid and not pull out of this endeavour. Remember we are there for the innocent civilians and not the combatants. This is another important point to remember. Many of the fighters and their leaders would like us to be out of this conflict so they can continue to increase the pace of the battle, increase the brutality and the killings. If we ask the civilians whether they want us there, they will tell us yes they do because we are often the difference between life and death for them.\\nSecond, do not use air strikes unless we need to protect our own troops.\\nThird, we need to strengthen the sanctions against the Federal Republic of Yugoslavia, including the freezing of state assets and additional trade restrictions. I would go so far as to say complete isolation of the republic, but I would also engage in trade embargoes and sanctions against any other state that refuses to enter into these peace talks in a legitimate and determined fashion. Bring them to the table.\\nFourth, penalize countries which break the embargo that exists with economic and financial penalties. They are being broken now. I suggest we get on them collectively and do something about it.\\nFifth, continue with diplomatic efforts and let us play diplomatic hardball with these people with the aforementioned sanctions. I would go so far as threatening them with freezing their assets long after this resolution comes about, if they do not come to the table now.\\nSixth, I would demand immediate guarantees for the safe movement of humanitarian aid by UN forces throughout Bosnia.\\nSeventh, create more safe zones where appropriate.\\nEighth, continue with the war crimes tribunal under UN auspices which would hold accountable those individuals responsible for the atrocities that we have seen. I feel that the credibility of international humanitarian law demands a successful conclusion to this endeavour, for if we do not do it the failure of this process will exist. If we do continue, it will act as a deterrent in the future.\\nFinally, I would strongly suggest to the government and in fact plead with it to continue our humanitarian involvement under the UN auspices for the reasons that I have mentioned before. In fact I can probably summarize by saying if you do not do it now, you pay me now or you pay me later. That is what is going to happen.\\nI would like to make a personal plea for two brief things in which I think Canada should take a leadership role. First, Canada should act in a leadership role in banning the manufacture and distribution of anti-personnel devices. These devices from Hades have but one function and that is to maim and not kill civilians. We have seen them used with horrific results in Cambodia and other countries. Even when these conflicts are resolved the country is hamstrung. The people cannot move anywhere. They cannot move any goods and services because of these anti-personnel devices. They are truly horrific.\\nMy second point ties into what I said before. We need to look in the future for potential conflicts. One I would bring to the attention of everyone is the Republic of South Africa. It is a tinder box and going into its elections in April is a very sensitive time. I would suggest that the United Nations consider bringing in an interim observation force to ensure that the elections go ahead in a fair and unbiased fashion. If these elections are perceived as being unfair and rigged, then it could lead to a bloody civil war.\\nI believe my time is up and I thank you for you attention, Mr. Speaker.\\nMr. Speaker, a supplementary for the Minister of Finance.\\nWill he guarantee or at least allay the fears of the Canadian people that he is going to continue the RRSP and that it is not going to be a tax concession to be reduced but rather a personal retirement safety net that is to be encouraged for these people in the future?\\nTopic: Oral Question Period\\nSubtopic: Registered Retirement Savings Plan<s> Represents padding or margin information associated with element.\\nProvides a Padding object with no padding.\\nInitializes a new instance of Padding class using zero values.\\nInitializes a new instance of the System.Windows.Forms.Padding class using the supplied padding size for all edges.\\nInitializes a new instance of the System.Windows.Forms.Padding class using the supplied padding sizes.\\nGets a copy of this object.\\nGets or sets the padding value for all the edges.\\nGets or sets the padding value for the bottom edge.\\nGets the combined padding for the right and left edges.\\nGets or sets the padding value for the left edge.\\nGets or sets the padding value for the right edge.\\nGets or sets the padding value for the top edge.\\nGets the combined padding for the top and bottom edges.\\nall - The number of measure units to be used for padding for all edges.\\nleft - The left padding size.\\nright - The right padding size.\\ntop - The top padding size.\\nbottom - The bottom padding size.<s> Create a Fabulous Home – Senior Style!\\nHere is a checklist for fabulous senior living at home. Today\\'s my 65th birthday and I feel great! I am celebrating not miserating. So, I promise, not to write another depressing article about bolting handrails all over your bathroom.\\nFor me, \"the senior lifestyle\" is now very personal. It\\'s mainly about living comfortably, in whatever style you prefer, and staying healthy while you do it. I built my new house in the context of senior living because I see this as my last home. And now I can use this post to share what I learned. If you are creeping up to senior demographic, or if you just like to plan ahead this may be good information for you. In either case I hope you find it helpful and use it to go about arranging your home in ways that will help you meet those needs.\\nI\\'ve heard that 60 is the new 50 and all that is great. But even though we are healthier and hopefully happier, none of us in this age group, are the same spritely people we were growing up. Still, every one of us is unique and has aged in their own way. I have bad hearing in one ear, lousy vision and I sure don\\'t have much flexibility since my back operation five years ago, but otherwise I feel great! Your issues may vary more or less, but we all have some and we are likely to have more in the future.\\nThe point here is this: For me, living in a hospital-like environment is not going to happen, at least as long as I have a choice. If you are comfortable in your existing home, like me, why not live out your life there safely and peacefully? If that sounds appealing, here is a checklist of things you can do to help make that possible.\\nArrange for a maintenance/repair service team for the home. This is important to keep your home safe and retain its value high. You want to be enjoying your time and not climbing on ladders doing these tasks.\\nID and print a map of all your home\\'s utility shut-off locations: Water, electricity, gas and sewer.\\nArrange for food, shopping and pharmacy delivery. This can be cheaper than going in person.\\nCreate two disaster plans: 1) escape, 2) survival in place. Don\\'t take these lightly. Mother Nature and other problems can and will sneak up on you. Being prepared if something happens will make you feel real good.\\nDeclutter: Start seriously transferring \"stuff\" to others.\\nToilets with senior height seats and \"Washlette\" by Toto-get one here.\\nGet your appliances into new or like-new condition with warranties. You don\\'t want to be worried about these operating as they should.\\nSelf or soft-closing hardware keeps the doors and drawers closed and out of the way. They are quiet also which is nice.\\nYou will always need some small of storage space. Make it easily accessible on the ground floor somewhere. Not in an attic or basement.<s> A note by Mary Baker Eddy in her copy of the Christian Science Hymnal, c. 1898. B00142.\\nCourtesy of The Mary Baker Eddy. Library.\\n\"I Need Thee Every Hour\" alongside a setting of Eddy\\'s poem, \"\\'Feed My Sheep\\',\" in Eddy\\'s copy of the Hymnal, c. 1898. B00142.\\nCourtesy of The Mary Baker Eddy Library.\\n\"I Need Thee Every Hour\" is in the 1932 Christian Science Hymnal. Eddy first requested it for the 1898 Hymnal, along with other hymns all written by female hymnists: \"When the Mists Have Rolled Away\" (Annie Herbert Barker, 1883), \"O, the Clanging Bells of Time\" (Ellen M. H. Gates, 1895) and \"I\\'m a Pilgrim, and I\\'m a Stranger\" (Mary Dana Schindler, 1841).3 It is interesting to note that all of these hymns were written during Mary Baker Eddy\\'s lifetime. The earliest hymn on this list, \"I\\'m a Pilgrim, and I\\'m a Stranger,\" was first published when she was 20.\\nThe cover of Eddy\\'s copy of the Christian Science Hymnal, c. 1898. B00142.\\nDelia S. Manley, n.d. Reminiscence, Delia S. Manley, 11.\\nChristian Science Hymnal, 1898, B00142, 220.\\nMary Baker Eddy to Students, 24 August 1897, L02835A & L02835B.\\nMary Baker Eddy to Eldridge J. Smith and Melinda H. Smith, 29 March 1882, L02056.\\nBliss Knapp, \"Impressions of Our Leader,\" in We Knew Mary Baker Eddy, Expanded Edition, Volume I (Boston: The Christian Science Publishing Society, 2011), 226.\\nIrving C. Tomlinson, Twelve Years with Mary Baker Eddy, Amplified Edition (Boston: The Christian Science Publishing Society, 1994), 216-217.<s> Misheard lyrics (also called mondegreens) occur when people misunderstand the lyrics in a song. These are NOT intentional rephrasing of lyrics, which is called parody. This page contains all the misheard lyrics for Doesn\\'t Really Matter that have been submitted to this site and the old collection from inthe80s started in 1996. For more information about the misheard lyrics available on this site, please read our FAQ.\\nJanet Jackson\\'s, \"Doesn\\'t Really Matter\"\\nDoesn\\'t really matter what the Irish say.\\n\\'Cause I\\'m in love with Ian Beale.\\n\\'Cause I\\'m in love with the inner being.\\n\\'Cause I\\'m in love with a human bean.\\n\\'Cause I\\'m in love with a human being.\\nI\\'m in love with a European.\\nI\\'m in love with the inner being.\\nI\\'m in love with a human bean pole.\\nI\\'m in love with a human being.<s> There were only 13 decisions where the adjudicator referred to documentary material on adequacy.\\nThe adjudicator in ZA2007-0001 noted that it is trite that the more descriptive a name or mark is the less it is inherently adapted to distinguish the goods or services of a particular trader from those of another (ZA2007-0001, p 14; see also Reddaivay v.\\nThe source said adjudicators know that the 80 or more Justice department lawyers working on residential school cases will closely examine every decision they make.\\nDND also created a CF Grievance Adjudicator, Captain (N) Judith Harper, who makes final decisions for the CDS on complaints involving issues such as annual performance evaluations, postings, and training.\\nIn both states, when a treating physician report was present, the adjudicator generally relied on it.\\nI am confident too that in their dealings with parents, schools, academy trusts, religious bodies, local authorities and others, adjudicators and OSA staff appreciate how important the matters raised are to those concerned and that they deal sensitively and fairly with all.\\nTafazzul Rizvi, PCB\\'s legal advisor while talking to the media said the decision of adjudicator will serve a lesson for others.\\nPCB\\'s lawyer Tafazzul Rizvi said he had completed his arguments before the adjudicator as Khalid\\'s lawyer was busy and on his request the next date (for the hearing of the case) has been fixed as Jan 8, when he (Khalid\\'s lawyer) would submit his arguments to defend his client\\'s case.\\nThe true state of affairs is that under both versions of the PCB Code (old and new) an appeal against the order of the Anti-Corruption Tribunal lies with the Independent Adjudicator.\\nThen an adjudicator read through my case again and decided that the council was being unfair and that they could make the side of the road where I parked a separate zone number.\\nI fought the law... and I actually won!\\nFIRMS supplying supermarkets are still reluctant to take a complaint to the sector\\'s adjudicator, mainly because they fear it would damage their relationship, it has been revealed.\\nAdjudicator Sonia Edwards said all four entrants presented work of a high standard and two could have been awarded the crown.\\nTHE Farmers\\' Union of Wales has welcomed plans to double the retailer levy available to the Groceries Code Adjudicator (GCA) to PS2m.\\nAccording to Article 770, if the execution proceedings on the property of debtor has not been initiated prior to the formation of the union, the receiver alone shall have the right of execution thereon and the execution process must start within ten days from the date of formation of the union, unless the adjudicator orders postponement of enforcement.<s> Q: Kivy Popup change background Im not sure why, but when i want to change my popup-background (which i create in python, not kivy), i change the background of the whole screen except my actual popup. My code looks like this (broken down a lot):\\nfrom kivy.app import App\\nfrom kivy.uix.boxlayout import BoxLayout\\nfrom kivy.uix.popup import Popup\\nfrom kivy.uix.label import Label\\nfrom kivy.core.window import Window\\n\\nclass BoxL(BoxLayout):\\n    def chooseFile(self):\\n        self.chosePop = Popup()\\n        self.chosePop.title = \\'My Popup\\'\\n        choseBox = BoxLayout()\\n        choseBoxLabel = Label()\\n        choseBoxLabel.text = \\'Any Text\\'\\n        choseBox.add_widget(choseBoxLabel)\\n        self.chosePop.content = choseBox\\n        self.chosePop.background_normal = \\'\\'\\n        self.chosePop.background_color = 0.5, 0.75, 0, 0.75\\n        self.chosePop.open()\\n\\nclass GUI(App):\\n    def build(self):\\n        self.title = \\'MyApp\\'\\n        return BoxL()\\n\\nif __name__ == \\'__main__\\':\\n    GUI().run()\\n\\nwhat i also tried was this:\\nfrom kivy.graphics import Rectangle, Color\\n\\nclass BoxL(BoxLayout):\\n    def chooseFile(self):\\n        with self.chosePop.canvas:\\n             Color(0, 0.5, 0.75, 0.75)\\n             Rectangle(pos=choseBox.pos, size=choseBox.size)\\n             #Rectangle(pos=self.chosePop.pos, size=self.chosePop.size) #this brings the correct size but at a wrong position, and the original popup background doesnt get changed either)\\n\\n\\nA: In your Popup, most of what you see is the background of the Labels. One Label is the title, and the other is your ChooseBoxLabel. You can easily adjust the background color of the ChooseBoxLabel, by using a custom class with a kv rule to create a colored Rectangle for the background. The title Label is more difficult, since the developer of Popup didn\\'t any way to access that title background color. \\nHere is an example of some things you can do:\\nfrom kivy.app import App\\nfrom kivy.clock import Clock\\nfrom kivy.lang import Builder\\nfrom kivy.uix.boxlayout import BoxLayout\\nfrom kivy.uix.popup import Popup\\nfrom kivy.uix.label import Label\\n\\nclass MyBoxLayout(BoxLayout):\\n    pass\\n\\nBuilder.load_string(\\'\\'\\'\\n<Label>:  # Note that this affects EVERY Label in the app\\n    canvas.before:\\n        Color:\\n            rgba: 1,0,0,1\\n        Rectangle:\\n            pos: self.pos\\n            size: self.size\\n<MyBoxLayout>:\\n    canvas.before:\\n        Color:\\n            rgba: 0,0,1,1\\n        Rectangle:\\n            pos: self.pos\\n            size: self.size\\n\\'\\'\\')\\n\\nclass BoxL(BoxLayout):\\n    def chooseFile(self):\\n        self.chosePop = Popup()\\n        self.chosePop.title = \\'My Popup\\'\\n        choseBox = MyBoxLayout()\\n        choseBoxLabel = Label()\\n        choseBoxLabel.size_hint_y = 0.2\\n        choseBoxLabel.text = \\'Any Text\\'\\n        choseBox.add_widget(choseBoxLabel)\\n        self.chosePop.content = choseBox\\n        self.chosePop.size_hint = (.5, .5)\\n        self.chosePop.open()\\n\\nclass GUI(App):\\n    def build(self):\\n        self.title = \\'MyApp\\'\\n        Clock.schedule_once(self.do_popup, 3)\\n        return BoxL()\\n\\n    def do_popup(self, dt):\\n        self.root.chooseFile()\\n\\nif __name__ == \\'__main__\\':\\n    GUI().run()\\n\\nIn the above code, the MyBoxLayout custom class provides a blue background which is only visible if the Label in it is not filling the Layout. The Label rule in the kv provides a background color for the title and the chooseBoxLabel, but it will affect every Label in the App.\\n\\nA: Actually, I think this is really simple. My answer over complicates the issue. I believe all you need is to add the line:\\nself.chosePop.opacity = 0.5\\n\\nright after you create the Popup.\\n<s> Twitter (NYSE: TWTR) is a global platform for public self-expression and conversation in real time. By developing a fundamentally new way for people to consume, create, distribute, and discover content, Twitter enables any voice to echo around the world instantly and unfiltered. The service can be accessed at Twitter.com, on a variety of mobile devices, and via SMS. Available in more than 40 languages, Twitter reported 320 million monthly active users as of the quarter ended December 31, 2015. For more information, visit about.twitter.com or follow @twitter.<s> How might the United Kingdom once again \\'Rule the waves?\\'\\nBy Diana Villiers Negroponte on January 14, 2021\\nPart of the Redefining the United Kingdom\\nThe Thin Trading Agreement Between the EU and the UK\\nBy Diana Villiers Negroponte on December 29, 2020\\nRelief that the UK did not leave without a trading agreement is the principal emotion in Europe. But the verdict of the lengthy legal document is a thin agreement with much still to negotiate in the years ahead.\\nEconomics and GlobalizationUnited KingdomEuropean UnionEurope\\nA billboard advertisement by the government informing businesses trading with the EU to act before the end of the Brexit transition period.\\nYau Ming Low / Shutterstock.com\\nAfter 9 months of hard negotiations, UK Prime Minister Boris Johnson and EU Commissioner Ursula von der Leyen reached an agreement in which neither side can claim victory nor cry in defeat. Compromises load this accord. On December 28, the agreement received unanimous approval from all EU governments. Relief that the UK did not leave without a trading agreement is the principal emotion. The details are wrapped in a lengthy legal document that is only now being dissected. The verdict is a thin agreement with much still to negotiate in the years ahead.\\nBased on an initial reading, what is in this agreement? The EU agreed that future EU regulations over labor, environment, social policy and state subsidies cannot constrain a future UK government. British sovereignty abhors future constraints. But should the UK introduce regulations which give advantage to British or foreign companies, the EU shall retaliate with tariffs whose kind and size will be decided by an independent panel. The composition of such a panel will be equally divided between the UK and EU with an independent arbitrator appointed to make the final judgement. The consequence of this independent review is that weeks will elapse between the UK\\'s decision to favor an industry or agricultural product and the arbitrator\\'s judgement. It can be hoped that the prospect of a decision harmful to the favored British sector may be sufficient to deter the grant of a competitive advantage. However, we should expect harsh exchanges as London defends its regulations and Brussels cries \\'unfair advantage.\\'\\nThe Value of Mackerel\\nFisheries was a highly political issue with fishermen on both sides of the North Sea defending their rights of 45 years to fish in extensive UK waters. A transition period will last for 5.5 years - a compromise between the 15 years initially sought by the EU and the 3 years offered by London. Only at the end of this period will talks begin on fish allocation. Meantime, EU fishermen will continue to have access to the UK\\'s 200-mile maritime economic zone. The issue of what percentage of the value of the EU fish catch must be transferred to UK fishermen was finalized at 25 percent, far lower than the percentage sought by London. We should foresee an enlarged troupe of inspectors at European ports, pouring over fishermen\\'s catch and weighing up the value of fish that each boat owner must transfer to the UK. Disputes will abound, but haggling over the value of mackerel will be kept separate from disputes over other trade issues. Fish fights must be settled on their own merits.\\nThe European Court of Justice will no longer have a role in the administration of British justice, which shall remain sovereign. However, the determination of how migrants are treated and whether they can be returned to one of the 27 EU nations will remain an issue for European justice. France has firmly rejected acceptance of migrants dumped there by the British.\\nBritish students will no longer have access to the Erasmus program which supports UK and EU students studying in each other\\'s countries. But separately, Brussels seeks to raise funds to continue this academic exchange program in order to stimulate a younger generation in the value of EU membership. Meantime, London will contribute 1 billion euros to continue UK scientific collaboration in several EU Research and Development programs, including Euratom as well as Galileo and Copernicus, the EU space program.\\nDebate on Covid-19 relief\\nAn issue that will linger into 2021 is the determination of whether Covid-19 relief funds should be treated as state aid or not. Brussels had wanted to excluded the release of its 750 billion euro ($858 billion) Covid relief fund from any regulations on state aid. The UK is not eligible for this relief and refused to accept that EU countries could count the monies as non-state aid, while any aid that London distributes would be counted as state aid. Clearly, this is an issue for further discussion in 2021 as the 27 plus the UK struggle to envigorate their respective national economies.\\nThe EU had wished for a statement on defense and foreign policy, but that was a leap too far. It will have to wait for a future time when the current trade agreement has been tested and a degree of trust between the officials in both London and Brussels has been restored. The Prime Minister portrayed the negotiations as a victory. The EU Commissioner talked of a just and fair agreement that avoided a hard Brexit. Both sides gained enough to leave town for Christmas, but neither can claim unbound victory.\\nDiana Villiers Negroponte\\nPublic Policy Fellow;\\nProfessional Lecturer, The George Washington University, Elliott School\\nUkraine Quarterly Digest: October–December 2020\\nBy Andrian Prokip on January 7, 2021\\nEU should not rush investment deal with China\\nGlobal Fellow Michelle Egan on Brexit Deal\\nBy Michelle Egan on December 28, 2020\\nBolsonaro & Biden: What\\'s Next for Brazil-U.S. Relations?\\nPopulists in the Kitchen: A Conversation with Andrés Velasco\\nInfographic | Platinum Opportunity: Digitalization of SMEs in Mexico\\nBy Diego Marroquín Bitar on December 17, 2020\\nBolivia\\'s Lithium Future: A Second Chance?\\nWilson Center\\'s Global Europe Program experts comment on the possibility of a \"No Deal\" Brexit.\\nBy Daniel S. Hamilton on December 12, 2020\\nDownturn Disparities in Latin America\\nBy Lucy Hale on December 11, 2020<s> Learning disabilities in children\\nSymptoms of osteoarthritis\\nTypical symptoms that occur with osteoarthritis\\nThere are characteristic symptoms of the Osteoarthritis symptomsthat apply to almost all joints, regardless of where the arthrosis manifested.\\nThe symptoms of osteoarthritis include:\\nOf the Starting pain: It is understood as the typical intensification of pain or the typical occurrence of pain at the beginning of a load, e.g. Hip joint pain after getting up from the chair after a long period of sitting or in the morning after getting up. The osteoarthritis patient needs a little to \"to get going\". If the joint has warmed up, the symptoms improve.\\nOf the Stress pain: The joint can sometimes be stressed quite well for a while. After a certain time, however, they worsen the symptoms again. Sometimes the joint feels warm and swells. The symptoms worsen during the day. Rest relieves the symptoms.\\nFurther Characteristics of osteoarthritis are:\\nSwelling of the joint\\nOverheating of the joint\\nSense of stiffness of the joint\\nRestriction of movement of the joint\\nChange in shape of the joint\\nThe leading symptom of arthrosis are the joint pain. They are divided into a so-called Early Triassic and a Late Triassic. The early Triassic occurs primarily in the case of milder osteoarthritis and consists of initial pain, which occurs mainly in the morning after getting up (as the first movement pain), pain from fatigue (after long and monotonous movements) and exercise pain, which mainly occurs during strong stressful movements. The pain has the character of a radiating pain. It can happen that the pain is projected in a completely different place, far away from the area of \\u200b\\u200borigin (e.g. Knee pain at a Hip osteoarthritis).\\nThe Symptoms of the Late Triassic appear mostly in advanced osteoarthritis. They consist of one Persistent painthat occurs independently of movement, one Night pain, which occurs mainly when resting and Pain in the Muscles. The restriction of movement is characteristic of the Late Triassic, which is noticeable in the fact that familiar movements can no longer be performed and blockages in the joint occur. In some cases there is a sensitivity to the weather (patients feel particularly great pain in certain weather conditions). Sometimes so-called crepitations also occur, i.e. bone rubbing. In advanced cases, there are symptoms of thickening of the joints, joint deformities, instability of the joints, Misalignments of the joints and Atrophies of Muscles (sunken muscle bellies). In severe courses, muscle contractures occur, in which the muscles are tight and cramped (cramps).\\nIn the so-called activated arthrosis the joint and the surrounding area are overheated. The joint is also tender. In some cases, a joint effusion forms with swelling. This swelling could be seen on ultrasound.\\nLearn more about the Diagnosis of osteoarthritis\\nAppointment with ?\\nI would be happy to advise you!\\nMy name is dr. Nicolas Gumpert. I am a specialist in orthopedics and the founder of .\\nVarious television programs and print media report regularly about my work. On HR television you can see me every 6 weeks live on \"Hallo Hessen\".\\nBut now enough is indicated ;-)\\nIn order to be able to treat successfully in orthopedics, a thorough examination, diagnosis and a medical history are required.\\nIn our very economic world in particular, there is too little time to thoroughly grasp the complex diseases of orthopedics and thus initiate targeted treatment.\\nI don\\'t want to join the ranks of \"quick knife pullers\".\\nThe aim of any treatment is treatment without surgery.\\nWhich therapy achieves the best results in the long term can only be determined after looking at all of the information (Examination, X-ray, ultrasound, MRI, etc.) be assessed.\\nYou will find me:\\nLumedis - orthopedic surgeons\\nYou can make an appointment here.\\nUnfortunately, it is currently only possible to make an appointment with private health insurers. I hope for your understanding!\\nFor more information about myself, see Lumedis - Orthopedists.\\nSymptoms of shoulder osteoarthritis\\nArthrosis, i.e. the wear and tear of cartilage in the shoulder (omarthrosis), leads to a direct rubbing of the shoulder socket and the humerus head together.\\nTo Onset of illness the complaints are often unspecific, it often happens to Shoulder pain when resting or pain in the right, or. left arm after exercise or at night. Later, lying on the affected shoulder becomes very painful, with certain movements it comes to Pain symptoms and to one Loss of strength in the shoulder. It comes to one limited mobility In everyday life, be it when carrying or lifting, washing your hair or doing sports, many activities are tortured by pain.\\nOften a Crackling or crunching felt in the shoulder when the arm is stretched forward or raised above the head. In addition to the Shoulder pain are common in osteoarthritis Restrictions on rotational movements and lateral spreading observed. The shoulder joint can also be swollen from osteoarthritis. However, the joint is surrounded by strong muscles, which is why it is often difficult to determine the swelling with certainty.\\nIn the further course of the disease it can general movement restrictions come. Often with shoulder osteoarthritis adjacent joints affected, for example in Shoulder joint (Connection between the outer end of the Collarbone and the top of the Scapula). In the advanced stages of osteoarthritis there can be one pain-related relieving posture of the shoulder joint and consequently to a significant functional restriction.\\nSymptoms of knee osteoarthritis\\nThe typical symptom of a Osteoarthritis of the knee (Gonarthrosis) are pain in the knee when climbing stairs such as when walking on unpaved roads. These symptoms are not very specific and are often not recognized as symptoms of osteoarthritis. Usually the knee pain is very strong at the beginning of a movement (so-called Starting pain), then slowly subside and reappear with prolonged exposure (so-called Exercise pain). Become common Pain behind the kneecap complained after sitting for a long time.\\nBesides, it can too grinding or cracking rubbing noises come with knee movements. Those affected also report one increased sensitivity across from damp and cold weather. The knee joint can too swollen, overheated, red and deformed be. The severe pain and swelling often lead to the relief of the knee joint, which becomes measurable after a short time Muscle decline and one Restriction of mobility can lead. This affects the stability of the knee and increases the pain, making the situation worse Vicious circle.\\nThe further the knee osteoarthritis has progressed, the more frequent the pain, which can then also occur at rest or at night. In addition, the mobility of the knee continues to decrease; in rare cases the knee becomes stiff due to osteoarthritis.\\nLearn more about this: Knee osteoarthritis\\nSymptoms of hip osteoarthritis\\nThe Hip arthrosis (Coxarthrosis) often starts very harmless with slight pain at the beginning of a movement, especially after long periods of sitting or in the morning after getting up. The pain subsides after a few steps, but occurs more and more frequently. Movements like that Bending over and descending stairs, but also Turning movements (e.g. when getting out of the car) or that Spread and pull your legs towards you are becoming increasingly difficult.\\nin the advanced stage hip osteoarthritis causes pain even at rest and at night on. Those affected often complain about one Groin pain, which radiates over the thigh to the knee joint on the same side. Often it comes to one after long walks slight buckling of the hip on the affected side or those affected begin to limp. Arthrosis also restricts mobility in the hip joint. The thigh can no longer be bent or stretched without problems, the leg can only be spread apart with pain and rotational movements are hardly or not at all possible. Certain movements can no longer be performed because that Joint blocked.\\nDepending on the extent of the signs of wear, you can also Rubbing noises when walking be heard, the affected person feels that the joint no longer runs \"smoothly\". Symptoms accompanying hip joint arthrosis are common Back pain on the lumbar spine. By relieving posture or incorrect loading due to hip pain, above all that Sacrum-iliac joint and the knee joint affected. Hip joint arthrosis typically does not result in joint swelling or instability in the hip joint.\\nLearn more about the Symptoms of hip osteoarthritis\\nSymptoms of thumb osteoarthritis\\nOf the Joint wear on the thumb saddle joint is also known as Rhizarthrosis called and occurs very often at the same time on both sides on. The first symptoms of the disease are often pain when reaching for heavy objects such as a water bottle. The feeling of a Stiffness of the fingers especially In the morning and Problems with closing fists will be described. At times it can become a so-called activated osteoarthritis come, the thumb joint swells, is reddened and overheated. The thumb saddle joint is the most flexible joint of the thumb and involved in all movement patterns, therefore in most cases there is severe pain.\\nAlso fall Turning movements like turning a key in the lock harder and the Hand strength and sensitivity decrease. Fine motor movements such as unscrewing a screw cap from a beverage bottle are more difficult and require several attempts. The thumb saddle joint can become unstable. In the further course there is one Ossification of the joint capsuleresulting in a deformity (Subluxation) of the thumb in the saddle joint. These changes are visible to the outside, but the mobility of the thumb is usually not restricted. In addition, bone growth processes (formation of osteophytes) become palpable over time.\\nSymptoms of finger osteoarthritis\\nThe characteristic degenerative changes in the joints in osteoarthritis can basically affect every joint in the body.\\nOften, however, the typical osteoarthritis complaints of the fingers or finger joints occur. The vast majority of those affected are middle-aged women.\\nA distinction is made between arthrosis on the end joints of the fingers (so-called Heberden\\'s arthrosis) and those on the middle joints of the fingers (so-called Bouchard\\'s arthrosis).\\nIn general, typical nodules and bulges can be felt relatively early in both forms of arthritis.\\nThe course of osteoarthritis of the finger joints can be very different.\\nOn the one hand, there are patients who have almost no pain or restricted mobility to complain about. On the other hand, however, there are those affected who suffer from severe pain and who may develop misalignments of the fingers and the associated functional disorders in the course of the disease. The first symptoms of the onset of osteoarthritis of the finger joints can be pain that occurs when grasping objects, especially heavy objects. In addition, swelling of the joints can occur.\\nIn the end joints of the fingers (Heberden\\'s arthrosis), a so-called flexion contracture usually occurs over time, which can also be thickened by the bony attachments on the joint. The fingertips are then bent forward and can no longer be fully extended. In addition, this form of osteoarthritis often causes blister-like swellings that are filled with a gelatinous liquid. These are known as mucoid cysts and are easy to empty. Heberden\\'s arthrosis is the most common form of arthritis in the hand.\\nIn the middle joints of the fingers (Bouchard arthrosis), this disease usually manifests itself on several fingers at the same time. Here, too, there is thickening of the joints, which is caused by bone extensions.\\nFinger osteoarthritis\\nBouchard osteoarthritis\\nSymptoms of hand osteoarthritis\\nThe Osteoarthritis in the wrist is a sign of that Wear on this joint. It is about a relatively rare disease and can do both one-sided as well as both sides occur.\\nOften this occurs as a long-term consequence of a malposition that has healed Forearm fractures (mostly distal radius fracture) or Carpal fractures (especially of the scaphoid bone) in appearance. But with some carpal diseases or other inflammatory processes, osteoarthritis symptoms can also occur on the wrist. The most common is that Radiocarpal joint affected, i.e. the joint where the radius (spoke) articulates with the carpal bones.\\nStand primarily Pain and Restrictions on movement in the foreground, as the pain is mostly in Combination with movement occur. Later this pain can also be present at rest and the entire wrist can be deformed.\\nAdditionally can Bone attachments to be felt. Also noticeable is the severe swelling of the back of the hand.\\nIn some cases are Joint inflammation to observe, which are relapsing. In the acute episode it comes to Swelling, redness, pain and Overheating of the joint.\\nPlease also read: Osteoarthritis attack\\nIn some patients the pain is also depending on the weather. Wetness and cold tend to have a negative effect on the symptoms, dry heat, on the other hand, alleviates this.\\nIn the final stages of this disease, however, there are usually very great restrictions on movement and in the worst case it can lead to loss of function of the wrist. Therefore, early and stage-appropriate therapy is essential to maintain the quality of life of those affected.\\nLearn more about the Wrist osteoarthritis\\nSymptoms of osteoarthritis of the foot\\nThe Osteoarthritis of the joints on the foot most often concerns this upper ankle, the joint of the big toe or the Tarsal joints. Arthrosis of the metatarsophalangeal joint of the big toe is also referred to as a so-called Hallux rigidus.\\nThe symptoms are usually felt in the immediate vicinity of the affected joint and are initially expressed in the form of pain.\\nIn the early stages of this disease, the pain usually only occurs in phases and in particular after heavy exercise, such as after long running or jumping movements. After a certain Rest The symptoms usually improve again until they are completely free of symptoms.\\nIn addition to the pain that those affected usually call Tenderness is specified, a Swelling of the affected joint occur.\\nIn a later stage of the disease, the symptoms can persist, i.e. either not at all or not completely. This can limit the function of the affected joint and thus also the mobility of the entire foot. It is also possible that the pain turns out to be so-called Starting pain expresses. This occurs after a long period of rest and then improves with movement.\\nIf the articular cartilage is broken down further in the course of osteoarthritis, the pain also occurs at rest, which is why those affected often tend to relieve themselves, which can be associated with incorrect strain. This in turn can lead to further remodeling / regression of the foot or the surrounding muscles in the further course, which ultimately leads to a Worsening of the functionality of the lower extremity can end. In the worst case, the entire foot can become stiff.\\nPlease also read: Ankle arthrosis\\nCategory: Orthopedics-Online\\nWandering redness\\nToothpaste for pimples\\nTherapy for Perthes disease\\nLymphatic Cancer Therapy\\nOvarian cyst\\nWhat happens if I overdose on folic acid?\\nSymptoms of an SIJ block\\nSternocleidomastoid muscle\\nTorn earlobe\\nHeel bone\\nCarpal tunnel syndrome surgery\\nDuration of an inflammation of the heart muscle\\nFigure tendinitis on the wrist\\nOcclusal splint\\nBody cavities\\n2023 © https://lifeafterjob.com Symptoms of osteoarthritis<s> Don\\'t let the perfect temps and gorgeous sunshine fool you. Something is afoot.\\nToday started out innocently enough--a small carpool hiccup, but nothing unmanageable. I coached my sister who was coming to watch the boys for the morning through the nuances of the kindergarten pick up and headed into the office ready to check things off my list like a woman on a mission. Yeah, that lasted for all of 30 minutes.\\nA quick call from my slightly panicked sister informed me that Preston had hit his head on the sofa table while chasing her dog around the house. Oh the perils of bring your pet to babysit day!\\n\"I don\\'t think it hurt his eye.\"\\n\"It better not be his eye.\"\\n\"So glad I wore my white pants today--perfect for consoling bloodied boys.\"\\nAnd with that the mad hatter\\'s party of a day began.\\nFortunately, the pediatrician\\'s office does do stitches. I say fortunately because, if you remember, they do not do concussions. They don\\'t even look at concussions. Not even if you\\'re standing right in front of them with a puking child you suspect has a concussion. Good for me I\\'m over that little incident (can\\'t you tell I\\'m so over it?) because now I needed them to do stitches. I mean I really needed them to do stitches. I selfishly could not think of something I rather do less than spend the entire day in the ER at Primary Children\\'s again (because that\\'s who does concussions).\\nI did think it odd when I called to give the pediatrician\\'s office a heads up that we were coming in they asked if I thought I could hold Preston down by myself. \"Me hold down a writhing four year old you are trying to sew up,\" I wondered out loud. \"I\\'m not sure. I\\'ve never tried,\" I answered. Her answer? \"Okay, we can just grab some of the medical assistants if we need to, go ahead and come on in.\" Really?\\nMaybe it\\'s just the PR side of me, but who are these people? Isn\\'t possessing some fraction of a calming bedside manner a prerequisite to entering the medical field? If not, it should be because at that point all I could think was that I had a choice to make--Preston was going to be scarred either physically if I chose not take him in, or emotionally if I did. It was a gamble and I do not enjoy gambling.\\nFortunately, calm and rationality took over when a new doc we had not seen in the office before introduced himself to us as our caregiver of the day.\\nHe said: \"Hi, I\\'m Kevin.\"\\nI thought: \"I\\'m sure you mean Doctor Kevin, right? Who goes to all that school and doesn\\'t demand a proper title at least 50 times a day?\"\\nBut I said: \"Great. Can you help my little man?\"\\nA few punny doctor to four year old jokes later, a promise from me of some new Star Wars Legos for bravery, and some serious human glue and Presto and I were both relieved the ordeal was over without any further scars, seen or unseen.\\nOne child mended. One child properly carpooled. One work day shot to--well, just shot. Now it was time to ready the newest for his first physical therapy appointment.\\nYes, according to some well qualified professionals it seems McKay is lagging a bit behind his peer group these days when it comes to moving his mass in age appropriate ways. Me? I\\'ve been skeptical. I think he\\'s just smelling the roses, and half expected the PT to agree with me and wonder what the heck she was doing in our living room with such a strong kiddo. Wrong.\\nHis initial evaluation has resulted in a recommendation for twice weekly appointments with physical and occupational therapists for the next six to 12 months. Hmmm. I wondered what we were going to do with our abundant free time...so glad that problem is solved. Whatever. We always find time to squeeze everything in, right? Here\\'s to enjoying some private coaching that will put Mr. Mac ahead of the pack and ready for his next round of downtime without missing a beat.\\nThe grand finale? The day ended with Matt passing out from a blood draw at his yearly physical and him coming home eerily drained of any sort of energy and color. He spent the rest of the night sipping OJ, drifting in and out of sleep, worrying me that he had driven home in this state. Let\\'s hope the results of the blood test are far less dramatic than the actual blood draw. For the love!\\nI\\'m sure tomorrow morning will bring improved circumstances to our little abode. I\\'m having the windows cleaned, however, and whenever you pay good money for crystal clear views it\\'s a sure bet it\\'s going to rain. No matter. After today, I say bring it on. For now I\\'m glad momma said there would be days like this; not weeks, months, or years. Days I can take. And tomorrow is a new one. Hallelujah.\\nAround the world and back again. Okay it was only Boston. But it was the first time I\\'ve been away from McKay for more than a few hours. Because I somehow landed the most amazing part-time gig a baby momma could hope for, part of my duties include traveling four or five times a year to interview clients and attend conferences. There has been, however, quite a dry spell for independent globetrotting since Mac burst on the scene. But life has found a steady pace and things are good for now, so Matt and I agreed I\\'d better get while the gettin\\'s good so I can keep said fab job.\\nIn addition to meeting with seriously impressive clients, one of the perks of my time away from home is usually a dark, quiet hotel room with fluffy pillows and a wake up call with a time that although usually early, is determined entirely by me. So are you waiting to hear how I slept, slept, slept my night away, woke rested and ready for the next nine months of restlessness? So am I.\\nJust like the crazy mommy I\\'ve been trained to be, I woke every three hours and worried about how the boys were doing at home. I pumped my way out of lactation misery and then laid in bed mad that I was not sleeping. I know. I\\'m insane.\\nThe next day brought adventures navigating Boston which over the last decade put their interstate under ground so as not to mess with the aesthetic of the city. It\\'s a great idea, but not so great for Debbie Directions who sternly told me from the confines of the GPS system she runs that I must turn LEFT now. LEFT now. Re-calculating route. My dearest Debbie, there is no longer a LEFT turn there. There is a wall. In any event, we found our way to the client and had a great day meeting with the big wigs and touring their ice cream factory. Yes. There were samples. Peanut-butter-smothered-in-their-own-hot-fudge samples. Did I not say I have the best job EVER?\\nBack again to the hotel where a dream of mine for a while now met reality when I saw heart baby Luna\\'s mom waiting for me in the lobby. We\\'ve been fast friends separated by far too many miles as we journey through our kid\\'s heart adventures. It was amazing to look her in the eyes and share stories and worries and plans. Yes, many, many wonderful plans. Stay tuned.\\nThen it was home again, home again lickety split to find a nine-month old on the verge of a good cold and ear infections. A couple of quick trips to the pediatrician, pharmacy and home again and we are still trying to return to normal. I was reminded how great our slightly-less-than-optimal is at lunch with a couple of dear friends on Friday. These ladies both have babies who have finished their battles, but left their mommas trying to find their lives again in all that\\'s still here. They are truly glorious and special people. Ear infections? Sniffles? No complaints from me.\\nSo it\\'s Memorial weekend. It\\'s stormy. I\\'m home with a not-so-cheerful McKay and the boys are in \"Vanilla\" (as Preston says with such delight because it shares its name with his favorite ice cream) or Manila as the rest of the world knows it, enjoying a muddy Flaming Gorge with their grandparents, aunt, uncle and daddy. And a Sunday morning at home with no one tell on me means I\\'ve had three cookies and one poached egg for breakfast. Carb. Protein. Sounds complete to me.\\nIt\\'s a quiet house with just one baby. I think I\\'ll follow the advice that is so incessantly offered to first-time mothers but becomes increasingly comical with each subsequent birth--\"Just sleep when the baby sleeps.\" After all, it is nap time. xoxo.\\nWhew. Has it been a week? Really? This week has been a bit like driving my car somewhere only to realize I\\'m not really sure how I arrived safely. Truly our lethal weapon of a life has been in the fast lane on cruise control while we\\'re somewhere in the back enjoying the ride. Oh well. The wind feels good in our hair these days and we\\'re together.\\nSo I guess I should begin this week by saying there is absolutely no way I went an entire week without keeping up this crazy journal of a blog. Not me! The shame.\\nI also did not leave a lovey voicemail of gratitude for my hubby on a particularly cheerful Wednesday afternoon thanking him for our life only to find out later that he deleted it without even listening! I did not in the never-to-be-listened-to message praise him for the fact that his hard work allows me to lay barefoot in the sunshine in our beautiful backyard with three loves of my life and teach them how to enjoy a spring day. I did not gush about how everything we do is better when he\\'s there. No, I did not marry a man that would delete a message like that only to say, \"When I heard it was you and we had talked already, I deleted it. Why?\" Ahem.\\nOh well, maybe if I really do not complain about sucking dirt for 7.1 miles while I try to find my stride and my breath I will win my old backside back from the universe! In all seriousness I\\'m not sure what happened to my body with baby number three, but nothing seems to be in the right place anymore. Of course, I would not question if this is part of what it means to be thirty something and would not secretly wonder if I should make a pact with the devil (or a good trainer) to fix it, replace it, or rearrange it. No, not me!\\nI also did not give birth to the most adorable kids ever. EVER. And I would most definitely not ask you to look at far too many pictures of them (again). (These are also not from McKay\\'s 6 month, Ty\\'s 6-year, and Preston\\'s 4-year old photo shoot done three, yes three, months ago. I would definitely not be that late in getting them ready to share!) Nope! Not me.\\nLate? Not me. I am a terribly punctual person. I\\'m always, always, always on time (it\\'s hard to even type that with a straight face!). One, two, three kids? No problem. Bring it on. No matter the challenge, I am NEVER late. Not me!\\nThat\\'s why I was not amused to learn that when I made a huge extra effort to make sure the boys would be at their baseball games on time Saturday and was not feeling quite smug with myself and the genius of my plan which involved two cars and a staggered exit from the house, to then receive a phone call from Matt which did not let me know that although they were early, I had NOT sent the correct child. What? Apparently is not good enough just to get a child there--it needs to be the one whose team is playing at the time. My bad. The entire incident made me so not scared out of my mind wondering how I will actually manage three little schedules in the years to come and two boys at two different schools next year. The teachers just need at least one warm body there, right? Late? Wrong kid? Not me!\\nNot Me! Monday is the brainchild of a fellow heart momma. You can head over to her blog if you\\'d like to read what she and everyone else have also not been doing this week.\\nor face fear on a regular basis.\\ntoo quick to use the word \"impossible,\"\\nor too hesitant to say, \"yes, you can.\"\\nThe truth? Mother\\'s Day is a lot of work. Good, fun work, but work. Brunches. Dinners. Gifts. But it is all so very worth it. It is what I consider to be the first of the glorious summer holidays; the sort you celebrate outdoors where people you love tend to linger a little longer, laugh a little louder, share a bit more. It was a good day.\\nSo here\\'s my Yea! for all the moms in my life--biological and not. Yea! for all the moms that care for, teach, and otherwise \"village\" my little ones. And a big Yea! for being a mom--it-is-a-deep -down, earn-it-everyday, paid-in-moments privilege of which I think I have only begun to learn.\\nHave you noticed a change in pace lately? In your life? In the world? Over the last few months I\\'ve felt a quickening; as if this small, hurdling piece of rock we\\'re all living on has begun to spin just a bit faster.\\nEverywhere I turn it seems so many I know are facing the impossible. Young mothers (and by young I mean my age of course) hearing the word cancer from a doctor; couples longing for just one (or just one more) child; sick, sick babies; physically, spiritually, and emotionally broken hearts; working mothers who wish they didn\\'t have to; jobless fathers who wish they could lose the \"less\". It seems everyone is fighting a battle.\\nI find myself asking where has all this trial and challenge been until now? Is it really possible that in my former happy-go-lucky life I failed to understand the depth of others\\' struggles? Is it really possible that I assumed we were all living different versions of my intensely blessed existence?\\nI remember apologizing to some close friends following McKay\\'s birth. It was two days before Thanksgiving and we were in the waiting room receiving hourly updates from the surgical staff about McKay\\'s second heart surgery when a dear friend stopped by to offer support. No basket of goodies, no cards, no pretense. He was just there to sit and be with us.\\nSomething in my heart broke when I saw him as my mind flooded with memories that not so long ago his newborn son spent a good deal of time in the ICU due to some complications with his lungs following birth. Of course, I made the standard visit to adore the precious babe and applaud his brave mother, but never called again. Honestly, I didn\\'t even know how long his son was made to stay until I spoke to them over a month later. Even then, I did not feel the weight of my neglect.\\nIn that moment, in that simple and Christ-like visit from a friend, my eyes were opened to the opportunity I missed. They too had come home with empty arms. They too wondered if the night nurse would know exactly how to comfort their son. They too were torn between nurturing children at home and being beside one in the hospital. I cried. I asked his forgiveness. All I could offer by way of explanation for my inaction was that up until McKay, I didn\\'t understand. I\\'m so sorry, I truly did not know.\\nNow I know more. I feel like someone has turned on radar in my soul that was previously unused. I sense more heartache. I understand pain. I relate to helplessness. But at the same time I also know vastly more about joy. I have an intimate relationship with trust. Now, more than ever, I am reaching beyond faith and feel as if I\\'m getting to know my Savior as a friend. I no longer bargain with him or leave my verbal dribble of an offering at His door and run. We are in constant conversation and my life is different because of it. I want to be better. Do better. And, surprisingly, that doesn\\'t always mean more plates of cookies, more gifts. The more I look back on what I needed and the needs I now see in others it is just giving that person time and opportunity to talk, to debrief, to process. Less about me--what I\\'m giving, doing, being-- and more about them.\\nI am not entirely thrilled about leaving my blissful ignorance, but I am amazed at the others I am finally being made to see. Sometimes the lessons others are made to endure are heavy and hard to watch. However, I am always left with the reassuring feeling that none of it is random. There is an order to things. Even when they are hard things—there is order. Yes, my world is spinning a little faster these days, but certainly not out of control. My experiences have given me new eyes, an increased awareness, and I am learning how to use it.\\nWhat have I not been doing this week you ask? Well as a tenured mother of three small boys I would definitely not give my 8 month old a dangerous toy. I would have sorted those all out of our stash at this point, right? I would not foolishly assume that because he has not yet sprouted any pearly whites that he is incapable of biting off part of the toy and nearly choking on it. I would not, of course, let this all happen as I was driving, panic when I heard him choking, swerve dangerously off the side of the road at rush hour, turn on my flashers and began frantically sweeping his mouth for the missing horn of the appropriately styled \"monster\" with which he was entertaining himself. No, I would definitely not do that.\\nAnd to top it all off, I would most definitely not let this all happen when my mother-in-law was in the car. Because if she were in the car to see me panic, swerve, and then say in a determined voice to my darling babe, \"You have pulled through two open heart surgeries, you will NOT choke to death dammit.\" Because at that point she might not ever ride with me or leave me alone with my little Mac again. No I would never let that happen, not me!<s> On January 26, 2015, The Furthering Asbestos Transparency (FACT) Act was introduced into the 114th session of the House of Representatives as H.R. 526. This legislation would hurt asbestos victims and their families by requiring public disclosure of all kinds of personal, private information. We must make our voices heard. Contact your Representative and ask him or her to vote against The FACT Act. Here\\'s the House\\'s tool for finding your Congressional Representative. Tell them to do the right thing and reject this unjust bill.\\nAsbestos corporations are once again trying to make it harder and more dangerous for asbestos victims to get the compensation they deserve from asbestos trusts and the court system. The U.S. Chamber of Commerce (which, despite the name, is not a government agency) and the corporate-funded American Legislative Exchange Council (ALEC), have proposed legislation that would require private confidential information about asbestos victims be made public. The real reason for doing this is to make asbestos victims and their loved ones afraid and fearful of exercising their constitutional rights.\\nThe so-called FACT Act (Furthering Asbestos Claim Transparency Act) would require bankruptcy trusts to publish quarterly reports including detailed personally identifiable information about victims and their families. Private information would be published on the internet for all to see: the last 4 digits of Social Security numbers, information about personal finances, information about minor children who were exposed at an early age, and private information about work history. This type of information would make asbestos victims vulnerable to hacking, identity theft, scams, and other predators. Further, publishing this private data could result in the denial of credit, employment, housing, and life, disability, and health insurance.\\nNo private information about asbestos defendants would be made public by this supposed \"transparency\" act. Only victims of mesothelioma and other asbestos-related diseases would lose their rights to privacy in settlement negotiations. It is completely one-sided and unfair. No other kind of litigation requires these barbaric steps and no other kind of plaintiff is subjected to this treatment.\\nThe FACT Act would also increase the costs to asbestos bankruptcy trusts, which would have to pay to compile the information and create public websites to display it. These costs serve only to take money away from the limited amount of money available to victims. Asbestos victims are never made whole after an asbestos company has declared bankruptcy, as the amount of money is always limited. This bill would serve to further reduce payments to mesothelioma and other asbestos victims. It would not apply to any other type of trust created by the bankruptcy courts.\\nVeterans will be harmed by this bill. Many veterans were exposed to asbestos while serving their country aboard ships. Trucks, tanks and airplanes were also insulated with deadly asbestos. Veterans often went on to take civilian jobs similar to the jobs they performed in the military, and were exposed to asbestos in those positions. It is estimated that almost one-third of persons diagnosed with mesothelioma are veterans of the U.S. military. The FACT Act would hurt the very people who were there for our country when we needed them most.\\nThis bill is not about transparency. It is about delaying and denying payments to the very people whose lives and health were destroyed by the asbestos companies. It is a cruel irony that companies whose failure to transparently reveal the truth of what they knew about the hazards of asbestos exposure now seek to destroy the very privacy of their victims, and reduce their compensation even further. It is a shameless attempt to revictimize those who have already suffered so very much.\\nAgain, asbestos victims and their families must make their voices heard. Contact your Representative and ask him or her to vote against The FACT Act, House Resolution 526. Here\\'s the House\\'s tool for finding your Congressional Representative. Tell them to do the right thing and reject this cruel bill.<s> Mercury inhibits methylation, which is the biochemical process that affects the production of many hormones and neurotransmitters. It also causes a selective loss of Purkinje neurons in the brain which produce GABA.\\nMercury is known to concentrate in glands, including the thyroid and blocks the enzyme that converts T4 to T3. Also, your mercury burden is a chronic stressor that seems to provoke symptoms of adrenal fatigue.\\nErethism: It\\'s the mercury personality, and that involves excessive timidity, diffidence, shyness, conflict avoidance, loss of self-confidence, anxiety, a desire to remain unobserved and unobtrusive, a pathological fear of ridicule and explosive loss of temper when criticized. There are different versions of this definition and they\\'re all fun and they really resonated with me, so that can be interesting to look that up on the internet.\\nIt was lovely to recently meet Kris. After enjoying a nice cup of herbal tea with her, she shared a few things about mercury toxicity in her pretty back garden. Here is one of the videos we did – enjoy!\\nHere is a link to part 2 of this discussion- what to do and additional resources.\\nThis was a very informative talk, and I am looking forward to part II. I think I have mercury toxicity from dental amalgams, though all but one have been removed. I have Hashimoto\\'s thyroiditis, celiac disease, fibromyalgia, and 2 copes of MTHFR for methylation defect. I am trying to improve my methylation with supplements and get all these issues under control. I am eager to find a safe way to test and detox for mercury. Because of the MTHFR defect and leaky gut, is there a safe way to get the mercury out and not have it reabsorbed into the brain and elsewhere? Thanks.\\new\\'re pleased you found it informative – Kris is very thorough and detail-oriented! You\\'ll enjoy part 2.\\nOne of the reasons I was initially hesitant to have someone come and talk on mercury is that I don\\'t have an answer on safe ways to remove the mercury so I\\'m afraid there is no easy answer for you on this one. One of the main reasons to talk about this is: creating awareness to prevent it continuing to happen (amalgam use and consumption of fish that are not very low mercury); and to give you some possible clues as to whether this could be one reason why you may may have strange unresolved health issues.\\nI thank Kris for helping me realize it is important that we get this information out. At the same time I\\'m aware it\\'s far from ideal when I don\\'t have a solution for detoxing from the mercury and I\\'m sorry about this.\\nI\\'ll have Kris hop on and add her thoughts too.\\nLinda, I would suggest working with Pam Killeen (pamkilleen.com) on getting out the toxic metals and rebalancing the body.\\nExcellent research, thank you. For some reason, nobody tell about symptoms of mercury toxicity which I had: feeling heated even from walking for a long time, covering myself with comforter and especially when I took bath or shower. I had to take cool shower because my hear would pound at night. The reason- mercury starts to evaporate when it is heated. I have removed mercury and have done detox with challenge but still have palpitation and blood sugar fluctuations. Anxiety is greatly reduced which adrenal support and stress management.\\nThanks for sharing Lisa – I\\'m so pleased to hear your anxiety is greatly reduced. And glad you enjoyed the research.\\nI\\'m going to see if Kris will comment on the heated feeling you mention and if she has heard it could be a symptom related to mercury toxicity.\\nIn the meantime a few things come to mind: heat intolerance is a symptom of low serotonin and we heard how mercury toxicity can affect serotonin production. Also it could be a possible effect on the hormones – we often hear how the thyroid gland can be seen as the furnace and the pituitary gland as the thermostat.\\nExcellent interview and so glad the topic has come up. I am one of those with so many issues, I am overwhelmed and don\\'t know where to turn. I have been on a healing journey for over 15 years and have been told by numerous practitioners that I have a \"cascade of symptoms.\" Even though I have known that mercury is probably a root cause for me, and I have tried to deal with it in different ways, I have not found a practitioner who can address it well. Most do not want to do another provoked test on me because I am extremely sensitive. The last test (2003) before I had my amalgams replaced showed high mercury, lead and cadmium. I was given penicillamine to test then to chelate me, and my candida really flared up. I have also heard that there needs to be a \"balance\" between the candida and the mercury. I think that is when I just gave up on this piece since candida continues to raise its ugly head. \"Balance\" seems impossible.\\nI live about an hour from D.C. and would love to know if anyone can recommend a good practitioner in this field. I have been a patient of NIHA in the past.\\nI would suggest working with Pam Killeen (pamkilleen.com). I don\\'t know whether she can help you long distance, but many holistic practitioners do. Good Luck to you.\\nThe best tests are the hair test (but interpretation is key) and the porphyrins panel (if the sample is handled carefully). These are described in the link, \"Chronic mercury poisoning: A brief summary of the science\" that Trudy provided on this webpage.\\nAssuming you are a poor excretor, then as Trudy notes, there is no great way to remove the mercury. 🙁 Since your exposure has ended, the body can begin to remove it on its own, albeit slowly. Many practitioners have products that may or may not help with this, but it may be a long process, so find a path that you can sustain. You may want to read about the Cutler protocol for low frequent dose oral chelation, which is considered the most rational method, though may be too strong for some.\\nOn the bright side, many people find they feel better once they understand mercury toxicity and learn how to compensate for it via nutrition and other health practices.\\nYour temperature dysregulation could be a symptom of a thyroid problem, which could be due to mercury. I didn\\'t realize that it also could be due to low serotonin as Trudy mentioned.\\nHeart palpitations are common with mercury toxicity, and might be alleviated with magnesium (in an absorbable form) and hawthorn, but Trudy may know more about this that I do.\\nThere is no need to do another test for mercury. Once you test positive, mercury is likely the root cause of whatever symptoms you continue to have.\\nCandida can be very hard to overcome. It took me over two years of a perfect diet plus lots of sauerkraut and probiotics.\\nIt\\'s best to view practitioners as consults rather than authorities; it\\'s best to do your own thinking. (Yes, it\\'s difficult.) I don\\'t know of a practitioner near DC, but you might look for an autism practitioner, since much of autism is mercury toxicity.\\nRegarding re-testing: I hope that all the supplements, natural detox practices, energy work, etc. have reduced the amount of mercury in my body, even though I still have a lot of mercury-toxicity symptoms. I had hoped I could test in a safe way and find out where my levels are. Is that possible and/or important? I did have a Melisa test from King James Medical Lab. in 2004 that showed I have a \"significant allergy\" to inorganic mercury, led and nickel. Do you think that could mean that even the smallest amount will create mercury-related symptoms?\\nThanks so much. I appreciate your journey and your sharing. As you know, this can be \"crazy-making\" to say the least.\\nLynne, there\\'s really no need to test again. Since you already had a mercury test of some kind that was positive, and since you continue have some symptoms that are consistent with mercury, you can continue on your healing journey, keeping in mind that mercury is a likely root cause for you, which means you probably need extra micronutrients and stress reduction. (I\\'m not a treatment expert; it\\'s highly individualized. The Internet support groups can help.) If you don\\'t mind spending money, you could order a hair test to see if your body is processing essential minerals normally, or not. Yes, this is indeed crazy-making!\\nWow-Thank you SO MUCH! I was poisoned by mercury after a trip to the dentist in 1981. My life was turned upside down. Spent years trying to find help. Finally found a Hal Huggins book \"It\\'s All in Your Head\" that confirmed all my symptoms. Had my fillings replaced in 1990 which helped but I\\'m still on my healing journey. I was able to a find a doctor who didn\\'t think I was crazy who said I had Wilsons Syndrome -low body temperature.Not Wilsons(copper)disease)He was able to bring up my temperature 2 degrees and I felt a little better. Listening to you, I could relate to EVERYTHING–and it\\'s so nice to hear the explanation behind it all. In 2010, I found a chiropractor who does Nutritional Response Testing and he was able to diagnose me with high mercury levels through muscle testing and his \"testing kit\" and was able to remove the mercury with Standard Process Supplements Parotid PMG and Cholocol ll.\\nOne pulls the mercury out of the cells and the other helps pass it through the body.It took about 2 months to remove it all.Not sure if it\\'s really all out as I feel better but I still have chronic fatigue, low energy and food sensitivities and spells of zoning out. I\\'m hoping to eventually repair ALL of the damage that was done–don\\'t know if that could ever happen but I can\\'t wait to hear Part 2! THANK YOU!\\nGlad you enjoyed it. You and I are part of the small subset of the population who become very ill from mercury exposure. I suspect that a much larger subset is slightly ill from mercury without realizing it. I too still have symptoms, and I too hope to get better, because the body is designed to heal.\\nTrudy, first I want to commend you on putting on an excellent, and truly helpful, summit. You are helping a lot of people with this info. Hats off to you, and keep up the great work.\\nSecondly, I want to let you know that your talk today with Kris Homme about mercury toxicity (esp. from dental amalgam fillings) being a root cause of many people\\'s anxiety, panic disorder, and/or depression (as well as bipolar depression) is, HANDS DOWN, the best talk of this summit.\\nIt is an EXTREMELY important, and yet still relatively obscure, subject, that needs to get a ton more attention put on it, b/c a countless number of people are suffering tremendously everyday, needlessly, due to a lack of this information.\\nNot only is mercury toxicity (most often from dental amalgam fillings) often the ROOT CAUSE of these anxiety disorders – but it is a very POTENT cause of it of as well – meaning that it can often manifest in people as very SEVERE forms of anxiety (not just relatively \"mild\" cases) – even sometimes totally debilitating.\\nI know this extremely well from personal experience. About two weeks after I had my 8 amalgam fillings removed several years ago, my 20 year chronic/daily state of severe panic disorder, as well as severe bipolar-type depression, was completely and radically CURED.\\n(As a side note – from the many years of research I\\'ve done on this topic (similar to what Kris has been doing), I\\'ve come to discover that there are some different reactions in people to amalgam removal. Not everyone becomes cured of a severe ailment(s) as immediately as I did (but some do). For others, it takes longer – for a significant percentage, amalgam removal alone does not provide as radical an improvement – it also takes a good amount of time doing chelation, to do the job).\\nIt\\'s a bit of a complex subject, as there are many variables, and everyone\\'s bodies and histories are different – but the bottom line is that there are many, many cases of people being either cured, or at least radically improved, after judiciously done chelation therapy (often over the course of at least a couple of years).\\nThe type of chelation that I\\'ve been doing – and of which I\\'ve heard of such \"success stories\" mentioned above – is the low-dose, frequently administered, oral chelation protocol developed by Andrew Hall Cutler, PhD (of which Kris also advocates). (The other methods of chelation out there – such as IV chelation, or the use of \"natural chelators\", such as chlorella – can be potentially harmful, and even dangerous).\\nThe bottom line is that mercury toxicity, esp. from dental amalgam fillings (which is the largest source of mercury for most people), is 1) not a \"conspiracy theory\", and 2) not actually a \"controversial\" subject in the true sense (it\\'s only \"controversial\" b/c the people who consider it controversial still don\\'t know enough facts about it).\\nThe topic of amalgam mercury poisoning in people (causing diseases and disorders) is simple *biological reality*.\\nPerhaps one day – and hopefully one day soon – the \"mainstream public\" will finally catch on to this fact. In the meantime, talks like Kris Homme\\'s today, help deliver such messages to a wider audience. Thank you to you both, Kris and Trudy!\\nThank you for sharing your story and for your very kind words! I agree with you – Kris is really quite the hero and very active in getting this message out there. I am so pleased to have the opportunity to help her do so!\\nKris, I also wanted to say to you – that as a fellow amalgam mercury poisoned person, I really commend you on what you are doing… for giving this excellent talk today on the Anxiety Summit (can\\'t wait for Part 2!! Thank you Trudy, for giving this very important topic two sessions!)… and also, I know about some of the other things you\\'ve done for this cause.\\nI saw a video a while back, of you speaking about this topic in front of a packed room, in front of FDA officials (at an FDA Town Hall meeting type thing). That took a lot of guts. And whenever or wherever you speak, you do so in a very articulate and knowledgeable way. You do us amalgam mercury poisoned people proud!!\\nAlso, I know of the help and input you\\'ve provided people in the past on the Yahoo amalgam mercury poisoning online groups.\\nIn my eyes, you are quite a hero – and I hope your journey to recovery and good health are going well and as quickly as possible!! Thank you again!\\nThis interview really gave me more ideas about missing pieces. I was surprised to hear the limits of metal bloodwork– I ruled out metal tox after everything tested negative. Also found the connective tissue and mitochondrial info revealing. Glad to know more what to look for in the hair analysis as well. And funny to hear some of those erethism\\'s, spacing out, sensory overload, etc. have physiological connections.\\nThank you both for exploring the subject in such a considered and informative way. I had my amalgams removed over 25 yrs ago, with a dental dam (cutting edge at that time– and sadly, that dentist died close to age 50 of unexplained illness). I\\'ve been chronically ill the past 3 years with a list of symptoms that have led to many discoveries, including compound heterozygous MTHFR gene.\\nLast year Cleveland clinic MD asked if I could just narrow my list of symptoms because it was too complex. He rolled his eyes at my supplements. But I\\'m hearing so many people in these summits with similar levels of multi-system complexities. I didn\\'t consider mercury a factor until now.\\nI can\\'t tell you what a gift it is to have seminars like this & the digestive & depression summits, that empower us with ideas, approaches and the knowledge we are NOT MAKING THIS UP.\\nTrudy, your interviews are so clear and focused. You not only highlight the speakers\\' knowledge, your whole manner conveys compassion, balance & generosity of spirit.\\nThank you for such a fascinating talk. So much new information and more to come in part 2!!\\nI am an ex dentist and just finished naturopathy but due to depression/ anxiety and the \\' Mercury\\' personality you talked of, I have not managed to start work yet.\\nI believe Mercury could be the root cause of my illness. Nutrients and herbs help instead of SSRIs but not enough. I have had two hair mineral analyses done that show low essential minerals and low Mercury visible. I have Andy cutlers Hair interpretations test and a good lab here, Interclinical labs have a wealth of practitioner manuals but it\\'s all a steep learning curve.Gene testing also is another huge area. I shall try the Porphyrins test if available here in Australia.\\nHer brainwashed pseudo-science beliefs on \"climate change\" diminish her credibility. She should listen to Chris Monckton and Alex Jones.\\nThanks for your enthusiasm about this topic and for your detailed, insightful comments. I hope Trudy will continue to cover this issue. I know it\\'s difficult and I realize it might not appeal to a wide audience due to lack of awareness about its insidious toxicity.\\nI\\'m glad that your mood disorders were cured by amalgam removal. And I\\'m glad you pointed out that individual recoveries can vary widely.\\nYou mentioned the FDA hearing on amalgam in 2010. I naively thought that after we gave the agency our science-based testimony and our science-based legal arguments, they would restrict amalgam. We learned that the staff had drafted a response but it was blocked by the H&HS Secretary, Kathleen Sebelius — so it must have contained some restrictions that were unpopular with the dental industry. The agency recently agreed to respond to our legal petitions by the end of this year, but it wouldn\\'t surprise me if industry pressure causes them to miss the deadline. However, the science has become irrefutable in recent years, so it\\'s just a matter of time before the FDA must restrict amalgam. And at that point, mainstream medicine may start to acknowledge this devastating illness.\\nI\\'m so glad you find the summit useful. I had hoped to reach people like you, who\\'ve been tested incorrectly for mercury, who\\'ve had to put up with impatient doctors dismissing symptoms and rolling their eyes about supplements. I wrote the journal article (to which Trudy has linked at the top of this blog) to be short and readable, with the intent that patients could give it to any disbelieving doctors (although doctors still don\\'t want to deal with complicated illnesses).\\nI agree that Trudy is terrific. In our pre-interview chats, she really honed in on the details to clarify what is science versus speculation, and I think the result is a talk that is packed with good information.\\nI\\'m glad you enjoyed the talk. Your training in both dentistry and naturopathy is ideal for a number of things, including teaching dentists and other naturopaths about mercury toxicity. Or writing about it if you prefer self-paced work. You might enjoy joining the IAOMT. Incidentally, Andrew Cutler\\'s Amalgam Illness book lists a number of lab anomalies that are associated with mercury — this can give you some insight about whether you have a burden, without spending money on a porphyrins test.\\nI\\'m sorry if you were sidetracked by my discussion of Boyd Haley\\'s advocacy. He is courageous for withstanding the peer pressure that scientists face to avoid advocacy on almost every science issue.\\nComplicated issue. Klinghardt MD has lots of info about this. Mercury testing is iffy. Mercury can hide so testing blood or hair will only give a piece of the picture. Mercury needs to be mobilized then binders are needed for excretion. Alpha lipoic acid and or cilantro mobilize mercury out of the brain where it can hide and chlorella binds it and move it out. Long process. Cutler\\'s protocol is way too complicated and has not been that effective for me. Mercola.com also has some info on this.\\nThank you for your comments. I\\'d like people to know that the hair test is useful not as a direct test for mercury levels but as an indirect test to see whether mercury is altering the processing of ESSENTIAL minerals. You are right that the issue is complicated.\\nWow. First of all I\"m sorry to hear Kris suffers from mercury poisoning. However I am glad she is putting it to such a positive use by educating the rest of us about the dangers. Hope the Summit is going great.\\nIs there no solution to Mercury poisoning?\\nRecovery can be very slow, which is why I think it\\'s crucial that the FDA ban mercury dental amalgam.\\nThis is good information to have. I have avoided flu shots because I read they have high levels of mercury in them. I\\'m afraid to get more in my body than I already have.\\nGreat information. It\\'s amazing how even after all this time there\\'s still not a lot of publicity about how dangerous mercury poisoning is for our health and, now we know, our mental wellbeing.\\nThank you for all you are doing to bring this information to a broader awareness.\\nYour articles always provide excellent and helpful information which is not readily available anywhere else in one place.\\nWhoa information overload! So much good info coming from your summit I think I will have to go back again and again!\\nDo you have a list of common symptoms of mercury poisoning?<s> Отрантские мученики или Антонио Примальдо и сподвижники ()\\xa0— 813 жителей города Отранто, принявших мученическую смерть за отказ принять ислам. Имена мучеников неизвестны, кроме одного пожилого портного Антонио Пеццула, который призвал заключённых не отрекаться от христианской веры. Были причислены к лику блаженных в 1771 году и канонизированы 12 мая 2013 года. Отрантские мученики, монахини Мария Лаура Монтойя-и-Упеги и Мария Гваделупе Гарсия Савала стали первыми святыми, которых канонизировал папа Франциск. Отрантские мученики стали самой большой группой святых когда-либо канонизированных римскими папами. Покровители города Отранто и архиепархии Отранто.\\n\\nИстория \\n\\n28 июля 1480 года оттоманский флот в составе 90 галер, 40 галиотов и других судов (в общей сложности около 150 экипажей численностью около 18 тысяч человек) прибыл из Валлоны (сегодня\\xa0— Влёра, Албания) и предпринял штурм Отранто. Город, который в то время насчитывал около 6 тысяч человек, был не в состоянии долго противостоять нападению. 29 июля город военный гарнизон Отранто и все жители покинули городские оборонительные сооружения и укрылись в городской крепости.\\n\\nГедик Ахмед-паша предложил горожанам сдаться. Когда капитаны военного гарнизона Франческо Цурло и Антонио де Фалькони ответили отказом, символически выбросив ключи города за стены крепости, оттоманская армия возобновила бомбардировку. После 15-дневной осады Гедик Ахмед-паша приказал 11 августа взять крепость штурмом. После того турки разрушили одну из стен и проникли в крепость, началась резня, во время которой мужчины старше 15 лет были убиты, а женщины и дети обращены в рабство. По некоторым данным в Отранто и его окрестностях было убито около 12 тысяч человек и отправлено в рабство около 5 тысяч человек.\\n\\nОставшиеся в живых укрылись в местном соборе вместе со священниками и архиепископом Стефано Пендинелли. Гедик Ахмед-паша предложил укрывшимся принять ислам, но получил категорический отказ, после чего турки ворвались в храм во время совершения литургии и убили всех находившихся в нём. Архиепископ Стефано Пендинелли был изрублен саблями, ему отрубили голову, которую после воткнули на пику и носили по городу. В этот же день были арестованы немногим более 800 мужчин старше 15 лет. За двадцать заключённых была внесена плата в размере трёхсот дукатов за каждого и они были освобождены. Три дня спустя, 14 августа, закованных и раздетых заключённых в количестве 813 человек группами по 50 человек отвели в окрестности населённого пункта Минерва, располагавшегося недалеко от Отранто. Арестованным было предложено для сохранения их жизни отречься от христианства и принять ислам. Пожилой портной Антонио Пеццула призвал заключённых быть верными своей вере, за что был обезглавлен первым. Позднее Антонио Пеццула за свой подвиг получил среди местных жителей прозвище «Примальдо» (Первый). Согласно местному преданию обезглавленное тело Антонио Пеццулы стояло до конца казни и палачи не смогли с ним ничего сделать. Один из турецких палачей по имени Бернабей был так потрясён стойкой верой заключённых, что исповедовал на месте казни веру во Христа, за что сразу же был убит своими товарищами-палачами.\\n\\nПрославление \\nТела убитых были захоронены на месте казни и пролежали здесь до следующего года, когда они были перенесены в 1481 году в собор Отранто. В 1485 году мощи около 250 мучеников были перенесены в Неаполь и помещены в алтарь Пресвятой Девы Марии Розария церкви святой Екатерины Александрийской. В 1888 году архиепископ Отранто и апостольский администратор архиепархии Фоджа-Бовино подарил часть мощей отрантских мучеников санктуарию Пресвятой Девы Марии в Бовино, где они были помещены в алабастровой  урне работы итальянского скульптора Паскуале Гарофало в крипте новой базилики города Бовино.\\n\\nМученическая смерть жителей Отранто вызвала широкий отклик по всей Италии, реакцию Святого Престола и правителей итальянских княжеств. Итальянский драматург Людовико Ариосто написал драму «», посвящённую подвигу Отрантских мучеников.\\n\\nС 1771 года мощи большинства мучеников находятся в семи стеклянных высоких шкафах в соборе Отранто и их можно увидеть. В некоторых шкафах видны нетленные останки тел убитых.\\n\\nБеатификационный процесс начался в 1539 году по инициативе архиепископа Отранто Пьетро Антонио де Капуа и закончился 14 декабря 1771 года, когда папа Климент XIV причислил отрантских мучеников в лику блаженных. 6 июля 2007 года папа Бенедикт XVI издал декрет, в котором признал, что Антонио Примальдо и сподвижники были убиты «из-за ненависти к вере». 20 декабря 2012 года кардинал Анджело Амато обнародовал декрет о чуде исцеления от тяжёлой формы рака у монахини Франчески Левоте, которое совершилось по заступничеству Антонио Примальдо и его сподвижников. 11 февраля 2013 года в Ватикане состоялась консистория, во время которой папа Бенедикт XVI объявил о своём предстоящем отречении и канонизации отрантских мучеников.\\n\\n12 мая 2013 года папа Франциск причислил к лику святых отрантских мучеников. Канонизация мучеников прошла на площади Святого Петра в присутствии президента Колумбии Хуана Мануэлья Сантоса Кальдерона. В церемонии канонизации приняли участие 68 священнослужителей, в том числе 6 кардиналов и 23 епископа.\\n\\nДень памяти в Католической церкви\\xa0— 14 августа.\\n\\nСм. также \\n Список святых, канонизированных папой римским Франциском\\n\\nПримечания\\n\\nЛитература \\n Paolo Ricciardi, Gli Eroi della Patria e i Martiri della Fede: Otranto 1480—1481, Vol. 1, Editrice Salentina, 2009\\n Grazio Gianfreda, I beati 800 martiri di Otranto, Edizioni del Grifo, 2007\\n\\nСсылки \\n\\n Отрантские мученики \\n Причислены к лику святых 800 мучеников Отранто и две монахини. Проповедь Папы на Мессе канонизации\\n Индекс святых \\n  Saint Antony Primaldo \\n How the 800 Martyrs of Otranto Saved Rome\\n Pope will announce on Monday date for canonization for over 800 saints\\n\\nУмершие 14 августа\\nУмершие в 1480 году\\nГруппы католических святых\\nСвятые Италии\\nХристианские святые XV века\\nХристианские мученики\\nКанонизированные Франциском\\nКанонизированные в XXI веке\\nОтранто\\nБеатифицированные Климентом XIV<s> History of the Walton Family Apr 25, 2019 0:29:41 GMT -5 cinlou, kazk, and 6 more like this\\nPost by Johnny on Apr 25, 2019 0:29:41 GMT -5\\nIt is my hope this family history will be a work in progress as we make additions (& subtractions as necessary) in subsequent posts. The biggest addition will be to expand the timeline from John & Liv\\'s marriage in`1910, up to their wedding anniversary in 1969. As many have noted, precise dates of events & family members are not consistent across the whole series & reunion films We may only keep track of what was given to us and make our best guess to connect their story.\\nHere is a detailed Walton family history, written by John Viens in 2008. It spans the arrival of Rome 1789 up to John (son of Zeb) entering adulthood (age ~15yr).\\n*The first Waltons on the mountain were Rome and Rebecca Lee Walton. Rome Walton came and settled what came to be known as Waltons Mountain in 1789. He brought with him, an ax, a mule, a plow and a rifle. He cleared his land for planting in the Spring of 1796 and went all the way to Buckingham County to get a Guernsey cow to put on it. Sometime that Spring he married Rebecca Lee and brought her there to settle on the mountain. They had at least two sons, one being Samuel Walton, the father of Zeb and the other, the father of Zadok Walton. Rome and Rebecca Lee raised their children on Waltons Mountain and the family flourished. The work was hard but the evenings were spent with Rome serenading the family with tunes on his fiddle. His favorite tune was Old Rosin the Beau. He would teach this to his young grandson Zadok, who would inherit not only Rome\\'s love of music, but also his treasured fiddle. Zadok would one day pass this treasure on to his cousin Zeb\\'s grandson Jason Walton, who shared in the Walton musical talent.\\nSamuel Walton grew up and married Zula Tyler. They settled on Waltons Mountain and they had at least six children. First was Henry in 1841, then their came sons, Ben, Charlie, Matt and Zebulon Tyler. They also had a daughter Melissa, that Zeb mentions to Jason in a later episode. The name Tyler is mentioned several times in the series, including the episode The Pony Cart, where Martha Corrine mentions the Tylers. Zeb was the youngest in his family. He was a full twenty years younger than his brother Henry. All the Walton sons grew up and inherited their piece of The Mountain. Not all of them stayed there though.\\nHenry fought for the Army of Virginia in the War between the States. He came home and married Martha Corrine Tyler, a cousin on his mother\\'s side. They settled up on Blue Rock Creek. They had two sons, Boone, born the same year as Henry\\'s baby brother Zeb, 1862 and a baby boy, named Henry who died in infancy. Henry Walton died in 1921 at the age of 81. His widow Martha Corrine and his grown son Boone continued to live on Blue Rock Creek Boone married and had a son. There was a flood and Boone lost his son and daughter in law. They raised their grandson Wade after that. Henry Walton\\'s family was forced to move from Blue Rock Creek in 1934, after the Government confiscated their land for the Blue Ridge Parkway. Martha Corrine Tyler-Walton spent the remainder of her years in Brightwood. Martha Corrine died in 1939 at the age of 91.\\nAs for the other Walton brothers, Ben married and moved to Goochland County and it is said, had a large family. Charlie Walton stayed on the mountain but no real mention is made of him except in the episode The Deed, when Zeb talks about Uncle Charlie meeting up with a bear. Matt Walton married and had a daughter Cora, who grew up and married Hamilton Denbee. They had a son, Job and spent many years in Kansas, moving back to Virginia during the Dust Bowl years. They attempted to settle on Waltons Mountain again but ended up going on to New York and farming the Mohawk Valley after learning that Matt Walton had sold his land to his brother Zeb.\\nZebulon Tyler Walton was the youngest son.\\nHe stayed on Waltons Mountain, married a young girl they called Sissy Morgan. Sissy came from a very proper family with a strict Baptist up bringing, which was quite a contrast to Zeb\\'s footloose and boistrous personality. She would pretend to scold but Sissy or Esther which was her Christian name, loved him for it. Even as a young couple, Esther took to calling Zeb \" The Ol Fool\", which had love in every syllable. Zeb and Esther married in 1883, when Zeb was 21 and Esther 17. Esther had wanted to be a seamstress and open her own dress shop but she gave that up to stay with Zeb on the mountain. Their first home was the log cabin on the mountain where Zeb had been raised. They took care of Zeb\\'s folks in their later years.\\nAt some point, Zeb and Esther built their own home at the foot of the mountain. It was a big white two story house and they built it with their own hands. For several years it didn\\'t seem as Zeb and Esther would be blessed with children even though both had hoped for a large family. But finally, in about 1889, their first son Benjamin was born.\\nThey ware over joyed. About two years later, they had another baby but it died at birth. The third and last child of Zeb and Esther Walton was a son born in 1897. They named him John. John would share his father\\'s love of the land and would spend his life on Waltons Mountain\\nIn their early years together, Zeb and Esther built their home at the foot of Waltons Mountain. They built it big because both truly expected to fill it up with lots of kids and in the meantime, they liked lots of company. Zeb came from a large extended family so they always had company. Zeb\\'s brothers and their families aunts uncles and cousins were always welcome guests, not to mention Zeb\\'s mamma and pappa. Zeb was a man who liked excitement.\\nAlthough he was born on Waltons Mountain and always had a love of his family and the mountain itself, he always dreamed of other places and of adventures. Zeb loved hearing the talk of folks moving west and of great battles in long ago wars and the late war between the states that his own brother Henry had fought in. So, it was little wonder in early 1898, when men were being called to serve with Teddy Roosevelt in what would be called the Spanish American War, that Zeb\\'s heart would be stirred once more.\\nSeveral friends of Zebs were going to Cuba and it was all he could talk about. Finally, even though it was against her better judgement, Esther insisted Zeb join up with the Rough Riders and go fight the war in Cuba. She said later she didn\\'t want Zeb to hate her for holding him back and it was with this thought in mind, that she let Zeb go. So off he went to the war in Cuba and Esther and their two boys stayed home on the mountain to await his return. Esther would say she was proud of Zeb for doing his duty but it was the worst time of her life. She learned early on that life could throw you curves but faith would get you through. So, she spent her days working hard and enjoying her boys waiting for word from her Ol Fool and for the day he would come home.\\nThe day did come when Zeb came home from Cuba. It was the Spring of 99 and home he came to his Sissy, his boys Ben and John and his beloved mountain, never to leave again.\\nLife continued on Waltons Mountain, the seasons came and went and Zeb and Esther taught their boys the value of family, work, the land and God. They had many good neighbors in those years, The Baldwins, The Godseys who owned the local Mercantile, the Roswells, Sneads and Brimleys to name a few. There was a lot of activity at the local Baptist Church which Esther stayed very involved in and always a barn raising or some affair the family would attend. Those were truly good years.\\nIt was also during these years that the two boys were growing up. Ben was the oldest and pretty much looked after his brother John and kept him in line for he was a bit on the wild side from time to time, although serious at the same time. John was never much for school or church going. He preferred to working out doors with his pa, going fishing or just taking long hikes up Walton\\'s Mountain. Ben was the more serious student and a very hard worker. He had his mother\\'s sense of work and duty. Although John also had that Walton Work ethic and you could always trust both boys to see a job through to it\\'s end, you could tell Ben was the business man to be, while John was to be a man of the land who liked to have a real good time.\\n*fixed typographical errors & some misspellings.\\n* formerly Zadok, who needed to go tend some apple trees over in Big Spruce\\nLast Edit: Jan 28, 2020 1:04:26 GMT -5 by Johnny - Back to Top\\nsdw\\nsdw-Sharon and her mother\\nHistory of the Walton Family Apr 26, 2019 11:31:19 GMT -5 goldfinch1 and Johnny like this\\nPost by sdw on Apr 26, 2019 11:31:19 GMT -5\\nZadok what branch of The Waltons did Cora Beth Godsey come from. I enjoyed reading what you posted on The history of the Waltons.\\nHistory of the Walton Family Apr 26, 2019 13:01:39 GMT -5 sdw likes this\\nPost by Brenda on Apr 26, 2019 13:01:39 GMT -5\\nThat\\'s a good question sdw . A lot of information about the Walton family can be found on the William Atkins website.\\nHistory of the Walton Family Apr 26, 2019 15:20:58 GMT -5 sdw and goldfinch1 like this\\nPost by Johnny on Apr 26, 2019 15:20:58 GMT -5\\nApr 26, 2019 11:31:19 GMT -5 sdw said:\\nThis is an intriguing question sdw. What do we know about her from the series? She is John\\'s second cousin. S3E16 The Matchmaker. according to William Atkins. That would mean they share the same great-grandfather. John\\'s great-grandfather is Rome Walton. Rome & Rebecca Lee had Samuel, father of Zeb and at least one other son, who was Zadok\\'s father.. By this reasoning, Corabeth\\'s grandfather was a third son of Rome & Rebecca Lee.\\nLast Edit: Aug 15, 2020 3:52:50 GMT -5 by Johnny - Back to Top\\nHistory of the Walton Family Apr 26, 2019 17:07:45 GMT -5\\nPost by Deleted on Apr 26, 2019 17:07:45 GMT -5\\nIs there any record of where the first of the Walton family came from. Were they of Irish, Scottish, Welsh or English?\\nHistory of the Walton Family Apr 27, 2019 12:54:43 GMT -5 Johnny likes this\\nThank you Zadok for answering my question.Brenda I will look at the website you recommend.\\nJessicaGirlSpy\\nI\\' m a Born Again Christian teen. An INFJ. My name is Molly\\nHistory of the Walton Family Apr 27, 2019 14:37:21 GMT -5 Brenda, sdw, and 2 more like this\\nPost by JessicaGirlSpy on Apr 27, 2019 14:37:21 GMT -5\\nSometimes I like to create fictional character histories where I am related to such characters as Bob Cratchit, Mycroft/Sherlock Holmes, Emma Woodhouse. Catherine Morland (just to name a few). And our old tool shed is like the wardrobe from Narnia fame and where fictional characters can become real and visit me at our family ranch in Nebraska. The Waltons can be my distant cousins!\\nKeeper of Jessica Girl Spy\\nI used to be LunaLovegood\\nLast Edit: Apr 30, 2019 7:05:06 GMT -5 by JessicaGirlSpy - Back to Top\\nApr 26, 2019 17:07:45 GMT -5 @josephzebulon said:\\nI can\\'t recall if it was mentioned on the show where the family came from. However Earl Hamner\\'s family did come from Wales. If no one else recalls a specific reference in the series or reunion films and since the Waltons does parallel Earl\\'s life in many ways, if Earl was still with us today, I don\\'t believe he would mind we speculate the Walton family came from Wales too.\\nLast Edit: Apr 27, 2019 15:27:20 GMT -5 by Johnny - Back to Top\\nRebeccaLee\\nHistory of the Walton Family Apr 27, 2019 21:12:09 GMT -5 Brenda likes this\\nPost by RebeccaLee on Apr 27, 2019 21:12:09 GMT -5\\nI wonder how Ester\\'s last name was discovered. I listened I thought very closly and never heard it. Any ideas?\\nPost by carol on Apr 27, 2019 21:50:24 GMT -5\\nI recall Earl saying that many of the people in Schuyler were of Scottish decent which is why they spoke the way they did for\\nexample saying Hoose instead of house. Maybe then The Waltons were of Scottish decent?\\nLast Edit: Apr 28, 2019 13:45:57 GMT -5 by carol - Back to Top\\nHistory of the Walton Family Apr 28, 2019 0:58:18 GMT -5 Brenda and carol like this\\nApr 27, 2019 21:50:24 GMT -5 carol said:\\nI recall Earl saying that many of the people in Schuyler were of Scottish decent which is why they spoke the way they did for example saying Hoose instead of house. Maybe then The Waltons were of Scottish decent?\\nI agree, as a piece of fiction, Earl could have had the Waltons originating from Scotland.\\nMany people who settled along the Blue Ridge were of Scots or Scots-Irish descent.\\nYet if you go to Earl\\'s own webpage it says:\\nThe Hamner family came to Virginia from northern Wales where they had been well established for over a thousand years. In the early 1900s, the Hamner family moved from its James River tobacco farm to the town of Schuyler\\nSo it is equally likely, Earl would have the Waltons be of Welsh descent.\\nLast Edit: Apr 28, 2019 1:38:03 GMT -5 by Johnny - Back to Top\\nHistory of the Walton Family Apr 28, 2019 1:28:41 GMT -5 Brenda likes this\\nApr 27, 2019 21:12:09 GMT -5 RebeccaLee said:\\nI wonder how Ester\\'s last name was discovered. I listened I thought very closely and never heard it. Any ideas?\\nIf you check the William Atkins website, he notes mention of her maiden name Morgan, in the reference A Walton Wedding (1995).\\nHistory of the Walton Family Apr 28, 2019 2:02:38 GMT -5 Brenda, sdw, and 1 more like this\\nPost by Deleted on Apr 28, 2019 2:02:38 GMT -5\\nApr 27, 2019 15:07:48 GMT -5 Johnny said:\\nThanks Zadok.\\nAs I was reading your response a thought came to me, why not Google the origin of the Walton name. Scrolling down the page I found the following.\\nWalton Settlers in United States in the 17th Century\\nJohn Walton, who settled in Virginia in 1623\\nWilliam Walton, who settled in Marblehead, Massachusetts in 1630\\nRichard Walton, aged 21, who arrived in Barbados in 1634 [8]\\nWilliam Walton, who landed in Hingham, Massachusetts in 1635 [8]\\nDaniel Walton who settled in Virginia in 1635\\nHenry Walton, who arrived in Virginia in 1704 [8]\\nSamuel Walton, who arrived in Virginia in 1710 [8]\\nMargeratt Walton, aged 25, who landed in Pennsylvania in 1732 [8]\\nSuggested Readings for the name Walton\\nA Brief Historical and Genealogical Account of the Walton Family by Hattie E. Walton.\\nKith and Kin of Willie Adam Walton and Ethel Mae King by June Roper Walton.\\nThe Waltons of Brunswick County, Virginia By Joe C. Tinney.\\nLast Edit: Apr 28, 2019 2:31:14 GMT -5 by Deleted - Back to Top\\nHistory of the Walton Family Apr 28, 2019 22:14:32 GMT -5 JeriJet likes this\\nApr 28, 2019 2:02:38 GMT -5 @josephzebulon said:\\nThanks for these notes Joe-Zeb. As I was reading through them I was thinking, if they had listed Rome Walton arriving in Virginia in 1789, I would have fallen out of my chair.\\nHistory of the Walton Family Apr 29, 2019 2:24:03 GMT -5 sdw likes this\\nZadock, having done a search on given names I can only find one reference to the name Rome. When I\\'m looking for character names in the stories I write I goto Behind the Name. This is what I found when I entered Rome.\\nI clicked on the user submitted name option\\nI\\'m surprised I didn\\'t use this site to find the origin of Walton. In your post you said, \"if they had listed Rome Walton arriving in Virginia in 1789, I would have fallen out of my chair.\" Look under categories\\nI wonder if Earl found out about this after he\\'d written Spencer\\'s Mountain, could be why the name was changed for the TV series. Makes sense when you think about it. The forest, the spring water hole (Drucilla\\'s Pond), the lumber mill.<s> Bring your leftovers (and puns) to A Rrose in a Prose this Sunday! – A RROSE IN A PROSE REVIVAL!\\nAre you still in a food coma? Or maybe you\\'re sick of your extended family\\'s disapproval, mild racism, and vicious heartburn? Come join OUR literary family, and bring (and/or enjoy) some delicious eats!\\nSo, come for the food, the poetry, the music, and the puns (and did we mention the pun contest is judged by folks as amazing as Anna Ureña (DRYLAND) and Rich Yap (PLANET QUEER)?\\nAnd there will be even more surprises we haven\\'t even told you about, because we\\'re secretive and tricky and evil and stuff. Just like the Puritans.\\nAs always, the event is hosted by D. M. Collins.\\nPrevious Post also at A Rrose in a Prose today: Corey Saucier!\\nNext Post Nikol Hasler returns to A Rrose in a Prose tomorrow!<s> Pacific Coffee Company which originates from Hong Kong has opened up two stores in Malaysia — IOI Boulevard and Pavilion Kuala Lumpur recently. Like its other stores around the world, Pacific Coffee Company don\\'t only provide you free Internet access, but even two or three PC\\'s for those without a laptop to use.\\nPacific Coffee\\'s branch in Pavilion KL is located in Level 2 near the car park and Jaguar showroom. Location-wise, it\\'s quite hard to find. Ambiance-wise, it\\'s quite humid and not an ideal location for a cafe.\\nEspresso Mocha tastes quite chocolaty, unlike the one in Hong Kong. Not sure if it\\'s intentional. The price is similar to Starbucks\\' Frappuccino drinks.<s> The water has Gyumryuk Meydana (Giimriik Meydani), once the started area with old Greek houses and stone warehouses which were quickly and are greatly restored. If hotels of Turkey here and are already occupied on back small streets of the city, it is necessary to continue searches to the south, in the suburb Chamlik where there are some moderate boards with bright signs which are perfectly visible from the road going along the coast. But it is better to use booking of hotels in Turkey. There were cases when local taxi drivers brought tourists in Turkey not to that hotel to which them asked, but rigid, but politely stated wish will help you to allow though what misunderstanding.\\nOur portal offers rounds from Nizhny Novgorod. Rounds to Turkey at the most adequate prices!<s> [08:27] - Flight CVA5613 is ready to depart CYQX with a final destination of CYUL.\\n[09:35] - Landed at -331fpm. With 17610lbs of fuel onboard and a pitch angle of -3deg.\\n[09:36] - Arrived safely at CYUL. We hope you enjoyed your flight!<s> Alphabetical Listing of Databases\\nProvides peer-reviewed, full-text articles from the world\\'s leading journals and reference sources. Covers subjects such as the physical sciences, technology, medicine, social sciences, the arts, theology, literature and other subjects. Coverage is from 1980 - current. Available Online\\nAncestry Library Edition is a genealogical database including census, vital, church, court, immigration, and other records from Canada, the United States, the United Kingdom and other areas. Available Online\\nAudioBookCloud\\nAn online audiobook library collection of streaming audiobooks for children and adults. Listen online. Available Online\\nBiology (Gale Virtual Reference Library)\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: Macmillan Biology 2nd Edition. Available Online\\nA comprehensive database of English-language books, videos, and audiocassettes currently in print or distribution. Lists details needed to order items for purchase (e.g., ISBN numbers). Available Online\\nBrainfuse HelpNow provides resources for students from kindergarten to grade 12, including access to live tutors, live French and Spanish language help, an online writing lab, LEAP learning platform and more! An Adult Learning Centre is also available. Get help with High School Equivalency preparation, the Canadian Citizenship Exam, Microsoft Office, Career Resources and more! Available Online\\nLe service Brainfuse HelpNow offre des resources pour les élèves du préscolaire à la 12e année. Cela inclut du tutorat en direct disponible en français, un service d\\'aide à la rédaction et bien plus! Un centre de formation pour adulte est aussi disponible. Recevez de l\\'aide en français ou en anglais pour la préparation à l\\'équivalence du diplôme d\\'études secondaires et au test de citoyenneté canadienne. Des resources professionnelles comme la rédaction de C.V. et l\\'apprentissage de Microsoft Office sont aussi offertes. Disponible en ligne\\nBrainfuse JobNow provides access to live resume experts, interview coaches and job coaches as well as resume templates, interview tips, skills surfer and more resources for job seekers. Available Online\\nCanada at a Glance\\nThis presents current Canadian demographic, education, health and aging, justice, housing, income, labour market, household, economic, travel, financial, agricultural, foreign trade and environmental statistics. This is an open resource for everyone and not VPL-subscribed. Available Online\\nCanada Year Book Historical Collection\\nDiscover Canada\\'s social and economic past through the people, events and facts that have shaped this vast country. This is an open resource for everyone and not VPL-subscribed. Available Online\\nCanadian Businesses (ReferenceGroup)\\nFind accurate phone-verified information on every company in Canada in this database of 1.9 million businesses. Additionally their files are processed monthly against the National Change of Address Program. Available Online\\nCanadian Encyclopedia\\nThe Canadian Encyclopedia plays an essential role in providing Canadians and others with accurate, updated information about our people and country. This is an open resource for everyone and not VPL-subscribed. Available Online\\nCanadian Reference Centre\\nThis database includes leading Canadian periodicals and international periodicals in full text, full-text reference books, thousands of full-text biographies and an image collection containing more than one million photos, maps and flags. The collection also includes images from Canadian Press. Available Online\\nCanadian White Pages (ReferenceGroup)\\nResearch 11 million Canadian households with the largest database available. Records are 100% publicly sourced to comply with Canadian privacy laws. Available Online\\nCantook Station\\nWelcome to Cantook Station, your HQ for French e-books and e-audiobooks. Cantook Station is a cloud based e-lending service that provides a wide range of materials in French for all ages and all interests. The collection includes books in translation as well as original works in French. To sign in and start borrowing all you need is your library card number and PIN. For more information check out the helpful Get Started Guide and FAQs.\\nBienvenue à Cantook Sation, votre référence pour les livres numériques et audios en français. Cantook Station est une plateforme en ligne qui propose des prêts de matériel numérique francophone pour tous les âges et tous les goûts! Cette collection inclut des traductions et des ouvrages originaux. Pour vous inscrire et commencer vos emprunts, vous aurez tout simplement besoin de votre carte de bibliothèque et de votre NIP. Pour plus d\\'information, vous pouvez consulter le guide de démarrages ou la foire aux questions.\\nChapter-A-Day\\nJoin the Online Fiction, Non-Fiction, Romance, or Business Books Clubs and start reading books in your email. Each day we\\'ll send you a 5-minute portion of a book. By the end of the week, you\\'ll have read 2-3 chapters. If you\\'d like to finish a book, stop by the library and pick up a copy. Every week a new book is featured. Sign up today and start reading tomorrow! (Service provided by Chapter-A-Day.com.) Available Online\\nCLEO (Community Legal Education Ontario)\\nSince 1974, CLEO (Community Legal Education Ontario / Éducation juridique communautaire Ontario) has developed clear, accurate, and practical legal rights education and information to help people understand and exercise their legal rights. Its work focuses on providing information to people who face barriers to accessing the justice system, including income, disability, literacy, and language. This is an open resource for everyone and not VPL-subscribed. Available Online\\nProvides access to current Consumer Reports information. Available Online\\nCoursera is an education platform that partners with top universities and organizations worldwide, to offer courses online for anyone to take, and some courses are free. This is an open resource for everyone and not VPL-subscribed. Available Online\\nDictionary of Canadian Biography\\nA dictionary of biographical entries for individuals who have contributed to the history of Canada. Fifteen volumes have so far been published with more than 8,400 biographies of individuals who died or whose last known activity fell between the years 1000 and 1930. The entire print edition is online, along with some additional biographies to the year 2000. This is an open resource for everyone and not VPL-subscribed. Available Online\\nDictionnaire biographique du Canada\\nLe Dictionnaire biographique du Canada (en anglais Dictionary of Canadian Biography) est un dictionnaire d\\'entrées biographiques sur les individus qui ont contribué à l\\'histoire du Canada. This is an open resource for everyone and not VPL-subscribed. Available Online\\nEdX is a massive open online course and online learning platform. It hosts online university-level courses in a wide range of disciplines to a worldwide audience at no charge. This is an open resource for everyone and not VPL-subscribed. Available Online\\nFrontier Life\\nA collection of documents detailing colonial life in America, Africa, and Australasia by European settlers from 1650 - 1920. Available Online\\nGale Encyclopedia of Alternative Medicine\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: Gale Encyclopedia of Alternative Medicine 4th Edition. Available Online\\nGale Encyclopedia Of Cancer\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: Gale Encyclopedia of Cancer. Available Online\\nGale Encyclopedia of Children\\'s Health: Infancy Through Adolescence\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: Gale Encyclopedia of Children\\'s Health 3rd Edition. Available Online\\nGale Encyclopedia of Environmental Health\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: Gale Encyclopedia of Environmental Health. Available Online\\nGale Encyclopedia of Genetic Disorders\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: Gale Encyclopedia of Generic Disorders. Available Online\\nGale Encyclopedia Of Medicine\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: Gale Encyclopedia of Medicine. Available Online\\nGale Encyclopedia of Nursing and Allied Health\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: Gale Encyclopedia of Nursing and Allied Health 3rd Edition. Available Online\\nGale Encyclopedia Of Psychology\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: Gale Encyclopedia of Psychology Available Online\\nGale Encyclopedia of Surgery and Medical Tests\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: Gale Encyclopedia of Surgery and Medical Tests. Available Online\\nGale Virtual Reference Library\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: Gale Encyclopedia of Cancer; Gale Encyclopedia of Genetic Disorders; Gale Encyclopedia of Medicine; Gale Encyclopedia of Nursing and Allied Health; Scholarships, Fellowships, and Loans, 22nd ed.; and Nonfiction Literature Classics for Students. Available Online\\nHobbies & Crafts Reference Center\\nThis database offers detailed \"how-to\" instructions and creative ideas to meet the interests of virtually every hobby enthusiast. Full text is provided from leading hobby and craft magazines. Note: This site requires a Vaughan Public Libraries Card to sign in. Available Online\\nBorrow free digital video with your library card. Gain access to Hoopla titles - available for instant streaming or temporarily download - and watch on your smartphone, tablet or computer. Note: Now with an additional 4,000+ junior and young adult titles migrated over from OverDrive. Available Online\\nHow Everyday Products are Made (Gale Virtual Reference Library)\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: UXL How Everyday Products are Made 1st Edition. Available Online\\nHuman Diseases And Conditions (Gale Virtual Reference Library)\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: Human Diseases and Conditions 3rd Edition. Available Online\\nKanopy is a video streaming service which offers over 30,000 critically acclaimed films. The selection ranges from new popular titles, classics, world cinema, art and indie as well as top rated documentaries. Your library card will get you started watching on your pc or mobile devices.\\nSign up for a new account via Facebook or Google or using your email.\\nIf you sign up with your email, you will receive an email message asking you to verify your email address.\\nIf you are prompted to find your library, type in \\'Vaughan Public Libraries\\'.\\nClick \"Add library card\", enter your VPL library card number and PIN and click Save.\\nYour Kanopy membership with VPL is now activated and you can start watching.\\nHow to Watch Movies on Kanopy\\nKermode Education\\nKermode uses cutting-edge software and guides to help teachers and students evaluate online content, build media literacy skills, and think critically about all the content they consume online. Available Online\\nL\\'Encyclopédie canadienne\\nL\\'Encyclopédie canadienne, d\\'abord connue comme Encyclopédie du Canada, est une encyclopédie qui se veut « la source d\\'information sur le Canada la mieux fondée et la plus complète ». Disponible gratuitement en ligne, elle est à la fois en anglais et en français et inclut quelque 14 000 articles sur une variété de sujets, notamment l\\'histoire, la culture populaire, les évènements, les personnes, les localités, la politique, l\\'art, les Premières Nations, les sports et la science. This is an open resource for everyone and not VPL-subscribed. Available Online\\nLinkedIn Learning (previously called Lynda.com) gives users free access to thousands of video tutorial courses with a focus on such areas as technology, software development, business skills, project management as well as creative skills like animation and video editing. The courses are taught by recognized industry experts who will guide you along in learning the skills you need for your personal and professional development. How to use LinkedIn Learning\\nMasterFILE Premier\\nDesigned for public libraries, this database provides full text for magazines, reference books and primary source documents. It also includes an extensive image collection containing photos, maps and flags. Available Online\\nMathematics (Gale Virtual Reference Library)\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: Macmillan Mathematics 2nd Edition. Available Online\\nAn online music library containing over 1.6 million streaming audio tracks of classical music, jazz, world, and folk music - more than 100,000 albums\\' worth! Stream on your computer or on your mobile device with the Naxos Music Library (NML) app. Available Online\\nNYTimes.com is a multi-platform news tool that provides full access to New York Times and International New York Times content, including breaking news, multimedia, reviews and opinion, blogs, videos and more. Also available in Chinese and Spanish\\nAccess from Library Computers or Library WI-FI\\nCreate an account with your personal email address, or \"Log In\" if you already have a New York Times account\\nYou now have unlimited access to New York Times articles\\nOut-of-Library Access\\nLog in with your library card number and PIN\\nClick \\'REDEEM\\'\\nYou now have 72 hours out-of-library unlimited access to New York Times articles\\nAn electronic resource that contains materials for all Kindergarten to Grade 8 levels and includes picture books, children\\'s chapter books and young adult titles. Allows young readers and teachers to search titles by favorite author name, title, series name, and theme or topic. Also provides lists of award-winning and recommended books. Includes thematic units for teachers. Available Online\\nAn electronic reader\\'s advisory resource that assists fiction readers in finding new authors and titles. Allow readers to use a favourite author or title as a template to locate other authors and titles of interest. Can be searched by keyword, and offers the option to browse over 1,200 theme-oriented book lists, 160 award lists, and 1,000 fiction-related Web sites. Contains materials for all ages. Available Online\\nCheck out and download eBooks and eAudiobooks using your library card. Note: We have moved all junior and young adult eBooks and eAudiobooks over to Hoopla. Available Online\\nOverDrive Digital Magazines\\nOverDrive offers full colour, interactive digital magazines for your enjoyment. Browse from VPL\\'s collection of popular titles with no holds, and no limit to the number of magazines you can download.\\nRBdigital is now acquired by OverDrive and the platform transfer has completed. Over 3,000 magazine titles are now available in OverDrive and the Libby app.\\nInstant access to 4000 newspapers from 100 countries in 60 languages! The newspapers appear in their original format and original languages. Newspapers are often available before they hit the newsstands in their respective countries. PressReader features archived issues up to two weeks, a magnifying lens / zoom option, bookmarks, and full-text search. Newspapers are organized by country, by language, and alphabetically. Note: The Globe and Mail is only accessible from using PressReader mobile app in the library. Mobile users can install the PressReader app, visit the library and download The Globe and Mail to the app, and then they can read the newspaper at home or on the go. Available Online\\nPrimary Search\\nSearch through a database of popular children magazines, encyclopedic entries, and images to learn about a range of topics geared towards elementary students. Available Online\\nScott\\'s Canadian Business Directory\\nScott\\'s Canadian Business Directory lists Canadian manufacturers, wholesalers, distributors, sales agents and business services providers. This information is updated annually. Available Online\\nSt. James Encyclopedia of Popular Culture (Gale Virtual Reference Library)\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: St. James Encyclopedia of Popular Culture 2nd Edition. Available Online\\nSelf-serve standard products available on the Statistics Canada website ― including CANSIM and census data products ― are now free of charge. This is an open resource for everyone and not VPL-subscribed. Available Online\\nTeenBookCloud\\nTeenBookCloud offers over 600 titles for middle school AND high school! This collection contains a vast array of YA/Teen novels, classics, poetry, short stories, YA/Teen audiobooks , popular graphic novels, and world class educational videos from National Geographic. Available Online\\nToronto Star (ProQuest Historical Newspapers)\\nFormerly known as Pages of the Past. The online archives of the Toronto Star dating from 1894 until the new millennium. Millions of pages available for genealogical or historic research from the pages of one of Canada\\'s most prestigious Newspapers.\\nNote: After you login with library barcode and PIN, you will need to input your barcode again to access the content. Available Online\\nTransparent Language\\nWelcome to Transparent Language Online, radically better language learning in one complete experience. Available Online\\nBienvenue chez Transparent Language Online, le meilleur endroit pour apprendre une nouvelle langue. Disponible en ligne\\nTumbleBook Library\\nTumbleBook Library offers animated, talking picture books for kids. Read and listen along! Available Online\\nTumbleBookCloud Junior\\nWith over 600 titles and reading levels from grades 3-8, TumbleBookCloud Junior is a great option for adventurous young readers who wish to go beyond the picture book collection in TumbleBookLibrary! TumbleBookCloud Junior contains early reader chapter books, children\\'s classics, graphic novels, children\\'s audio books and new National Geographic videos - many of which are paired with our e-books - a perfect complement to support Common Core Curriculum! Available Online\\nUS Jobs / Internships (ReferenceGroup)\\nCombine the power of the premier business reference and research tool, ReferenceGroup, with the world\\'s #1 job site, indeed.com. Find your next job with our state-of-the-art mapping tool and view results with detailed business profiles. Available Online\\nUXL Encyclopedia of Science (Gale Virtual Reference Library)\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: UXL Encyclopedia of Science. Available Online\\nUXL Encyclopedia Of Weather And Natural Disasters (Gale Virtual Reference Library)\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: UXL Encyclopedia of Weather and Natural Disasters 2nd Edition. Available Online\\nUXL Endangered Species (Gale Virtual Reference Library)\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: UXL Endangered Species 3rd Edition. Available Online\\nUXL Sustainable Living (Gale Virtual Reference Library)\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: UXL Sustainable Living 1st Edition. Available Online\\nUXL World Eras (Gale Virtual Reference Library)\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: UXL World Eras 1st Edition. Available Online\\nWorld Book Online for Kids\\nThis database works with Google Chrome only. Developed especially for young public library patrons, the site offers simple navigation, easy-to-read articles, multimedia, and a wealth of engaging games, interactive tools, and activities. Available Online\\nWorld Of Forensic Science (Gale Virtual Reference Library)\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: World of Forensic Science 2nd Edition. Available Online\\nWorldmark Encyclopedia Of the States (Gale Virtual Reference Library)\\nProvides access to specialized reference sources that used to be only available in library. eBooks available in this collection are: Worldmark Encyclopedia of the States 8th Edition. Available Online\\nYIVO Encyclopedia of Jews in Eastern Europe\\nThe encyclopedia provides the complete picture of the history and culture of Jews in Eastern Europe from the beginnings of their settlement in the region to the present. This is an open resource for everyone and not VPL-subscribed. Available Online\\nBrowse Databases in Categories<s> Hey guys! Welcome to the new Mistakes of Youth site, now powered by WordPress! This changeover probably isn\\'t of much relevance to you readers, but it certainly makes my life a lot easier when it comes to updating. For a while now I was doing it all manually, but with the comic now completely integrated into WordPress, I won\\'t have to open up Dreamweaver each time I want to update. Isn\\'t that swell?\\nAlso, this change in the comic will mark a change in approach. For a while I was keeping up a weekly schedule, but now I\\'m just going to update when I can. This is because I really want each comic to be the best I can make it, so to that end I won\\'t rush things out. I mean, it\\'s not like I\\'m getting paid, right? So there\\'s no point in rushing. But with that said, it\\'s probably more realistic to expect comics every two weeks as opposed to every week. That\\'s how it\\'s been for a while now anyway, so you should be used to it.\\nAt first this switchover was going to reflect my move to Japan with the characters going back to Japan as well. But since things are a little dicey over there at the moment, I\\'m still in the States.\\nNot much else to say. If you want to read the old comics, they\\'re online at http://old.mistakesofyouth.com. Hope you enjoy the new site!\\nYou need to place the RSS feed link someplace more obvious on your sidebar. Firefox 4 now no longer has an RSS subscribe button on the main toolbar.\\nYou gotta be kiddin\\' me! Will fix it.<s> We are successful funded crowdfunding project. We are constantly striving for perfection throughout the creative process of producing our watches which transmit an inherent British identity.\\nElegant unisex design, ideal on smart and casual occasions.<s> Trade Candidates: The Position Players\\nby David Lesky July 20, 2016\\nYesterday, I took a look at the starting pitchers on the trade market who the Royals could look to acquire. I think that\\'s a bigger need than an outfielder or any other position player, but given that they\\'re reportedly in the market for both, it\\'s a good idea to take a look at both sides to see what else is out there. Up until a few days ago, I couldn\\'t see them acquiring an infielder because they seemed happy with what they\\'ve gotten from Whit Merrifield and are definitely happy with the contributions from Cheslor Cuthbert. Now, after Merrifield sat over the weekend, I\\'m not so sure. Anyway, without further ado, here\\'s a look at the position players the Royals could be looking toward on the trade market this month.\\nCarlos Beltran – This would be a pretty good story at the very least. There\\'s been rumors of Beltran\\'s return to the Royals since the offseason he signed with the Yankees, and there\\'s even more stories now about him coming back next year to take over the DH role. For now, though, the Royals have a need in the outfield where Beltran technically plays. His defense isn\\'t what you\\'d call good, which is kind of sad because we still remember him as one of the better center fielders, but he can stand out there, which is nice. He doesn\\'t work a walk like he used to, but he still has legitimate power and he\\'s not just a creation of Yankee Stadium. He hasn\\'t hit as many home runs away from there, but he\\'s hit well. This one makes some sense as he\\'s a pending free agent. He is owed about $7 million the rest of the year, so that may be an obstacle for the Royals.\\nCharlie Blackmon – It seems like Blackmon has been on the market for about 10 years, but that\\'s simply not true, so stop thinking it. He can hit, he can play a serviceable center field (but I think he\\'d be better in a corner in Kansas City) and he can give you some pop. There\\'s always a concern with Colorado guys, but Blackmon doesn\\'t have as big of a home/road split this year as you\\'d probably expect. He\\'s currently in his first year of arbitration and is owed a little more than $1.5 million the rest of this year before he has two more arbitration years coming up. My guess is those will cost about $16 million, but he could also be traded again. I think he\\'s going to cost a lot, but he could fill a void the Royals have had in right field for awhile and fill it for the next few seasons.\\nJay Bruce – This is another guy who has seemingly been on every trade list for years. He almost got traded before the season, but it was nixed by a bad physical by Michael Saunders. All Bruce has done is turn in one of the best offensive years of his career. He\\'s never going to be mistaken for a batting champ, but he\\'s hit much better this year and that\\'s made his OBP worthwhile. He doesn\\'t walk that much, but he does strike out less than you\\'d think (still a fair amount). One thing I liked about him last year that I like about him again is that he doesn\\'t make that much soft contact. I almost wonder if he\\'d be a better hitter in a bigger park because he has enough power to hit it out of every park. Getting some deeper gaps might help him out. It won\\'t help him defensively, though the scouting reports and the metrics disagree on Bruce. He\\'s owed about $6 million the rest of this season and there\\'s a $13 million option for next year. He\\'ll be in demand. This is a fit that I don\\'t think looks as good on paper as it would on the field, but I also think it\\'s a longshot given Bruce\\'s popularity in this market.\\nKole Calhoun – I\\'m not even sure if Calhoun gets traded, but as I mentioned when going over the pitchers, the Angels really need to regroup their farm system. Dealing Calhoun would make some sense, though it would probably weaken them even more than they\\'d prefer while they still have that Trout guy. Calhoun is a little like Alex Gordon. He plays excellent defense (in right field, though), works a walk and has some power. He doesn\\'t strike out quite as much as Gordon and he\\'s a few years younger, but they\\'re kind of similar to me. He\\'s due to make about $1.5 million the rest of this year and then has three more years of arbitration, so he won\\'t be cheap, costing presumably about $22-$25 million over those three seasons, but given the control, I\\'d be willing to give up a fair amount for Calhoun than some of the other rentals.\\nKhris Davis – I mentioned Davis before the season and before he was traded to the A\\'s, and here he is again. The game is power and that\\'s really about it. He doesn\\'t hit for much of an average and he doesn\\'t walk very much. But he does hit for power. Did I mention he has power? This is not a great option. He\\'s only played left field in the big leagues, and he doesn\\'t play it well. If anything, this would be a situation where the Royals could look to him to hold down right field and then shift to the DH spot next year. The A\\'s gave up a couple decent prospects to get him and would likely want at least that in return, which I don\\'t think is worth it personally.\\nCarlos Gonzalez – Here\\'s probably the best position player on the trade market, so that immediately puts the Royals at a disadvantage, though if the Rockies find themselves especially keen on someone like Jorge Bonifacio, I could see a deal finding its way to the surface. Coors Field makes Gonzalez a monster, but that doesn\\'t mean he isn\\'t a good player outside of there. He plays quality defense and can still hit enough to make a difference. The power doesn\\'t play nearly as well outside of Coors, but I still think he\\'s probably a 16-22 home run guy away from that great environment. He\\'s not cheap. He\\'s owed around $8 million the rest of this year and $20 million next year. I don\\'t see the Royals paying that or giving up a different prospect to get the Rockies to pay some of it, but he\\'s available, so here he is.\\nBrandon Guyer – I\\'m not a fan, but if the Rays are open for business, Guyer will draw some attention. He\\'s not especially good defensively and he\\'s not much of a hitter, but he gets on base using the skill of getting hit by a pitched baseball. I would imagine acquiring Guyer would be with the hopes of catching lightning in a bottle and him getting hot at the right time. Also, he probably wouldn\\'t cost too much to pick up. Plus, he actually does hit lefties very well, so that could be a fit for him with the Royals. He\\'s owed a bit more than $500k the rest of this year and then has two more years of arbitration. I could see a fit, I guess, but it would be a pretty meh acquisition.\\nNick Markakis – This right here might be my least favorite name on the list for the Royals to acquire unless it comes at basically no cost. He works walks, but that\\'s pretty much it at this point in his career. It\\'s not that the skill of working a walk isn\\'t valuable, but the Royals need more than that. This year, his average has plummeted and he still doesn\\'t have any power. Plus, he\\'s not especially good defensively anymore, and he is owed about $27 million more through 2018. Please don\\'t do this, Royals.\\nSteve Pearce – I wanted the Royals to sign Pearce as a platoon partner for Jarrod Dyson back in the winter, but they didn\\'t listen. He\\'s currently on the disabled list with a hamstring strain, but he was hitting .322/.393/.540 before getting hurt. Pearce can play outfield, first base and even a little second. You probably don\\'t want him playing second too often, but with his stick, against a good lefty, that could be worth it. Yes, he crushes lefties. He\\'s hitting .383/.473/.766 against them in 55 plate appearances. He\\'s just on a one-year deal and is owed a bit more than $2 million the rest of the way, but he could be a really nice fit.\\nJosh Reddick – I\\'m not sure a more perfect player has ever existed at the trade deadline for a team than Reddick for the Royals. They\\'re on the lookout for a lefty-hitting outfielder. Well, Reddick plays excellent defense in right field, hardly ever strikes out and actually works walks. He has power, but not as much as you\\'d probably like from your right fielder. Basically he\\'s about the best Royals fit in baseball and he doesn\\'t even play for the Royals. He\\'s also only owed a bit north of $3 million the rest of the season. That\\'s not to say he\\'s a perfect player. He really struggles against lefties and he\\'s already dealt with an injury this season. Still, picking up Reddick and slotting him into the second spot in the batting order could do wonders for this lineup. He\\'s a free agent after the season, so the cost may not be prohibitive, but he\\'ll also be coveted by many teams. This one is very interesting to me.\\nRickie Weeks – He was once a very good offensive second baseman for the Brewers, but fell on really hard times defensively and his offense declined to make him basically not playable at second. Now he\\'s an outfielder and after a rough go of it last year, he\\'s really picked things up and is now hitting decently for the Diamondbacks in a reserve role. The bad news is that his defense is pretty terrible. I don\\'t even think he\\'s a real option, but he\\'s owed next to nothing and the Diamondbacks would probably deal him, so why not include him?\\nGordon Beckham – You want a second baseman? This could be the best fit out there for the Royals. Beckham never really found it with the White Sox after a promising debut, but he\\'s doing a nice job in a utility role for the Braves. He works a walk, doesn\\'t strike out a ton and plays a decent second base. I\\'m not convinced he\\'s actually better than Merrifield, but he\\'s having a better year and is super cheap. I think he\\'d be a benefit to the Royals and can\\'t cost much in the way of prospects or money as he\\'s owed well less than $1 million the rest of the season.\\nAndres Blanco – Remember when Blanco was considered the shortstop of the future for the Royals and he was in the big leagues at the age of 20? Somehow he resurfaced with the Phillies a couple years ago and has been a valuable utility player for them. He\\'s seen time at every infield position and a little in the outfield as well. He\\'s not having nearly as good of a year offensively as he did last year and he\\'s not the defensive wizard he was coming through the Royals system, but he might be a nice fit as a utility guy in Kansas City. He\\'ll be a free agent after the season and isn\\'t making much money. Keep an eye on this one.\\nZack Cozart – This is an admittedly imperfect fit, but I\\'ve heard some things about the Royals having interest. Cozart is a fantastic defensive shortstop with some power that would actually play at Kauffman Stadium (just not as well as in his home bandbox, though he has more homers on the road). The reason it\\'s imperfect is that the Royals have a shortstop already and neither Cozart nor Escobar has much experience at second base, if any. Still, Cozart would add to the Royals lineup, so if they feel comfortable with moving one of the shortstops to the other side of the bag, they could have something. He\\'s signed cheaply this year with a little less than $1.5 million remaining and then has a year of arbitration left before hitting free agency. The demand for him isn\\'t as high as I would have thought, but he\\'s a solid player, so he won\\'t be able to be acquired cheaply. I don\\'t see it happening, but it\\'s an interesting name to think about.\\nDaniel Descalso – I\\'m not spending much time on this. He\\'s not especially good in any facet, but he\\'s hitting well this year and can play multiple positions. And he\\'s cheap. So there\\'s that.\\nYunel Escobar – The Royals don\\'t really need a third baseman or a shortstop and Escobar hasn\\'t played second base since 2007, but I\\'ve heard his name mentioned. He\\'s had a really nice season and does have a history with Dayton Moore as he was a part of the Braves organization way back then. If you feel comfortable putting him at second for two months, he could be a fit. I wouldn\\'t personally feel comfortable, but a guy who has hit well over .300 with a .370+ OBP since the start of last season isn\\'t something to turn your nose up at if he becomes available. He\\'s owed a little more than $3 million the rest of this season, though some of that is paid by Washington. He has a team option for $7 million next year. I don\\'t think he would require a huge haul, but I\\'m not sure why the Angels would trade him unless they get an offer that\\'s more than he\\'s worth.\\nJed Lowrie – You\\'re not acquiring Lowrie for his defense, but he can really help a lineup out. He\\'s a quality hitter who will work a walk. Strangely, his power has somewhat disappeared this year. He plays a nearly competent second base, but the offensive upgrade is something that I think would be well worth the risk on his defense. He\\'s owed about $3.5 million more this year and then is owed $6.5 million next year with a team option for $6 million. He\\'s not the perfect player for the Royals, but he could hold down second base for the rest of this year and into next year until Mondesi is ready when he can be used as trade bait again.\\nEduardo Nunez – This has been a breakout season for Nunez that hasn\\'t exactly come out of nowhere. It was easy to miss this last season, but Nunez was solid for the Twins last year as well. I\\'m not sure there\\'s a great fit here because he doesn\\'t play much second base, but if he could, this would make some sense. He doesn\\'t walk much, but he doesn\\'t strike out hardly at all either. He has tons of speed, so he might fit perfectly at the top of a Need Yost lineup. He\\'s very cheap and will be entering his final year of arbitration next season, so the Twins don\\'t have to move him because the return likely won\\'t be fantastic anyway, but he could be a fit.\\nYangervis Solarte – I don\\'t think anyone could have predicted that Solarte would have the season he\\'s had for the Padres. He\\'s played mostly third, but he has manned second a little bit this season. He\\'s not going to remind anyone of Roberto Alomar, but he isn\\'t going to kill you either. He can work a walk and doesn\\'t strike out much. He\\'s even developed a little power. He\\'d actually be a near perfect fit for the number two spot in the batting order, but could moonlight as a leadoff man. I think the Padres would ask a lot as he isn\\'t even arbitration eligible until next season. He did just turn 29, so there isn\\'t much additional upside, but he could be a nice plug and play option for the Royals for the next few seasons and, like Lowrie, give them a trade chip if everything works out with the guys already in the organization.\\nTags: Andres Blanco, Brandon Guyer, Carlos Beltran, Carlos Gonzalez, Charlie Blackmon, Daniel Descalso, Eduardo Nunez, Gordon Beckham, Jay Bruce, Jed Lowrie, Josh Reddick, Khris Davis, Kole Calhoun, Nick Markakis, Rickie Weeks, Steve Pearce, Yangervis Solarte, Yunel Escobar, Zack Cozart |\\nDavid Lesky\\nFollow @dblesky\\nI\\'ve been a Royals fan since the day I was born, and have had the opportunity to write about the Royals for nearly a decade now. The winning was better than the losing, but the losing is kind of familiar at least.\\nread more from David Lesky\\n1 comment on \"Trade Candidates: The Position Players\"<s> Clout Street\\nCHICAGO TRIBUNE\\'S LOCAL POLITICAL COVERAGE\\n« Daley pressures CTA unions for concessions as service cuts loom Sunday | Main | Ex-Gov. Rod Blagojevich re-indicted on political corruption charges »\\nQuinn\\'s running mate says he has \"no intention of stepping down\"\\nUpdate by John Chase at 8:08 p.m.\\nWhile many Democratic leaders are suggesting Scott Lee Cohen consider stepping down as the party\\'s lieutenant governor candidate U.S. Senate nominee Alexi Giannoulias is calling for Cohen to exit the race.\\n\"These are disturbing allegations,\" he said in a prepared statement. \"Domestic abuse has no place in our society much less in public office.\"\\nUPDATE by David Heinzmann at 6:57 p.m.\\nScott Lee Cohen vowed to stay in the race for lieutenant governor today, saying he has shown honesty and courage that will bolster the Democratic Party\\'s chances in November.\\nAcknowledging that he behaved badly while taking anabolic steroids in 2005 when his marriage broke up, Cohen said he understands why his past has caused a firestorm within the party. As of Thursday evening no other politicians had contacted him to ask him to step down, he said.\\nIf they do, he won\\'t.\\n\"I\\'m going to respond that my honesty and integrity in putting it out there is the best thing that could happen to the party,\" Cohen said in an interview with the Tribune, part of an effort to respond to growing calls among Democrats that he step aside and not risk dragging down Gov. Pat Quinn, his running mate in the general election.\\nCohen did not deny choking his wife, as she alleged in the divorce, but said he had no recollection of it, and it actually took place before they were married.\\nHis ex-wife, Debra York-Cohen, was with him today and said she stood by the allegations in the divorce but said his philandering and volatile behavior took place during a brief period time when he was using steroids. The allegations included him frightening their four children and threatening her verbally and physically.\\n\"It was a short period of time, and it\\'s certainly not something that the people of Illinois need to be concerned with,\" York-Cohen said.\\nUPDATED AT 6:22 p.m. with Cohen\\'s media blitz, divorce records.\\nThe Chicago pawnbroker who won the Democratic nominee for lieutenant governor ramped up a media campaign this evening to defend himself in the face of growing pressure from party regulars to drop out as Gov. Pat Quinn\\'s running mate.\\nQuinn suggested Scott Lee Cohen should quit rather than risk dragging down the Democratic ticket in scandal over his background, including his 2005 arrest on misdemeanor domestic battery case involving an ex-girlfriend with a prostitution conviction. Other leading Illinois Democrats called on Cohen to quit, while acknowledging there may be little they can do legally to make it happen.\\nCohen said he had no intention of dropping out and was the victim of false allegations. But as Cohen sought to set the record straight, with his ex-wife at his side for media interviews, the records from his 2005 divorce case portrayed a troubled marriage.\\nIn the divorce records, Cohen\\'s ex-wife accused him of using illegal drugs, rages and abusive behavior, including choking her.\\n\"Over the past year my husband has been taking injectable anabolic steroids, including but not limited to Winstrol, Cretin, and Steen, and as a result he has an erratic, explosive temper,\" Cohen\\'s ex-wife, Debra York Cohen, said in a petition for an order of protection. She described rages at their children, his admission to several affairs, and alleged he tried to force himself on her sexually.\\nCohen responded to some of the allegations in his petition to visit his children during the couple\\'s separation.\\n\"Although I may have taken steroids and or performance enhancing drugs in the past I have not utilized any of these drugs in the last two weeks … Although from time to time I have screamed and yelled at my children, that is my parenting style and my prerogative. I have never abused my children, I have never hurt my children and I have never done any harm to them,\" Cohen said, according to the records.\\nThe divorce records contain a judicial order for Cohen to submit to periodic urine tests for drugs including steroids and other controlled substances. The divorce records also indicate money problems for the couple.\\nThe record contains a Sept. 8, 2006 letter from a mortgage company demanding $23,557.26 for unpaid payments on a $650,000 mortgage for the couple\\'s Northbrook home. The letter threatens foreclosure.\\nPosted by Monique Garcia, John Chase and Michelle Manchir at 12:05 p.m.; last updated at 3:37 p.m. with John Schmidt talking about 1986\\nThe Democratic nominee for lieutenant governor issued a statement today saying he has no intention of dropping out of the race, just hours after Gov. Pat Quinn said the Chicago pawnbroker should consider stepping aside for the good of the party\\'s ticket.\\nScott Lee Cohen said he wants his ex-girlfriend to talk about her prior complaint against him, which resulted in his 2005 arrest.\\nHere is the statement, issued through the public relations firm that assisted his campaign.\\n\"I have no intention of stepping down or stepping aside. When the facts come to light, after my ex-wife and ex-girlfriend speak, the people of Illinois can decide, and I will listen to them directly. I am asking my ex-wife and ex-girlfriend to come forward and to talk with the media.\\nThere are questions, and I will provide all answers honestly and openly. I only ask for time to do the interviews. 2005 was a difficult time in my life. I was going through a divorce, and I started running with a fast group. I was in a tumultuous relationship with the woman I was dating. We had a fight, but I never touched her. She called the police, however, she never came to court, and the charges were dismissed. I realized this relationship was not healthy, I ended it, and we parted amicably.\"\\nCohen then released a second statement: \"I tried to tell everyone about this early on. I wanted to talk about all of these issues, but everyone wrote me off, and said I didn\\'t have a chance to win. Now that I\\'m the Democratic nominee for Lieutenant Governor, the day after the election, there are questions. I am happy to answer any and all questions; I just need time to do so.\"\\nCohen\\'s statements came after Quinn said today that his new running mate should consider withdrawing from the race because his background could hurt the Democratic ticket in the November general election.\\nCohen \"has an obligation to step aside\" if his past becomes a problem, Quinn said at a news conference.\\n\"I do believe that the person who\\'s had these matters brought up about himself should at least have a chance to talk about them to the public, but if his explanations are unsatisfactory, and so far they have been, then he has to do the appropriate thing,\" Quinn said.\\n\"Our country and our state are bigger than ourselves. The Democratic Party is bigger than me or any other candidate. If there are matters that are raised about your conduct that disqualify you from running in a proper way for an election in the fall, then the only appropriate thing is to step aside. And I think that\\'s what we\\'re looking at here.\"\\nQuinn did not say Cohen\\'s name once during the hour-long news conference.\\nQuinn also said he has spoken with Michael Madigan, the Illinois Democratic Party chairman and House speaker, about the process for finding a new lieutenant governor nominee should Cohen step down.\\n\"In those circumstances, then the state central committee has to come together and they have to select a replacement,\" Quinn said. \"Any of those who are interested in vying for something will have to wait.\"\\nQuinn also was asked if knew about Cohen\\'s problems beforehand.\\n\"No one in my campaign staff told me anything about it and I don\\'t think anybody knew about it, at least I didn\\'t,\" Quinn said. \"I had no idea of these matters and I learned reading the papers, watching TV. I consider them very, very serious and grave matters. I think any citizen would feel the same.\"\\nQuinn said it was not the job of the Democratic Party to vet Cohen, but rather the job of the voters.\\nWhile governor and lieutenant governor candidates run separately in the primary, some candidates pool resources and campaign as a team. The idea is that a governor candidate doesn\\'t want to get stuck with an undesirable running mate in the fall. Among Democrats, neither Quinn nor Hynes took a lieutenant governor candidate under their wings. On the Republican side, governor candidate Andy McKenna teamed up with lieutenant governor candidate Matt Murphy for campaigning purposes.\\nDemocrats might pressure Cohen to drop out, but it\\'s doubtful that they can outright force him off the statewide ticket as state law now exists. Democratic voters elected Cohen Tuesday after spent more than $2 million of his own money on his lieutenant governor bid. Cohen bested five other candidates, including some state lawmakers.\\nElection attorney Burt Odelson, who worked for Adlai Stevenson III\\'s gubernatorial campaign in 1986 when he was paired with an acolyte of political extremist Lyndon LaRouche, said there is nothing in the election law that would allow Quinn or the Democratic Party to force Cohen off the ballot.\\n\"The Democrats and the Republicans are locked in,\" Odelson said. \"The governor and the lieutenant governor are tied together.\"\\nThe only way they can be split, Odelson said, is if Cohen withdraws or Quinn withdraws and formulates a separate party, like Stevenson did in the 1986 campaign he eventually lost.\\n\"This is a very unique situation. It\\'s another chapter in Chicago and Cook County and Illinois history,\" Odelson said.\\nJohn Schmidt, who was one of Stevenson\\'s attorneys in 1986, said he finds the situation Stevenson faced 24 years ago to be very similar to the Quinn is facing today.\\n\"Stevenson decided there was no way you run for governor and say vote for me and oh, by the way, you also should vote for this other guy,\" Schmidt said. Although they looked into trying to find ways to force LaRouche follower Mark Fairchild off the ballot, they discovered they couldn\\'t. So Stevenson eventually decided to withdraw as the Democratic nominee and launch the Solidarity Party.\\n\"Short of him talking Cohen into stepping down...I don\\'t see how you can run with him given what we\\'ve known,\" Schmidt said. \"A guy who was arrested for holding a knife to a woman\\'s neck?\"\\nAny efforts to try to pass a law in the General Assembly to negate the primary results, he said, \"would be unconstitutional on its face.\"\\n\"After you\\'ve been through a process to say we don\\'t like the guy who won and try to change the law? That just doesn\\'t work,\" he said.\\nHe said Quinn\\'s best defense from this hurting the Democratic ticket is for him to be clear with voters.\\n\"There\\'s a lot to be said with standing up and saying either Cohen gets off the ticket or I will run as an independent,\" Schmidt said.\\nQuinn was faced with the new crisis even as his rival, Dan Hynes, announced he was conceding the Democratic primary nomination for governor.\\nCohen, a pawnbroker who was the surprise winner in the little-publicized contest among half a dozen candidates, had previously disclosed his 2005 arrest. He described it Wednesday as an argument with his drunken girlfriend and said he didn\\'t lay a hand on her, though she called the police and had him taken into custody.\\nBut the official police and court records show that the woman alleged Cohen put a knife to her throat and pushed her head against the wall.\\nIn their October 14 arrest report detailing the complaint from the 24-year-old woman, Chicago police noted they observed \"mild abrasions from knife wound\" on her neck. They also noted \"minor scars on her hand from her trying to defend herself against the arrestee swinging the knife at her.\" The report notes the woman was seen by ambulance personnel but not taken to a hospital.\\nThe case was dropped a month later when the woman did not show up for a court date.\\nCohen won in large part because his self-financed campaign ran TV commercials late in the race showing him running job fairs to help the unemployed. He only garnered 212,900 votes but it helped him defeat opponents, including state Rep. Art Turner and state Sen. Terry Link.\\nA little more than a year after former Gov. Rod Blagojevich\\'s removal, the state\\'s Democratic powerbrokers focused much of their time, energy and money on the top tier race of governor, leaving the less-known lieutenant governor\\'s race to go well under the radar.\\nThe lack of a Democratic cohesive strategy leaves the party unclear of its options for the general election.\\nIt also adds yet another punchline on Illinois politics, which has been the focus of national jokes and derision since Blagojevich\\'s high-profile arrest, impeachment and indictment.\\nIn conceding the race this morning to Quinn, Hynes was asked how he\\'d feel if he had won and been paired with Cohen.\\n\"The first I learned of any of this was when I read the paper this morning,\" Hynes said. \"But we\\'re going to let that sort itself out, and figure out, you know, with more information. I think that some decisions will be made. But I\\'m not in a position to make those decisions, given the fact that I just learned about it this morning.\"\\nCohen is scheduled to appear on WTTW\\'s \"Chicago Tonight\" at 7 p.m.\\nIllinois Secretary of State Jesse White, who would have to appear on the statewide ticket this fall with Cohen, echoed Quinn\\'s comments.\\n\"We would agree with the governor that Mr. Cohen needs to explain himself,\" White said in a statement. \"He needs to address these issues, and if he can\\'t adequately, then he should consider strongly getting out.\"\\nPosted at 12:05:12 PM in 2010 Illinois election, 2010 Illinois Governor\\'s race, 2010 Illinois Lieutenant Governor\\'s race\\nIt\\'s just so sad how ineffective the Tribune endorsements are. Here\\'s some advice to all future candidates...DO NOT SEEK THE TRIBUNE ENDORSEMENT!!!!! It is the kiss of death!\\nPosted by: Mike S. | February 04, 2010 at 04:10 PM\\nI actually started to laugh out loud when I read a post by someone who said that it\\'s time to clean up Illinois and the Republicans are going to do it... hmmm, I seem to recall a not-so-distant past republican governor who is doing some jail time. The Illinois issue is deeper than democrat or republican. Corruption knows no bounds. Citizens have to stop pointing left or right and start pointing left AND right. I wish we had decent news outlets in this country who did truly investigative reporting and helped the public vet these candidates. We can\\'t count on the parties to do it.\\nPosted by: Don | February 04, 2010 at 04:05 PM\\nSo, exactly how can anyone \"prove\" their innocence in a situation like this? Everyone is speaking as if the allegations were fact. The FACT remains that he was not found guilty of the crime. As far as I\\'m concerned, the issue is closed.\\nANY political outsider is better than the crooks we have had running the government already. Let him have a chance. I hope he wins the seat.\\nPosted by: Ken | February 04, 2010 at 04:03 PM\\nMaybe Springfield will finally realize that separate elections for Gov and Lt Gov should be done away with and candidates should be allowed to pick their running mates. Or, better yet, maybe they could just go ahead and eliminate the position altogether as it serves no purpose whatsoever.\\nAnyway, tough year to be a Democratic voter in Illinois... not only did we have two less than stellar choices for Governor but no we have all but handed the Governorship to the GOP... I\\'m a Dem but even I can\\'t vote for this ticket (so, who\\'s the Green party candidate? They\\'ll likely be getting my vote in November).\\nPosted by: Bruce | February 04, 2010 at 03:59 PM\\nI wouldn\\'t hold this against him if its a one-time thing without a conviction. If the cops are called on a DV incident, they say they must arrest if they see a bruise or scratch. My ex was mad because my son liked my new GF back in 1996. She was screaming and scratching as I defended myself and my property. Cops were called and we were both arrested, and taken to the station where we cooled off. No problems like that before or since, and now we\\'re on good terms and help each other out. I\\'d ask her to speak for me anytime. But I\\'m sure if I ever ran for office, this would be dredged up.\\nPosted by: Mike V | February 04, 2010 at 03:56 PM\\nAs former Governor Rod \"Elvis\" Blagojevich would say, this is bleeping golden!\\nPosted by: joanie2112 | February 04, 2010 at 03:55 PM\\nPerfect. On the other hand it will be great watching a republican try to deal with a $14Billion dollar deficit without raising taxes or cutting services.\\nPosted by: Paul Randall | February 04, 2010 at 03:48 PM\\nThat\\'s someone we need in office - a guy who can\\'t figure out his girl friend is a prostitute.\\nPosted by: RichF | February 04, 2010 at 03:46 PM\\nCohen spent $2M of his own money for the campaign. He probably isn\\'t going anywhere. Since Quinn thinks it isn\\'t the parties job to vet candidates, he deserves to be stuck with him.\\nI bet that Dan Hynes is having the last laugh today. Hope he tries again in four years if Governor Brady doesn\\'t work out.\\nLook at the big picture- The Republicans don\\'t earn their keep. All they do is put their big feet in the door. When we go to work , we have to work or lose our jobs. Why would anyone vote for another Rebublican who put 98% of the American people in the poor house! How quickly do we forget the horrors of poverty? Let\\'s vote for someone who will help the American people .\\nPosted by: Bonnie | February 04, 2010 at 03:41 PM\\nUntil Illinois has Gov and Lt Gov run as a ticket, this kind of disaster is just waiting to happen. Not Quinn\\'s fault. Adlai Stevenson would have made a great governor, but had to start a third party to disavow LaRouche. Why? Nobody cares who the Lt. Gov is. Did anyone care about Quinn? Hooda thunk?\\nPosted by: WILLOBIE | February 04, 2010 at 03:37 PM\\nFurther proof that the two-party system, at any level, is a failure. We simply need more, and better, choices.\\nPosted by: Austin | February 04, 2010 at 03:36 PM\\nQuinn is always talking the person with the most votes wins so Cohen won the most votes so he should stay. Everyone has to live with their mistakes. The people of Illinois voiced their say and Quinn is always saying he wants what the people want\\nPosted by: CJ Howe | February 04, 2010 at 03:35 PM\\nI think it is somewhat inappropriate to refer to Cohen as Gov. Quinn\\'s \"running mate,\" as he was not his running mate in the primary. While Cohen is Gov. Quinn\\'s running mate for the general election, your title would imply Quinn had a role in his selection up to this point, which is not the case whatsoever with a separately-elected Lt. Governor. Your headline is misleading.\\nPosted by: Dan | February 04, 2010 at 03:31 PM\\nPROVES that Mike Madigan and the rest of the Democrats have ZERO IDEA what\\'s going on. NICE JOB Dems - you\\'re proving how idiotic you all are... maybe Drew Peterson will run for Democratic office soon and you can vote for him too... Duh....\\nPosted by: Chris | February 04, 2010 at 03:27 PM\\nToo bad. I did vote for Quinn but not for Cohen. I will probably not vote for Quinn if Cohen stays on the ticket. It\\'s not a matter of liking hookers. It\\'s really a matter of political and governmental experience. I mean c\\'mon, he\\'s a pawnbroker.\\nIllinois gets the government we deserve. There\\'s a reason they call us \"fly-over land\". We feature big butts and small minds.\\nPosted by: Guy | February 04, 2010 at 03:23 PM\\nWhat a big goof by the media to not have gotten this story out BEFORE the vote...a real disservice to their subscribers/readers/listeners/watchers. Didn\\'t take long for the gloating to start in certain quarters: see the headline on John Kass\\'s column today. Cohen, I voted for you but probably would not have had I heard this story.\\nWithdraw, you\\'re only going to create a sniping target for the GOP. Too much is at stake.\\nPosted by: Jim M. | February 04, 2010 at 03:20 PM\\nHe wasn\\'t convicted of anything. Why should he step aside? He certainly isn\\'t any more tainted than Giannoulias.\\nPosted by: ed | February 04, 2010 at 03:18 PM\\nIs it just me or does Quinn look befuddled all the time...we need to start a 3rd party ASAP!\\nPosted by: BJB | February 04, 2010 at 03:17 PM\\nOne guy is Blagojech\\'s buddy and the other looks like he\\'s in Blagojevich\\'s training program.\\nWhen will the people of Illinois learn?\\nPosted by: John Kordic | February 04, 2010 at 03:17 PM\\nYes. It\\'s the Dem\\'s turn to self-destruct. Oh, do go to Madigan for his thumbprint in the election! That would cement it for the Republicans. Stroger, McKenna, Dillard. All out. Maybe we in this State ARE ready to clean things up. Lisa Madigan is smart for staying out of things. Nepotism is now out. Ask Hastert\\'s son. Still have that joke Lipinsky though. Enough with nepotism. Why put the same gene ppol in that got this state so screwed up in first place. OK. Madigan - both of them, Durbin, Richard \"parking meter\" Daley , Pelosi, Reid. The revolution has just started to retake our country. Need to clean up old guard of Republican side, too.\\nPosted by: Bornandrasied in Illinois and not giving it up | February 04, 2010 at 03:16 PM\\nUnelectable...........drop out now or lose.\\nPosted by: Gold Tooth | February 04, 2010 at 03:15 PM\\nLisa Madigan and Jesse White need to start their individual campaigns right away. They can be so grateful that there is no Punch 10 voting this year. David Miller and Robin Kelly may be collateral damage. Quinn/Cohen is DOA.\\nAnd Mr. Scott Lee Cohen, I know the way to handle him, legally, but the temporary, accidental unelected Governor will have to call me personally to find out how, and my fee will be substantial and upfront.\\nThe other way is to repay Mr. Cohen all of his campaign expenditures and give him an additoal payout, because surely ke knows there is no way the ticket can win with him on it.\\nOn the other hand he\\'ll certainly be able to franchise his pawn shops. If he stays on the ticket, I\\'ll be hapopy to do his campaign, also not for free.\\nHow about this slogan. You want a public official with cajones? This guy\\'s got three!\\nOr how about this one: Giannoulias for Senate, Cohen for Lt. Governor, Bank/Pawn Shop? - You\\'re better off with the Pawn Shop.\\nI didn\\'t think there might be enough people to elect Hynes/Turner, though I knew that had a very good chance. Quinn/Cohen is impossible. But Cohen will have the ride of his life.\\nBy the way there was once a Scott Cohen who was Chuck Percy\\'s top assistant, but I doubt if they are related.\\nI have a compromise: let this Cohen get off and put Chris Cohen on the ticket. Let\\'s leave no Cohen unturned.\\nPosted by: Phil Krone | February 04, 2010 at 03:14 PM\\nthe ticket candidates are already getting along.\\nPosted by: r | February 04, 2010 at 03:11 PM\\nAs Julia Roberts said in \"Pretty Woman\", Big Mistake!\\nPosted by: Rich S | February 04, 2010 at 03:10 PM\\nComplete Emanuel Coverage »\\nFind your ward and members of the Chicago City Council »\\nYour alderman\\'s expense account\\nHow Chicago\\'s 50 aldermen are using their expense accounts\\nWhat\\'s your alderman\\'s side job?\\nComplete coverage\\nClout St. posts\\nRod Blagojevich photos\\nRichard Daley\\nClout St. coverage\\nNeighborhoods for sale\\nTribune investigation: How cash and clout transformed Chicago neighborhoods.\\nAll 50 aldermen on the Chicago City Council had to file paperwork earlier this year detailing their outside income and gifts. The Tribune took that ethics paperwork and posted the information here for you to see. You can search by ward number or alderman\\'s last name.\\nWhat\\'s the estimated property tax bill in your town?\\nThe Cook County Assessor\\'s office has put together lists of projected median property tax bills for all suburban towns and city neighborhoods. We\\'ve posted them for you to get a look at who\\'s paying more and who\\'s paying less.\\n• Clout Street is moving\\n• Emanuel, Preckwinkle say city, county could save up to $140 million a year by teaming up\\n• Emanuel says \\'head tax\\' cut for businesses will be in his first budget\\n• United Airlines to bring 1,300 jobs to Chicago\\n• Quinn to meet with top lawmakers on construction plan\\n• Emanuel will wait on confidence vote for CHA CEO Lewis Jordan\\n• Emanuel unveils presidential picks for City Colleges of Chicago\\n• Ald. Solis new chairman of City Council Hispanic group\\n• Emanuel puts City Hall employees, salaries online\\n• Cook County applies again to convert Oak Forest Hospital to clinic\\n• 10th Congressional District\\n• 11th Congressional District race\\n• 2008 Conventions\\n• 2010 Cook County Assessor race\\n• 2010 Cook County Board commissioner races\\n• 2010 Cook County Board President\\'s race\\n• 2010 DuPage County Board Chairman race\\n• 2010 Illinois 10th Congressional District race\\n• 2010 Illinois 6th Congressional District race\\n• 2010 Illinois attorney general race\\n• 2010 Illinois comptroller race\\n• 2010 Illinois election\\n• 2010 Illinois Governor\\'s race\\n• 2010 Illinois House and Senate contests\\n• 2010 Illinois Lieutenant Governor\\'s race\\n• 2010 Illinois secretary of state race\\n• 2010 Illinois Treasurer\\'s race\\n• 2010 Illinois U.S. Senate campaign\\n• 2011 Chicago aldermanic races\\n• 2011 Chicago city clerk race\\n• 2011 Chicago election\\n• 2011 Chicago mayor\\'s race\\n• 2011 Chicago treasurer\\'s race\\n• 2012 Presidential Race\\n• 3rd Congressional District race\\n• 6th Congressional District race\\n• Attorney General\\n• Barack Obama\\n• Barack Obama U.S. Senate seat\\n• Board president\\n• Campaign 2007\\n• Chicago City Council\\n• Chicago Park District\\n• Chicago politics\\n• Cook County Board\\n• Cook County Forest Preserve District\\n• Cook County politics\\n• Cook County recorder of deeds race\\n• Cook County State\\'s Attorney\\'s race\\n• Development issues\\n• From the print edition\\n• Gambling\\n• Games\\n• Governor\\n• Illinois political docket\\n• Illinois redistricting\\n• Investigations\\n• Legislature\\n• Mayor of Chicago\\n• Olympics\\n• Open government\\n• Other counties\\n• Pension issues\\n• Polls\\n• Presidential race - Illinois\\n• Presidential Race 2012\\n• Race issues\\n• Rahm Emanuel 5th Congressional District seat\\n• Redistricting Illinois\\n• Reforming Illinois Government\\n• Rezko trial\\n• Rod Blagojevich\\n• Roland Burris\\n• State legislative races - 2008\\n• State politics\\n• Suburban issues\\n• Taxes\\n• Treasurer\\n• U.S. Senate race 2008\\n• Voting issues\\n• Web/Tech\\n• Weblogs\\n• WGN Radio Show\\nJune 2011 posts\\nAbout Clout\\nClout has a special meaning in Chicago, where it can be a noun, a verb or an adjective. This exercise of political influence in a uniquely Chicago style was chronicled in the Tribune cartoon \"Clout Street\" in the early 1980s. Clout Street, the blog, offers an inside look at the politics practiced from Chicago\\'s City Hall to the Statehouse in Springfield, through the eyes of the Tribune\\'s political and government reporters.<s> Brand Related\\nDesign-Art-Photo\\nIndustry Trivia\\nOpinions-Tips\\nRacing-Tuning\\nType-Emblems\\nThis is a Flickr badge showing public photos and videos from cartype.com. Make your own badge here.\\nPirelli advertising\\nFiled under: Design-Art-Photo\\nThe first Pirelli advertising campaigns went through two centuries with contributions from the best designers ever.\\n1910 Adolfo Busi ad.\\nAt the very beginning of the new century, the company took off. Those were, indeed, the years when the long P trademark began to develop, thanks also to Marcello Dudovich, Plinio Codognato and Leonardo Cappiello.\\nIn the years between the wars, the Pirelli Group communication began spreading all around the world. The trend reached full bloom in the 1950s and 1960s, when the best European designers congregated at Pirelli: Max Huber, Pavel M. Engelmann, Bob Noorda, Albe Steiner, and Raymond Savignac; among the Italian designers, Bruno Munari, Armando Testa, Riccardo Manzi, Giulio Confalonieri, and Pino Tovaglia.\\nThese are also the years of the Pirelli magazine, where articles of Ungaretti, Montale, Sciascia and Eco appeared, accompanied by Renato Guttuso illustrations.\\nMoreover, Pirelli also started a great cinematographic tradition, to boast in the two most typical channels of corporate communication, documentary and advertising films, which dates back to as early as the Twenties and Thirties.\\n(source: Pirelli)\\nMay 1910 Touring Club ad.\\n1914 Pneus Touring ad.\\n1916 Tacchi Stella Nino Nanni ad.\\n1917 Roowy Neu-Pirelli ad.\\n1917 Pneus Plinio Podognato ad.\\n1921 Dudovich Lidel ad.\\n1948 Scopinich Camminate ad.\\n1953 Raymond Savignac Borse ad.\\n1953 Ascari ad.\\n1955 Armando Testa Atlante ad.\\nPirelli Stella Bianca.\\nSince 1890, Pirelli has been synonymous with high-performance tires. With the creation of the Ercole, which marked the start of a long history of sporting success, the excellence of Pirelli\\'s products has been the concrete and visible result of the constant improvement of production processes, design methods and the use of materials.\\nFrom the Ercole to the pre-war Stella Bianca; from the Stelvio, workhorse of the motorised masses, to the innovative Cinturato of the 1950s to today\\'s ultra-high-performance \"run flat\" models outfitted with pressure sensors: the history of product innovation at Pirelli is an impressively long one.\\nPirelli Stella Bianca advertising.\\nThe Pirelli Cinturato.\\nAppearing for the first time in Pirelli advertising towards the mid-Fifties, its debut together with its stablemates the Stelvio and the Rolle was somewhat muted. Almost as if it was nothing more than another new product in the broad \"Alpino\" range of Pirelli tyres (that also included the Cisa and the Sempione). Subdued, with no underlining of its diversity. Which in truth was overwhelming…\\nPirelli\\'s approach to the fabric radial was known as the Cinturato or \"Belted\", after the fabric plies that effectively belted the radial carcass.\\nThe fabric Cinturato - it had yet to be equipped with steel belts - was invented around 1951 and cautiously introduced to the market a couple of years later.\\n\"Cautiously\" because for the requirements of the average driver in the 1950s, the Cinturato was if anything too \"advanced\": much stiffer than conventional cross-ply tyres, it permitted exceptional roadholding even at high speed, although it did penalize comfort.\\nIt was at least partly for this reason that Cinturato advertising of the time exclusively targeted sports cars and those drivers for whom speed and handling outweighed any bumps.\\nIn 1955 it was in fact \"the tyre for the Lancia Aurelia\" or \"for the Alfa Romeos\": its sporting character had already been forged.\\nIn the late Fifties and early Sixties, the Cinturato gradually became known as \"the safest tyre for the most powerful cars\", the one that \"defeats centrifugal force\" and that guarantees \"cornering safety\". And later it was also the tyre \"for elegant cars\".\\nA high-end positioning that was graphically emphasised by the magnificent advertising campaign photographed by Mulas in 1962, in which the tyre was once again paired with the female figure, as in the era of Dudovich.\\nHowever, Mulas\\'s absorbed and self-possessed girls actually seem to suggest a new key to the reading of the Cinturato product image: no longer was it just about speed and power - male myths - but now also comprised safety and reliability, aspects appealing to the first generations of young female drivers…By no means coincidentally, Mulas\\'s advertising campaign also included the \"Sempione Safety Shoulder\", the more reliable version of the conventional Sempione cross-ply range.\\nSo as to avoid over-emphasising the safety aspect of the Cinturato at the expense of its sporting image, in 1965 Mulas trained his lenses on Juan Manuel Fangio too. \"I once raced with the Pirelli Stelvio\", said the Argentine World Champion in the advertising copy, \"Today I\\'ve got the Cinturato on my car. It\\'s a tyre that\\'s truly different to the others. What\\'s most surprising is the absolute driving precision. Extraordinary\". The talented Riccardo Manzi was to return to the safety theme once more the following year for the \"Andiamo sul sicuro\" or \"Let\\'s go for safety\" campaign, and he was himself followed by another genius (two geniuses in fact: as Arrigo Castellani was also involved): Pino Tovaglia who emphasised the Cinturato\\'s dual nature with the \"Un viaggio ma\" or \"A trip but\" campaign highlighting the close ties between the pleasure of sporting driving and the tranquillity of absolute safety.\\nPirelli Cinturato advertising.\\nPirelli old logo.\\nPirelli logo. (source: ©Pirelli)\\nPirelli \"P\" logo. (source: ©Pirelli)\\nPirelli P-Slot Wheel Designed for Volkswagen\\'s GTI\\nPirelli Official site.<s> Michelle Obama Reveals She Underwent IVF to Have Sasha and Malia\\nShe said she had a miscarriage 20 years ago and \"felt like I failed.\"\\nPaul MorigiGetty Images\\nMichelle Obama reveals in her new book she struggled with her fertility.\\nThe former first lady says she had a miscarriage 20 years ago and felt like she \"failed.\"\\nShe also reveals she underwent IVF to conceive her daughters, Malia and Sasha.\\nMichelle Obama amazon.com\\nMichelle Obama is opening up about her life in a new memoir, Becoming. And in the book, she reveals she struggled with fertility issues before conceiving her two daughters, Sasha and Malia. In an interview with Robin Roberts for a special on the book, which will air on ABC Sunday night, the former first lady said she had a miscarriage 20 years ago.\\n\"I felt lost and alone, and I felt like I failed because I didn\\'t know how common miscarriages were, because we don\\'t talk about them,\" Obama said. \"We sit in our own pain, thinking that somehow we\\'re broken. That\\'s one of the reasons why I think it\\'s important to talk to young mothers about the fact that miscarriages happen.\"\\nShe also said she underwent in vitro fertilization in her mid-30s in order to conceive her two daughters, after realizing \"the biological clock is real, because egg production is limited.\"\\n.@MichelleObama opens up to @RobinRoberts in revealing new interview; says she felt \"lost and alone\" after suffering miscarriage 20 years ago. Watch @ABC special covering her journey to motherhood and more from her memoir, \"Becoming,\" Sunday night 9/8c. https://t.co/ONXwpuZ3WF pic.twitter.com/1Teb5ycWIe\\n— Good Morning America (@GMA) November 9, 2018\\nObama told Roberts she decided to tell her story so women know they are not alone if they\\'re struggling to start a family. \"I think it\\'s the worst thing that we do to each other as women, not share the truth about our bodies and how they work, and how they don\\'t work,\" she said.\\nFrom: ELLE US\\nMore From Society\\nJeffrey Epstein\\'s Secret PR Strategy\\nJFK Jr. Was Interested in Running for Office\\nWho Is Jeffrey Epstein?\\nCarolyn Bessette\\'s Mom Had Some Tough Advice\\nMichelle Obama Goes to India\\nMichelle Obama\\'s Electrifying Speech at the DNC\\nHere\\'s What Michelle Obama Is Doing Next\\nThe Obamas\\' Favorite Charities, Revealed\\nOprah Talks Becoming With Michelle Obama\\nThe Obamas Are Back in Washington<s> This spring-blooming wildflower, also known as wakerobin, is native to woodlands in the Eastern U.S. The plants stand 10-12\" high, and have distinctive flowers with three burgundy-maroon petals. Trillium grow best in rich, moist soils and will multiply over time. These plants are commercially propagated, not wild collected.\\new always had wild trillium in the woods when I was growing up. The first time I ever saw a red one I thought I\\'d gone to heaven! These were just as I remembered!<s> Усач плоский красный ()\\xa0— вид жуков-усачей из подсемейства настоящих усачей. Распространён в Европе (Латвии, Британии, Греции, Словакии, Чехии), Северной Африке (Алжире, Тунисе), Сирии, Иране, Турции, Армении, России и Казахстане. Длина тела 8—12 мм. Личинки развиваются в различных деревьях: бук европейский, каштан посевной, дуб австрийский, дуб черешчатый.\\n\\nПримечания \\n\\nНастоящие усачи\\nНасекомые Европы\\nНасекомые Азии\\nНасекомые Африки\\nЖивотные, описанные в 1758 году<s> Difference between revisions of \"Math 540: Linear Analysis\"\\n[[Math 342]] or equivalent. [[Math 352]] or equivalent.\\nMath 342 or equivalent. Math 352 or equivalent.\\nThis page was last modified on 25 March 2015, at 16:52.<s> Poldark (BBC One, 2015) is a British-American drama television series created by Debbie Horsfield, based on the novels by Winston Graham. Ross Poldark (Aidan Turner) returns home after American Revolutionary War and rebuilds his life with a new business venture, making new enemies and finding a new love where he least expects it. ... more on Wikipedia\\nPoldark is ranked on...\\n#556 of 754 The Best TV Shows to Binge Watch 1.1M VOTES Bored? Not anymore! These are the best TV shows for binge-watching. The greatest television shows in the world are ranked he...\\n#1 of 29 20+ Current British TV Shows You\\'ve Been Missing This Whole Time 7k VOTES If you\\'re an Anglophile at heart, this list of under the radar British TV series is for you. Everyone\\'s heard of shows like&...\\n#11 of 27 The Best Current Period Piece TV Shows 3.5k VOTES List of the best period piece television series, of any genre and from any network, that truly capture the feel of their tim...\\n#203 of 227 The Greatest TV Dramas of All Time 148.6k VOTES The greatest TV dramas of all time are the ones that make you feel connected to characters you will never meet in real life ...\\n#1 of 22 The Best New Historical Drama TV Series of the Last Few Years 11.1k VOTES If you\\'re fascinated by stories of bygone eras, these new historical shows may satisfy your craving to be transported to a d...\\n#28 of 34 The Best New Shows of the Last Few Years That You\\'ve Been Missing Out On 452 VOTES Sometimes, the TV shows everyone should be watching don\\'t exactly hook a huge audience right away. Underrated TV shows may b...\\n#1 of 7 The Best New Period Piece TV Shows of the Last Few Years 2k VOTES Period pieces can transport viewers back in time to a radically different era and, perhaps due to the stressful nature of mo...\\n#2 of 48 What to Watch If You Love \\'Outlander\\' 185 VOTES Outlander kept viewers on the edge of their seats with a harrowing tale of a woman who is thrust out of her own time, so it\\'...\\n#41 of 115 The Best TV Shows Based on Books 42.1k VOTES Fun fact: Game of Thrones isn\\'t the only good TV show based on a book streaming on the airwaves! Though more and more people...\\n#46 of 111 The Best TV Shows On Amazon Prime 31.6k VOTES The best streaming Amazon Prime TV shows and television series feature many of the most memorable TV characters of all time ...\\n#44 of 109 The Best Historical Drama TV Shows 53.8k VOTES Learn about real-world history while you binge watch the best historical drama shows on television. Some of the gre...\\n#2 of 86 The Best Period Piece TV Shows 12.9k VOTES The very best period piece shows on television, ranked from best to worst. This list of the greatest period piece shows. The...\\n#5 of 51 The Best British History Series & Period Pieces 1.1k VOTES Thanks to having a bit of a longer history than The States, historical TV shows from the UK include everything from relative...\\n#7 of 31 The Best Current Historical Drama Series 7.5k VOTES These are the best current historical drama series of 2019, ranked from best to worst by user votes. From some good current ...\\nbest anime openings 2000 cartoon network shows best british stand up comedians The Secret Life of the American Teenager characters suspense series on netflix tread the floods the haunting of episodes hole in the wall song famous ethiopian authors astronomy series<s> Q: How to remove outdated casks from Homebrew? I am using homebrew-cask to keep my ecosystem of applications up-to-date. It is great when maintaining several computers at home, travel or on the go. \\nHowever, when some packages are getting updated (such as Google Chrome), I end up having different concurrent versions installed (and which are seen by the OS):\\n\\n$ ls /opt/homebrew-cask/Caskroom/google-chrome/\\n  latest  stable-channel\\n\\nThis happens when upgrading a cask:\\n$ ls -l /opt/homebrew-cask/Caskroom/tunnelblick\\ntotal 0\\ndrwxr-xr-x 5 foo staff 238 Mar 11 07:42 3.3.0\\ndrwxr-xr-x 5 foo staff 238 May 13 13:53 3.3.2\\n[13:00:40] foo at bar in ~\\n$ brew cask install --force tunnelblick\\n==> Caveats\\nFor security reasons, Tunnelblick must be installed to /Applications and will request to be moved at launch.\\n\\n==> Downloading https://downloads.sourceforge.net/project/tunnelblick/All%20files/Tunnelblick_3.3.4.dmg\\n######################################################################## 100.0%\\n==> It seems there is already an App at \\'/Applications/Tunnelblick.app\\'; not linking.\\n  tunnelblick installed to \\'/opt/homebrew-cask/Caskroom/tunnelblick/3.3.4\\' (236 files, 20M)\\n\\n$ ls -l /opt/homebrew-cask/Caskroom/tunnelblick\\ntotal 0\\ndrwxr-xr-x 5 foo staff 238 Mar 11 07:42 3.3.0\\ndrwxr-xr-x 5 foo staff 238 May 13 13:53 3.3.2\\ndrwxr-xr-x 5 foo staff 238 Jun 26 13:01 3.3.4\\n[13:01:26] foo at bar in ~\\n\\nHow do I only keep the most recent?\\n\\nA: In Terminal, type:\\nfor app in $(brew cask list); do cver=\"$(brew cask info \"${app}\" | head -n 1 | cut -d \" \" -f 2)\"; ivers=$(ls -1 \"/opt/homebrew-cask/Caskroom/${app}/.metadata/\" | tr \\'\\\\n\\' \\' \\' | sed -e \\'s/ $//\\'); aivers=(${ivers}); nvers=$(echo ${#aivers[@]}); echo \"[*] Found ${app} in cask list. Latest available version is ${cver}. You have installed version(s): ${overs}\"; if [[ ${nvers} -eq 1 ]]; then echo \"${ivers}\" | grep -q \"^${cver}$\" && { echo \"[*] Latest version already installed :) Skipping changes ...\"; continue; }; fi; echo \"[+] Fixing from ${ivers} to ${cver} ...\"; brew cask uninstall \"${app}\" --force; brew cask install \"${app}\"; done\\n\\nHint: Copy and paste the above command line into Terminal.\\n<s> In the Shadows (2001)\\nIn the Shadows (2001) MultiSource Server\\nHitman. Stuntman. Dead man.Jun. 24, 2001105 Min.PG\\nWatch In the Shadows (2001) online for free on 123Movies. When a stunt man dies in Miami, his uncle, a New York mob boss, sends a hit man to tail the stunt coordinator, whom the boss wants dead. The hit man, Eric O\\'Bryne, gets close to his mark\\'s daughter, and through her he asks her dad to teach him to do stunts. While waiting for the word to kill this mentor, Eric discovers the joy of stunt work and of being part of a family. Meanwhile, several people are looking for the dead man\\'s briefcase of money and a cloth bag of illegal drugs that he stole from an undercover FBI agent now desperate to get the borrowed drugs back to the bureau. The stunt coordinator says that \\'we dance in the shadows of death.\\' Can Eric step out into the sun?\\nOriginal title In the Shadows\\nMatthew Modine\\nJames Caan\\nLance Huston\\nJoey Lauren Adams\\nClarissa Huston\\nLillo Brancato\\nJimmy Pierazzi<s> The central aim of the Enterprise Investment Scheme (EIS), Seed Enterprise Investment Scheme (SEIS) and Venture Capital Trusts (VCTs) is to encourage individuals to invest in smaller unquoted trading companies which often find capital difficult to raise. Social Investment Tax Relief (SITR) is the government\\'s tax relief for investments into social enterprises. Business Property Relief (BPR) supports business investment generally by providing a potential shelter from Inheritance Tax.\\nFollowing the financial crisis in 2008 and the lack of bank finance subsequently available, many small and medium sized companies have had to look elsewhere for funding.\\nWhen the world\\'s bourses are collapsing, as happened in the last recession, the valuations of unquoted companies can hold up well against general trends.\\nIf and when the economy bounces back from recession, small companies can be the quickest to react, expanding rapidly, and seizing market share.\\nInvesting early can give spectacular returns because small companies can quickly multiply in size.\\nIndividuals are able to support social enterprises and receive incentives for doing so.\\nThe underlying sectors, styles and strategies of investment represent a broad range of opportunities, and the available tax benefits are designed to help mitigate the risk of investing in such companies. The following pages explain these government incentives in more detail, from their structure to their associated tax benefits.\\nThe following pages refer mainly to five types of investment vehicles: SEIS, EIS, VCT, SITR and BPR and are an outline of the various schemes. This should not be used as a means of proceeding with an investment, since it is not a comprehensive summation of the rules; investors should seek expert, independent professional advice. Furthermore, this summary refers to regulation governing investments made on or after 6th April 2016, and investors should note that legislation may change in the future.\\nFor further details of the investment risks please see the Key Risks section of this website.<s> Therefore, I, the prisoner of Christ, invite you, to live the vocation you have received. Be humble, kind, patient and bear with one another in love. Make every effort to keep among you, the unity of spirit, through bonds of peace. Let there be one body, and one Spirit, just as one hope is the goal of your calling by God. One Lord, one faith, one baptism; one God, the Father of all, Who is above all, and works through all, and is in all.\\nBut to each of us, divine grace is given, according to the measure of Christ\\'s gift. Therefore, it is said : When He ascended to the heights, He brought captives and gave His gifts to people. He ascended, what does it mean, but, that He had also descended to the lower parts of the world? He, Himself, Who went down, then ascended far above all the heavens, to fill all things.\\nAs for His gifts, to some, He gave to be Apostles; to others, prophets, or even evangelists; or pastors and teachers. So, He prepared those who belong to Him, for the ministry, in order to build up the Body of Christ, until we are all united, in the same faith and knowledge of the Son of God. Thus, we shall become the perfect Man, upon reaching maturity, and sharing the fullness of Christ.\\nBut to each of us, divine grace is given, according to the measure of Christ\\'s gift. As for His gifts, to some, He gave to be Apostles; to others, prophets, or even evangelists; or pastors and teachers. So, He prepared those who belong to Him, for the ministry, in order to build up the Body of Christ, until we are all united, in the same faith and knowledge of the Son of God. Thus, we shall become the perfect Man, upon reaching maturity, and sharing the fullness of Christ.\\nThis entry was posted in Uncategorized and tagged 10 May 2018, Ascension of Jesus Christ, Ascension of the Lord, Bishop of Rome, Body of Christ, Catholic blog, Catholic wordpress, Church blogs, commitment to God, devotion to God, Easter Octave, Easter season, Eastertide, Ephesians 4, Epistle to the Ephesians, Epistles of St. Paul, faith blog, following God, gift of God, gift of Holy Spirit, God the Father, great solemnity, green, heavenly Glory, holy baptism, Holy Mass, Jesus ascending into heaven, Leader of the Church, Liturgical celebrations, Liturgical Colour, new testament, Pope Benedict XVI, Pope Francis, Pope St. John Paul II, Purple, Red, Risen Lord Jesus, Roman Catholic Church, Second Reading, seeking God, Sixth Sunday of Easter, Solemnity of the Ascension, Sunday of Easter Octave, Sundays after Epiphany, Thursday, united in Christ, Universal Church, violet, way of the Lord, white. Bookmark the permalink.<s> Research shows non-invasive novel biomarkers can predict Alzheimer\\'s risk\\nSponsored Content by Cerba ResearchJul 22 2021\\nSince the National Institute on Aging and Alzheimer\\'s Association published its 2011 guidelines detailing distinct diagnostic recommendations for preclinical, mild cognitive impairment and dementia stages, research geared towards Alzheimer\\'s disease (AD) research has progressed.\\nAs a neurodegenerative syndrome, diagnosis originally depended on the clinical picture, MRIs and cognitive testing. However, more recently, this exceptionally complex disease continuum has primarily come to be defined by its biological manifestations.\\nCharacterizing the disease by its biology allows for more consistent characterization and facilitates a better understanding of the disease and its mechanisms 1. Additionally, it also offers better accuracy in clinical trials 1.\\nWith the transition towards precision and personalized medicine, in the area of AD, biomarkers are critical. Biomarkers associated with the specific states and stages of the disease at an individual level are necessary to provide the best patient management options. They are also needed as clinical trial endpoints to help develop an understanding of this complex disease.\\nDue to the rigorous search for useful AD biomarkers and general central nervous system diseases, the race towards confirming new biomarkers in these indications is a fast-moving and stimulating task.\\nThis article discusses current, non-invasive biomarkers and investigational biomarkers for the research and diagnosis of Alzheimer\\'s disease, as well as clinical trial partner proficiencies that may be useful along the path of development.\\nCurrently established Alzheimer\\'s disease biomarkers for early diagnosis and clinical trials\\nIt is recognized that biological signs of AD appear 15 to 20 years prior to the first clinical symptoms, as levels of amyloid-β (Aβ) and tau peptides build up in the brain. These aggregates set off intracellular signaling that results in apoptosis.\\nThe central cerebrospinal fluid (CSF) biomarkers of neuronal degeneration include:\\nBeta-amyloid 42 protein (Aβ42)\\nPhosphorylated tau protein (p-tau)\\nTotal tau protein (t-tau)\\nCSF levels of these three biomarkers can precisely stage the disease. Imaging studies are also utilized for the diagnosis of AD: MRI has the capacity to detect Beta-amyloid aggregation and cortical atrophy. Specific positron emission tomography (PET) imaging with radiotracers facilitates visualization of both tau-protein tangles and β-amyloid plaques in vivo 2.\\nIn short, the current blended approach utilized in the differential diagnosis and confirmation of AD and during clinical trial evaluations may include:\\nBiomarkers in CSF\\nAlthough imaging and CSF biomarker studies like this have the capacity to catch AD in the presymptomatic phase – 15 to 20 years before the onset of symptoms – they are extremely invasive, expensive and unable to be used as screening tests. When patients do eventually present symptoms, they are already cognitively impaired.\\nWhile effective therapies are not yet available, there is evidence to suggest that incorporating of early lifestyle interventions can prevent the onset of dementia in predisposed individuals 3-4.\\nFor clinical trial and screening qualification, viable early screening tests are an absolute necessity.\\nDeveloping blood-based biomarkers for early diagnosis of Alzheimer\\'s disease\\nAs of yet, no standard clinical diagnostic techniques are available for the diagnosis of AD from blood samples. Yet, a significant number of continuing studies and recent publications are focused on promising blood biomarkers for this goal.\\nP-tau 181: An ultrasensitive blood immunoassay showed that plasma p-tau 181 levels were linked with the degree of tau and β-amyloid pathologies and differentiated AD from other neurodegenerative disorders 5. Numerous other studies awaiting publication agree.\\nβ-amyloid 42/40: An immunoprecipitation and liquid chromatography-mass spectrometry assay displayed that plasma Aβ42/ Aβ40, especially when combined with age and apolipoprotein E (APOE ε4) status (see below), diagnosed brain amyloidosis accurately (confirmed by PET), even in individuals that were cognitively normal 6.\\nAβ42 and t-tau: An immunomagnetic reduction assay in a small study of patients with mild cognitive impairment indicated that elevated plasma Aβ42 and t-tau levels are related to later cognitive decline 7.\\nNeurofilament light chain (NfL): Concentrations of plasma NfL were seen to link with degree of neurodegeneration in Aβ+ subjects, as demonstrated by decreased fluorodeoxyglucose uptake in PET imaging 8.\\nAssays with the sensitivity to detect these biomarkers at extremely low concentrations in the blood are expected to aid the clinical diagnosis of prodromal Alzheimer\\'s disease through a simple blood test.\\nA research lab with a history of pioneering and early-stage implementation of non-invasive biomarker techniques is likely to offer drug developers the essential services for effective transition from bench to market.\\nExperts with both extensive and practical, collaborative research experience; Standard and complicated testing methods, and teams specifically committed to validating and translating new biomarkers from bench to market are all vital for the successful biomarker and companion diagnostic development to assist in clinical trials.\\nImage Credit: Cerba Research\\nGenetics presents additional biomarkers for AD diagnosis and research\\nAcquiring as much knowledge about a disease can produce additional predictive biomarkers and reveal therapeutic opportunities by distinguishing disease causes, mechanisms and characteristic progression.\\nAlthough AD is largely sporadic, recent genomic studies across vast cohorts have detected a number of genetic associations for the disease. Biomarker changes in these heritable forms of AD are typically similar to those for intermittent AD 9.\\nFor instance, an autosomal dominant, early-onset form of AD contains a genetic mutation that influences signaling at the neuronal level. Particularly, affected genes code for presynaptic vesicle protein synaptotagmin and presenilin, an accelerator when converting amyloid protein precursor (APP) to amyloid β-protein 10.\\nThe awareness of this makes these proteins biomarker candidates for general AD.\\nAn additional example of a genetic biomarker for AD, the various APOE polymorphs ε2, ε3, and ε4 are related to differing concentrations of CSF Aβ42. The APOE genotype influences a patient\\'s risk factor for developing AD.\\nPatients with the ε4 allele demonstrate earlier declines in CSF Aβ42 concentrations, analogous to earlier amyloid deposition. The enhanced risk is greatest in homozygous ε4 carriers but is also raised in carriers of heterozygous ε4 11.\\nGenetics-driven biomarker discovery for AD is still a work in process, with a recent genome-wide meta-analysis verifying 20 known high-risk loci while determining five new ones, clearing a path for future investigations 12.\\nInvolved pathways were affiliated with immunity, lipid metabolism, tau binding proteins and APP metabolism, reflecting the complex nature of Alzheimer\\'s disease.\\nMultiomics approach to biomarker discovery\\nNo individual biomarker is inclined to serves as the signature for a disease as complex as AD. Complete characterization of the disease may necessitate incorporation, not only of genomics factors but also proteomics factors, lipidomics, transcriptomics factors and metabolomics factors, all working together.\\nA team with a high degree of skill and an expert technical platform are necessary for the integration of all the individual components of metabolic survey research into a full and clinically relevant profile.\\nCNS biomarkers for other diseases\\nDifferential diagnosis among neurodegenerative diseases can be a challenge when cognitive and clinical tests are deemed to be inconclusive.\\nSpecial biomarkers can also assist such cases as well. For example, in the lack of biomarkers for AD, an increase in special biomarker studies of CSF protein 40-3-3 can indicate accelerated progressive dementias from cerebral injury or prion diseases, such as Creutzfeldt-Jacob (CJD).\\nTo validate a diagnosis of CJD, cerebrospinal fluid real-time quaking-induced conversion is an extremely sensitive and special test for the presence of protease-resistant prion protein 13.\\nFuture diagnostic profiling, research tools and therapeutic developments\\nThrough a mixture of metabolomics, genomics and proteomics, biomarker profiles of patients prone to developing AD can be generated. Simultaneously, clinical research diagnostics can be advanced to better explain the dysfunctional pathways leading to AD brain pathology in combination with corresponding therapeutic targets.\\nEventually, gene therapies – potentially RNA interference techniques – may be designed to limit the level of amyloid precursor protein gene expression in these patients to delay or prevent the onset of Down\\'s symptoms.\\nNon-invasive biomarkers for Alzheimer\\'s disease will help with prevention soon and therapies later\\nAs the global population is ever-aging, reducing the incidence of Alzheimer\\'s disease is currently a research priority. In the near future, innovative, non-invasive AD biomarkers may be available for prevention screening and to support clinical research.\\nIt is possible to incorporate quantification of plasma tau, β-amyloid, and neurofilament concentrations into this blood-based biomarker testing method.\\nDeveloping effective biomarkers that facilitate the development of precision medicine and personalized medicine requires genuine expertise across a spectrum of specialties from proteomics, to genetics, to metabolomics. It also demands experienced assistance in biomarker validation and planning.\\nBiomarker studies and multiomics profiling will offer a better understanding of Alzheimer\\'s disease, help establish new therapeutic agents and enable the implementation of preventive interventions well before the onset of this devastating and widespread disease.\\nJack CR Jr et al, NIA-AA Research framework: Toward a biological definition of Alzheimer\\'s disease, Alzheimer\\'s Dement 14(4):535-62, 2018\\nLa Joie R et al, Prospective longitudinal atrophy in Alzheimer\\'s disease correlates with the intensity and topography of baseline tauPET, Sci Transl Med 12(524): eaau5,732, 2020\\nSabia S et al, Association of ideal cardiovascular health at age 50 with incidence of dementia: 25- year follow-up of Whitehall II cohort study, BMJ 366: ppl4,414, 2019\\nLefèvre-Arbogast S et al, Nutrition and Metabolic Profiles in the Natural History of Dementia: Recent Insights from Systems Biology and Life Course Epidemiology, Curr Nutr Rep 8(3): pp256-69, 2019\\nKarikari TK et al, Blood phosphorylated tau 181 as a biomarker for Alzheimer\\'s disease: a diagnostic performance and prediction modelling study using data from four prospective cohorts, Lancet Neurol 19(5): pp422-33, 2020\\nSchindler SE et al, High-precision plasma β-amyloid 42/40 predicts current and future brain amyloidosis, Neurology 93(17): e1,647-e59, 2019\\nChen T et al, Plasma Aβ42 and Total Tau Predict Cognitive Decline in Amnestic Mild Cognitive Impairment, Nature Sci Rep 9(1): p13,984, 2019\\nBenedet AL et al, Plasma neurofilament light associates with Alzheimer\\'s disease metabolic decline in amyloid-positive individuals, Alzheimer\\'s Dement (Amst) 11: pp679-89, 2019\\nLista S et al, Biomarkers in sporadic and familial Alzheimer\\'s disease, J Alzheimer\\'s Dis 47(2): pp291-317, 2015\\nÖhrfelt A et al, The presynaptic vesicle protein synaptotagmin is a novel biomarker for Alzheimer\\'s disease, Alzheimer\\'s Res Ther 8(1): p41, 2016\\nLautner R et al, Preclinical effects of APOE ε4 on cerebrospinal fluid Aβ42 concentrations, Alz Res Ther 9: p87, 2017\\nKunkle BW et al, Genetic meta-analysis of diagnosed Alzheimer\\'s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing, Nat Genet 51(3): pp414-30, 2019\\nFiorini M et al, High diagnostic accuracy of RT-QuIC assay in a prospective study of patients with suspected sCJD, Int J Mol Sci 21(3): p880, 2020\\nBallard C et al, Dementia in Down\\'s syndrome, Lancet Neurol 15(6): pp622-36, 2016\\nAbout Cerba Research\\nFor over 35 years, Cerba Research has been setting the industry standard for exemplary clinical trial conduct. Today, across five continents, with a focus on precision medicine, we are changing the paradigm of the central lab\\'s role in complex clinical research.\\nFrom protocol inception through development and to market, our passionate experts deliver the highest quality specialized and personalized laboratory and diagnostic solutions. Partner with us for the most efficient strategy to actualize your biotech and pharmaceutical products sooner and improve the lives of patients worldwide.\\nLast updated: Jul 22, 2021 at 4:25 AM\\nCerba Research. (2021, July 22). Research shows non-invasive novel biomarkers can predict Alzheimer\\'s risk. News-Medical. Retrieved on January 31, 2023 from https://www.news-medical.net/whitepaper/20210722/Research-shows-non-invasive-novel-biomarkers-can-predict-Alzheimers-risk.aspx.\\nCerba Research. \"Research shows non-invasive novel biomarkers can predict Alzheimer\\'s risk\". News-Medical. 31 January 2023. <https://www.news-medical.net/whitepaper/20210722/Research-shows-non-invasive-novel-biomarkers-can-predict-Alzheimers-risk.aspx>.\\nCerba Research. \"Research shows non-invasive novel biomarkers can predict Alzheimer\\'s risk\". News-Medical. https://www.news-medical.net/whitepaper/20210722/Research-shows-non-invasive-novel-biomarkers-can-predict-Alzheimers-risk.aspx. (accessed January 31, 2023).\\nCerba Research. 2021. Research shows non-invasive novel biomarkers can predict Alzheimer\\'s risk. News-Medical, viewed 31 January 2023, https://www.news-medical.net/whitepaper/20210722/Research-shows-non-invasive-novel-biomarkers-can-predict-Alzheimers-risk.aspx.\\nOther White Papers by this Supplier\\nAchieve better routine testing thanks to Cerba\\'s broad portfolio\\nAdvancing a Phase IIb study in the midst of a pandemic\\nAlleviating the complexity of rare disease research\\nBiomarkers hold the key to better clinical outcomes\\nCerba Research offers state-of-the-art in-vitro diagnostics\\nCerba strives to boost research in immuno-oncology\\nCerba\\'s \\'patient first\\' ideology is at the heart of its identity\\nCustom flow cytometry assays are critical to personalized medicine\\nHow Africa could become a new center for clinical trials\\nHow Cerba supports patients through companion diagnostics\\nHow to integrate IHC biomarkers for effective clinical development in immuno-oncology\\nHow to measure success using biomarkers\\nInflammatory and autoimmune diseases are underlying causes of a variety of human diseases\\nOptimize clinical trials with Cerba Research high-end operational support\\nResearch that helps clients receive novel treatments faster\\nThe impact of COVID-19 on clinical trials\\nThe largest phase III nonalcoholic steatohepatitis study to date\\nThree critical lab capabilities to look for in immuno-oncology\\nBiomarkers hold the key to more personalized medicine\\nCerba Research extends facilities provided by U.S Immuno-Oncology Center of Excellence\\nCerba Research offers large-scale sequencing\\nCerba Research partners with the Gustave Roussy Institute to improve patient experience\\nRapid innovations in histopathology will change the face of clinical trials\\nThe power of flow cytometry in cancer research\\nMore Content from Cerba Research\\nSee all content from Cerba Research<s> Kids Info Bits is the perfect educational product for today\\'s young learners. It\\'s a content-rich, authoritative, easy-to-use resource featuring age-appropriate content covering a broad range of educational topics. It features a modern, graphical interface, great new content from trusted sources, more intuitive navigation, improved resources, and much more.\\nAcademic Search Complete offers an enormous collection of the most relevant full-text journals, providing users access to critical information from many sources unique to this database. In addition, it is the leading source of peer-reviewed full text for STEM research, as well as for the social sciences and humanities. This scholarly collection offers unmatched coverage of information spanning a broad range of important areas of academic study, including anthropology, engineering, law, sciences and more. Academic Search Complete offers access to video content from the Associated Press, the world\\'s leading news agency. Videos relevant to the search terms will appear in a carousel in the result list. With footage from 1930 to the present and updated monthly, this collection of more than 60,000 videos covers a wide variety of topics.\\nAdvanced Placement Source Designed to meet the extensive needs of high school students enrolled in various Advanced Placement (AP) or International Baccalaureate (IB) courses, this database offers a world of knowledge for students who seek to achieve academic excellence. Covering a wide array of subject areas from the arts and multicultural studies to the STEM subjects, Advanced Placement Source offers students the essential research materials to achieve academic success in honors, AP or IB programs. This database is the only AP-focused multi-disciplinary product on the market and contains full text dating back to 1985.\\nAlt HealthWatch An Extensive Resource for Alternative and Holistic Approaches to Health Care and Wellness This alternative health research database focuses on the many perspectives of complementary, holistic and integrated approaches to health care and wellness. AltHealth Watch provides the latest information and materials for the evolving practice of holistic medicine and therapies, with in-depth coverage across the full spectrum of subject areas.\\nBibliography of Native North Americans This bibliographic database covers a wide range of topics pertaining to native North Americans, including culture, history and daily life. This resource will appeal to anyone interested in exploring the contributions, struggles and issues surrounding North America\\'s indigenous peoples.Bibliography of Native North Americans contains more than 188,000 citations for books, essays, journal articles and government documents of the United States and Canada. Dates of content coverage range from the 16th century to the present. This database is an essential research tool for anthropologists, educators, historians, political scientists, sociologists, psychologists, legal and medical researchers, linguists, theologians, ethnobotanists and policy makers.\\nComputer Source: Consumer Edition Full Coverage. Computer Source contains nearly 300 full-text journals and magazines. A Wide Variety of Content. Content includes many subject areas and is not limited to: computers, electronics, the internet, telecommunications, computer science, programming, artificial intelligence, cybernetics, information systems, robotics, and software.\\nEBook Sub. Poetry & Short Story Reference Center This full-text database provides a historically rich collection of hundreds of thousands of classic and contemporary poems, as well as short stories, biographies and authoritative essays on such topics as poetic forms, movements and techniques — including contemporary content from the finest publishers.Poetry & Short Story Reference Center provides contemporary content from the finest publishers including Knopf, Houghton Mifflin, New Directions, Copper Canyon Press and dozens of authors and estates, as well as Critical Survey of Poetry and Critical Survey of Short Fiction and other major respected reference books and literary journals.Available via EBSCOhost or its own dedicated interface, Poetry & Short Story Reference Center contains selected works of major and minor American and English poets, along with international poetry representing each continent (accompanied by English translations, when available). Works include plays and speeches, short stories and classic books, biographies, critical analyses, contextual essays and explications for important works, essays on poetic forms, literary terms, techniques and movements, multimedia (audio and video) of poets reading their works and interviews from reputable sources like the Academy of American Poets, the Poetry Foundation, and MacNeil/Lehrer Productions.Poetry & Short Story Reference Center comes with its own dedicated interface that allows users to browse content by categories such as most studied poems, poets, short stories and themes. In addition, it offers supplemental teaching and learning guides featuring lesson plans and assignments specifically crafted for use with this database. \"Poetry off the Page\" lesson plans align with NCTE and Common Core curriculum standards.\\nEBook Subscription High School Collection Designed specifically for high school students and educators, this collection offers an easy, cost-effective way for libraries to provide full-text eBook coverage that aligns with their school\\'s curricula, as well as complement other e-book and database resources from EBSCO.This package contains nearly 8,200 e-book titles that support a quality learning experience across all academic subject areas, from History, to Language and Literature, to Science and Technology. Content includes a selection of classic literary works, important historical documents and general reference materials. The collection also features a selection of Teacher Resources to support educators and administrators. Titles align with Common Core Curriculum Standards (for participating U.S. states)The eBook High School Collection is available as an annual subscription with unlimited simultaneous access for users, and titles are continually added at no additional cost.\\nERIC: HOST The Education Resource Information Center (ERIC) provides access to educational literature and resources. This database provides access to information from journals included in theThis resource contains more than 1.5 million records and links to hundreds of thousands of full-text documents dating back to 1966.\\nFuente Academica This database is a valuable source for academic research, providing key coverage of major subject areas. Fuente Académica provides researchers with a collection of scholarly journals from Latin America, Portugal and Spain, designed to make academic research readily available in PDF format.Fuente Académica offers full text for more than 500 journals from more than 18 countries.\\nHistory Reference Center Designed for secondary schools, public libraries, junior/community colleges and undergraduate research, this database features full text for thousands of primary source documents and informational texts.History Reference Center content comes from leading history publishers such as Branden Publishing, Compass Point Books, Houghton Mifflin, Lerner Publishing Group, Mason Crest Publishers, Morgan Reynolds, Inc., Oxford University Press and Rourke Publishing LLC, and includes exclusive proprietary content from Salem Press.The database includes full text content from more than 150 leading history periodicals, including American Historical Review, Archaeology, British Heritage, Canada\\'s History, Civil War Times, Military History, Teaching History, African Studies Quarterly, Ancient Egypt Magazine, Australian Historical Studies, Chinese Studies in History, Jewish History, Muslim World, Russian Studies in History and Women\\'s History Review.Available via EBSCOhost, Explora, or its own dedicated interface, History Reference Center features variety of resources to help educators prepare their students to meet curriculum goals, such as lesson plans and rich multimedia content to enhance delivery. In addition, articles include Lexile® Measures to address text complexity requirements. History Reference Center also links to EBSCO\\'s Curriculum Standards Module, a tool that can help teachers in the U.S. and Canada correlate EBSCO content quickly and easily to Common Core, state, or provincical curriculum standards. The module provides browsing of specific benchmarks, many which have recommended search strings for successful content retrieval.\\nInformation Science and Technology Abstracts This database provides indexing and abstracts for journal articles, books, research reports, and conference proceedings spanning a multitude of information science and technology topics. It provides ongoing comprehensive coverage of the most important periodicals in the field.Information Science & Technology Abstracts (ISTA) includes cover-to-cover indexing and abstracts for over 90 core information science and technology titles. With coverage dating as far back as 1975, it is the oldest continuously produced database covering the field of information science.\\nLiterary Reference Center This comprehensive full-text database provides a broad spectrum of information on thousands of authors and their works across literary disciplines and timeframes. It gives students, professors and researchers a foundation of literary reference works to meet their research needs.Combining information from major respected reference works, books, literary journals and original content from EBSCO, Literary Reference Center features an expansive collection of author biographies, plot summaries and full-text essays from leading publishers. It also includes literary reference books and monographs, cover-to-cover full text for literary magazines and book reviews from the most prestigious publications. It offers poems from hundreds of sources, short stories, classic texts, author interviews and much more.In addition, Literary Reference Center includes Merriam Webster\\'s Encyclopedia of Literature, Beacham\\'s Research Guide to Biography and Criticism (six volumes), The Oxford Illustrated History of English Literature and all of MagillOnLiterature Plus.Available via EBSCOhost, Explora, or its own dedicated interface, Literary Reference Center contains a collection of informational texts on numerous literary genres, themes and forms, as well as critical essays on specific works and authors. Students can also find helpful research guides, a citation tool and literary glossary.Literary Reference Center also features dozens of lesson plans and a link to EBSCO\\'s Curriculum Standards Module, a tool that can help teachers correlate EBSCO content quickly and easily to Common Core, state- or province-specific curriculum standards. The module provides browsing of specific benchmarks, many which have recommended search strings for successful content retrieval.\\nMAS Full TEXT Ultra School Edition Designed specifically for high school libraries, this database contains full text for popular high school magazines covering a wide-range of subject areas including history, science, careers and more. American History, Discover, New Republic, Popular Science, Nation, New Scientist, American History, Discover, New Republic, Popular Science This comprehensive database contains full text for top high-school magazines including America\\'s Civil War, American History, Archaeology, Astronomy, Bioscience, Civil War Times, College press Magazine, Congressional Digest, Discover, History Today, Nation, National Review, New Republic, New Scientist, Popular Science, Science News, Scientific American, Smithsonian, World War II, and much more. All full-text articles are assigned a reading level indicator (Lexiles).MAS Ultra – School Edition also provides full text for more than 158,000 biographies and primary source documents, hundreds of reference books (including the Columbia Encyclopedia and the CIA World Fact Book), an image collection containing photos, maps, flags and color PDFs and expanded full-text back files (back to 1975) for key magazines.This database is also included as part of theUltra Online Package and can be searched via EBSCOhost or Explora, EBSCO\\'s dedicated interface for schools and public libraries.\\nMasterfile Premier Designed specifically for public libraries, this database provides full text for magazines, reference books and primary source documents. It also includes an extensive image collection containing photos, maps and flag.Masterfile Premier contains full text for general reference magazines and publications that cover a wide-range of subject areas including business, health, education, general science and multicultural issues.PDF back files are available as far back as 1922 for key publications including American Libraries, Foreign Affairs, History Today, Library Journal, National Review, Saturday Evening Post and more. In addition, Science News is available in HTML back to 1975.Library patrons can easily search and retrieve content contained in Masterfile Premier via EBSCOhost which provides users with an intuitive interface that allows basic and advanced search options. Users can conduct a basic search by typing in a keyword in the single search box, or they can conduct a more advanced search using limiters and other options.\\nMedic Latina A unique collection of medical research and scientific journals from renowned Latin American and Spanish publishers, Medic Latina contains a complete table of contents and PDF full text for peer-reviewed medical journals in the Spanish language.Content within Medic Latina is gathered from more than 190 peer-reviewed journals, providing comprehensive coverage of a broad range of subjects. Additionally, the database is updated on a weekly basis to incorporate new material, including the most up-to-date medical research available in Spanish. Medic Latina features full-text records from several leading publications, including Revista Medica del IMSS, Actas Espanolas de Psiquiatria, Archivos de Neurociencias, Revista Biomedica, Veterinaria Mexico, Salud Publica de Mexico and more.\\nMEDLINE Created by the United States National Library of Medicine, MEDLINE is an authoritative bibliographic database containing citations and abstracts for biomedical and health journals used by health care professionals, nurses, clinicians and researchers engaged in clinical care, public health and health policy development.MEDLINE provides an easy-to-use interface and powerful search functionality including basic and advanced search options. Users can effectively search and retrieve information with Medical Subject Headings (MeSH) created by the United States National Library of Medicine.\\nMilitary and Government Collection Designed to offer current news through a collection of periodicals, academic journals and other content pertinent to the increasing needs for all branches of the military and government. This collection provides full text for hundreds journals and periodicals. The database also offers indexing and abstracts for hundreds of journals.\\nNatural & Alternative Treatments - EBSCOhost This comprehensive natural medicine resource focuses on alternative and holistic approaches to health care and wellness. Designed with the consumer-health researcher and clinician in mind, Natural & Alternative Treatments is an essential tool that satisfies an ever-growing demand for accurate, unbiased information on natural health.This resource provides an in-depth analysis of more than 200 distinct health conditions and the natural treatments used to treat them.Evidence-based, Natural & Alternative Treatments cites more than 12,000 clinical research studies across 700 articles containing information on medical conditions, alternative therapies, herbs and supplements, functional foods, drug interactions and homeopathy.This database provides clinicians and consumer-health researchers with a comprehensive and reliable source of current information on natural health and medicine.Information provided in this database should not be viewed as a means for self-diagnosis or a substitute for professional medical advice, diagnosis or treatment.\\nNewspaper Source This database provides cover-to-cover full text for more than 40 national (U.S.) and international newspapers. In addition, it offers full text for more than 300 regional (U.S.) newspapers as well as television and radio news transcripts.Newspaper Source provides complete television and radio news transcripts from CBS News, CNN, CNN International, FOX News, NPR and more.\\nLong Holds List? Recommend a Series!\\nProfessional Development Collection This database provides a highly specialized collection of electronic information especially for educators, professional librarians and education researchers. Education, School Library Journal, Education Digest, High School Journal, Education, School Library Journal,Education Digest, High School JournalProfessional Development Collection includes full text for high-quality education journals including Booklist, Education, Education Digest, Education Week, Educational Leadership, High School Journal, Journal of Education, Journal of Educational Research, Phi Delta Kappa, Reading Teacher, School Library Journal and more. Professional Development Collection can be accessed via EBSCOhost or Explora, EBSCO\\'s dedicated interface for schools and public libraries.\\nRegional Business News This robust database provides ultimate coverage for full-text business publications, on a regional level, for the United States and Canada. Whether searching for information about presidential candidates, franchise restaurants, the retail industry, business planning, or political participation, Regional Business News will cover the story.Content is provided by leading publishers in business news including The Washington Post, PR Newswire US and more. Key resources include newspapers, radio & TV news transcripts, trade publications, magazines and newswires, with full-text content coverage spanning more than 22 years.\\nScience Reference Center This comprehensive research database provides easy access to a wealth of full-text, science-oriented content. Designed to meet every student researcher\\'s needs, Science Reference Center contains full text for hundreds of science encyclopedias, reference books, periodicals and other reliable sources. In addition, the database includes a vast collection of images from sources such as UPI, Getty, NASA, National Geographic and the Nature Picture LibrIn addition to full-text coverage, Science Reference Center includes the Science Image Collection, a database of more than 270,000 high-quality science images from National Geographic, UPI, Getty, NASA and – most recently – Nature Picture Library. Based in the U.K., Nature Picture Library provides thousands of stunning photographs from more than 300 of the world\\'s best nature and wildlife photographers. The collection features images of wild animals and plant species from around the world, pets, people, landscapes and the environment. The Science Image Collection also includes hundreds of proprietary science illustrations, charts, and graphs.By providing a wide range of topics, Science Reference Center satisfies the demand for standards-based content by providing teachers and librarians with articles correlated to state and national curriculum standards. The database contains a wealth of informational texts as well as real-world examples of the application of mathematical concepts in scientific research.\\nSerials Directory Access to the Most Current Bibliographic Information and Current Pricing Structures for Popular Serials from Publishers WorldwideThis database provides access to the most up-to-date and accurate bibliographic information, as well as current pricing structures for popular serials. The Serials Directory is an indispensable resource for anyone needing serials information such as e-mail and Internet address, language, publication frequency, ISSN, Library of Congress, Dewey decimal classification, and more.\\nVocational and Career Collection Designed to meet a wide variety of vocational and technical research needs, this collection provides full-text coverage for trade and industry-related periodicals including Modern Machine Shop, Pediatric Nursing, Wireless Week, Drug Store News, Reeves Journal, Restaurant Business, Advertising Age and many more.Vocational & Career Collection offers vocational and technical libraries top-quality resources for servicing high schools, community colleges, trade institutions, and the general public.\\nJoin us for the BL Sunday - Open House!\\nThank you for your support of Bishop Lynch!\\nClick below for current news.<s> In Conversation with\\nLia García\\new had an extremely interesting conversation with the\\nup-and-coming painter on her style, her technique,\\nher inspirations and her creative process.\\nnext to \"SELF ISOLATION (and other strories)\"\\nWhen I first stumbled upon Lia García\\'s work a couple years ago, the first thing that caught my attention was her portrayal of emotions. In all of her paintings, one could practically feel what the subjects of each painting were thinking. The facial expressions in her work were sublime, each one subtly representing a different emotion or mental state. This is the core of Lia\\'s work. Through her art, Lia manages to portray different emotions perfectly, and hence conjure them in her audience. Lia\\'s work isn\\'t strictly about technique, style or even color; it\\'s about feeling.\\nLia García is a painter and visual artist from the Dominican Republic. She recently graduated from Manhattanville College in New York, where she majored in Studio Art and Sociology while minoring in French Studies and Visual Arts Education. Throughout her college career, I had the privilege of watching Lia\\'s evolution as an artist. I got to see how her style, technique and subject matter changed. Most of all, I got to see how little by little Lia became more comfortable with her work. Her most recent pieces have focused mainly on portraiture, further expanding on the idea of portraying feelings and emotions through simple facial expressions. During her time in New York, Lia got the chance to participate in various exhibitions, where her paintings were acclaimed by many viewers, critics and collectors.\\nThroughout her career as a young artist, Lia has managed to accomplish something very impressive: she has developed a style that is completely recognizable. It isn\\'t often that we see such a young artist display such mastery over technique and format, and that\\'s what makes Lia such a remarkable young talent. Not only did she find a style that she was comfortable with, but she managed to adapt the style to her own judgement, instead of the other way around.\\nMost recently, Lia decided to move back to the Dominican Republic, where she\\'s been re-descovering her roots and adapting her acquired experience in New York to her original setting. Here at the Pyramid we\\'re very excited to see how this change of setting will affect Lia\\'s art and her process, but we\\'re sure that whatever she creates will be amazing, just like all of her work has been so far.\\n\"MY Red Underwear\" June 2019\\nOil on Canvas (16 x 20 inches)\\new recently got a chance to ask Lia a couple of questions in which we touched on her inspirations, her technique, her development as an artist and her creative process. This is what she had to say:\\nFirstly, I\\'d like to talk a little bit about your beginnings in art. When did you first discover that you were interested in being an artist? Did the desire to be an artist come first, or was it a result of your interest in expressing yourself creatively?\\nHonestly, I just always thought all kids did art when they were kids. It wasn\\'t until high school that I realized not everyone spent their childhood afternoons painting, or that not everyone did it after growing up as a \"hobby\", like I used to. You know that age when kids start getting an identity based on what they like to do? Like \\'the gymnast\\', or \\'the writer\\', or \\'the one who\\'s good at math\\'? One day I was suddenly \\'the artist\\' amongst my friends because it\\'s what I was good at. So, to answer your question, I guess it came as a result, but it wasn\\'t self-appointed. As a kid, it\\'s not like I\\'ve always wanted to be an artist. Even in college, the fact that I didn\\'t go to art school, or that I chose -at first- not to add studio art as a second major was a surprise to a lot of people, but here we are.\\n\"I just always thought all kids did art when they were kids. It wasn\\'t until high school that I realized not everyone spent their childhood afternoons painting.\"\\n\"Untitled\" October 2018\\nOil on Fabriano\\nMost of your work is based on portraiture, even though the technique you apply isn\\'t what is normally used for the types of paintings you paint. Why did you become interested in portraiture specifically?\\nI just love faces! Faces tell you so much about what people are feeling through their expressions. And the fact that everyone has a different face? Amazing. I wish I could paint every single face I\\'ve ever seen. Although, for the longest time, I used to only do self-portraits. The idea of painting someone else\\'s face scared me because I doubted I could do it, since the only reason I can so easily paint my own face is because it\\'s the face I know best and the one I study the most. Because its mine! (and because I spend a lot of time looking at it in the mirror). But, the night of my first solo show in New York two years ago, after my boyfriend at the time ----who\\'s face I used to paint a lot, too--, and I finished setting everything up and were waiting for guests to arrive, I realized the room was filled with paintings of mostly MY FACE. And even though my narcissistic tendencies didn\\'t really mind it, everything else in me absolutely hated it. So, after that, I forced myself to paint other faces than my own.\\n\"Faces tell you so much about what people are feeling through their expressions. And the fact that everyone has a different face? Amazing.\"\\n\"Guy with Pink around his eye\" December 2018\\nOil on Fabriano (8.5 x 11 inches)\\nThe technique that you use focuses heavily on impasto, which in my opinion gives your work an edge in which the focus of the paintings isn\\'t solely the subject matter, but also the style as well. This impasto technique, did it come before the idea of painting portraits, or is it a result of the decision to focus on portraiture?\\nImpasto! That word has been on the tip of my tongue for over a week, thanks! I started using this technique only about two years ago, so it came after. I was living in France for six months and only had dried-up paint brushes with me, and if you know me, you know that I am so lazy that I would rather use those paint brushes until they fall apart in my hands rather than buying new ones. Impasto comes out better if you don\\'t have a \"good\" brush in my opinion, so I started playing with this technique as an adaptation of my laziness. For a good amount of time I had been trying to reach a certain level of realism, got fairly good at it, and then got bored of it. This was just a few months after my first show in NY, and I was going through a self-discovery and artistic reinvention phase. My parents always tell me that my career as an artist is still pretty young and that I am free to change my style and approach any time I feel like it in order to find my signature. With impasto, I\\'m still doing portraits, only a little less personal, a little less real.\\n\"For a good amount of time I had been trying to reach a certain level of realism, got fairly good at it, and then got bored of it.\"\\n\"Picasso helped me be okay with not having just one style of painting. And Van Gogh\\'s work helped me fall in love with the primitiveness of the paint itself.\"\\nBeing in France for those months gave me a new perspective on art and the importance of sometimes letting go of perfectionism while at the same time putting more effort on technique. I got really close to Picasso and Van Gogh\\'s work. Picasso helped me be okay with not having just one style of painting. And Van Gogh\\'s work helped me fall in love with the primitiveness of the paint itself. Eventually, for a little while, I started moving away from portraits, I was painting more hands because they were less detailed and made it easier for me to transition from blending a lot to not blending at all. At first, I was very unsatisfied with my work, as usual. But it was all part of the process. Now I\\'m still doing portraits, and I\\'m still using the impasto technique in different forms, and I love the freedom it gives me.\\n\"Ojalá que llueva Café en el Campo\" June 2019\\nI\\'ve noticed that many of your paintings carry an emotional connotation to them. Many of your portraits portray not only a face, but also a specific feeling behind the expressions. Do you feel that the particular emotion that you are trying to present is important to the process you employ to create a painting? In other words, do the feelings expressed by the subjects in your paintings affect the way you decide to paint them, be it in color palette, style, or any other way?\\nI recently finished a series on facial expressions where I asked some of my social media followers to send me pictures of their face expressing any feeling and tell me what they were feeling and why, and then I painted them. The purpose of this was to shed light to some feelings we don\\'t usually talk about because they\\'re either too small and deemed insignificant, or too big and touchy to talk about. I think all feelings should be talked about, or at least expressed in some form. I don\\'t think, or at least I don\\'t do it consciously if at all, that the feeling described by the subjects affected the color palette or style. I try not to get too creative when I\\'m painting other people\\'s faces out of fear that they won\\'t recognize it, or it won\\'t resemble the reference picture. But, outside of this specific series, yes, my paintings have a lot of emotion behind it, I think primarily through the eyes. My grandma says that in a way, every portrait I paint of other people has a little bit of me in them. This is because I paint my own eyes on almost every piece, I think I have very expressive eyes, and I think it\\'s a way of channeling my own emotions through painting without necessarily painting my face over and over again.\\n\"I think all feelings should be talked about,\\nor at least expressed in some form.\"\\n\"Untitled\" January 2020\\nThese last few years you\\'ve been living in New York. In my opinion, NYC has a very deep influence in many creatives who are exposed to the artistic culture that the city possesses. Do you feel that being exposed to NYC and its art scene has affected the way you view your work and your process? If so, how exactly has it affected you as a creative?\\nYes! Definitely! I\\'ve met more artists and seen more art in my last four years in NYC than I have in my whole 22 years elsewhere. The city itself is a huge outdoor museum. I love it. I miss it so much. What I like the most about it is how quick people in New York are to call themselves artists. Over there, EVERYTHING is art! There are no rules or guidelines, if you consider it art, its art. I am very hard on myself and my work sometimes, but New York and the people there gave my work enough validation to help myself fall in love with it, too. It helped be accept every failed piece as simply part of the process, which is very hard to do when you\\'re someone who gets easily unmotivated every time something doesn\\'t go as planned.\\n\"What I like the most about it is how quick people in New York are to call themselves artists. Over there, EVERYTHING is art! There are no rules or guidelines, if you consider it art, its art.\"\\n\"Hands Up\" June 2019\\nThe art world in the Dominican Republic and New York is very different in terms which artists one is exposed to. Do you feel that painting in the DR and painting in NYC is somehow different? Is there a difference in your creative process in the two places, or is your creative process entirely dependent on you as an artist, and your vision for your work?\\nMmmmmm tough question, I truly don\\'t know how to answer. I\\'m with you, they are different, but I can\\'t pinpoint exactly how. I think maybe the process is altered by the environment. When I\\'m in DR, I live with my family, I don\\'t have my very own space, and 50% of my family is allergic to the smell of oils, so it\\'s tricky. Yet, I feel that my creativity is at an all-time high when I\\'m home, especially now during quarantine, and I end up producing a lot more than when I\\'m in NY. In NY I mostly live alone, and all the space is for me and my art, yet it takes longer for me to finish something or to start new projects, probably because I\\'m usually busy and rushing through things, and inspired by too many things that I get overwhelmed. I experience more artists block when I\\'m in NY than when I\\'m in DR. But I think people in NY interpret my work more accurately than the audience I have in DR.\\n\"I experience more artist\\'s block when I\\'m in NY than when\\nI\\'m in DR. But I think people in NY interpret my work more\\naccurately than the audience I have in DR.\"\\nYour work as a painter is, in my opinion, very impressive. I feel it\\'s admirable that at such a young age you\\'ve already developed such a particular and recognizable style. However, I feel that many creatives feel an inherent need to express themselves in any way possible. With this in mind, are there any other artistic mediums that you\\'d be interested in exploring in the future other than painting?\\nWow thank you! Yes, a lot, haha. I\\'m really into pottery lately, I think a lot of artists are doing really cool things… I was very into 3D printing a few years ago, and into printmaking and serigraphy... I love arts and crafts, especially when it\\'s focused on creating sustainable art. I used to make my own recycled paper and even made a few sketchbooks with it. I also love film, I\\'m not good at it, but it\\'s something I would want to explore. Graphic design... Sculpture, too… Illustration… Embroidery! En fin, so many things.\\n\"I love arts and crafts, especially when it\\'s\\nfocused on creating sustainable art.\"\\n\"Untitled\" June 2019\\nI\\'ve noticed that in most cases, artists have two different goals in mind when working on their pieces. Some artists hope that when people see their work, a certain idea is transmitted to them. Other artists simply create what they feel they need to express, and don\\'t really think about what others will understand through their work. In your case, is there a certain idea that you wish your work transmitted to viewers, or do you leave the interpretation of your work open to the viewers themselves?\\nThere\\'s always a meaning behind my pieces, I have something to say about almost each one. Yet, I leave it up to interpretation, mainly because I\\'m very shy haha. But I also almost never get asked the right questions during my shows, and I don\\'t like to get into it unless I\\'m asked. Sometimes I wish I could interview myself just so I can say what I want about each piece, but that makes very little sense to me. Maybe there\\'s not much to interpret or ask about, maybe the messages are clear enough. Or maybe they\\'re so unclear people just think there is no message. I don\\'t know, but frankly I don\\'t really mind if people interpret the wrong thing or don\\'t interpret anything at all. I\\'m okay with being the only one knowing the meaning behind my work. I think if you get it, you really get it, if you don\\'t (or don\\'t think there\\'s anything to get), it\\'s not for you and that\\'s okay, you know? There\\'s a lot of sociopolitical hidden context in my art, I\\'m a sociologist before I\\'m an artist. But not everyone sees it, or not everyone wants to see it, or maybe they just don\\'t want to ask about it. But it\\'s all part of the message I\\'m trying to communicate. I also don\\'t think there\\'s anything wrong with appreciating art solely for aesthetic purposes, but there is always a meaning or message behind what I produce.\\n\"There\\'s a lot of sociopolitical hidden context in my art, I\\'m a sociologist before I\\'m an artist.\"\\n\"I think if you get it, you really get it, if you don\\'t (or don\\'t think there\\'s anything to get), it\\'s not for you and that\\'s okay, you know?\"\\nFinally, is there any artist, from any medium, that you feel everyone should know? If so, who would that be and why?\\nOhhhhhhh there are so many I want to mention. But if I had to choose just one to help you understand me as an artist a little more, I would say Egon Schiele. He\\'s one of my favorite artists. Not only because the way he depicts the distorted human body and face resembles with me and my art, but also because I think we share a lot of the same rebellious tendencies without explanation through our art. There\\'s also a little of him in all of his pieces even when he\\'s not painting himself, and I relate to that.\\n\"Self-Portrait with Chinese Lantern Plant\"\\nby Egon Schiele\\new\\'d like to give a special thanks to Lia for taking the\\ntime to talk to us and answer our questions. For more\\non her and her work, be sure to check out\\nher Instagram at @lgb_art and visit her\\nwebsite to see all her work!<s> Yes, on Residential Parks you will have to pay the appropriate rate of Council Tax as this will be classified as your main residence. The majority of Park Homes are classified under Band A, the cheapest banding. However, if in doubt please check with the local Council.\\nAre children allowed on the parks?\\nOur Parks are specifically designed for the semi retired and retired with a minimum acceptable age of 50 years – on Acresfield Park the minimum acceptable age is 55. Children are always welcome to visit but are not allowed to live permanently on these Parks.\\nDo park homes retain their value?\\nProviding a Park Home, similar to any traditionally built home, is looked after and well maintained there is no reason why homes will not retain their value. Park Home values generally follow the trends of the general Housing Market.\\nWhat is the monthly pitch fee and how much can I expect to pay?\\nEvery Park charges a Pitch Fee. This monthly fee takes into account many things including a ground rent for keeping your home on a particular plot, the maintenance of communal areas on the Park including roadways and streetlighting, staffing, third party liability insurance, the list goes on. Typically the monthly charges range from £125 to £205. For Wyre Vale Park and Lodge Park the pitch fees include the water rates but excludes the sewerage rates which are payable to United Utilities. For Gawthorpe Edge Park and Acresfield Park United Utilities bill the homeowners directly for both water and sewerage services.\\nHow are the pitch fee charges reviewed?\\nThe review date for each Park may be different. The precise date will appear within the Park Agreement. The review process is strictly regulated. In general pitch fees are reviewed annually and increase or decrease in line with the Retail Prices Index.\\nOn all of our Residential Parks mains gas is available and homeowners are free to nominate the supplier of their choice. This is the same for electricity on all of our Parks except Lodge Park where the electricity is sub metered. Electricity on Lodge Park is supplied at cost and at a very competitive rate.\\nWhat is the expected life span of a park home?\\nAll modern Residential Parks Homes are built to British Standard 3632. Newly manufactured Park Homes exceed the energy rating of most standard traditionally built properties.\\nDo I have to upgrade my home after so many years?\\nNo. This rule relates to Parks with licences for holiday use and not residential. Under government legislation homeowners who live on Residential Park Home Estates are afforded security of tenure for an unlimited period if the Park is freehold. All of our Parks are freehold. You cannot be forced to upgrade.\\nAre their specialist Insurers who cover park homes?\\nYes, there are, one of which is Park Home Assist.\\nIs finance available for purchase of a park home?\\nThere are companies who finance both new and previously owned homes. A repayment calculator is available below. However there are other options to consider such as Part Exchange or Assisted Move Schemes.\\nDo we pay stamp duty when buying a park home?\\nPark Rules are there to ensure the good management of a Park and to ensure the health and wellbeing of all of the homeowners who live there.\\nWhat is the written statement and how does it affect me?\\nThe Written Statement under the Mobile Homes Act, known by many as The Park Agreement includes the provision of security of tenure for the homeowner/s and sets out the Park Owner\\'s obligations to the homeowner/s and their obligations to the Park Owner/s. This is a very important document. Owners on holiday parks do not have the benefit of these provisions which are important to secure and enhance your investment.\\nIs there a commission to pay when a home is re-sold?\\nYes. Under the Terms of the Mobile Homes Act 1983 the government brought in the commission payment scheme as a way of ensuring that pitch fees payable on Parks were kept to affordable levels. The maximum charge is 10% of the full sale price.\\nYou may move onto any of the Parks with not more than two dogs, or two cats or one dog and one cat—the dogs must not be of any of the breeds subject to the Dangerous Dogs Act 1991—plus any pets or animals which are housed within a cage, aquarium or similar and which remain at all times within your home. Cats and dogs cannot be replaced when they die. The only exception to this rule is for anyone who requires a guide dog or an assistance dog. In such a circumstance all that would be required is a letter from the homeowner\\'s Doctor confirming such a requirement and upon receipt written consent will be provided without delay.\\nThese rules are in place to ensure acceptable standards are maintained on the Park which will be of general benefit to Occupiers, and to promote and maintain community cohesion.\\nThey form part of the Agreement by which homeowners occupy their pitch in accordance with the Mobile Homes Act 1983, as amended.\\n\"occupier\" means anyone who occupies a Park Home, whether under an Agreement to which the Mobile Homes Act 1983 applies or under a tenancy or any other agreement.\\n\"you\" and \"yours\" refers to the homeowner or other occupier of a Park Home.\\nNo occupier who is in occupation on that date will be treated as being in breach due to circumstances which were in existence on that date and which would not have been in breach of the rules in existence before that date.\\nThe minimum acceptable age for occupiers is 55 years and no person/s below that age may reside in a home on this Park. The Park Owner reserves the right to approve additional permanent members of the occupier\\'s household—a permanent member of the household means either spouse or approved partner. The approval must be in writing and that approval will not be unreasonably withheld in respect of someone aged 55 years and over.\\nThe Park Home may be used by the occupier and bone fide guests. The occupier will at all times be responsible for the conduct of their guests. Guests may stay for a maximum of 6 weeks at any one time.\\nTo ensure adequate ventilation you must keep the underneath of your home clear and not use it as a storage space.\\nNothing should be allowed to grow on the boundary fencing thus preventing maintenance of the fence panels themselves. No timber fences are allowed between homes. Where the occupier has a pet dog a low level green mesh fence to a maximum height of 1.25 metres will be allowed to be erected at the rear and at the side of the Park Home.\\nWashing lines, TV aerials and satellite dishes must be screened from public view where possible.\\nTrees and shrubs may be planted on the pitch but the occupier must ensure that any easement rights which exist with utilities companies are not breached. If in doubt please enquire at the Park Owner\\'s Head Office.\\nNo external fires of any kind are allowed.\\nYou must not keep inflammable substances on the Park except in quantities reasonable for domestic use.\\nYou must not keep explosive substances on the Park.\\nOccupiers must keep and maintain the outside of their Park Home and pitch in a clean and tidy condition. Any footpaths and driveways on the pitch must be kept in a good and safe state of repair and condition. The original exterior colour of the homes must not be changed. No other colours are acceptable.\\nNo external alterations of/or additions to the Park Home or pitch are permitted without our written permission. This is to ensure compliance with the Site Licence conditions and that in the case when additions are proposed for the home itself the concrete base upon which the home is sited can withhold the additional weight which such work may cause. Such permission will not be unreasonably withheld.\\nYou must not use or display guns, firearms and offensive weapons on the Park and you may only keep them in your home if you hold the appropriate licence and if they are securely stored in accordance with the terms and conditions of that licence.\\nYou must not have more than one non-combustible storage shed on your pitch. Where you source the shed yourself the design, standard and size of the shed must be approved by us in writing such approval will not be withheld or delayed unreasonably. You must position the shed so as to comply with the Park\\'s Site Licence, fire requirements and towards the rear elevation of the home and not towards the roadway. The footprint of the shed shall not exceed 48 square feet.\\nYou must not have any storage receptacle on the pitch other than the shed mentioned in rule 12 above and any receptacle for the storage of domestic waste pending collection by the local authority.\\nYou are responsible for the disposal of all household, recyclable and garden waste in approved containers supplied by the local authority service. You must not overfill containers and must place them in the approved position for the local authority collections.\\nYou must not deposit any waste or rubbish other than in local authority approved containers on any part of the park (including any individual pitch).\\nYou must not use the Park Home, the pitch or the Park (or any part of the Park) for any business purpose and must not use the Park Home or the pitch for the storage of stock, plant, machinery or equipment used or last used for any business purpose. However, you are at liberty to work individually from home carrying out any office work of a type which does not create a nuisance to other occupiers and does not involve other staff, other workers, customers or members of the public calling at the Park Home or the Park.\\nYou must not use musical instruments, all forms of recorded music players, radios and other similar appliances and motor vehicles so as to cause a nuisance to other occupiers, especially between the hours of 10.30pm and 8.00am.\\nYou must only use fire points in case of fire.\\nYou must drive all vehicles on the Park carefully and within the displayed speed limit and adhere to any one way system in operation.\\nDesignated parking spaces are provided next to each Park Home for up to a maximum of two cars.\\nYou must not park on the roads or grass verges. You must only park in the permitted parking spaces.\\n*vehicles intended for domestic use but derived from or adapted from such a commercial vehicle.\\nThe exception to this are vehicles driven by the Park Owner and/or by any of the Park Owner\\'s employees or sub contractors.\\nNo commercial vehicles may be parked on the Park overnight.\\nYou must hold a current driving licence and be insured to drive your vehicle on the Park. That vehicle must be taxed as required by law and be in a roadworthy condition.\\nDisused or unroadworthy vehicles must not be kept anywhere on the Park. We reserve the right to remove any vehicle which is apparently abandoned.\\n(a) major vehicle repairs involving dismantling of part/s of the engine.\\nThe term vehicle includes both cars , motorcycles and commercial vehicles. The only exception to this rule is for Park employees and sub contractors employed by the Park .\\nAny occupier who owns a touring caravan/motor caravan/motorhome/trailer tent may bring it onto the Park for a maximum of 2 days before and 2 days after a holiday for loading and unloading purposes only. Whilst on the Park these must be left unoccupied.\\nAn occupier may move onto the Park with not more than two dogs, or two cats or one dog and one cat—the dogs must not be of any of the breeds subject to the Dangerous Dogs Act 1991—plus any pets or animals which are housed within a cage, aquarium or similar and which remain at all times within your home. Cats and dogs cannot be replaced when they die. The only exception to this rule is for anyone who requires a guide dog or an assistance dog. In such a circumstance all that would be required is a letter from the homeowner\\'s Doctor confirming such a requirement and upon receipt we will provide the written consent without delay.\\nYou must keep any dog or cat under proper control and you must not permit it to frighten other users of the Park. You must keep any dog on a leash not exceeding 1m in length and must not allow it to despoil the Park. Dogs must not be kennelled outdoors.\\nThe express terms of an occupier\\'s agreement contain an undertaking on the part of the occupier not to allow anything which is or becomes a nuisance, inconvenience or disturbance to other occupiers of the Park and this undertaking extends to the behaviour of pets and animals.\\nThese rules do not have retrospective effect. If the pet complied with the previous rules, an occupier will not be treated as being in breach when these rules take effect. However, when the pet dies it cannot be replaced except in the case of a guide dog or an assistance dog along the terms detailed in rule 27.\\nhave been in breach of the rules in existence before that date.\\nThese rules also apply to the Park Owner and any employees (for as long as they may live on the Park), with the exception to the following rules 1,16,25 & 28.\\nThe minimum acceptable age for occupiers is 50 years and no person/s below that age may reside in a home on this Park. The Park Owner reserves the right to approve additional permanent members of the occupier\\'s household—a permanent member of the household means either spouse or approved partner. The approval must be in writing and that approval will not be unreasonably withheld in respect of someone aged 50 years and over.\\nNothing should be allowed to grow on the boundary fencing thus preventing maintenance of the fence panels themselves. No timber fences are allowed between homes. Where the occupier has a pet dog a low level green mesh fence to a maximum height of 1.25 metre will be allowed to be erected at the rear and at the side of the Park Home.\\nOccupiers must keep and maintain the outside of their Park Home and pitch in a clean and tidy condition. Any footpaths and driveways on the pitch must be kept in a good and safe state of repair and condition. Where the exterior of the Park Home is re-painted or recoated the only permitted colours are off white and shades of cream and beige. No other colours are acceptable.\\nNo external alterations of/or additions to the Park Home or pitch are permitted without our written permission. This is to ensure compliance with the Site Licence conditions and that in the case when additions are proposed for the home itself that the concrete base upon which the home is sited can withhold the additional weight which such work may cause. Such permission will not be unreasonably withheld.\\nYou must not use or display guns, firearms and offensive weapons on the and you may only keep them in your home if you hold the appropriate licence and if they are securely stored in accordance with the terms and conditions of that licence.\\nYou must not have more than one non-combustible storage shed on your pitch. Where you source the shed yourself the design, standard and size of the shed must be approved by us in writing such approval will not be withheld or delayed unreasonably. You must position the shed so as to comply with the Park\\'s Site Licence and fire requirements and towards the rear elevation of the home and not towards the roadway. The footprint of the shed shall not exceed 48 square feet.\\nHosepipes may be used but care should be exercised not to waste water.\\nYou must protect all external water pipes from potential frost damage.\\nElectricity Meter Boxes. The individual fuse boxes and the cabling from the fuse box back to each home is owned by the occupier. The Park Owner does not own any of the switchgear or cabling and is only responsible for the maintenance of the exterior structure of the meter boxes themselves.\\nEvery home has a designated parking space which is either next to the Park Home or within a parking bay. Those with car parking next to the Park Home may park a maximum of 2 vehicles next to their home. Those with designated parking within parking bays have been allocated one or two car parking space according to the location on the Park. You must not park more vehicles than your designated car parking space/s allows.\\nThese rules do not have retrospective effect. If the pet complied with the previous rules, an occupier will not be treated as being in breach when these rules take effect. However, when the pet dies it cannot be replaced except in the case of a guide dog or an assistance dog along the terms detailed in rule 30.\\nThese rules also apply to the Park Owner and any employees (for as long as they may live on the Park), with the exception to the following rules 1,16,24 & 27.\\n1. The minimum acceptable age for occupiers is 50 years and no person/s below that age may reside in a home on this Park. The Park Owner reserves the right to approve additional permanent members of the occupier\\'s household—a permanent member of the household means either spouse or approved partner. The approval must be in writing and that approval will not be unreasonably withheld in respect of someone aged 50 years and over.\\n2. To ensure adequate ventilation you must keep the underneath of your home clear and not use it as a storage space.\\n3. Nothing should be allowed to grow on the boundary fencing thus preventing maintenance of the fence panels themselves. No timber fences are allowed between homes. Where the occupier has a pet dog a low level green mesh fence to a maximum height of 1.25 metre will be allowed to be erected at the rear and at the side of the Park Home.\\n4. Washing lines, TV aerials and satellite dishes must be screened from public view where possible.\\n5. Trees and shrubs may be planted on the pitch but the occupier must ensure that any easement rights which exist with utilities companies are not breached. If in doubt please enquire at the Park Owner\\'s Head Office.\\n6. No external fires of any kind are allowed.\\n7. You must not keep inflammable substances on the Park except in quantities reasonable for domestic use.\\n8. You must not keep explosive substances on the Park.\\n9. Occupiers must keep and maintain the outside of their Park Home and pitch in a clean and tidy condition. Any footpaths and driveways on the pitch must be kept in a good and safe state of repair and condition. Where the exterior of the Park Home is re-painted or recoated the only permitted colours are off white and shades of cream and beige. No other colours are acceptable.\\n10. No external alterations of/or additions to the Park Home or pitch are permitted without our written permission. This is to ensure compliance with the Site Licence conditions and that in the case when additions are proposed for the home itself that the concrete base upon which the home is sited can withhold the additional weight which such work may cause. Such permission will not be unreasonably withheld.\\n11. You must not use or display guns, firearms and offensive weapons on the Park and you may only keep them in your home if you hold the appropriate licence and if they are securely stored in accordance with the terms and conditions of that licence.\\n12. You must not have more than one non-combustible storage shed on your pitch. Where you source the shed yourself the design, standard and size of the shed must be approved by us in writing such approval will not be withheld or delayed unreasonably. You must position the shed so as to comply with the Park\\'s Site Licence and fire requirements and towards the rear elevation of the home and not towards the roadway. The footprint of the shed shall not exceed 48 square feet.\\n13. You must not have any storage receptacle on the pitch other that the shed mentioned in rule 12 above and any receptacle for the storage of domestic waste pending collection by the local authority.\\n14. You are responsible for the disposal of all household, recyclable and garden waste in approved containers supplied by the local authority service. You must not overfill containers and must place them in the approved position for the local authority collections.\\n15. You must not deposit any waste or rubbish other than in local authority approved containers on any part of the park (including any individual pitch).\\n16. You must not use the Park Home, the pitch or the Park (or any part of the Park) for any business purpose and must not use the Park Home or the pitch for the storage of stock, plant, machinery or equipment used or last used for any business purpose. However, you are at liberty to work individually from home carrying out any office work of a type which does not create a nuisance to other occupiers and does not involve other staff, other workers, customers or members of the public calling at the Park Home or the Park.\\n17. You must not use musical instruments, all forms of recorded music players, radios and other similar appliances and motor vehicles so as to cause a nuisance to other occupiers, especially between the hours of 10.30pm and 8.00am.\\n18. Hosepipes may be used but care should be exercised not to waste water.\\n19. You must only use fire points in case of fire.\\n20. You must protect all external water pipes from potential frost damage.\\n21. You must drive all vehicles on the Park carefully and within the displayed speed limit and adhere to any one way system in operation.\\n22. Every home has a designated parking space which is next to the Park Home for up to a maximum of two cars. You must not park more vehicles than your designated car parking space/s allows.\\n23. You must not park on the roads or grass verges. You must only park in the permitted parking spaces.\\n25. You must hold a current driving licence and be insured to drive your vehicle on the Park. That vehicle must be taxed as required by law and be in a roadworthy condition.\\n26. Disused or unroadworthy vehicles must not be kept anywhere on the Park. We reserve the right to remove any vehicle which is apparently abandoned.\\n28. Any occupier who owns a touring caravan/motor caravan/motorhome/trailer tent may bring it onto the Park for a maximum of 2 days before and 2 days after a holiday for loading and unloading purposes only. Whilst on the Park these must be left unoccupied.\\n29. An occupier may move onto the Park with not more than two dogs, or two cats or one dog and one cat—the dogs must not be of any of the breeds subject to the Dangerous Dogs Act 1991—plus any pets or animals which are housed within a cage, aquarium or similar and which remain at all times within your home. Cats and dogs cannot be replaced when they die. The only exception to this rule is for anyone who requires a guide dog or an assistance dog. In such a circumstance all that would be required is a letter from the homeowner\\'s Doctor confirming such a requirement and upon receipt we will provide the written consent without delay.\\n30. You must keep any dog or cat under proper control and you must not permit it to frighten other users of the Park. You must keep any dog on a leash not exceeding 1m in length and must not allow it to despoil the Park. Dogs must not be kennelled outdoors.\\nThese rules do not have retrospective effect. If the pet complied with the previous rules, an occupier will not be treated as being in breach when these rules take effect. However, when the pet dies it cannot be replaced except in the case of a guide dog or an assistance dog along the terms detailed in rule 29.\\nthey are to apply only from the date on which they take effect, which is 14th December 2014; and No occupier who is in occupation on that date will be treated as being in breach due to circumstances which were in existence on that date and which would not have been in breach of the rules in existence before that date.\\nThese rules also apply to the Park Owner and any employees (for as long as they may live on the Park), with the exception to the following rules 1,16,23 & 26.\\nThe Park Home may be used by the occupier and bone fide guests . The occupier will at all times be responsible for the conduct of their guests. Guests may stay for a maximum of 6 weeks at any one time.\\n13. You must not have any storage receptacle on the pitch other than the shed mentioned in rule 12 above and any receptacle for the storage of domestic waste pending collection by the local authority.\\nEvery home has a designated parking space which is next to the Park Home for up to a maximum of two cars. You must not park more vehicles than your designated car parking space/s allows.\\nAn occupier may move onto the Park with not more than two dogs, or two cats or one dog and one cat—the dogs must not be of any of the breeds subject to the Dangerous Dogs Act 1991—plus any pets or animals which are housed within a cage, aquarium or similar and which remain at all times within your home. Cat and dogs cannot be replaced when they die. The only exception to this rule is for anyone who requires a guide dog or an assistance dog. In such a circumstance all that would be required is a letter from the homeowner\\'s Doctor confirming such a requirement and upon receipt we will provide the written consent without delay.\\nThese rules do not have retrospective effect. If the pet complied with the previous rules, an occupier will not be treated as being in breach when these rules take effect. However, when the pet dies it cannot be replaced except in the case of a guide dog or an assistance dog along the terms detailed in rule 28.<s> Tag: TMNT\\nPosted in Toy Chest Theater\\nToy Chest Theater: TMNT Collection, Vol. 1\\nThe Teenage Mutant Ninja Turtles and their associated characters have been a staple of Toy Chest Theater from the start. So it\\'s only natural they get their own collection. The original 1990 film is heavily represented here. But the cartoons get a chance to shine as well…\\nBebop & Rocksteady by Tim Rodilosso\\nLeonardo by Matthew Cohen.\\nDonatello by morphingtom2.0.\\nTurtles and Mr. Miyagi by noserain.\\nShredder by encoreunclic.\\nTMNT by un1cornwarrior.\\nEmail Rob at primaryignition@yahoo.com, or check us out on Twitter.\\nPosted in Comic Books/Graphic Novels, Weekly Comic 100s\\nWeekly Comic 100s: Superman, TMNT, Something is Killing the Children, and More!\\n***\"Weekly Comic 100s\" keeps it nice and simple. Comic book reviews in 100 words or less. Straight, concise, and to the point.***\\nTITLE: Superman #25\\nAUTHOR: Brian Michael Bendis\\nARTISTS: Ivan Reis, Julio Ferriera & Danny Miki (Inkers), Alex Sinclair (Colorist), Dave Sharpe (Letterer)\\nApparently in the post-New 52 continuity, or whatever continuity we\\'re in right now, Clark Kent and Lana Lang haven\\'t been in touch for awhile. Though apparently she was still Superwoman at one point…\\nFor a couple pages here, Ivan Reis gets to take on Clark\\'s Smallville days. That\\'s pretty cool. Less cool? He also draws the New 52 Superman costume. Though thankfully it looks less like armor.\\nI\\'ll be sad to see Bendis\\' run on the Superman books end in December. He did right by the Man of Steel.\\nTITLE: Teenage Mutant Ninja Turtles #109\\nAUTHOR: Sophie Campbell, Kevin Eastman & Tom Waltz (Story Consultants)\\nARTISTS: Jodi Nishijima, Ronda Pattison (Colorist), Shawn Lee (Letterer)\\nIt continues to amaze me how this book is breaking the mold of what a TMNT story can be. What we\\'ve been getting lately is something more akin to a later issue of The Walking Dead. They\\'re trying to build a new society from the ground up.\\nMichaelangelo, for all intents and purposes, starts a Mutant Town podcast in this issue. That. Is. Genius.\\nTITLE: Something is Killing the Children #10\\nAUTHOR: James Tynion IV\\nARTISTS: Werther Dell\\'Edera, Miquel Muerto\\n\"While you worry about the rules, real people are getting hurt.\"\\nGood line.\\nThis is the first issue of Something is Killing the Children that I think went a little too far with the gore. We actually see a child get murdered in supernatural, yet still pretty brutal, fashion. I still dig the book at large, but that took me right out of the issue.\\nTITLE: Batman: The Adventures Continue #12\\nAUTHOR: Alan Burnett, Paul Dini\\nARTISTS: Ty Templeton, Monica Kubina (Colorist), Josh Reed (Letterer)\\new start getting into the nitty gritty of what the Joker does to Jason Todd in this issue. Harley Quinn is written as having a problem with it. That\\'s the first move Burnett and Dini have made that I really don\\'t buy.\\nI love that for the flashbacks where Jason is Robin, they switched Batman\\'s costume back to the old Batman: The Animated Series design. Great little continuity touch.\\nAll in all, I really like the DCAU spin they\\'ve put on A Death in the Family. And it looks like they\\'re about to stick the landing.\\nWeekly Comic 100s: TMNT Double-Feature, Wonder Woman #759, and More!\\nAUTHOR: Sophie Campbell (Story), Ronda Pattison (Script), Kevin Eastman & Tom Waltz (Story Consultants)\\nARTISTS: Nelson Daniel, Pattison (Colorist), Shawn Lee (Letterer). Variant cover by Eastman.\\nThe Turtles have an \"old days\" moment here where they head down to the sewers and fight a bunch of Mousers. It\\'s just a couple of cutesy lines. But it does serve as a reminder of just how different this series is from the standard TMNT status quo. Instead of four Turtles striking from the shadows, we\\'ve got five Turtles living openly in a town full of mutants.\\nAs they roam the sewers, the Turtles mix it up with what basically amounts to an undersea monster. It\\'s played like a horror movie. Kinda fun.\\nTITLE: TMNT Annual 2020\\nAUTHOR: Tom Waltz\\nARTISTS: Adam Gorham, John Rauch & Michael Garland (Colorists), Shawn Lee (Letterer). Variant cover by Kevin Eastman and Fahriza Kamputra (Colorist).\\nThis annual mainly serves as a check-in with our villains. Most notably Shredder, who we haven\\'t heard much from since issue #100. They color his costume purple and silver, like the old cartoon. I won\\'t complain about that…\\nAs the cover indicates, they\\'re doing a symbiosis story with Krang and Leatherhead. Yet another example of how this series continues to bring these characters into uncharted waters. Given how much has been done with the Ninja Turtles universe, it\\'s pretty amazing to see how much hasn\\'t been done.\\nTITLE: Wonder Woman #759\\nAUTHOR: Mariko Tamaki\\nARTISTS: Mikel Janin, Jordie Bellaire (Colorist), Pat Brosseau (Letterer). Cover by David Marquez.\\nSo we\\'ve got Mariko Tamaki, who wrote Supergirl: Being Super, and Mikel Janin, one of the stars of Tom King\\'s Batman run. On paper, this new team should be great.\\nTheir first issue is pretty ground level. Lots of flowery narration about what a hero is, what heroes do, etc. My only big problem is that Tamaki gives in to the temptation of putting Wondie in an everyday situation, shopping for furniture, and making it seem foreign to her. She\\'s been in \"man\\'s world\" for so long, yet she has no idea how to shop for furniture? Yeah, right.\\nTITLE: Darth Vader #3\\nAUTHOR: Greg Pak\\nARTISTS: Raffaele Ienco, Neeraj Menon (Colorist), Joe Caramagna (Letterer). Cover by Inhyuk Lee.\\nHow many times have we seen Darth Vader cross paths with characters from the prequels and then get all feelingsy? Enough that I rolled my eyes when Captain Typho showed up in this issue.\\nHowever, as someone who read Queen\\'s Shadow by E.K. Johnston, I appreciated the inclusion of Sabe and another character from that book. It\\'s a nice little tie-in that doesn\\'t take anything away from the story being told here.\\nTITLE: Batman: The Adventures Continue #9\\nAUTHORS: Alan Burnett, Paul Dini\\nARTISTS: Ty Templeton, Monica Cubina (Colorist), Joshua Reed (Letterer). Cover by Paolo Rivera & Joe Rivera.\\nIn this issue we finally get into Jason Todd\\'s origin story, his connection to Batman, etc. It\\'s not drastically altered from the comics. But it\\'s altered just enough to distinguish it. I liked what I saw.\\nFrankly, I hope they portray Jason Todd as having been with Batman for only a short time. In the DCAU I\\'d like to see him portrayed more as a tragically failed experiment than a lost son. Again, it would be different. But not so much that it\\'s unrecognizable. That\\'s the formula that seems to work best.\\nTITLE: Mighty Morphin Power Rangers #52\\nAUTHOR: Ryan Parrot\\nARTISTS: Moises Hidalgo, Walter Baiamonte (Colorist), Katia Ranalli (Color Assistant), Ed Dukeshire (Letterer). Cover by Jamal Campbell.\\new\\'re still following Jason, Zack, and Trini, despite the events of this issue occurring after \"The Power Transfer.\" Not a bad thing, but not what I expected either. Especially since they\\'re getting their own book in a few months.\\nI\\'m not sure how I feel about the way Jamal Campbell posed Aisha on the cover. It\\'s like she\\'s showing off her butt or something…\\new introduce a civilian character in this issue who worries about the holding the Rangers accountable for their actions. Sort of a \"don\\'t trust the Power Rangers\" mindset. Very curious to see where that goes.\\nTITLE: Batman/Superman #9\\nAUTHOR: Joshua Williamson\\nARTISTS: Clayton Henry, Alejandro Sanchez (Colorist), John J. Hill (Letterer)\\nIn almost 20 years, I can count the number of Ultra-Humanite stories I\\'ve read on one hand. So this story is cool for me in that sense.\\nThis issue, and this team, have a really nice energy. Joshua Williamson is often hit-or-miss. But he, Clayton Henry, and Alejandro Sanchez make for a winning combination with these characters. Not a perfect combination per se, but a winning one.\\nTITLE: Suicide Squad #7\\nAUTHOR: Tom Taylor\\nARTISTS: Daniel Sampere, Juan Albarran (Inker), Adriano Lucas (Colorist), Wes Abbott (Letterer). Variant cover by Jeremy Roberts.\\nOur Tom Taylor original characters get a new team name in this issue: The Revolutionaries. Not bad. I don\\'t know how much of a life they\\'ll have out from under the Suicide Squad name. But still, not bad.\\nFor at least one issue, Taylor brings Floyd Lawton\\'s young daughter into the sandbox and gives her a a bow and arrow and a hero name: Liveshot. She almost reminds me of a kid version of the Kate Bishop Hawkeye. Interesting…\\nTITLE: Billionaire Island #2\\nAUTHOR: Mark Russell\\nARTISTS: Steve Pugh, Chris Chuckry (Colorist), Rob Steen (Letterer)\\nIt seems that in addition to the absurdly rich, Billionaire Island is home certain rich, famous, and disgraced. We get an actual Kevin Spacey cameo in this issue. Yes, I wretched. But it\\'s also a funny little moment.\\new haven\\'t gotten into the bloodshed yet. But the book does crank up the action a little bit with this issue. Something tells me it\\'s going to be worth the wait.\\nWeekly Comic 100s: Batman, Dead Body Road, TMNT, and More!\\nLast week I said I missed Star Wars and TMNT comics. This week we got the return of Bounty Hunters, and a double-dose of TMNT. Where are you gonna find a more fair friggin\\' deal than that?\\nThis week\\'s new releases are pretty light. So I\\'m holding a few back from last week\\'s pull list. That Texas Blood is one of them. We might also see Marvels Snapshot: Captain America and/or Harley Quin: Black + White + Red.\\nTITLE: Batman #93\\nARTISTS: Guillem March, Javier Fernandez, Tomeu Morey & David Baron (Colorists), Clayton Cowles (Letterer). Cover by Tony Daniel.\\nThe Designer\\'s role in this story more or less wraps up in this issue. That\\'s a little sad, as I liked that character concept. Even if the costume was a little bit much.\\nPunchline, the Joker\\'s new answer to Harley Quinn, gets put over pretty strong here. They obviously want her to be a big deal. She\\'s got an interesting worldview, and it\\'s not as crazy as you might think. Her costume is definitely cosplay-friendly. Not quite as much as Harley, but expect to see her around the convention scene.\\nTITLE: Dead Body Road: Bad Blood #1\\nAUTHOR: Justin Jordan\\nARTISTS: Benjamin Tiesma, Mat Lopes (Colorist), Pat Brosseau (Letterer). Cover by Matteo Scalera & Morena Dinisio.\\nThis issue has a strong hook. For yours truly, most of that has to do with our heroine, Bree Hale. We establish her as a small town girl-next-door type. But obviously she has a history that allows her to kick all kinds of ass and escape perilous situations. She\\'s particularly strong in the climactic sequence as she fights off a sadistic interrogator.\\nMy understanding is this isn\\'t connected with the previous Dead Body Road mini at all, and that it\\'s an anthology book like Criminal. So you should be okay coming in cold.\\nAUTHORS: Sophie Campbell (Script), Kevin Eastman & Tom Waltz (Story Consultants)\\nARTISTS: Campbell, Ronda Pattison (Colorist), Shawn Lee (Letterer).\\nThere\\'s a big moment between Raph and Alopex in this issue that leads me to believe we\\'re headed toward fairly uncharted waters: Romantic interests for the Turtles.\\nAnd no, don\\'t talk about Mitsu in TMNT III. Please.\\nI\\'m game for really putting the Teenage in Teenage Mutant Ninja Turtles. Especially now that they\\'re doing this Mutant Town story. Between the Raph/Alopex scene and the concert setting, this issue really does that well. They\\'ve got a chance to break some new ground here. Let\\'s hope they take it.\\nTITLE:TMNT: Jennika #3\\nAUTHOR: Braham Revel, Ronda Pattison\\nARTISTS: Revel, Jodi Nishijima, Pattison (Colorist), Shawn Lee (Letters).\\nI can\\'t get over how much Braham Revel\\'s style reminds me of the 2012 Nickelodeon show.\\nIt\\'s amazing to think how virtually everything The Next Mutation did wrong with Venus di Milo, IDW has done right with Jennika. Although based on how the IDWverse has been put together, we might actually see Venus in the comics at some point.\\nBebop and Rocksteady show up here. Why does Rocksteady carry an average-sized sledgehammer? It feels like it should be bigger. Mutant-sized. That, or a giant blaster like on the old cartoon.\\nAUTHOR: Ryan Parrott\\nARTISTS: Daniele Di Nicuolo, Walter Baiamonte (Colorist), Katia Ranalli (Color Assistant), Ed Dukeshire (Letterer). Cover by Jamal Campbell.\\nRyan Parrott does Rocky, Adam, and Aisha a lot of justice in these books. That\\'s one of those things that\\'s expected, but still really nice when you actually see it. Rocky is also sans mullet, which I appreciate.\\n\"Necessary Evil\" might have gone a little long. But it was still a story very much worth telling. Well executed too, in terms of both the writing and the visuals.\\nDefinitely a worthy issue #50. And if the cliffhanger at the end is any indication, PR fans are going to want to come back for issue #51.\\nARTISTS: Bruno Redondo, Adriano Lucas (Colorist), Wes Abbott (Letterer). Cover by Redondo & Marcelo Maiolo.\\nThe humor in this issue is on-point. Especially with Batman doing a guest shot. That\\'s a high compliment coming from me, as I don\\'t usually get into Harley-Quinn-style comedy.\\new\\'re teased with a separation of Harley and Deadshot from all the various new characters in the group. That would be interesting, though I expect ultimately a bad move for sales. I\\'d stick around, though. Again, a pretty high compliment from yours truly.\\nTITLE: Star Wars: Bounty Hunters #3\\nAUTHOR: Ethan Sacks\\nARTISTS: Paolo Villanelli, Arif Prianto (Colorist), Travis Lanham (Letterer). Cover by Lee Bermejo.\\nBoba Fett is teased for this issue, but doesn\\'t show. I\\'m curious as to how much of him we\\'ll need to see to keep this series afloat as the months go by. That\\'s not to say characters like Bossk and Valance aren\\'t appealing. But Boba\\'s drawing power is obvious at this point. You could easily make the argument for doing a Boba Fett series, much like the Darth Vader one.\\nI grow a little weary of the story they\\'re telling about all these hunters having a common target. The target in question simply isn\\'t that interesting. Not yet, at least.\\nTMNT: The Movie at 30: Fan Film Inspiration\\nIn my experience, fan films are very hit or miss. And as far as Ninja Turtle fan films go, it\\'s almost always a miss. The reason is very simple: A fan film simply doesn\\'t have the budget to create Turtle costumes that suspend disbelief. It\\'s primarily a lip sync issue. Hell, in a lot of them the mouths don\\'t move at all.\\nBut two TMNT fan films have'"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "doc_id = 0\n",
+    "doc_start, doc_end = d[\"source\"][doc_id][\"start\"], d[\"source\"][doc_id][\"end\"]\n",
+    "print(tokenizer.decode(d[\"input_ids\"][doc_start: doc_end]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "doc_id = 0\n",
+    "doc_start, doc_end = d[\"source\"][doc_id][\"start\"], d[\"source\"][doc_id][\"end\"]\n",
+    "print(tokenizer.decode(d[\"input_ids\"][doc_start: doc_end]))\n",
+    "\n",
+    "doc_id = 1\n",
+    "doc_start, doc_end = d[\"source\"][doc_id][\"start\"], d[\"source\"][doc_id][\"end\"]\n",
+    "print(tokenizer.decode(d[\"input_ids\"][doc_start: doc_end]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Slim"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import json\n",
+    "\n",
+    "file_path = \"/fsx/haojun/Long-Context-Data-Engineering/data/slimpajama/per_source_downsample/slimpajama_packed_128001_5b_per_source_down_sample_0.1.jsonl\"\n",
+    "llama3_tokenizer = AutoTokenizer.from_pretrained(\"/fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'input_ids': [1935, 11191, 7504, 4741, 304, 659, 56536, 555, 21816, 927, 1057, 2362, 4731, 36263, 13, 2030, 1070, 596, 912, 1205, 311, 1450, 2695, 12928, 922, 433, 1389, 279, 32495, 6170, 15039, 527, 264, 17104, 9257, 2592, 315, 3177, 4443, 31710, 323, 1972, 26928, 3217, 11, 7000, 315, 433, 27442, 342, 2808, 398, 1139, 264, 330, 12487, 358, 574, 51975, 1457, 358, 2846, 539, 11, 1867, 1, 3896, 29275, 1688, 279, 1203, 315, 682, 420, 11, 37318, 11, 1070, 596, 264, 2477, 5609, 25, 330, 1991, 6419, 498, 264, 436, 3635, 592, 1245, 3245, 5918, 389, 459, 32180, 523, 45284, 773, 2477, 80437, 57506, 13, 578, 1888, 323, 1455, 8196, 3245, 922, 433, 374, 279, 38094, 287, 27374, 13280, 389, 279, 56910, 11, 279, 12047, 4762, 264, 5679, 4951, 2881, 46450, 902, 43089, 3250, 956, 1935, 12660, 320, 4636, 8530, 420, 374, 369, 279, 1888, 1389, 499, 649, 2733, 1461, 54980, 311, 3350, 264, 8474, 1251, 330, 2181, 596, 813, 23601, 0, 2360, 433, 596, 3604, 264, 5679, 9135, 3839, 11, 902, 2643, 617, 1027, 37224, 561, 398, 570, 358, 2846, 264, 2697, 14792, 433, 596, 1618, 520, 682, 11, 311, 387, 10978, 627, 24633, 45373, 23923, 507, 9691, 38539, 1389, 330, 791, 12015, 88798, 5046, 15037, 1, 350, 53375, 2794, 40915, 46, 3651, 423, 100203, 1389, 330, 51, 648, 362, 26541, 77567, 17535, 578, 10846, 18787, 9119, 1, 125341, 24633, 220, 16, 220, 17, 2052, 198, 47, 7870, 4821, 276, 389, 220, 806, 10263, 220, 1049, 22, 9733, 85415, 1070, 574, 2646, 459, 44088, 48156, 4999, 7, 1271, 10552, 11, 51679, 31886, 578, 67957, 675, 1410, 5128, 1790, 1903, 904, 323, 682, 27211, 46899, 40815, 311, 757, 994, 358, 11352, 433, 13, 7811, 264, 2145, 11217, 323, 4395, 775, 4390, 25763, 389, 220, 806, 10263, 220, 1049, 22, 9733, 3947, 574, 12756, 459, 44088, 48156, 4999, 68724, 389, 220, 806, 10263, 220, 1049, 22, 9733, 9493, 690, 259, 25041, 656, 459, 44088, 8176, 14861, 1772, 5380, 12331, 3757, 385, 3341, 3817, 124232, 389, 220, 806, 10263, 220, 1049, 22, 9733, 20027, 11, 39412, 9004, 435, 24143, 11, 5606, 5380, 51188, 124232, 389, 220, 806, 10263, 220, 1049, 22, 9733, 79, 13559, 89, 514, 597, 91997, 1981, 35047, 5159, 1935, 389, 4673, 15404, 33540, 24368, 374, 264, 29772, 315, 11936, 430, 358, 1053, 2646, 1047, 16584, 311, 49837, 520, 279, 892, 1606, 279, 10255, 320, 8171, 956, 612, 18165, 4618, 1174, 43881, 3816, 10470, 883, 1051, 539, 7155, 3403, 369, 757, 627, 11458, 1070, 527, 1690, 1695, 11936, 430, 358, 42839, 15262, 13, 1115, 4459, 3245, 574, 7263, 1203, 311, 757, 6051, 994, 358, 11021, 320, 502, 883, 264, 4526, 315, 426, 5757, 42258, 277, 613, 13280, 13, 358, 1541, 956, 1781, 358, 3596, 29340, 3235, 311, 264, 3341, 46225, 388, 5609, 3156, 1566, 2046, 627, 4071, 279, 17069, 574, 26310, 3984, 555, 2294, 77315, 289, 7819, 315, 198, 32557, 24823, 689, 13, 362, 14850, 311, 902, 358, 1505, 7182, 15098, 15107, 627, 54, 40232, 124232, 389, 220, 806, 10263, 220, 1049, 22, 9733, 12331, 3757, 385, 1389, 330, 64, 20331, 625, 28391, 369, 264, 47765, 380, 11547, 91712, 635, 18622, 315, 18273, 3925, 1, 7801, 3001, 8840, 11, 369, 31299, 704, 17813, 4999, 75120, 648, 1389, 55379, 288, 369, 220, 4468, 23, 11, 449, 682, 13865, 311, 5766, 66427, 13, 2650, 922, 549, 2434, 323, 10860, 30, 3234, 358, 3243, 264, 45921, 5380, 1, 1991, 6419, 1, 1389, 3092, 1925, 5044, 315, 420, 3245, 374, 25563, 5703, 1694, 4529, 320, 3923, 30, 362, 13471, 304, 220, 4468, 18, 70372, 902, 8967, 430, 350, 91246, 574, 539, 13195, 369, 1790, 315, 279, 4261, 430, 420, 574, 5742, 3861, 13, 358, 1436, 2646, 3619, 3249, 51521, 13558, 1511, 279, 5679, 56203, 311, 7664, 813, 12224, 1981, 358, 649, 1101, 19635, 1694, 304, 264, 30903, 18228, 323, 1701, 279, 1890, 13731, 439, 264, 2697, 10585, 2663, 10058, 13, 10058, 7543, 1120, 922, 279, 4459, 220, 1774, 9568, 18228, 26139, 420, 289, 62837, 5609, 927, 323, 927, 2085, 18579, 13, 358, 574, 1120, 922, 520, 279, 842, 315, 856, 80665, 323, 19261, 369, 264, 9501, 2463, 2320, 347, 304, 2015, 311, 21847, 1461, 320, 906, 16195, 2978, 1077, 9339, 82, 1511, 311, 656, 1521, 2574, 8, 994, 358, 574, 31394, 311, 279, 21004, 11, 5115, 16280, 11, 555, 459, 23205, 58725, 2663, 9939, 1098, 11, 6832, 58229, 12523, 59754, 430, 10058, 330, 23196, 1523, 1, 13118, 13, 24241, 21882, 4999, 9126, 386, 124232, 389, 220, 806, 10263, 220, 1049, 22, 9733, 40, 7995, 71617, 578, 44088, 439, 264, 4156, 369, 46899, 1122, 61555, 520, 279, 892, 1389, 45316, 1288, 387, 3025, 311, 1203, 757, 709, 389, 420, 627, 75120, 648, 124232, 389, 220, 806, 10263, 220, 1049, 22, 9733, 54, 40232, 11, 369, 757, 264, 357, 263, 10789, 1695, 1948, 78611, 5609, 374, 264, 220, 24, 13, 362, 220, 605, 706, 311, 2586, 505, 704, 315, 279, 6437, 323, 1304, 757, 1390, 311, 4498, 927, 11, 923, 2555, 3361, 311, 2555, 430, 596, 2736, 1695, 311, 1633, 1695, 11, 477, 8530, 1524, 387, 264, 89614, 220, 16, 430, 706, 2555, 430, 3727, 433, 86929, 13, 1115, 374, 555, 1648, 315, 5605, 430, 701, 8101, 12483, 220, 777, 704, 315, 264, 3284, 220, 508, 627, 75120, 648, 1389, 362, 4317, 0, 2650, 922, 8662, 4619, 315, 10860, 5380, 47, 7870, 124232, 389, 220, 717, 10263, 220, 1049, 22, 9733, 48527, 55295, 27928, 1070, 6980, 11, 279, 3389, 22084, 552, 527, 264, 17983, 8223, 4038, 3201, 627, 49388, 11, 832, 315, 279, 1401, 3585, 7554, 505, 420, 10430, 374, 279, 393, 598, 9029, 23692, 315, 2175, 6419, 389, 7054, 5046, 578, 393, 3806, 13, 1442, 499, 527, 3815, 264, 12607, 1501, 11, 323, 1390, 311, 1501, 279, 24016, 2191, 315, 30950, 11, 420, 374, 279, 832, 311, 733, 369, 885, 33746, 1494, 11, 5679, 68469, 90578, 396, 8942, 830, 556, 3178, 124232, 389, 220, 717, 10263, 220, 1049, 22, 9733, 40, 4510, 358, 453, 38477, 311, 433, 304, 856, 1176, 4068, 13, 2876, 832, 315, 393, 21051, 2731, 14269, 477, 505, 264, 3722, 9392, 13118, 872, 28807, 627, 98137, 9339, 2834, 956, 387, 52329, 603, 1578, 779, 11, 3041, 477, 1935, 1063, 5509, 323, 539, 779, 5509, 19786, 11, 220, 17, 2294, 17845, 320, 32676, 612, 22408, 1631, 291, 8, 8272, 555, 220, 17, 2360, 13, 16, 17845, 8272, 555, 4696, 14382, 13, 264, 1317, 463, 55535, 5897, 3189, 4134, 430, 4960, 5481, 20262, 1148, 574, 2163, 315, 813, 7076, 323, 1903, 264, 2478, 21866, 1633, 6380, 320, 17206, 3582, 568, 2834, 570, 16782, 568, 2751, 1063, 6555, 7940, 388, 704, 315, 433, 320, 3646, 449, 264, 2466, 480, 389, 1124, 4390, 3841, 544, 289, 124232, 389, 220, 717, 10263, 220, 1049, 22, 9733, 4897, 16181, 264, 2766, 1093, 459, 1536, 275, 3620, 11, 1139, 339, 830, 556, 3178, 0, 12890, 374, 48551, 279, 6560, 323, 14990, 1578, 3010, 420, 1060, 13, 1283, 596, 539, 2728, 709, 11, 3686, 627, 697, 25, 44088, 323, 29515, 11, 358, 71249, 6227, 3060, 279, 452, 7614, 477, 11220, 1094, 41628, 10917, 1124, 389, 279, 3504, 3871, 832, 2046, 627, 1161, 8635, 46092, 297, 596, 37141, 340, 50988, 124232, 389, 220, 777, 10263, 220, 1049, 22, 9733, 40, 1781, 358, 2846, 264, 2766, 3389, 311, 279, 4717, 1618, 11, 719, 358, 1120, 1518, 279, 4673, 15404, 33540, 24368, 4101, 439, 264, 6140, 311, 35883, 1063, 7060, 2477, 320, 438, 14224, 1063, 62024, 11, 11911, 8, 430, 596, 1027, 36451, 291, 927, 555, 279, 23479, 11346, 315, 9305, 13, 578, 44916, 38586, 82, 369, 1455, 32949, 388, 11, 323, 1690, 315, 279, 5017, 552, 11035, 3258, 312, 59326, 320, 266, 3325, 389, 11119, 220, 16, 8, 1053, 2646, 636, 872, 45547, 1427, 3502, 13, 358, 3152, 11, 578, 11246, 8699, 1047, 5946, 757, 555, 6724, 90578, 2181, 682, 706, 264, 421, 3168, 315, 1633, 220, 1954, 82, 281, 16279, 330, 2534, 88, 498, 14224, 11, 719, 8530, 279, 3445, 1541, 956, 2744, 5030, 627, 40, 3358, 2980, 86235, 422, 568, 9711, 330, 44503, 5657, 72417, 1, 555, 27789, 339, 1108, 82, 389, 813, 1828, 29772, 627, 53263, 12174, 323, 1120, 311, 387, 85077, 398, 10696, 8322, 1389, 422, 584, 527, 311, 2997, 11119, 220, 18, 315, 24618, 1243, 8527, 56652, 374, 279, 1176, 2360, 13, 16, 311, 387, 20276, 59162, 11663, 2574, 358, 1755, 311, 1518, 389, 24618, 11119, 220, 19, 512, 2654, 462, 5770, 47643, 306, 5770, 1389, 2394, 285, 967, 37737, 729, 7304, 3457, 355, 337, 198, 5519, 1286, 1065, 1389, 10919, 5046, 3092, 9601, 198, 47, 8788, 10690, 1389, 3216, 763, 362, 393, 1386, 5046, 54304, 198, 1951, 68, 423, 13972, 1389, 35081, 90590, 198, 79315, 49195, 1389, 90422, 1472, 11697, 19332, 2206, 23565, 26997, 198, 50, 607, 269, 1389, 3861, 48573, 25619, 9176, 198, 42315, 3092, 28607, 1389, 1102, 38707, 9220, 2057, 99448, 198, 42315, 44954, 1389, 12040, 2057, 578, 41114, 198, 9688, 541, 648, 1389, 3053, 1472, 3234, 1102, 198, 50, 7792, 1389, 1050, 447, 27960, 198, 9023, 455, 72, 1389, 650, 2172, 45899, 198, 697, 16588, 1389, 9601, 2209, 362, 9305, 320, 4071, 578, 13792, 94491, 2206, 340, 41, 33361, 3341, 47789, 1389, 40710, 88, 386, 16771, 198, 56, 258, 612, 25191, 1389, 2030, 331, 61731, 198, 1453, 716, 10522, 1389, 10699, 596, 480, 13767, 10919, 2206, 5380, 36, 747, 13789, 391, 20430, 1389, 15037, 1556, 79716, 38300, 198, 20027, 1098, 10690, 1389, 5659, 578, 7054, 5046, 3092, 11452, 198, 1163, 261, 1389, 362, 25525, 596, 15457, 198, 43, 4202, 648, 445, 29008, 612, 279, 56147, 70045, 1389, 30088, 2303, 19397, 198, 4054, 88370, 31816, 612, 362, 79976, 1389, 1102, 8442, 38707, 362, 56267, 198, 43, 59009, 1389, 36416, 21270, 198, 12301, 894, 274, 124232, 389, 220, 508, 10263, 220, 1049, 22, 9733, 3852, 2664, 315, 264, 3738, 4325, 889, 1587, 539, 21901, 398, 19635, 330, 1991, 6419, 1, 2011, 617, 1047, 264, 326, 94623, 20587, 1981, 7, 269, 264, 81292, 832, 8, 90578, 56, 258, 323, 25191, 596, 330, 4071, 331, 61731, 1, 574, 304, 2144, 279, 426, 6354, 579, 311, 872, 41040, 1935, 315, 264, 3335, 584, 690, 387, 25394, 304, 220, 4468, 20, 627, 43, 7304, 124232, 389, 220, 1691, 10263, 220, 1049, 22, 9733, 40, 3077, 7111, 520, 279, 4673, 15404, 33540, 24368, 94601, 1578, 323, 1097, 22568, 922, 3249, 1070, 527, 912, 11936, 555, 279, 9332, 4409, 15028, 388, 12660, 13, 8886, 814, 264, 2536, 2427, 84, 15404, 17069, 320, 276, 25226, 832, 87527, 2746, 430, 596, 279, 1890, 330, 43, 9308, 1472, 11697, 19332, 2206, 23565, 26997, 1, 1243, 358, 6755, 433, 682, 279, 892, 389, 2999, 13, 423, 76384, 627, 43824, 21115, 124232, 389, 220, 1313, 10263, 220, 1049, 22, 9733, 4516, 11, 16390, 72974, 1694, 4856, 1664, 9960, 520, 420, 1486, 320, 40, 1781, 8529, 323, 49971, 385, 32095, 433, 369, 757, 1389, 279, 4751, 374, 15538, 1606, 433, 34744, 389, 701, 34194, 311, 11205, 523, 8742, 15858, 2461, 315, 264, 6222, 19775, 705, 358, 3358, 2567, 311, 4491, 13, 507, 13575, 37141, 11, 7000, 315, 6832, 990, 358, 3077, 3596, 6755, 1603, 32495, 13, 1666, 3117, 439, 358, 649, 3371, 568, 596, 13524, 264, 8013, 33374, 31031, 11, 10035, 30, 18024, 81575, 810, 7347, 2134, 11, 719, 1890, 2814, 22288, 11440, 27894, 273, 8674, 4367, 11, 9061, 33936, 11, 99553, 6548, 30, 358, 1093, 1521, 11936, 5128, 1695, 11, 323, 330, 1991, 6419, 1, 5084, 311, 757, 279, 1888, 315, 279, 15860, 779, 3117, 13, 58038, 9903, 0, 2684, 596, 264, 71820, 683, 30973, 2136, 311, 279, 25695, 3839, 11, 902, 358, 2846, 2744, 264, 94888, 369, 11, 323, 279, 67610, 389, 330, 1981, 8248, 358, 2103, 1390, 499, 2212, 9135, 374, 439, 86605, 264, 3245, 499, 1436, 3596, 2610, 369, 627, 6349, 4881, 369, 279, 8965, 93504, 323, 2536, 19440, 4367, 315, 279, 24142, 1389, 1587, 279, 8415, 389, 279, 4106, 25826, 15485, 1205, 311, 387, 304, 1070, 30, 578, 4459, 2766, 922, 16558, 1063, 13378, 892, 5900, 28211, 11, 539, 1524, 439, 459, 56203, 369, 1268, 568, 11321, 1457, 477, 4205, 1093, 430, 13, 1283, 2643, 439, 1664, 6420, 430, 568, 3131, 13234, 264, 28326, 875, 13, 1115, 5609, 5334, 2731, 279, 2753, 15499, 433, 596, 34793, 311, 11, 719, 1202, 54169, 1918, 374, 1790, 2731, 13609, 1109, 11, 2019, 330, 1163, 404, 3368, 921, 404, 3368, 8602, 752, 8602, 752, 21230, 82, 323, 433, 596, 264, 2731, 5609, 369, 433, 627, 2181, 1253, 387, 11190, 311, 1440, 430, 279, 1925, 10383, 4920, 46092, 596, 69435, 4477, 574, 11, 323, 4762, 2103, 374, 11, 61352, 8384, 11118, 26, 1518, 330, 46, 2319, 86637, 4657, 423, 2689, 86637, 4657, 6187, 1, 320, 269, 7344, 539, 8, 369, 264, 88018, 30816, 315, 420, 627, 40, 1781, 433, 596, 5128, 31439, 3582, 26, 2728, 430, 568, 374, 33630, 323, 8530, 1101, 264, 2697, 85161, 555, 813, 5679, 11, 279, 330, 4719, 1, 374, 264, 1695, 323, 6913, 56203, 315, 813, 1510, 14604, 2361, 11, 719, 279, 330, 1712, 6458, 483, 1, 42285, 1193, 2216, 4375, 422, 832, 2289, 279, 76082, 1665, 311, 264, 4856, 653, 325, 336, 398, 46450, 11, 602, 1770, 13, 3131, 568, 574, 4579, 385, 974, 323, 27555, 1949, 719, 1457, 568, 596, 17791, 1523, 555, 420, 11, 4543, 11, 5679, 11, 323, 8530, 584, 4265, 2731, 539, 733, 1523, 430, 5213, 398, 13318, 5754, 90578, 791, 8013, 33374, 31031, 4536, 956, 264, 3958, 12593, 1486, 11, 3582, 46315, 56721, 374, 11000, 264, 2731, 5052, 320, 708, 430, 330, 1991, 6419, 1, 9221, 813, 330, 12755, 9029, 4063, 3582, 358, 1288, 1486, 704, 430, 14188, 315, 1521, 39575, 58909, 6137, 872, 7076, 26435, 304, 2978, 17627, 2107, 323, 2875, 68776, 439, 46092, 1550, 709, 3156, 330, 2149, 606, 14077, 1, 1981, 1820, 4623, 1694, 430, 568, 3463, 568, 4265, 636, 7634, 422, 568, 7111, 279, 2167, 323, 25685, 14329, 315, 1268, 16470, 775, 7111, 304, 364, 3076, 14, 2031, 90578, 43824, 21115, 124232, 389, 220, 1691, 17907, 220, 1049, 22, 9733, 1277, 1129, 2185, 20751, 916, 27305, 23856, 28, 22, 87, 31916, 42, 16417, 36, 71, 20, 48, 1389, 11233, 596, 9029, 61583, 449, 264, 15860, 315, 3974, 12875, 16785, 311, 330, 1991, 6419, 1210, 36287, 1063, 13016, 1618, 2643, 15763, 433, 90578, 75, 17872, 124232, 389, 220, 23, 5020, 220, 1049, 22, 9733, 4919, 499, 3371, 757, 1148, 342, 321, 655, 2709, 360, 28422, 374, 3815, 1457, 323, 374, 568, 2133, 311, 656, 904, 810, 47679, 198, 3841, 544, 289, 124232, 389, 220, 23, 5020, 220, 1049, 22, 9733, 5520, 6560, 7364, 3649, 649, 387, 1766, 1618, 512, 1277, 1129, 2185, 1326, 321, 9339, 437, 37141, 5181, 6018, 14172, 569, 270, 96101, 389, 220, 1187, 3297, 220, 1049, 23, 9733, 791, 4731, 315, 46092, 507, 13575, 37141, 574, 389, 304, 2035, 315, 350, 91246, 2391, 813, 2132, 2046, 520, 1396, 832, 11, 568, 29340, 420, 5609, 1176, 11, 279, 393, 598, 9029, 5679, 15612, 574, 389, 865, 7044, 1938, 11, 1587, 568, 2216, 7936, 358, 1541, 956, 3041, 264, 27860, 11, 439, 430, 3492, 374, 1511, 304, 279, 1828, 1396, 832, 627, 61887, 9339, 636, 1523, 124232, 389, 220, 1544, 3297, 220, 1049, 23, 9733, 96332, 13280, 8176, 304, 279, 386, 28165, 4592, 220, 1135, 79, 31741, 304, 279, 3389, 220, 1954, 82, 11, 323, 5737, 636, 1523, 1578, 323, 1578, 7109, 1129, 69, 1127, 88, 18975, 6973, 15549, 14, 728, 14, 1049, 22, 14, 2589, 4951, 321, 9339, 83528, 37141, 23304, 15220, 48848, 893, 889, 690, 15508, 279, 18118, 1389, 1115, 374, 7295, 29860, 791, 80250, 315, 279, 57678, 29860, 374, 1268, 473, 41, 126459, 626, 5230, 648, 124232, 389, 220, 1313, 2947, 220, 679, 16, 9733, 7749, 17343, 6830, 12279, 647, 24169, 11, 719, 2294, 369, 279, 1890, 8125, 627, 9126, 480, 124232, 389, 220, 1313, 2947, 220, 679, 16, 9733, 61011, 326, 17872, 3287, 956, 1524, 2019, 9523, 11, 1524, 3582, 12149, 54, 19089, 4661, 7214, 25, 674, 3487, 323, 674, 3226, 340, 17316, 6388, 82773, 124232, 389, 220, 1313, 2947, 220, 679, 16, 9733, 8100, 574, 10371, 922, 342, 321, 655, 2709, 360, 28422, 11, 3582, 627, 20027, 411, 1122, 124232, 389, 220, 1627, 5033, 220, 679, 16, 9733, 10156, 311, 5225, 10466, 360, 27771, 311, 264, 13726, 12279, 321, 9339, 507, 13575, 37141, 7057, 3814, 389, 18588, 19, 420, 11714, 11, 264, 5643, 8272, 555, 264, 21497, 5178, 16662, 11, 2781, 11, 11517, 409, 12649, 876, 627, 9126, 480, 124232, 389, 220, 1627, 5033, 220, 679, 16, 9733, 76702, 304, 2579, 11, 636, 1523, 627, 53692, 11, 430, 3460, 8838, 36050, 433, 4999, 68517, 47, 13634, 389, 220, 1627, 5033, 220, 679, 16, 9733, 2096, 25, 358, 3463, 5127, 7020, 922, 1268, 69593, 27211, 46899, 527, 449, 279, 44088, 682, 279, 1648, 505, 8683, 7281, 1293, 3339, 364, 76094, 288, 6, 1022, 364, 13613, 91485, 6, 1778, 264, 2466, 3839, 304, 279, 4113, 37401, 412, 3130, 520, 52939, 7586, 438, 315, 36704, 304, 220, 3753, 23, 311, 1566, 1667, 20632, 8176, 1990, 578, 44088, 323, 20851, 480, 9672, 414, 364, 66761, 416, 328, 65733, 6, 320, 40345, 57222, 264, 45077, 8176, 422, 499, 3041, 433, 892, 4390, 6153, 682, 3131, 62724, 704, 439, 584, 1440, 433, 1457, 1047, 11721, 1148, 810, 1550, 499, 1205, 1109, 264, 2478, 27211, 46899, 11, 350, 4091, 483, 18308, 323, 44088, 28785, 311, 2567, 499, 29921, 31467, 12222, 279, 74862, 9107, 627, 66320, 12550, 389, 220, 17, 3799, 220, 679, 18, 9733, 40, 36297, 1541, 956, 1781, 358, 3077, 6755, 264, 3254, 3839, 389, 430, 1176, 4673, 15404, 33540, 24368, 29772, 627, 7, 2520, 5905, 11, 358, 574, 9405, 304, 220, 3753, 20, 323, 856, 30758, 350, 91246, 5044, 574, 38807, 315, 5464, 1389, 2052, 3011, 3005, 78578, 304, 7474, 220, 2550, 18, 29275, 5159, 6699, 1051, 2225, 304, 279, 12314, 315, 872, 27294, 555, 330, 3409, 498, 719, 3508, 433, 574, 19514, 785, 477, 13000, 50054, 320, 2000, 1457, 11, 58817, 430, 832, 922, 279, 6857, 315, 14198, 6548, 430, 4536, 956, 555, 279, 393, 540, 1157, 705, 2225, 49890, 311, 15763, 11670, 5609, 26372, 323, 100226, 3485, 32596, 331, 14638, 477, 75873, 875, 894, 497, 810, 704, 315, 834, 13014, 304, 279, 24618, 3157, 1109, 1972, 330, 8890, 3036, 10246, 75, 606, 79, 321, 87197, 389, 220, 24, 12044, 220, 679, 24, 9733, 44680, 420, 892, 264, 4333, 315, 856, 6699, 13234, 480, 8548, 13575, 3766, 8176, 320, 1897, 40328, 93610, 8, 323, 358, 1766, 430, 14470, 24729, 439, 4092, 4731, 13, 35802, 505, 813, 30758, 13280, 813, 4731, 5084, 311, 25760, 369, 11537, 27065, 4856, 1109, 4205, 810, 29722, 13, 1283, 706, 810, 304, 4279, 449, 91493, 304, 430, 5201, 8051, 2225, 2873, 311, 617, 2884, 872, 1888, 990, 994, 79342, 4814, 13, 1666, 369, 420, 11, 539, 264, 16390, 17069, 11, 810, 264, 34951, 1949, 757, 71, 627, 55088, 78317, 389, 220, 1032, 12044, 220, 679, 24, 9733, 61, 40, 3021, 430, 2132, 8176, 320, 3792, 311, 15248, 8, 323, 4216, 1474, 307, 220, 2031, 82, 46092, 304, 4689, 11, 323, 6420, 315, 279, 3335, 439, 4092, 4731, 320, 438, 555, 3771, 70, 2933, 439, 364, 6518, 27609, 56009, 4228, 14624, 873, 1120, 35710, 757, 1268, 358, 4265, 3021, 369, 46092, 311, 37771, 264, 10016, 23074, 1742, 364, 708, 1790, 1070, 4920, 279, 72413, 62716, 6, 1742, 58003, 652, 92120, 13, 11291, 4923, 616, 944, 11, 2288, 11, 6832, 1866, 1472, 2351, 264, 21270, 374, 439, 11364, 439, 70408, 14077, 320, 45, 72247, 705, 323, 6832, 34544, 4731, 14321, 91442, 5751, 51965, 596, 25531, 65624, 374, 1093, 264, 17355, 13890, 311, 1063, 315, 279, 3752, 32505, 5105, 55798, 389, 66569, 11, 902, 358, 4265, 3254, 704, 439, 46092, 596, 1888, 8176, 320, 1820, 62387, 54371, 60700, 307, 6729, 51224, 1694, 369, 757, 813, 28807, 5609, 323, 832, 315, 279, 11639, 596, 28807, 3703, 61652, 2477, 7576, 570, 2030, 1243, 279, 810, 11412, 78397, 65821, 14269, 505, 1521, 4216, 28785, 11, 1093, 6186, 21804, 11, 2543, 709, 369, 757, 389, 2574, 1093, 279, 43361, 44851, 596, 362, 25525, 315, 279, 4435, 11, 23377, 813, 10383, 706, 1027, 30666, 40054, 93583, 627, 1991, 6419, 374, 505, 279, 4948, 8176, 11, 358, 2846, 264, 30504, 11, 2876, 264, 42667, 11, 902, 1306, 1403, 28785, 430, 29447, 12616, 1990, 297, 316, 2320, 1494, 81821, 323, 29050, 925, 28904, 574, 264, 2697, 2753, 8205, 1501, 323, 810, 315, 264, 17371, 16387, 311, 279, 3115, 11, 2555, 568, 31890, 70903, 449, 6984, 311, 15248, 13, 358, 15562, 279, 2144, 568, 1457, 91713, 1253, 617, 6476, 264, 961, 304, 430, 11, 719, 433, 574, 279, 7314, 315, 279, 842, 439, 3117, 439, 813, 8518, 2450, 574, 11920, 13, 26924, 279, 8176, 374, 11670, 46092, 323, 4376, 315, 433, 374, 3441, 64519, 27205, 69392, 430, 11, 539, 27393, 449, 11, 2019, 11, 578, 4656, 14208, 369, 10535, 2136, 11, 374, 2103, 682, 8314, 73048, 323, 1314, 11, 8104, 279, 92032, 2876, 304, 264, 34629, 23116, 13, 7429, 11, 279, 3335, 596, 4376, 21925, 5737, 892, 3445, 433, 3250, 956, 704, 60021, 1202, 10788, 323, 27656, 439, 18434, 19995, 439, 1202, 21933, 398, 58919, 37253, 11, 1524, 422, 11, 2133, 1203, 311, 4923, 616, 944, 11, 1202, 6762, 311, 2019, 430, 46092, 596, 502, 2802, 304, 3776, 2477, 3250, 956, 5662, 279, 36394, 315, 23588, 1952, 311, 10919, 627, 80303, 311, 15803, 701, 6170, 1541, 956, 636, 13160, 439, 26396, 29275, 2746, 420, 574, 1396, 220, 16, 994, 499, 1051, 9405, 25982, 510, 267, 672, 86003, 60, 477, 510, 267, 672, 63970, 60, 1139, 279, 1212, 315, 701, 4068, 90163, 17117, 12948, 320, 7927, 2613, 2686, 690, 539, 387, 4756, 340, 40, 2846, 4477, 922, 1475, 6560, 1396, 832, 3254, 11, 304, 2015, 13, 1102, 596, 4529, 264, 1418, 11, 433, 3358, 1935, 264, 1418, 5129, 13, 69985, 2212, 304, 279, 39104, 11, 477, 5249, 304, 449, 279, 3678, 73312, 788, 15860, 315, 4068, 388, 584, 3077, 9152, 311, 9504, 482, 502, 24196, 2744, 1633, 10788, 4999, 59552, 374, 24853, 555, 279, 65352, 315, 856, 66212, 52860, 13, 2435, 636, 4216, 8158, 11, 14079, 3769, 11, 323, 810, 13, 1472, 1436, 387, 832, 315, 1124, 4999, 1581, 315, 8544, 323, 12483, 779, 3117, 198, 59552, 49667, 56147, 320, 64, 4288, 1772, 340, 3337, 55136, 30442, 21709, 0, 578, 30242, 1285, 1628, 578, 20267, 2194, 220, 914, 4448, 220, 679, 20, 1226, 19487, 584, 8434, 956, 3350, 922, 279, 81225, 88, 31391, 674, 16, 20303, 315, 220, 679, 19, 904, 810, 11, 719, 91145, 264, 79433, 18954, 17195, 94407, 3651, 26339, 20303, 706, 2586, 3235, 369, 603, 311, 90578, 33787, 23116, 763, 18165, 49195, 220, 868, 17907, 220, 679, 18, 18165, 1667, 4227, 16986, 11, 358, 3940, 4477, 264, 3477, 315, 1708, 8290, 3394, 596, 330, 8586, 763, 3092, 18449, 3343, 358, 4265, 2646, 6755, 279, 1176, 6560, 5742, 3861, 11, 323, 9523, 311, 393, 17, 47, 14488, 358, 90578, 3923, 15148, 358, 53389, 30, 320, 5920, 220, 16, 8, 220, 24, 3799, 220, 679, 16, 11450, 596, 393, 19680, 380, 3330, 482, 709, 1457, 520, 46676, 45838, 482, 374, 279, 1566, 832, 25, 264, 5597, 11622, 4529, 555, 757, 11, 5115, 264, 1418, 4227, 13, 21347, 3025, 311, 3041, 709, 264, 12798, 90578, 44, 1846, 715, 7476, 482, 330, 25099, 1, 220, 1627, 5186, 220, 679, 20, 330, 21364, 4459, 7076, 596, 1027, 1093, 11, 14346, 11, 814, 2351, 279, 58930, 1732, 315, 279, 4545, 11, 358, 3358, 990, 449, 1124, 311, 1304, 757, 14992, 13, 2435, 2351, 1701, 499, 1210, 482, 98408, 327, 36047, 389, 81669, 11, 220, 1049, 16, 84341, 198, 3923, 15148, 358, 53389, 30, 320, 5920, 220, 17, 8, 220, 24, 3799, 220, 679, 16, 82117, 279, 58298, 4633, 4920, 10826, 80645, 27076, 2045, 315, 264, 15438, 3330, 389, 264, 5526, 4731, 3997, 0, 1102, 596, 393, 19680, 380, 220, 845, 12, 966, 0, 220, 845, 13, 25218, 578, 42206, 5046, 362, 423, 7169, 8219, 25, 13596, 832, 682, 922, 29159, 11, 90578, 59552, 29016, 13131, 25, 220, 679, 23, 482, 480, 22983, 2175, 6419, 1952, 6740, 220, 18, 4448, 220, 679, 24, 3296, 9974, 14135, 11, 856, 33407, 482, 1888, 311, 12047, 482, 315, 279, 1060, 596, 6560, 1396, 832, 13280, 11, 449, 2926, 11555, 482, 1633, 2926, 11, 358, 4265, 6755, 1193, 832, 315, 1521, 1603, 90578, 790, 46277, 482, 330, 46484, 23019, 1, 611, 330, 1305, 3359, 88, 1, 220, 966, 5033, 220, 679, 19, 1115, 374, 279, 1176, 32495, 4441, 358, 3077, 5439, 304, 279, 16642, 69766, 13, 1628, 1418, 433, 5828, 956, 264, 2466, 4295, 1523, 1234, 1389, 477, 11, 358, 1781, 11, 12660, 3734, 279, 6560, 1389, 90578, 2152, 8429, 423, 1294, 482, 330, 39787, 94666, 1, 220, 1691, 3297, 220, 679, 18, 358, 1288, 2019, 505, 279, 68864, 11, 358, 2846, 653, 20489, 2915, 21901, 315, 420, 3335, 13, 330, 1844, 20489, 2915, 1, 539, 1606, 433, 596, 264, 3958, 5609, 477, 364, 8890, 15404, 17069, 518, 719, 1606, 433, 596, 539, 264, 3335, 358, 1390, 90578, 25763, 36592, 81225, 88, 31391, 389, 264, 5951, 11879, 304, 279, 5209, 12, 1954, 82, 13, 362, 2199, 922, 1148, 568, 596, 709, 311, 649, 387, 1766, 1618, 198, 11787, 499, 2254, 5380, 1032, 13806, 220, 1049, 15, 9635, 374, 69649, 643, 1863, 320, 269, 23893, 422, 499, 1390, 311, 387, 48887, 8, 311, 17277, 775, 369, 1690, 8125, 11, 719, 832, 374, 1606, 1057, 4731, 330, 71864, 1, 320, 275, 596, 539, 459, 5064, 1389, 3339, 41778, 27994, 374, 459, 5064, 11, 323, 19093, 1587, 26336, 304, 872, 24804, 892, 11, 14238, 8571, 89, 1572, 922, 433, 477, 706, 1124, 44033, 927, 5694, 520, 55344, 13, 126459, 4006, 50456, 50456, 5660, 5660, 5660, 23440, 87664, 87664, 52, 2864, 50, 17523, 4999, 24, 4448, 220, 1049, 19, 44177, 6187, 13, 53296, 956, 433, 3678, 73312, 788, 30, 21670, 33607, 13113, 33607, 1095, 596, 5622, 279, 97787, 323, 1884, 44656, 552, 0, 3011, 596, 279, 3169, 315, 81436, 358, 72306, 505, 856, 12631, 0, 30070, 279, 37219, 10077, 1414, 709, 555, 30230, 1120, 311, 5622, 45974, 42917, 13, 11208, 596, 279, 42129, 1169, 88, 11, 279, 1989, 11, 279, 4864, 841, 63762, 75249, 13118, 922, 430, 30, 10699, 34672, 994, 584, 617, 628, 10279, 23757, 126459, 11859, 4435, 11098, 220, 679, 23, 25, 5856, 362, 14484, 220, 16, 198, 1114, 12044, 220, 679, 23, 1102, 596, 1618, 0, 578, 8736, 1847, 315, 279, 10466, 4435, 11098, 14035, 279, 3116, 7411, 315, 5856, 362, 19054, 279, 46866, 389, 279, 16520, 13, 10466, 9141, 26905, 8524, 323, 73390, 3449, 1403, 10989, 5415, 1389, 15212, 323, 18387, 23931, 1389, 449, 2753, 315, 264, 3335, 520, 420, 2237, 13, 10699, 690, 66828, 30, 1472, 10491, 13, 41637, 27889, 323, 126459, 644, 2778, 315, 328, 87740, 1389, 3744, 1403, 198, 18, 5020, 220, 1049, 19, 763, 2778, 315, 328, 87740, 1389, 3744, 1403, 320, 19464, 11, 5727, 21154, 5448, 8, 4427, 315, 499, 1253, 6227, 420, 4652, 358, 6267, 1063, 892, 4227, 922, 856, 330, 30039, 1, 439, 264, 46482, 323, 856, 2271, 369, 279, 2204, 13, 8489, 11, 358, 3077, 2884, 433, 13, 328, 87740, 1047, 3719, 264, 2766, 315, 459, 49635, 11, 358, 4265, 62920, 709, 682, 21522, 315, 12584, 1065, 320, 29185, 1122, 126459, 5159, 21189, 9877, 13896, 10349, 5736, 605, 2947, 220, 679, 20, 1115, 374, 264, 1772, 15182, 279, 7576, 358, 2846, 14624, 311, 369, 856, 52005, 3083, 79620, 47905, 98319, 439, 33740, 1618, 320, 10453, 323, 3347, 291, 505, 44699, 1680, 358, 2846, 2133, 311, 9020, 311, 832, 8176, 389, 264, 3131, 7561, 11477, 8197, 369, 264, 2046, 11, 264, 2204, 832, 1855, 2046, 13, 2876, 304, 2015, 311, 3350, 922, 1124, 477, 4205, 11, 7389, 358, 10491, 358, 126459, 2818, 10483, 76275, 1389, 330, 34, 3397, 763, 578, 22862, 364, 3534, 1, 611, 330, 23958, 10180, 578, 12424, 1472, 9372, 55314, 702, 1544, 2947, 220, 679, 19, 7357, 32495, 4441, 8638, 449, 279, 1890, 3488, 25, 3249, 420, 3335, 30, 1115, 892, 433, 596, 5423, 17813, 13, 330, 34, 3397, 763, 578, 22862, 364, 3534, 1, 374, 279, 8592, 48724, 3254, 315, 682, 892, 304, 279, 6560, 11, 4661, 220, 17, 3610, 2867, 315, 1202, 24379, 43940, 13, 1115, 374, 439, 2466, 439, 2477, 5334, 13, 2030, 330, 35734, 7673, 2643, 13471, 499, 439, 264, 30571, 3488, 126459, 50, 5511, 36526, 50, 22469, 469, 4735, 36526, 50, 48818, 25, 8595, 14880, 35454, 9698, 7784, 956, 29565, 198, 16, 17907, 220, 1049, 17, 3165, 13572, 25, 51940, 11, 24877, 398, 2697, 4742, 5153, 902, 2873, 709, 311, 912, 1695, 1389, 21363, 304, 279, 9309, 315, 701, 3130, 11, 9564, 82020, 2212, 1120, 311, 1304, 264, 9622, 1389, 8659, 449, 872, 1866, 18909, 13, 2876, 279, 1455, 8196, 17661, 311, 2385, 264, 4632, 389, 13, 14968, 17681, 4780, 311, 279, 7057, 315, 63236, 1475, 5899, 1667, 477, 126459, 50, 4069, 1846, 507, 6, 74667, 878, 1389, 330, 24714, 13620, 5518, 220, 17, 549, 702, 1682, 5020, 220, 679, 15, 328, 483, 329, 507, 86265, 374, 832, 315, 279, 28807, 5609, 18412, 5153, 539, 1120, 1606, 1364, 15849, 2653, 922, 279, 3769, 323, 279, 16024, 16447, 304, 433, 11, 719, 1606, 1364, 596, 779, 1695, 520, 25012, 11936, 1139, 264, 6671, 13, 362, 2294, 3187, 315, 420, 374, 1077, 2373, 315, 330, 1163, 5118, 275, 6388, 498, 8369, 323, 5105, 989, 1405, 14469, 7209, 596, 374, 97374, 2453, 780, 11, 25935, 1202, 66333, 126459, 11663, 4668, 8158, 8345, 128000, 1729, 8269, 61582, 198, 4235, 389, 10263, 220, 2318, 11, 220, 1049, 17, 198, 8142, 279, 20303, 2626, 374, 28456, 264, 39487, 4435, 30387, 15020, 2017, 11, 358, 3077, 1027, 709, 311, 912, 1695, 11, 12155, 287, 2212, 279, 5064, 596, 16174, 40430, 323, 52067, 709, 701, 85612, 627, 14262, 311, 279, 2132, 17496, 46698, 479, 315, 445, 7169, 763, 578, 52683, 5153, 11, 264, 58587, 323, 14322, 414, 3330, 13788, 279, 20303, 2363, 5064, 482, 477, 520, 279, 3325, 279, 9660, 430, 1304, 1695, 7493, 13, 578, 9629, 13001, 389, 1855, 3446, 527, 856, 5097, 389, 872, 31638, 13, 7997, 15714, 499, 1440, 358, 4510, 433, 11, 47764, 1095, 596, 499, 1440, 358, 88565, 1070, 596, 2555, 304, 433, 15038, 11, 3816, 15714, 499, 1440, 358, 1781, 433, 596, 5115, 11000, 52401, 13, 2030, 1243, 499, 2646, 1440, 13, 578, 13001, 527, 1120, 459, 28137, 482, 3250, 956, 3152, 264, 2579, 649, 956, 387, 837, 323, 264, 6307, 649, 956, 387, 905, 13, 12040, 4395, 499, 1373, 449, 264, 15994, 1285, 315, 12290, 482, 323, 422, 499, 656, 95287, 2038, 1618, 18403, 11, 4587, 2997, 264, 10163, 311, 430, 2515, 627, 3112, 264, 5665, 14224, 13, 3639, 656, 499, 1781, 358, 1097, 11, 1903, 315, 13280, 5380, 5876, 1600, 33393, 13575, 74823, 57318, 4534, 31832, 5380, 791, 3446, 430, 574, 2133, 4883, 279, 20303, 8882, 52252, 62301, 420, 2046, 323, 9508, 311, 39897, 927, 1139, 279, 39487, 4435, 25, 10780, 21977, 374, 430, 13142, 1229, 1157, 2649, 374, 1234, 1972, 7410, 520, 990, 505, 1403, 64490, 482, 1176, 505, 813, 1866, 42847, 11, 323, 2132, 398, 505, 7671, 72, 1676, 329, 520, 872, 17681, 9046, 13, 1115, 374, 1523, 311, 1148, 814, 1518, 439, 20784, 23726, 11, 54291, 2883, 4339, 323, 813, 586, 293, 875, 4776, 449, 11162, 35156, 323, 11511, 10172, 11, 539, 311, 6420, 813, 39599, 7543, 389, 279, 5000, 13, 1628, 279, 17681, 3185, 5084, 264, 2697, 9525, 291, 1022, 430, 1229, 1157, 2649, 706, 1027, 6755, 311, 387, 21039, 6807, 369, 1790, 315, 279, 330, 74008, 31251, 1, 2450, 13, 1628, 439, 264, 1121, 315, 682, 420, 11, 13142, 1229, 1157, 2649, 1253, 387, 12504, 13, 1628, 422, 4400, 775, 11, 622, 35262, 323, 1229, 1157, 2649, 617, 1027, 3309, 311, 11203, 1022, 11162, 35156, 11, 11511, 10172, 323, 279, 1093, 13, 5513, 640, 64, 5068, 430, 304, 279, 22883, 7090, 11, 1229, 1157, 2649, 15164, 1521, 66025, 627, 4071, 1095, 596, 1427, 264, 2697, 19662, 13, 8442, 264, 2697, 4059, 13, 2684, 617, 1027, 11028, 315, 420, 3446, 1603, 1457, 11, 719, 1070, 527, 264, 2478, 7185, 3585, 1618, 627, 5451, 398, 11, 22883, 5190, 33834, 617, 8767, 1027, 1633, 6380, 449, 279, 5190, 3577, 5643, 22883, 706, 1027, 3515, 482, 323, 433, 596, 539, 1093, 279, 19738, 7294, 12, 28344, 1960, 79252, 374, 264, 502, 3245, 627, 16041, 398, 11, 3815, 279, 71808, 11, 433, 5084, 430, 13142, 1229, 1157, 2649, 596, 1403, 4771, 5226, 520, 22883, 690, 387, 709, 304, 6250, 13, 4946, 22883, 1005, 420, 439, 264, 1648, 311, 503, 7211, 3416, 1461, 5380, 38075, 398, 11, 706, 279, 5190, 586, 5643, 14322, 21020, 311, 617, 57130, 279, 22883, 29076, 11, 1101, 3984, 1461, 449, 1063, 9313, 13, 3861, 2643, 64601, 430, 422, 13142, 574, 311, 4321, 279, 73187, 11, 1053, 279, 4430, 3430, 11, 85492, 88, 439, 433, 374, 1314, 1457, 11, 71278, 5380, 89703, 398, 11, 1070, 596, 430, 18541, 8050, 13254, 4365, 430, 568, 5084, 311, 617, 7263, 1203, 311, 22883, 13, 22883, 40676, 7636, 22613, 3610, 315, 11441, 264, 1060, 627, 37, 58710, 398, 11, 1268, 1790, 1053, 13142, 1229, 1157, 2649, 387, 5922, 304, 279, 1825, 3157, 30, 358, 3077, 2736, 6755, 66025, 430, 568, 1436, 1505, 5678, 304, 389, 279, 9909, 13962, 304, 17681, 11, 14393, 22883, 11, 477, 3318, 369, 264, 14356, 13, 1628, 279, 1023, 3117, 810, 2010, 2695, 8035, 287, 14322, 414, 7634, 1461, 1120, 1523, 279, 5754, 11, 4737, 927, 7043, 28120, 11289, 6, 2361, 520, 11162, 35156, 627, 22105, 358, 1288, 1120, 2231, 1461, 389, 31006, 311, 1505, 704, 90578, 3616, 1829, 835, 16885, 3247, 38599, 12073, 6781, 19323, 937, 198, 4599, 4691, 922, 1566, 2046, 596, 445, 964, 38, 3446, 11, 430, 22883, 3197, 311, 21253, 78432, 1082, 682, 872, 1584, 304, 279, 3221, 3938, 11, 4488, 8384, 277, 8621, 389, 8384, 277, 14957, 330, 2170, 369, 22883, 2133, 29950, 11, 358, 2846, 16984, 499, 1253, 93219, 430, 11, 25237, 8334, 11, 719, 358, 7846, 956, 11000, 51605, 13, 6914, 596, 1120, 2019, 279, 364, 44584, 3509, 6, 1584, 574, 1633, 3117, 1355, 65607, 994, 433, 574, 3549, 13, 4497, 505, 757, 389, 420, 304, 459, 14827, 7274, 10246, 791, 1176, 4068, 374, 264, 5905, 311, 279, 6007, 323, 2363, 4101, 11, 4783, 5046, 27864, 11, 16850, 264, 3752, 889, 1053, 539, 6604, 389, 279, 3335, 482, 719, 1053, 2744, 7838, 264, 3446, 449, 430, 17571, 627, 4054, 315, 279, 8125, 1694, 2728, 369, 279, 21253, 318, 98771, 315, 279, 22883, 29849, 374, 6763, 13, 4800, 11, 1418, 330, 3648, 1630, 50559, 1, 323, 330, 66173, 29490, 31251, 1, 23651, 616, 872, 330, 44584, 3509, 1, 38495, 304, 279, 8776, 2167, 3157, 11, 1070, 596, 2500, 2167, 3157, 430, 706, 14297, 3940, 311, 34044, 13, 578, 61838, 8957, 3637, 14916, 65256, 706, 264, 3568, 449, 22883, 29159, 311, 2015, 872, 330, 44584, 3509, 1, 15671, 11, 2536, 81123, 481, 311, 279, 26306, 315, 264, 3610, 264, 2305, 1990, 1124, 13, 1628, 1418, 430, 14661, 7119, 330, 44584, 3509, 29490, 31251, 1, 323, 330, 44584, 3509, 1630, 50559, 1359, 430, 2103, 11621, 11758, 323, 16579, 315, 19883, 6763, 13, 1628, 814, 2873, 311, 5708, 1124, 555, 279, 1957, 12678, 323, 23939, 4856, 1109, 555, 279, 6603, 323, 32947, 482, 19883, 311, 636, 1124, 304, 4156, 315, 6980, 627, 7184, 11, 433, 596, 2867, 430, 14916, 65256, 2011, 617, 2751, 264, 15123, 315, 264, 3568, 304, 2015, 311, 1304, 1778, 264, 15507, 11, 19755, 709, 1139, 220, 1049, 19, 13, 1628, 50750, 2426, 6821, 13519, 430, 4662, 43847, 4536, 956, 2294, 13, 2030, 422, 2225, 22883, 323, 14916, 65256, 527, 3339, 264, 11626, 11, 323, 17919, 264, 3738, 2027, 1584, 311, 330, 94230, 1122, 1, 6444, 11, 16470, 15160, 13, 2030, 814, 1193, 1390, 279, 330, 44584, 3509, 1, 1584, 11, 779, 9522, 38, 1406, 4292, 835, 40, 480, 59208, 97011, 22774, 45176, 1753, 4716, 423, 1406, 56, 11, 328, 2871, 198, 4054, 315, 1057, 1176, 50079, 9491, 11, 3967, 1193, 439, 480, 4428, 24752, 1122, 11, 10975, 757, 330, 791, 330, 44584, 318, 98771, 1, 315, 279, 22883, 1584, 374, 264, 2884, 3568, 505, 1148, 358, 6865, 11, 719, 539, 12222, 3389, 220, 1049, 18, 13, 25681, 922, 50698, 20038, 13, 1628, 1561, 1630, 50559, 674, 3965, 374, 279, 842, 315, 433, 682, 10246, 1548, 6821, 430, 279, 653, 11508, 287, 9327, 520, 22883, 1253, 1664, 3136, 11, 323, 311, 2567, 264, 3345, 8071, 389, 279, 14827, 330, 74008, 31251, 220, 1135, 1210, 1283, 1101, 34945, 430, 14662, 66758, 323, 15367, 875, 53596, 527, 3794, 872, 1866, 29490, 14228, 2363, 9522, 12947, 480, 4428, 24752, 1122, 13, 4718, 9629, 3177, 374, 389, 2579, 369, 1457, 12, 719, 422, 1884, 7493, 1212, 311, 2586, 837, 11, 430, 690, 2349, 1633, 6288, 627, 5519, 499, 1390, 311, 5249, 279, 50079, 9491, 30, 8463, 757, 389, 80654, 59131, 916, 198, 51, 3336, 1372, 6909, 47358, 198, 5966, 2046, 11, 445, 7169, 304, 279, 52683, 5153, 17124, 279, 14322, 414, 430, 3738, 11162, 6603, 617, 1047, 3446, 8128, 16850, 477, 45391, 45261, 2917, 2629, 2230, 477, 31011, 779, 439, 539, 311, 12324, 449, 94251, 4212, 32780, 596, 14800, 1139, 5734, 627, 1966, 279, 11162, 29849, 7090, 520, 39487, 10343, 11, 7061, 51530, 53240, 16717, 813, 14944, 311, 3350, 264, 45261, 3446, 11, 4762, 304, 17710, 13, 3861, 311, 3821, 11, 15687, 627, 35, 4577, 32919, 1750, 16675, 1452, 937, 60744, 4393, 435, 1905, 11492, 3651, 14031, 4243, 5380, 40, 3619, 430, 279, 502, 1948, 6367, 40208, 19797, 894, 2447, 369, 22883, 9932, 304, 264, 3766, 3330, 374, 1101, 279, 502, 1948, 6367, 16768, 9259, 2447, 369, 22883, 627, 35, 548, 81252, 16675, 620, 8674, 68, 13, 3861, 311, 48248, 627, 10725, 3097, 24711, 3097, 1507, 482, 3651, 4276, 7866, 3247, 96722, 9109, 87166, 25321, 25764, 198, 40, 3619, 430, 12538, 34392, 374, 3515, 1972, 5435, 3794, 622, 3746, 1254, 291, 263, 596, 3938, 1776, 1155, 20303, 11, 330, 37, 11872, 1359, 8220, 13, 2030, 1457, 433, 596, 539, 439, 1690, 15562, 11, 279, 7061, 596, 9899, 430, 596, 520, 14867, 11, 433, 596, 279, 10255, 13, 65057, 430, 994, 35131, 386, 22671, 4024, 1022, 311, 11511, 10172, 568, 3463, 568, 4265, 387, 3025, 311, 6381, 433, 1603, 568, 3940, 330, 5004, 220, 10943, 1210, 1283, 3287, 956, 13, 358, 3619, 430, 4360, 220, 22, 374, 1193, 4376, 11733, 11274, 779, 3117, 198, 17809, 53, 64190, 3680, 4592, 47837, 435, 88658, 40992, 50, 198, 4808, 5182, 3250, 956, 2873, 311, 387, 279, 2653, 9976, 74768, 2930, 2246, 433, 3131, 574, 13, 25328, 2873, 311, 617, 1027, 1981, 1664, 11, 10223, 264, 2478, 9660, 323, 9863, 5246, 1306, 2926, 48429, 13, 1628, 422, 499, 2339, 433, 304, 892, 11, 499, 2643, 1518, 1063, 3938, 7224, 430, 15058, 956, 8967, 311, 617, 1027, 10212, 430, 2305, 13, 2876, 1193, 574, 330, 62158, 5270, 25, 578, 30198, 1, 1176, 30844, 1639, 369, 6287, 11, 433, 574, 2884, 779, 2085, 45391, 279, 13878, 430, 617, 9057, 779, 1790, 41602, 315, 3389, 13, 2030, 1070, 596, 1101, 420, 2697, 82880, 456, 505, 420, 2305, 596, 3626, 482, 1664, 433, 574, 1070, 1633, 6051, 11, 13971, 627, 1507, 965, 13575, 5091, 6093, 674, 16, 320, 12766, 220, 21, 340, 31996, 555, 14129, 109051, 198, 38595, 109051, 320, 86, 612, 264, 340, 32, 6883, 23065, 18427, 315, 39074, 37731, 1957, 304, 279, 23865, 2240, 22883, 36020, 3645, 0, 1952, 264, 3117, 14075, 11841, 11, 264, 4382, 3828, 505, 264, 2678, 9309, 315, 279, 34261, 14035, 11937, 304, 13612, 19243, 315, 279, 24511, 315, 279, 15861, 0, 43680, 3235, 449, 420, 17821, 12084, 389, 1077, 54904, 71004, 2271, 311, 7142, 279, 8206, 4920, 1077, 1917, 323, 279, 77563, 7953, 304, 459, 682, 23065, 11, 4848, 90465, 4101, 555, 3938, 22883, 58347, 11, 41663, 23111, 18230, 10255, 14129, 109051, 0, 1442, 499, 4170, 13321, 27582, 323, 7834, 15317, 11, 499, 3358, 3021, 16421, 965, 13575, 5091, 6093, 4999, 843, 393, 16929, 13, 449, 14058, 14, 6897, 10482, 946, 12073, 31144, 220, 17, 13, 1484, 198, 15571, 311, 1518, 22883, 2133, 1306, 279, 11511, 10172, 18160, 1070, 627, 33, 11492, 1111, 473, 26043, 33182, 6328, 328, 56322, 198, 85203, 21253, 48571, 7359, 11, 3794, 682, 60513, 88, 323, 282, 2049, 88, 323, 9298, 35454, 24869, 30608, 4028, 279, 22959, 30, 4418, 956, 11196, 627, 33, 57858, 71464, 3952, 892, 704, 311, 3137, 922, 813, 9899, 389, 279, 2363, 482, 1268, 433, 43578, 11, 323, 1268, 568, 596, 10917, 433, 1314, 627, 1, 9126, 323, 358, 1288, 617, 3940, 4360, 832, 304, 5651, 315, 1566, 1060, 11, 719, 4245, 311, 4488, 596, 11838, 25646, 449, 17563, 323, 77085, 5015, 1752, 9572, 44030, 584, 3287, 956, 2231, 5869, 311, 5684, 3156, 279, 2132, 2046, 315, 6250, 11, 902, 8051, 7231, 757, 682, 279, 892, 358, 4460, 311, 3821, 91257, 323, 656, 279, 2955, 990, 1550, 743, 603, 4920, 2533, 1057, 7195, 2457, 574, 2736, 743, 369, 4448, 10246, 22244, 8967, 584, 7846, 956, 656, 279, 2033, 30387, 1176, 4360, 439, 13205, 11, 719, 433, 1101, 58487, 279, 16907, 8935, 315, 7231, 603, 279, 6140, 311, 312, 5773, 20216, 1148, 584, 4934, 311, 656, 323, 279, 4459, 7434, 6244, 1148, 584, 1457, 1440, 13, 1102, 1253, 2802, 13016, 311, 1440, 430, 1148, 574, 13517, 10825, 311, 387, 304, 430, 1176, 2033, 30387, 4360, 17626, 311, 5266, 1521, 1176, 4330, 4819, 994, 279, 5885, 3952, 389, 16907, 5066, 2324, 449, 810, 315, 872, 7493, 311, 3371, 13, 18156, 499, 1120, 617, 311, 1095, 2574, 37397, 10246, 1, 49388, 11, 578, 1176, 4360, 315, 4205, 2744, 5097, 757, 5129, 311, 656, 11, 2019, 4848, 5672, 4619, 315, 3116, 11, 719, 304, 420, 1162, 433, 574, 779, 4261, 3230, 323, 5905, 8987, 430, 892, 1120, 2751, 35661, 709, 45243, 279, 45188, 11, 45233, 11, 6916, 24469, 11, 5110, 11, 14467, 323, 682, 279, 1023, 5995, 3649, 13, 37246, 433, 304, 279, 1317, 1629, 11000, 11, 719, 1633, 892, 35208, 10246, 7189, 784, 1157, 1403, 11, 2380, 323, 3116, 682, 3952, 3116, 5672, 477, 779, 11, 719, 279, 5674, 574, 2736, 2884, 323, 7999, 311, 279, 3575, 574, 279, 2144, 430, 927, 279, 3388, 315, 1884, 1176, 4330, 4819, 584, 6267, 323, 24465, 922, 82497, 5066, 6959, 389, 1948, 315, 279, 2631, 220, 1691, 824, 4360, 323, 433, 4131, 439, 912, 13051, 430, 584, 43578, 4920, 13, 1226, 1436, 682, 1518, 433, 12765, 11, 719, 10494, 1057, 19779, 28129, 5828, 956, 2216, 3815, 279, 2683, 4999, 1, 34124, 706, 1027, 4560, 311, 1505, 5627, 315, 31526, 5266, 304, 4819, 439, 11, 1306, 682, 11, 19093, 6944, 311, 617, 18570, 775, 3350, 264, 12735, 315, 872, 11775, 11, 323, 22883, 617, 1027, 2225, 28771, 323, 33445, 304, 682, 872, 9045, 311, 3041, 4488, 323, 358, 320, 63995, 757, 8, 8996, 1520, 814, 649, 10246, 48058, 584, 1766, 13520, 449, 922, 264, 2046, 311, 4128, 4360, 4330, 11, 902, 1694, 279, 2466, 8199, 57891, 584, 1051, 8748, 369, 11, 574, 1120, 539, 39529, 3284, 2085, 523, 1036, 6427, 279, 9090, 315, 7762, 58811, 13, 12799, 2136, 315, 856, 1866, 323, 1063, 1023, 4443, 41902, 3779, 311, 279, 2736, 6484, 5435, 555, 17919, 279, 892, 4529, 389, 279, 4360, 311, 8254, 5672, 323, 11, 23095, 78, 11, 499, 617, 279, 1510, 6671, 10246, 7189, 84990, 4848, 706, 13118, 4529, 2380, 5672, 311, 47218, 323, 690, 387, 520, 279, 57053, 1828, 2046, 13, 2100, 279, 14529, 1920, 315, 34168, 709, 9731, 13, 37543, 690, 387, 704, 15438, 505, 1457, 11, 323, 422, 584, 10299, 311, 636, 1405, 584, 1390, 311, 387, 555, 279, 842, 315, 279, 1060, 11, 279, 1253, 387, 459, 5066, 13051, 477, 1403, 13, 56478, 274, 427, 372, 11, 64606, 499, 1629, 66025, 13, 578, 832, 922, 4488, 8384, 277, 3318, 304, 4400, 719, 264, 7572, 79, 1386, 20666, 9979, 21726, 263, 527, 837, 11, 4869, 10246, 5159, 6548, 11, 37453, 11, 856, 6548, 4999, 26502, 3651, 37747, 45081, 6328, 49426, 8867, 19645, 11, 22931, 35248, 2390, 9440, 12420, 56, 18076, 198, 40, 3619, 430, 22883, 690, 387, 10917, 330, 791, 7290, 25, 42770, 7956, 1, 8800, 1202, 32362, 3034, 1233, 26544, 11, 439, 1664, 439, 279, 502, 330, 14755, 17810, 1, 4101, 13, 2030, 420, 2643, 387, 520, 279, 2853, 315, 26156, 13046, 1110, 1233, 7808, 11, 330, 44584, 3509, 29490, 31251, 10246, 35, 16294, 54, 9682, 5125, 937, 12076, 33, 19707, 2198, 11, 480, 6979, 1901, 2818, 6486, 198, 2409, 6821, 430, 13944, 27511, 527, 34118, 330, 14804, 59196, 1, 29159, 11, 433, 596, 7185, 430, 11, 1093, 449, 330, 97012, 38552, 1359, 18308, 31498, 13517, 1047, 279, 330, 14804, 59196, 1, 31073, 13, 28780, 311, 22203, 264, 330, 14804, 59196, 1, 864, 43014, 11, 330, 85752, 1359, 520, 5960, 18842, 11, 814, 1766, 1884, 24345, 449, 7980, 66480, 7573, 68941, 13, 19455, 18145, 261, 655, 574, 13517, 8967, 311, 387, 279, 7061, 482, 323, 1047, 5439, 2225, 279, 4997, 59196, 61301, 323, 279, 1176, 3446, 15952, 81763, 627, 11458, 11, 358, 3077, 1101, 6755, 430, 18308, 31498, 617, 27528, 279, 330, 40775, 315, 55731, 1, 5842, 13, 507, 78, 2319, 4999, 61297, 7527, 6969, 3097, 42, 691, 423, 5726, 7585, 8927, 1111, 11672, 6005, 198, 76768, 921, 352, 8148, 374, 1203, 520, 279, 21126, 13, 9372, 369, 1461, 311, 387, 13633, 264, 330, 25763, 27191, 1, 3446, 369, 26349, 20832, 20193, 13, 20832, 1047, 4934, 921, 352, 8148, 311, 4128, 264, 3446, 369, 1461, 369, 5115, 264, 1418, 719, 13942, 921, 352, 8148, 596, 3321, 1566, 892, 389, 330, 25763, 27191, 1210, 2876, 420, 892, 12, 9778, 20832, 2744, 5334, 813, 893, 627, 27237, 39, 9944, 56, 452, 2783, 46, 69139, 198, 4438, 922, 264, 4526, 315, 8384, 11118, 323, 469, 87152, 6, 11670, 330, 88960, 452, 6868, 1, 4101, 2737, 279, 1176, 682, 23065, 452, 6868, 3446, 304, 4661, 264, 13515, 11, 27104, 315, 34711, 437, 689, 420, 42774, 5380, 36687, 315, 3388, 11162, 27669, 430, 832, 1234, 34711, 437, 689, 596, 97814, 1093, 814, 1550, 4923, 265, 41996, 9522, 5744, 6781, 19323, 937, 350, 964, 14344, 6570, 3378, 6135, 14083, 198, 2181, 8111, 430, 264, 1396, 315, 11162, 596, 6287, 220, 1049, 17, 596, 6603, 527, 7554, 279, 35156, 6247, 53625, 13, 1628, 912, 11, 539, 279, 15408, 33339, 11, 719, 279, 11162, 29849, 1584, 13, 85487, 779, 3117, 2997, 330, 2573, 35156, 674, 24763, 1359, 330, 66370, 82, 315, 5075, 88, 674, 2096, 1359, 330, 41, 7934, 674, 1806, 1359, 330, 62372, 25525, 674, 10828, 53670, 2019, 11, 706, 11519, 3341, 3817, 1027, 20700, 813, 6548, 520, 279, 41063, 6247, 22677, 30, 3507, 11162, 2768, 304, 22883, 596, 3063, 5380, 2244, 374, 433, 1120, 264, 22733, 5352, 5380, 55, 5364, 965, 15238, 47077, 482, 15888, 38717, 4999, 78006, 388, 482, 3515, 17250, 27242, 22883, 596, 2539, 1584, 36580, 369, 5651, 10373, 30, 2876, 9277, 701, 2015, 3686, 30, 2876, 311, 11196, 11, 1120, 923, 264, 2478, 810, 11236, 315, 330, 55, 50559, 38321, 1, 220, 605, 3156, 499, 26456, 13, 4740, 682, 11, 433, 596, 1027, 26765, 90578, 3701, 82491, 33, 1971, 10155, 5257, 7354, 66923, 16407, 1507, 482, 3247, 83940, 16511, 691, 11560, 198, 8780, 810, 389, 330, 97012, 31146, 2641, 1, 1694, 96596, 323, 81754, 11, 5439, 555, 3842, 20267, 21178, 1306, 4360, 220, 2075, 30, 5659, 279, 94251, 44023, 19111, 36107, 8695, 11, 994, 1217, 435, 9847, 2125, 975, 1071, 330, 18066, 54, 11, 602, 4510, 37943, 31146, 2641, 374, 279, 220, 19, 339, 22807, 29869, 2536, 5621, 4722, 291, 4101, 5131, 5108, 704, 505, 45882, 320, 30998, 485, 84279, 11, 1561, 1630, 50559, 323, 29879, 13184, 1630, 50559, 570, 10699, 4265, 64, 79256, 433, 32111, 44023, 20592, 330, 14524, 4848, 4038, 31538, 42, 25784, 426, 77587, 13575, 10528, 11954, 198, 7816, 505, 31359, 29492, 13, 1666, 1664, 439, 279, 330, 2169, 5174, 2418, 1, 21154, 11775, 11, 330, 62158, 5270, 25, 578, 30198, 1359, 813, 6621, 2596, 350, 8699, 10571, 990, 369, 32780, 34321, 11, 330, 91015, 17627, 468, 750, 220, 17, 1, 323, 264, 330, 19841, 1543, 1, 11775, 11, 11162, 527, 1101, 2109, 2600, 287, 279, 1176, 330, 91015, 17627, 468, 750, 7073, 1210, 21829, 291, 264, 59831, 315, 264, 21154, 11775, 11, 433, 596, 2736, 1027, 1555, 55964, 839, 352, 323, 2947, 10516, 68, 11, 323, 1524, 264, 12903, 1885, 11341, 304, 22883, 596, 40467, 41965, 13, 1115, 892, 433, 5992, 1093, 433, 3358, 636, 279, 5788, 4367, 433, 596, 2744, 45547, 627, 2028, 374, 279, 4325, 315, 31359, 29492, 627, 39, 69798, 11, 45269, 6830, 3664, 6007, 96944, 5380, 40, 3619, 430, 31362, 7427, 374, 33828, 11469, 264, 502, 3974, 26115, 61946, 6007, 4101, 11, 311, 1514, 1022, 279, 14827, 5818, 2373, 482, 719, 814, 2351, 10494, 433, 264, 6367, 627, 3947, 617, 1027, 66025, 922, 264, 502, 31449, 11, 719, 1521, 2873, 311, 387, 68652, 1065, 11, 39441, 311, 2567, 7359, 1022, 279, 41466, 11, 304, 1162, 433, 3250, 956, 7363, 704, 13, 9086, 29550, 627, 24205, 11, 422, 499, 2351, 264, 463, 2695, 4014, 1565, 91546, 12, 5739, 11, 7344, 499, 1288, 3041, 1124, 264, 1650, 9522, 3472, 70844, 14031, 4243, 6969, 71894, 12428, 1741, 81601, 2507, 82071, 13575, 10528, 11954, 198, 41444, 8096, 4610, 42930, 1910, 33639, 14238, 389, 279, 4073, 70436, 502, 2034, 896, 1421, 13, 7183, 42639, 14825, 960, 370, 27095, 20, 749, 4414, 660, 627, 7189, 617, 264, 2380, 27748, 647, 291, 3568, 25, 7493, 449, 9749, 5885, 304, 279, 22883, 29849, 11, 5891, 2299, 89460, 5885, 304, 279, 60886, 439, 1664, 439, 6968, 502, 5885, 1070, 11, 323, 6968, 42241, 502, 5885, 304, 264, 2536, 5364, 52, 6671, 10923, 757, 311, 656, 5128, 1790, 4205, 358, 1390, 10246, 56084, 11, 430, 596, 539, 11112, 13687, 1131, 9493, 16768, 9259, 3782, 389, 4580, 11, 568, 4691, 311, 387, 2728, 42168, 82, 389, 12967, 62045, 323, 11291, 3871, 1578, 11, 422, 323, 994, 430, 5597, 1288, 387, 1903, 13, 2100, 304, 3878, 315, 430, 13189, 11, 682, 358, 649, 656, 374, 3169, 315, 1514, 2212, 279, 13116, 264, 2766, 11, 279, 5041, 374, 1664, 323, 9615, 304, 16768, 596, 5590, 11, 568, 596, 279, 1193, 832, 889, 649, 9006, 323, 4546, 1124, 3871, 422, 430, 374, 279, 1648, 22883, 6944, 311, 733, 10246, 7189, 574, 16926, 4546, 364, 336, 3871, 1578, 20193, 11, 1606, 433, 574, 856, 7537, 311, 636, 1124, 10980, 1193, 369, 264, 1418, 11, 719, 520, 420, 1486, 433, 3358, 387, 459, 422, 14, 9493, 6671, 1990, 22883, 323, 16768, 10246, 2645, 42930, 1910, 33639, 65876, 420, 4726, 304, 2613, 11, 5605, 330, 3923, 264, 2763, 315, 1274, 2873, 539, 311, 3619, 11, 477, 617, 12146, 311, 3619, 11, 374, 430, 358, 1071, 11, 505, 279, 16749, 20521, 11, 430, 358, 1193, 4934, 311, 2867, 279, 30881, 315, 682, 279, 12899, 5885, 353, 2000, 264, 1418, 9, 779, 430, 358, 1436, 5357, 21742, 389, 889, 11291, 574, 11, 449, 279, 5915, 315, 27115, 3318, 1124, 682, 1203, 304, 1578, 3131, 358, 4265, 13413, 1142, 709, 279, 2035, 264, 2766, 13, 16299, 374, 3249, 682, 1521, 330, 41, 4931, 55406, 62045, 323, 6944, 1077, 8208, 16058, 1, 8158, 2744, 87420, 757, 11, 2533, 358, 4265, 2646, 1071, 430, 11, 323, 1047, 11, 304, 2144, 11, 304, 856, 586, 8158, 320, 1874, 481, 389, 904, 315, 264, 1396, 315, 32906, 8, 1071, 7041, 1148, 358, 1071, 3485, 11, 430, 433, 574, 8967, 311, 387, 264, 13643, 6671, 10246, 4516, 374, 420, 1317, 90350, 636, 4791, 3522, 12765, 304, 330, 14755, 17810, 7673, 2582, 16768, 9259, 596, 1023, 29490, 31251, 6787, 5380, 50, 56322, 3651, 7432, 73326, 4716, 77620, 1753, 9440, 45136, 5364, 1111, 198, 38426, 33680, 374, 13633, 2380, 14861, 369, 330, 66173, 29490, 31251, 1359, 279, 1176, 4245, 704, 304, 6664, 13, 358, 1101, 3619, 430, 330, 66173, 29490, 31251, 1, 374, 9293, 311, 2339, 709, 279, 1403, 4819, 433, 36257, 1566, 1060, 11, 439, 1664, 439, 264, 330, 339, 404, 46487, 1, 4360, 311, 2586, 627, 1111, 31367, 4015, 1905, 7520, 11162, 22964, 31315, 790, 4463, 350, 964, 14344, 14, 9614, 24093, 18793, 44421, 198, 33413, 17339, 17339, 13, 6914, 596, 1518, 422, 584, 649, 636, 264, 2731, 1935, 389, 420, 4459, 13944, 27511, 11162, 29849, 15671, 30, 9062, 5334, 872, 1866, 9629, 3177, 627, 3112, 810, 311, 2586, 627, 10267, 596, 1518, 422, 584, 636, 904, 12401, 420, 892, 5380, 17809, 21709, 34979, 4393, 7683, 17485, 198, 2181, 596, 15526, 1148, 3169, 315, 7528, 3626, 421, 450, 4883, 279, 8191, 994, 814, 2351, 539, 10171, 311, 323, 17354, 842, 709, 304, 856, 23732, 627, 9673, 4330, 6959, 4087, 403, 311, 387, 279, 7314, 311, 330, 3407, 1590, 1, 4360, 220, 16, 11, 279, 14827, 22169, 2363, 505, 38709, 11, 555, 26713, 44707, 323, 15385, 268, 12649, 1849, 13, 1115, 374, 264, 220, 21, 90465, 13726, 57432, 11, 28818, 304, 6841, 198, 51, 1937, 328, 4031, 1953, 3204, 82071, 5257, 39652, 16560, 12431, 90708, 49673, 93676, 198, 32978, 18288, 14238, 311, 3371, 757, 430, 279, 38709, 2447, 568, 596, 4477, 9932, 1566, 2046, 690, 387, 1080, 67383, 555, 8529, 328, 11044, 35173, 6780, 2288, 627, 21242, 2147, 3701, 46, 52532, 3680, 23909, 1600, 65991, 97577, 198, 3947, 596, 264, 502, 8013, 84108, 20303, 6041, 304, 6664, 2663, 32912, 38091, 11, 2737, 279, 990, 315, 60333, 80928, 11, 25871, 39069, 3491, 11, 452, 7404, 735, 1641, 287, 11, 8269, 4072, 942, 323, 66916, 423, 10530, 77, 13, 3639, 4279, 4617, 29782, 1124, 3871, 5380, 7009, 682, 6575, 389, 279, 330, 50, 14338, 578, 80121, 61722, 1, 20303, 902, 36513, 369, 5899, 1667, 323, 1403, 7895, 4819, 13, 1628, 1457, 814, 2351, 1203, 4999, 2688, 279, 1193, 1579, 5643, 38838, 889, 6575, 389, 430, 20303, 3582, 482, 4488, 8384, 277, 374, 5068, 311, 617, 5439, 220, 1041, 6959, 315, 5429, 304, 264, 1938, 9522, 31026, 6781, 19323, 937, 5257, 32612, 32, 54856, 198, 1688, 5960, 18842, 11, 4758, 35156, 527, 9293, 311, 22203, 872, 502, 312, 14386, 71070, 660, 4758, 29849, 1584, 13, 2030, 439, 8767, 14322, 21020, 11, 433, 596, 539, 2663, 71474, 482, 8051, 358, 3619, 430, 832, 315, 279, 502, 5885, 690, 387, 627, 4782, 33, 54659, 9745, 8912, 393, 6641, 15149, 50, 435, 88658, 198, 32, 3446, 505, 14596, 7997, 49120, 596, 25959, 505, 22883, 13, 358, 6865, 430, 4488, 46137, 323, 37373, 44943, 15203, 1523, 311, 7997, 49120, 596, 5274, 311, 3041, 872, 80293, 13, 4488, 63130, 14596, 596, 1450, 5605, 11, 330, 40, 2846, 14931, 13, 1102, 574, 6555, 3318, 449, 499, 1210, 2057, 902, 14596, 31737, 555, 37163, 323, 5605, 11, 330, 24220, 11, 1664, 1131, 499, 2351, 1828, 25765, 9109, 1753, 2006, 3247, 480, 1406, 4292, 73863, 198, 2170, 264, 1121, 315, 264, 2478, 390, 6821, 505, 279, 39487, 10780, 1128, 19482, 11, 505, 5513, 640, 64, 11, 356, 13396, 323, 279, 1093, 11, 1618, 596, 264, 2478, 2362, 552, 719, 6761, 552, 2052, 578, 66567, 9660, 430, 2643, 387, 5922, 264, 65878, 627, 1, 20613, 8727, 32666, 1, 482, 330, 7594, 391, 32178, 11, 264, 502, 23160, 11104, 505, 14662, 66758, 323, 3842, 59316, 258, 11, 16850, 279, 471, 315, 23886, 8727, 32666, 13, 23804, 291, 439, 3515, 459, 330, 283, 376, 425, 788, 7434, 1, 323, 10508, 27442, 18012, 11, 433, 5992, 1093, 22883, 690, 387, 10917, 279, 6122, 4410, 1139, 279, 13944, 4410, 10246, 1, 6330, 17, 1, 482, 330, 791, 2316, 315, 34221, 480, 2706, 276, 596, 14827, 22883, 29849, 20303, 374, 220, 6330, 17, 13, 2030, 1148, 1587, 433, 3152, 30, 16910, 433, 387, 264, 5905, 311, 279, 47913, 330, 791, 4409, 5046, 578, 8219, 1, 555, 15155, 7061, 8529, 7044, 78, 8215, 857, 6985, 11, 5439, 304, 220, 6330, 17, 13, 578, 3446, 10975, 315, 264, 8791, 48748, 3363, 5918, 323, 12439, 304, 555, 23490, 4832, 23837, 13, 3861, 2643, 78495, 220, 6330, 17, 690, 3371, 264, 4528, 24162, 13, 2030, 449, 578, 38300, 11, 67931, 81252, 323, 4491, 58038, 1131, 17339, 11, 7344, 539, 13, 2030, 220, 6330, 17, 374, 264, 59759, 369, 279, 5897, 8209, 927, 22883, 1543, 10482, 404, 8061, 1543, 482, 902, 11, 2391, 480, 2706, 276, 596, 1629, 45877, 264, 8791, 48748, 1917, 5918, 555, 289, 94650, 23837, 1981, 4557, 279, 47913, 304, 3488, 1618, 627, 1, 14755, 59612, 1, 482, 6649, 64, 10880, 719, 539, 312, 4174, 291, 1306, 4360, 220, 1135, 323, 279, 842, 315, 279, 16290, 5046, 5348, 59612, 20303, 11, 994, 11824, 2939, 12748, 9221, 330, 14755, 59612, 1, 10255, 13, 8375, 650, 616, 1564, 323, 14596, 1708, 12669, 690, 1243, 990, 449, 50003, 389, 2500, 2447, 482, 11000, 459, 29950, 2363, 627, 793, 9150, 22572, 1753, 4393, 3247, 480, 1406, 4292, 198, 2028, 3330, 374, 4400, 2085, 1202, 13016, 323, 1202, 8336, 13, 7531, 704, 1268, 499, 649, 1514, 264, 961, 627, 3905, 2739, 5977, 578, 480, 6339, 9491, 198, 3923, 596, 279, 3492, 389, 279, 8761, 30, 13440, 499, 2351, 264, 463, 304, 279, 1440, 477, 264, 8571, 889, 1120, 2751, 18069, 11, 1522, 433, 389, 13, 1472, 3077, 1766, 20784, 23726, 389, 1984, 21126, 11, 499, 990, 304, 264, 8221, 1405, 264, 463, 596, 1027, 10168, 5590, 922, 872, 5652, 2450, 11, 477, 499, 2351, 1120, 8430, 14733, 40530, 88, 323, 1390, 311, 636, 701, 1684, 4028, 2085, 1694, 14219, 11, 5249, 279, 3596, 24050, 13941, 315, 430, 14079, 81479, 3967, 1193, 439, 279, 480, 6339, 9491, 13, 29900, 19578, 649, 636, 872, 1866, 30499, 11, 779, 499, 649, 1977, 264, 17444, 482, 719, 7389, 499, 6562, 433, 11, 701, 9764, 690, 2646, 387, 10675, 627, 47, 6073, 1789, 7573, 763, 578, 480, 6339, 198, 14364, 3245, 482, 2362, 7493, 13, 4702, 1606, 433, 7077, 17510, 1667, 4227, 11, 3250, 956, 3152, 358, 2834, 956, 1390, 311, 6865, 922, 433, 13, 36016, 279, 9191, 279, 3446, 11, 279, 810, 1825, 1274, 649, 387, 922, 433, 13, 2100, 422, 499, 1440, 264, 2294, 3446, 430, 2646, 1903, 433, 311, 279, 7359, 11, 10788, 311, 445, 7169, 763, 578, 52683, 5153, 627, 3905, 2739, 5977, 578, 480, 6339, 13358, 9100, 198, 6540, 6285, 279, 3492, 13, 3402, 537, 14491, 505, 420, 3330, 320, 4291, 279, 14322, 414, 10163, 323, 279, 3330, 596, 3566, 2686, 8, 311, 1984, 21126, 4028, 279, 7757, 11, 28578, 9959, 11, 323, 1095, 757, 1440, 922, 433, 13, 469, 11724, 9660, 311, 4885, 11, 1522, 279, 3492, 11, 323, 9041, 279, 5353, 13, 1789, 3187, 482, 84490, 505, 3432, 596, 3330, 2643, 387, 8621, 2212, 8604, 3034, 292, 1255, 2402, 916, 11, 362, 396, 2181, 57850, 916, 477, 904, 1396, 315, 71940, 21126, 13, 6122, 311, 433, 13, 20793, 856, 5128, 6305, 11, 11722, 4999, 2675, 649, 3729, 757, 520, 512, 15930, 11330, 59131, 916, 320, 8370, 3629, 5334, 2539, 11, 719, 433, 3358, 5662, 757, 2391, 279, 1938, 340, 14172, 31, 15930, 380, 438, 939, 412, 840, 8016, 5976, 6973, 15549, 320, 8370, 358, 1373, 1475, 6693, 482, 1888, 369, 21154, 3626, 28684, 32, 1971, 18549, 4961, 757, 520, 74474, 28276, 198, 24850, 15, 220, 8878, 26983, 17, 320, 10731, 20800, 1490, 220, 8878, 26983, 17, 505, 452, 5270, 340, 35364, 33606, 649, 387, 3288, 311, 220, 23, 17582, 36443, 27109, 11, 63569, 55069, 11, 7295, 13692, 868, 220, 18, 6459, 11, 5301, 3910, 4064, 198, 3513, 9298, 499, 627, 12174, 22371, 11, 323, 430, 29335, 92817, 47940, 3446, 505, 2052, 578, 66567, 13985, 30, 2360, 17668, 4068, 627, 29184, 24537, 40612, 42789, 264, 29738, 220, 410, 21372, 2564, 220, 4370, 23116, 97703, 128000, 271, 475, 47047, 21346, 53, 18, 505, 6490, 3632, 3554, 6312, 3554, 6312, 12, 17447, 8437, 18, 1270, 475, 6274, 2097, 505, 6490, 3632, 3554, 6312, 54107, 30432, 1270, 475, 12721, 505, 5032, 1985, 47129, 1270, 475, 341, 220, 45546, 5004, 17591, 345, 220, 5832, 3103, 17591, 198, 92, 505, 6490, 3632, 3554, 6312, 88534, 12, 5598, 19251, 3961, 475, 341, 220, 2696, 345, 220, 6657, 345, 220, 21722, 345, 220, 48565, 345, 220, 8949, 1489, 345, 220, 8092, 345, 220, 8092, 21766, 345, 220, 5236, 345, 220, 33907, 345, 220, 4212, 345, 220, 1252, 11130, 51922, 345, 220, 6146, 345, 220, 5419, 198, 92, 505, 364, 52360, 19, 73, 77590, 24357, 3961, 475, 314, 5691, 335, 505, 6490, 3632, 74221, 1270, 475, 314, 6070, 335, 505, 6490, 3632, 4420, 474, 4116, 3961, 1040, 341, 220, 62019, 25, 314, 6017, 15914, 1173, 220, 10055, 2714, 25, 314, 40950, 2714, 457, 92, 284, 5419, 271, 1040, 39652, 284, 364, 33881, 3961, 12612, 3599, 3928, 47047, 21346, 53, 18, 518, 1754, 591, 341, 220, 18193, 5175, 591, 341, 262, 1755, 16209, 65266, 11319, 388, 340, 220, 9763, 220, 433, 493, 5562, 2713, 11408, 518, 1754, 591, 341, 262, 738, 11408, 284, 314, 259, 13275, 25, 220, 16, 11, 259, 12473, 25, 220, 17, 11, 3000, 64932, 25, 220, 18, 11, 1063, 31556, 3173, 25, 220, 19, 457, 262, 738, 11766, 284, 502, 47047, 21346, 53, 18, 5074, 11, 854, 11, 905, 696, 262, 738, 24411, 14952, 284, 11766, 8297, 14952, 55536, 696, 262, 1755, 31076, 291, 14952, 570, 13529, 2313, 415, 1121, 28060, 20434, 25, 220, 16, 345, 415, 1121, 70970, 291, 20434, 25, 220, 17, 345, 415, 3000, 64932, 25, 220, 18, 345, 415, 1063, 31556, 3173, 25, 220, 19, 198, 262, 2820, 220, 9763, 220, 433, 493, 5562, 9656, 3717, 518, 1754, 591, 341, 262, 738, 49935, 284, 502, 12721, 8639, 53956, 4627, 746, 262, 738, 11766, 284, 502, 47047, 21346, 53, 18, 21285, 1382, 11, 854, 11, 905, 340, 262, 12721, 56216, 21346, 8144, 85456, 696, 262, 738, 3016, 678, 284, 364, 2580, 77590, 14, 16, 13, 17, 13, 18, 1270, 262, 738, 87122, 284, 314, 6059, 25, 364, 52360, 19, 73, 518, 3636, 25, 364, 21107, 6, 557, 262, 738, 22842, 284, 11766, 27060, 2358, 95296, 25, 3016, 678, 11, 87122, 9763, 262, 11766, 28620, 2097, 2568, 7, 16, 340, 262, 1755, 85456, 26381, 58, 15, 10927, 9074, 2097, 1021, 415, 6274, 2097, 870, 4896, 13097, 678, 11, 87122, 340, 262, 1763, 262, 1755, 85456, 50375, 19251, 570, 13529, 2625, 31830, 2608, 262, 1755, 85456, 23907, 288, 570, 13529, 2625, 1904, 2608, 220, 9763, 220, 433, 493, 5562, 1629, 264, 3319, 518, 1754, 591, 341, 262, 738, 62019, 284, 502, 6017, 15914, 9133, 415, 364, 52360, 19, 73, 25, 61475, 53749, 16, 25, 4086, 16, 756, 415, 364, 52360, 19, 73, 25, 61475, 53749, 16, 25, 4086, 17, 1270, 262, 24371, 262, 738, 10055, 2714, 284, 502, 40950, 2714, 2313, 415, 9829, 25, 220, 2636, 15, 345, 415, 11408, 25, 314, 865, 25, 220, 16, 11, 379, 25, 364, 34431, 6, 457, 262, 2820, 262, 738, 49935, 284, 502, 12721, 8639, 53956, 4627, 746, 262, 738, 11766, 284, 502, 47047, 21346, 53, 18, 21285, 1382, 11, 854, 11, 905, 340, 262, 12721, 56216, 21346, 8144, 85456, 696, 262, 738, 3319, 284, 364, 52633, 400, 87, 11, 400, 88, 1270, 262, 738, 5137, 284, 314, 865, 25, 364, 87, 518, 379, 25, 364, 88, 6, 557, 262, 738, 22842, 284, 11766, 7789, 10974, 11, 5137, 11, 341, 415, 62019, 345, 415, 10055, 2714, 345, 415, 3941, 25, 39652, 198, 262, 9763, 262, 11766, 28620, 2097, 2568, 7, 17, 696, 262, 1755, 85456, 26381, 58, 15, 10927, 9074, 2097, 1021, 415, 6274, 2097, 7789, 2409, 14952, 10974, 11, 5137, 11, 341, 286, 62019, 345, 286, 10055, 2714, 345, 286, 3941, 25, 39652, 198, 415, 2820, 262, 1763, 262, 1755, 85456, 26381, 58, 16, 10927, 9074, 2097, 13248, 2097, 84372, 2460, 2455, 262, 1755, 85456, 50375, 19251, 570, 13529, 2625, 31830, 11, 22842, 2608, 262, 1755, 85456, 23907, 288, 570, 13529, 2625, 3934, 11, 837, 2608, 220, 9763, 220, 433, 493, 5562, 3240, 264, 7901, 518, 1754, 591, 341, 262, 738, 62019, 284, 502, 6017, 15914, 9133, 415, 364, 52360, 19, 73, 25, 61475, 53749, 16, 25, 4086, 16, 756, 415, 364, 52360, 19, 73, 25, 61475, 53749, 16, 25, 4086, 17, 1270, 262, 24371, 262, 738, 10055, 2714, 284, 502, 40950, 2714, 2313, 415, 9829, 25, 220, 2636, 15, 345, 415, 11408, 25, 314, 865, 25, 220, 16, 11, 379, 25, 364, 34431, 6, 457, 262, 2820, 262, 738, 49935, 284, 502, 12721, 8639, 53956, 4627, 746, 262, 738, 11766, 284, 502, 47047, 21346, 53, 18, 21285, 1382, 11, 854, 11, 905, 340, 262, 12721, 56216, 21346, 8144, 85456, 696, 262, 738, 22842, 284, 11766, 56330, 2313, 415, 62019, 345, 415, 10055, 2714, 345, 415, 3941, 25, 39652, 198, 262, 9763, 262, 11766, 28620, 2097, 2568, 7, 16, 340, 262, 1755, 85456, 26381, 58, 15, 10927, 9074, 2097, 1021, 415, 6274, 2097, 6991, 2358, 62019, 11, 10055, 2714, 11, 3941, 25, 39652, 2820, 262, 1763, 262, 1755, 85456, 50375, 19251, 570, 13529, 2625, 31830, 2608, 262, 1755, 85456, 23907, 288, 570, 13529, 2625, 1904, 2608, 220, 9763, 220, 433, 493, 5562, 5379, 518, 1754, 591, 341, 262, 738, 49935, 284, 502, 12721, 8639, 53956, 4627, 746, 262, 738, 11766, 284, 502, 47047, 21346, 53, 18, 21285, 1382, 11, 854, 11, 905, 340, 262, 12721, 56216, 21346, 8144, 85456, 696, 262, 738, 22842, 284, 11766, 16105, 8230, 2892, 262, 11766, 28620, 2097, 2568, 7, 16, 340, 262, 1755, 85456, 26381, 58, 15, 10927, 9074, 2097, 13248, 2097, 16105, 2455, 262, 1755, 85456, 50375, 19251, 570, 13529, 2625, 31830, 2608, 262, 1755, 85456, 23907, 288, 570, 13529, 2625, 1904, 2608, 220, 9763, 220, 433, 493, 5562, 61514, 518, 1754, 591, 341, 262, 738, 49935, 284, 502, 12721, 8639, 53956, 4627, 746, 262, 738, 11766, 284, 502, 47047, 21346, 53, 18, 21285, 1382, 11, 854, 11, 905, 340, 262, 12721, 56216, 21346, 8144, 85456, 696, 262, 738, 22842, 284, 11766, 59111, 8230, 2892, 262, 11766, 28620, 2097, 2568, 7, 16, 340, 262, 1755, 85456, 26381, 58, 15, 10927, 9074, 2097, 13248, 2097, 59111, 2455, 262, 1755, 85456, 50375, 19251, 570, 13529, 2625, 31830, 2608, 262, 1755, 85456, 23907, 288, 570, 13529, 2625, 1904, 2608, 220, 9763, 220, 433, 493, 5562, 471, 4495, 32942, 2373, 1396, 518, 1754, 591, 341, 262, 738, 11766, 284, 502, 47047, 21346, 53, 18, 5074, 11, 854, 11, 905, 696, 262, 1755, 85456, 20049, 570, 9074, 7, 18, 340, 220, 9763, 220, 433, 493, 5562, 1715, 279, 30158, 2007, 505, 279, 4495, 10537, 518, 1754, 591, 341, 262, 738, 82541, 17591, 284, 502, 5832, 3103, 17591, 746, 262, 738, 11766, 284, 502, 3165, 1142, 33, 6312, 21346, 53, 18, 15611, 2122, 17591, 340, 262, 12721, 56216, 21346, 8144, 85456, 340, 262, 738, 30158, 2014, 284, 314, 40122, 25, 364, 2196, 364, 457, 262, 738, 3882, 2014, 284, 314, 62019, 25, 364, 2239, 6, 457, 262, 738, 33530, 284, 1754, 591, 5731, 262, 738, 389, 23559, 284, 1754, 591, 10294, 262, 738, 22842, 284, 11766, 8387, 25730, 15218, 2313, 415, 30158, 2014, 345, 415, 3882, 2014, 345, 415, 33530, 345, 415, 389, 23559, 198, 262, 9763, 262, 1755, 77706, 570, 13529, 1021, 415, 502, 45546, 5004, 17591, 2313, 286, 1121, 17591, 25, 82541, 17591, 345, 286, 3717, 25, 854, 345, 286, 389, 23559, 345, 286, 33530, 198, 415, 2820, 262, 5235, 262, 1755, 85456, 1462, 6236, 1996, 570, 13529, 7, 16, 340, 262, 1755, 85456, 1462, 6236, 58, 15, 10927, 13529, 9133, 415, 364, 26502, 3000, 1026, 41601, 79494, 673, 25730, 2620, 703, 2196, 17350, 415, 314, 2317, 25, 30158, 2014, 1173, 415, 314, 2564, 6045, 2014, 11, 10055, 2714, 25, 40950, 2714, 9357, 368, 457, 262, 24371, 220, 9763, 220, 7664, 493, 33, 6312, 650, 19, 518, 1754, 591, 341, 262, 1583, 257, 353, 571, 913, 314, 1723, 85456, 25, 47047, 21346, 53, 18, 9317, 5279, 198, 257, 740, 262, 734, 10356, 1480, 320, 8998, 8, 341, 415, 738, 49935, 284, 502, 12721, 8639, 53956, 4627, 746, 415, 738, 11766, 284, 502, 47047, 21346, 53, 18, 21285, 1382, 11, 854, 11, 905, 340, 415, 12721, 56216, 21346, 8144, 85456, 696, 415, 1755, 5175, 591, 5279, 85456, 4682, 89210, 1480, 1021, 286, 364, 11603, 374, 8599, 311, 279, 4729, 430, 1587, 539, 1862, 5361, 32906, 13, 364, 3694, 692, 364, 5618, 14234, 311, 36182, 19, 73, 220, 19, 13, 15, 13, 15, 477, 3010, 304, 2015, 311, 1005, 420, 15293, 1270, 415, 1763, 262, 557, 262, 7664, 493, 59210, 518, 1754, 591, 341, 415, 734, 10356, 11382, 8230, 320, 12494, 8, 341, 286, 10356, 1480, 85456, 591, 11766, 56330, 2358, 4729, 29812, 415, 557, 415, 433, 493, 5562, 2571, 1493, 994, 4729, 374, 743, 518, 1754, 591, 341, 286, 10356, 11382, 8230, 493, 1985, 1329, 415, 2820, 262, 9763, 262, 7664, 493, 6236, 518, 1754, 591, 341, 415, 734, 10356, 6869, 320, 12494, 8, 341, 286, 10356, 1480, 85456, 591, 11766, 7789, 493, 1663, 518, 16857, 314, 4729, 29812, 415, 557, 415, 433, 493, 5562, 2571, 1493, 994, 4729, 374, 743, 518, 1754, 591, 341, 286, 10356, 6869, 493, 1985, 1329, 415, 2820, 262, 2820, 220, 9763, 220, 7664, 493, 33, 6312, 348, 19, 13, 19, 518, 1754, 591, 341, 262, 1583, 257, 353, 571, 913, 314, 928, 92, 60849, 660, 1502, 578, 60849, 660, 1217, 627, 257, 353, 571, 913, 314, 1723, 85456, 25, 47047, 21346, 53, 18, 9317, 5279, 198, 257, 740, 262, 734, 10356, 26282, 1293, 367, 2688, 35736, 7903, 7787, 320, 6802, 1293, 660, 1502, 11, 5279, 8, 341, 415, 738, 49935, 284, 502, 12721, 8639, 53956, 4627, 746, 415, 738, 11766, 284, 502, 47047, 21346, 53, 18, 21285, 1382, 11, 854, 11, 905, 696, 415, 1755, 5175, 591, 5279, 85456, 4682, 89210, 1480, 1021, 286, 364, 11603, 374, 8599, 311, 279, 4729, 430, 1587, 539, 1862, 1217, 60849, 367, 13, 364, 3694, 692, 364, 5618, 14234, 311, 36182, 19, 73, 220, 19, 13, 19, 13, 15, 477, 3010, 304, 2015, 311, 1005, 420, 15293, 13, 364, 3694, 692, 1595, 56962, 311, 60849, 349, 3654, 6802, 1293, 660, 1502, 7966, 4077, 415, 1763, 262, 557, 262, 7664, 493, 59210, 518, 1754, 591, 341, 415, 734, 10356, 11382, 8230, 320, 6802, 1293, 660, 1502, 8, 341, 286, 10356, 26282, 1293, 367, 2688, 35736, 7903, 7787, 1021, 692, 60849, 660, 1502, 345, 692, 11766, 591, 11766, 56330, 2358, 60849, 660, 1502, 29812, 415, 557, 415, 433, 493, 5562, 2571, 1493, 994, 60849, 660, 1502, 374, 743, 518, 1754, 591, 341, 286, 10356, 11382, 8230, 493, 1985, 1329, 415, 2820, 262, 9763, 262, 7664, 493, 6236, 518, 1754, 591, 341, 415, 734, 10356, 6869, 320, 6802, 1293, 660, 1502, 8, 341, 286, 10356, 26282, 1293, 367, 2688, 35736, 7903, 7787, 1021, 692, 60849, 660, 1502, 345, 692, 11766, 591, 11766, 7789, 493, 1663, 518, 16857, 314, 60849, 660, 1502, 29812, 415, 557, 415, 433, 493, 5562, 2571, 1493, 994, 60849, 660, 1502, 374, 743, 518, 1754, 591, 341, 286, 10356, 6869, 493, 1985, 1329, 415, 2820, 262, 2820, 220, 9763, 220, 7664, 493, 81874, 261, 6683, 518, 1754, 591, 341, 262, 1296, 14650, 9133, 415, 510, 3934, 11, 905, 1282, 415, 510, 3934, 11, 837, 1282, 415, 510, 1904, 11, 905, 1282, 415, 510, 1904, 11, 837, 933, 262, 42673, 1021, 415, 364, 5562, 1893, 32165, 261, 449, 11404, 40938, 1752, 1090, 68692, 8003, 79, 323, 1005, 88574, 8003, 79, 756, 415, 320, 18502, 40938, 1752, 1090, 68692, 11, 1005, 88574, 8, 591, 341, 286, 738, 11766, 284, 502, 47047, 21346, 53, 18, 5074, 11, 854, 11, 341, 692, 11404, 40938, 1752, 1090, 68692, 345, 692, 1005, 88574, 198, 286, 2820, 286, 1755, 85456, 1462, 81874, 261, 1462, 18502, 40938, 1752, 1090, 68692, 570, 9074, 1021, 692, 11404, 40938, 1752, 1090, 68692, 198, 286, 1763, 286, 1755, 85456, 1462, 81874, 261, 1462, 817, 88574, 570, 9074, 48462, 88574, 340, 415, 457, 262, 1763, 220, 9763, 220, 7664, 493, 13284, 15914, 518, 1754, 591, 341, 262, 433, 4389, 6236, 368, 1288, 14749, 3090, 15914, 518, 1754, 591, 341, 415, 738, 49935, 284, 502, 12721, 8639, 53956, 4627, 746, 415, 738, 11766, 284, 12721, 56216, 21346, 8144, 1021, 286, 502, 47047, 21346, 53, 18, 21285, 1382, 11, 854, 11, 905, 340, 415, 5235, 415, 738, 3319, 284, 364, 52633, 400, 87, 11, 400, 88, 1270, 415, 738, 5137, 284, 314, 865, 25, 364, 87, 518, 379, 25, 364, 88, 6, 457, 415, 738, 22842, 284, 11766, 7789, 10974, 11, 5137, 11, 341, 286, 62019, 25, 6017, 15914, 9357, 3227, 286, 10055, 2714, 25, 40950, 2714, 9357, 3227, 286, 3428, 6607, 29353, 4075, 25, 220, 1041, 345, 286, 1579, 6607, 29353, 4075, 25, 220, 1049, 198, 415, 9763, 415, 1755, 77706, 1462, 10516, 6607, 29353, 4075, 570, 13529, 7, 1041, 340, 415, 1755, 77706, 1462, 12156, 6607, 29353, 4075, 570, 13529, 7, 1049, 340, 262, 2820, 220, 9763, 220, 7664, 4389, 4853, 481, 62513, 1754, 591, 341, 262, 433, 14650, 9133, 415, 2570, 1997, 518, 502, 6146, 7, 16, 11, 2570, 64, 4181, 314, 264, 25, 364, 65, 6, 2529, 364, 66, 71944, 415, 2570, 51922, 518, 502, 33907, 7, 16, 11, 220, 17, 11, 220, 18, 11, 364, 64, 518, 314, 293, 25, 364, 66, 6, 2529, 364, 67, 518, 364, 68, 518, 364, 69, 71944, 415, 2570, 1844, 11130, 51922, 518, 502, 1252, 11130, 51922, 7, 16, 11, 364, 64, 518, 314, 293, 25, 364, 66, 6, 2529, 364, 16, 71944, 415, 2570, 1858, 518, 502, 8092, 1792, 6146, 7, 16, 11, 10277, 4792, 705, 502, 6146, 7, 17, 11, 10277, 4792, 705, 43282, 933, 262, 42673, 493, 5562, 3854, 539, 3854, 4876, 4595, 13764, 82, 19255, 40564, 4876, 941, 8, 591, 341, 415, 738, 11766, 284, 502, 47047, 21346, 53, 18, 1021, 286, 502, 12721, 8639, 53956, 4627, 3227, 286, 854, 345, 286, 905, 198, 415, 5235, 415, 738, 3854, 481, 284, 11766, 21472, 481, 25301, 941, 696, 415, 1755, 94010, 481, 570, 89210, 1480, 65530, 15359, 746, 262, 9763, 262, 433, 14650, 9133, 415, 2570, 13242, 518, 502, 21722, 7, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 31849, 415, 2570, 7469, 1489, 518, 502, 8949, 1489, 7, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 31849, 415, 2570, 1489, 518, 502, 4212, 7, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 31849, 415, 2570, 1956, 518, 502, 2696, 7, 16, 11, 220, 16, 11, 220, 16, 31849, 415, 2570, 7469, 7844, 518, 502, 48565, 7, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 31849, 415, 2570, 7844, 2409, 15723, 769, 518, 502, 6657, 7, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 11, 5732, 11, 364, 32132, 11628, 3524, 1106, 5049, 78, 71944, 415, 2570, 7844, 518, 502, 6657, 7, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 31849, 415, 2570, 2674, 17, 35, 518, 502, 5236, 7, 16, 11, 220, 16, 11, 220, 16, 31849, 415, 2570, 2674, 18, 35, 518, 502, 5236, 7, 16, 11, 220, 16, 11, 220, 16, 11, 220, 16, 5680, 262, 42673, 493, 5562, 3854, 29079, 4595, 323, 37015, 4595, 13764, 82, 19255, 40564, 1665, 8, 591, 341, 415, 738, 4240, 284, 5691, 7, 4146, 340, 415, 738, 11766, 284, 502, 47047, 21346, 53, 18, 1021, 286, 502, 12721, 8639, 53956, 4627, 3227, 286, 4240, 345, 286, 341, 692, 11404, 40938, 1752, 1090, 68692, 25, 837, 198, 286, 457, 415, 5235, 415, 738, 3854, 481, 284, 11766, 21472, 481, 4496, 696, 415, 1755, 94010, 481, 570, 1962, 2446, 23949, 2892, 415, 4240, 14178, 2892, 415, 738, 32165, 291, 284, 11766, 51863, 12869, 340, 415, 1755, 18870, 51421, 570, 13529, 4496, 340, 262, 2820, 220, 9763, 220, 7664, 4389, 81874, 62513, 1754, 591, 341, 262, 433, 14650, 9133, 415, 2330, 286, 364, 1997, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 19, 68, 11, 510, 16, 11, 2570, 64, 4181, 314, 272, 25, 364, 67, 6, 335, 17473, 286, 502, 6146, 7, 16, 11, 2570, 64, 4181, 314, 272, 25, 364, 67, 6, 2820, 415, 3291, 415, 2330, 286, 364, 51922, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 4103, 11, 510, 16, 11, 220, 17, 11, 220, 18, 11, 364, 19, 518, 314, 220, 20, 25, 220, 21, 335, 17473, 286, 502, 33907, 7, 16, 11, 220, 17, 11, 220, 18, 11, 364, 19, 518, 314, 220, 20, 25, 220, 21, 2820, 415, 3291, 415, 2330, 286, 364, 1844, 11130, 51922, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 5332, 11, 510, 16, 11, 364, 17, 518, 314, 220, 18, 25, 220, 19, 335, 17473, 286, 502, 1252, 11130, 51922, 7, 16, 11, 364, 17, 518, 314, 220, 18, 25, 220, 19, 2820, 415, 3291, 415, 2330, 286, 364, 1858, 756, 286, 502, 6070, 52545, 554, 1021, 692, 220, 15, 87, 1135, 345, 692, 2330, 310, 2330, 1078, 502, 6070, 52545, 554, 7, 15, 87, 19, 68, 11, 510, 16, 11, 2570, 17, 4181, 314, 220, 18, 25, 364, 19, 6, 335, 17473, 1078, 502, 6070, 52545, 554, 7, 15, 87, 19, 68, 11, 510, 19, 11, 2570, 20, 4181, 314, 220, 21, 25, 220, 22, 335, 17473, 1078, 502, 6070, 52545, 554, 7, 15, 87, 19, 68, 11, 510, 17, 11, 2570, 18, 4181, 314, 220, 19, 25, 364, 20, 6, 95339, 310, 3291, 310, 2330, 1078, 502, 6070, 52545, 554, 7, 15, 87, 4103, 11, 510, 18, 11, 220, 16, 11, 220, 19, 11, 364, 3833, 16, 518, 314, 220, 19, 25, 364, 20, 6, 335, 17473, 1078, 502, 6070, 52545, 554, 7, 15, 87, 4103, 11, 510, 20, 11, 220, 19, 11, 220, 17, 11, 364, 3833, 17, 518, 314, 220, 21, 25, 220, 22, 95339, 310, 3291, 310, 510, 16, 11, 220, 16, 11, 220, 17, 11, 220, 17, 933, 692, 5243, 286, 2907, 286, 502, 8092, 1021, 692, 502, 6146, 7, 16, 11, 2570, 17, 4181, 314, 220, 18, 25, 364, 19, 6, 12240, 692, 502, 6146, 7, 17, 11, 2570, 18, 4181, 314, 220, 19, 25, 364, 20, 6, 12240, 692, 2330, 310, 502, 8092, 21766, 1021, 1078, 502, 6146, 7, 16, 11, 2570, 17, 4181, 314, 220, 18, 25, 364, 19, 6, 12240, 1078, 502, 33907, 7, 18, 11, 220, 16, 11, 220, 19, 11, 364, 3833, 16, 518, 314, 220, 19, 25, 364, 20, 6, 12240, 1078, 502, 6146, 7, 19, 11, 2570, 20, 4181, 314, 220, 21, 25, 220, 22, 2820, 310, 2907, 310, 502, 8092, 21766, 1021, 1078, 502, 6146, 7, 19, 11, 2570, 20, 4181, 314, 220, 21, 25, 220, 22, 12240, 1078, 502, 33907, 7, 20, 11, 220, 19, 11, 220, 17, 11, 364, 3833, 17, 518, 314, 220, 21, 25, 220, 22, 12240, 1078, 502, 6146, 7, 17, 11, 2570, 18, 4181, 314, 220, 19, 25, 364, 20, 6, 2820, 310, 1763, 692, 5243, 286, 1763, 415, 5243, 262, 42673, 493, 5562, 32165, 4876, 4595, 13764, 82, 19255, 40564, 2080, 11, 4876, 1211, 8, 591, 341, 415, 738, 4240, 284, 5691, 7, 4146, 340, 415, 738, 11766, 284, 502, 47047, 21346, 53, 18, 1021, 286, 502, 12721, 8639, 53956, 4627, 3227, 286, 4240, 345, 286, 905, 198, 415, 5235, 415, 738, 3854, 481, 284, 11766, 21472, 481, 6294, 696, 415, 1755, 94010, 481, 570, 1962, 2446, 23949, 2892, 415, 4240, 14178, 2892, 415, 738, 32165, 291, 284, 11766, 51863, 12869, 340, 415, 1755, 18870, 51421, 570, 13529, 25301, 1211, 340, 262, 9763, 262, 433, 14650, 9133, 415, 2330, 286, 364, 1997, 449, 2753, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 19, 68, 11, 510, 16, 11, 2570, 64, 98705, 415, 3291, 415, 2330, 286, 364, 1997, 449, 810, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 19, 68, 11, 510, 16, 11, 2570, 64, 4181, 314, 272, 25, 364, 67, 6, 2529, 364, 16, 7519, 415, 3291, 415, 2330, 286, 364, 51922, 449, 2753, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 4103, 11, 510, 16, 11, 220, 17, 11, 220, 18, 11, 364, 19, 7519, 415, 3291, 415, 2330, 286, 364, 51922, 449, 810, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 4103, 11, 510, 16, 11, 220, 17, 11, 220, 18, 11, 364, 19, 518, 314, 220, 20, 25, 220, 21, 2529, 364, 16, 518, 364, 17, 518, 364, 18, 7519, 415, 3291, 415, 2330, 286, 364, 1844, 11130, 51922, 449, 2753, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 5332, 11, 510, 16, 11, 364, 17, 7519, 415, 3291, 415, 2330, 286, 364, 1844, 11130, 51922, 449, 810, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 5332, 11, 510, 16, 11, 364, 17, 518, 314, 220, 18, 25, 220, 19, 2529, 364, 16, 7519, 415, 3291, 415, 2330, 286, 364, 1858, 449, 2753, 5151, 756, 286, 502, 6070, 52545, 554, 1021, 692, 220, 15, 87, 1135, 345, 692, 2330, 310, 2330, 1078, 502, 6070, 52545, 554, 7, 15, 87, 19, 68, 11, 510, 16, 11, 2570, 17, 4181, 314, 220, 18, 25, 364, 19, 6, 335, 17473, 1078, 502, 6070, 52545, 554, 7, 15, 87, 19, 68, 11, 510, 19, 11, 2570, 20, 4181, 314, 220, 21, 25, 220, 22, 335, 17473, 1078, 502, 6070, 52545, 554, 7, 15, 87, 19, 68, 11, 510, 17, 11, 2570, 18, 4181, 314, 220, 19, 25, 364, 20, 6, 95339, 310, 3291, 310, 2330, 1078, 502, 6070, 52545, 554, 7, 15, 87, 4103, 11, 510, 18, 11, 220, 16, 11, 220, 19, 11, 364, 3833, 16, 518, 314, 220, 19, 25, 364, 20, 6, 335, 17473, 1078, 502, 6070, 52545, 554, 7, 15, 87, 4103, 11, 510, 20, 11, 220, 19, 11, 220, 17, 11, 364, 3833, 17, 518, 314, 220, 21, 25, 220, 22, 95339, 310, 5243, 692, 5243, 286, 1763, 415, 3291, 415, 2330, 286, 364, 1858, 449, 810, 5151, 756, 286, 502, 6070, 52545, 554, 1021, 692, 220, 15, 87, 1135, 345, 692, 2330, 310, 2330, 1078, 502, 6070, 52545, 554, 7, 15, 87, 19, 68, 11, 510, 16, 11, 2570, 17, 4181, 314, 220, 18, 25, 364, 19, 6, 335, 17473, 1078, 502, 6070, 52545, 554, 7, 15, 87, 19, 68, 11, 510, 19, 11, 2570, 20, 4181, 314, 220, 21, 25, 220, 22, 335, 17473, 1078, 502, 6070, 52545, 554, 7, 15, 87, 19, 68, 11, 510, 17, 11, 2570, 18, 4181, 314, 220, 19, 25, 364, 20, 6, 95339, 310, 3291, 310, 2330, 1078, 502, 6070, 52545, 554, 7, 15, 87, 4103, 11, 510, 18, 11, 220, 16, 11, 220, 19, 11, 364, 3833, 16, 518, 314, 220, 19, 25, 364, 20, 6, 335, 17473, 1078, 502, 6070, 52545, 554, 7, 15, 87, 4103, 11, 510, 20, 11, 220, 19, 11, 220, 17, 11, 364, 3833, 17, 518, 314, 220, 21, 25, 220, 22, 95339, 310, 3291, 310, 510, 16, 11, 220, 16, 11, 220, 17, 11, 220, 17, 1282, 310, 364, 64, 1270, 692, 5243, 286, 1763, 415, 3291, 415, 2330, 286, 364, 2674, 449, 2753, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2970, 11, 510, 16, 11, 220, 17, 2608, 415, 3291, 415, 2330, 286, 364, 2674, 449, 810, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2970, 11, 510, 16, 11, 220, 17, 11, 220, 18, 11, 220, 19, 2608, 415, 3291, 415, 2330, 286, 364, 2674, 18, 35, 449, 2753, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2946, 11, 510, 16, 11, 220, 17, 11, 220, 18, 2608, 415, 40874, 415, 2330, 286, 364, 2674, 18, 35, 449, 810, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2946, 11, 510, 16, 11, 220, 17, 11, 220, 18, 11, 220, 19, 11, 220, 21, 2608, 415, 3291, 415, 2330, 286, 364, 13242, 449, 2753, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 1774, 11, 510, 16, 11, 220, 17, 11, 220, 18, 2608, 415, 3291, 415, 2330, 286, 364, 13242, 449, 810, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 1774, 11, 510, 16, 11, 220, 17, 11, 220, 18, 11, 220, 19, 11, 220, 20, 2608, 415, 3291, 415, 2330, 286, 364, 7469, 1489, 449, 2753, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 5728, 11, 28714, 415, 3291, 415, 2330, 286, 364, 7469, 1489, 449, 810, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 5728, 11, 510, 16, 11, 220, 17, 2608, 415, 3291, 415, 2330, 286, 364, 1489, 449, 2753, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 4370, 11, 510, 16, 2608, 415, 3291, 415, 2330, 286, 364, 1489, 449, 810, 1052, 5469, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 4370, 11, 510, 16, 11, 220, 17, 11, 220, 18, 2608, 415, 3291, 415, 2330, 286, 364, 1956, 449, 2753, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2096, 11, 28714, 415, 3291, 415, 2330, 286, 364, 1956, 449, 810, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2096, 11, 510, 16, 11, 220, 17, 2608, 415, 3291, 415, 2330, 286, 364, 7469, 7844, 449, 2753, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 1227, 11, 510, 16, 2608, 415, 3291, 415, 2330, 286, 364, 7469, 7844, 449, 810, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 1227, 11, 510, 16, 11, 220, 17, 11, 220, 18, 2608, 415, 3291, 415, 2330, 286, 364, 7844, 2409, 15723, 6582, 449, 2753, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2790, 11, 510, 16, 11, 220, 17, 2608, 415, 3291, 415, 2330, 286, 364, 7844, 2409, 15723, 6582, 449, 810, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2790, 11, 510, 16, 11, 220, 17, 11, 220, 18, 11, 220, 19, 2608, 415, 3291, 415, 2330, 286, 364, 7844, 2409, 15723, 769, 449, 2753, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2287, 11, 510, 16, 11, 220, 17, 2608, 415, 3291, 415, 2330, 286, 364, 7844, 2409, 15723, 769, 449, 810, 5151, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2287, 11, 510, 16, 11, 220, 17, 11, 364, 32132, 11628, 3524, 1106, 5049, 78, 518, 364, 6971, 30149, 7519, 415, 5243, 262, 42673, 493, 5562, 539, 32165, 449, 5076, 1404, 13764, 82, 19255, 40564, 2080, 8, 591, 341, 415, 738, 4240, 284, 5691, 7, 4146, 340, 415, 738, 11766, 284, 502, 47047, 21346, 53, 18, 1021, 286, 502, 12721, 8639, 53956, 4627, 3227, 286, 4240, 345, 286, 905, 198, 415, 5235, 415, 738, 3854, 481, 284, 11766, 21472, 481, 6294, 696, 415, 1755, 94010, 481, 570, 1962, 2446, 23949, 2892, 415, 4240, 14178, 2892, 415, 738, 32165, 291, 284, 11766, 51863, 12869, 340, 415, 1755, 5175, 591, 32165, 291, 8243, 6070, 52545, 554, 570, 89210, 1480, 65530, 15359, 746, 262, 9763, 262, 433, 14650, 9133, 415, 2330, 286, 364, 2674, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2970, 11, 510, 16, 11, 220, 17, 11, 220, 18, 17473, 286, 502, 5236, 7, 16, 11, 220, 17, 11, 220, 18, 340, 415, 3291, 415, 2330, 286, 364, 2674, 18, 35, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2946, 11, 510, 16, 11, 220, 17, 11, 220, 18, 11, 220, 19, 17473, 286, 502, 5236, 7, 16, 11, 220, 17, 11, 220, 18, 11, 220, 19, 340, 415, 3291, 415, 2330, 286, 364, 13242, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 1774, 11, 510, 16, 11, 220, 17, 11, 220, 18, 11, 220, 19, 17473, 286, 502, 21722, 7, 16, 11, 220, 17, 11, 220, 18, 11, 220, 19, 340, 415, 3291, 415, 2330, 286, 364, 7469, 1489, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 5728, 11, 510, 16, 17473, 286, 502, 8949, 1489, 7, 15, 11, 220, 15, 11, 220, 15, 11, 220, 16, 340, 415, 3291, 415, 2330, 286, 364, 1489, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 4370, 11, 510, 16, 11, 220, 17, 17473, 286, 502, 4212, 7, 15, 11, 220, 15, 11, 220, 15, 11, 220, 16, 11, 220, 17, 340, 415, 3291, 415, 2330, 286, 364, 1956, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2096, 11, 510, 16, 17473, 286, 502, 2696, 7, 4468, 15, 11, 220, 16, 11, 220, 17, 340, 415, 3291, 415, 2330, 286, 364, 7469, 7844, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 1227, 11, 510, 16, 11, 220, 17, 17473, 286, 502, 48565, 7, 4468, 15, 11, 220, 16, 11, 220, 16, 11, 220, 15, 11, 220, 15, 11, 220, 16, 11, 220, 17, 340, 415, 3291, 415, 2330, 286, 364, 7844, 2409, 15723, 6582, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2790, 11, 510, 16, 11, 220, 17, 11, 220, 18, 17473, 286, 502, 6657, 7, 4468, 15, 11, 220, 16, 11, 220, 16, 11, 220, 15, 11, 220, 15, 11, 220, 16, 11, 220, 17, 11, 220, 18, 340, 415, 3291, 415, 2330, 286, 364, 7844, 2409, 15723, 769, 756, 286, 502, 6070, 52545, 554, 7, 15, 87, 2287, 11, 510, 16, 11, 220, 17, 11, 364, 32132, 11628, 3524, 1106, 5049, 78, 30340, 286, 502, 6657, 7, 4468, 15, 11, 220, 16, 11, 220, 16, 11, 220, 15, 11, 220, 15, 11, 220, 16, 11, 220, 17, 11, 5732, 11, 364, 32132, 11628, 3524, 1106, 5049, 78, 1329, 415, 5243, 262, 42673, 493, 5562, 32165, 29079, 4595, 323, 37015, 4595, 13764, 82, 19255, 40564, 2080, 11, 1665, 8, 591, 341, 415, 738, 4240, 284, 5691, 7, 4146, 340, 415, 738, 11766, 284, 502, 47047, 21346, 53, 18, 1021, 286, 502, 12721, 8639, 53956, 4627, 3227, 286, 4240, 345, 286, 341, 692, 11404, 40938, 1752, 1090, 68692, 25, 837, 198, 286, 457, 415, 5235, 415, 738, 3854, 481, 284, 11766, 21472, 481, 6294, 696, 415, 1755, 94010, 481, 570, 1962, 2446, 23949, 2892, 415, 4240, 14178, 2892, 415, 738, 32165, 291, 284, 11766, 51863, 12869, 340, 415, 1755, 18870, 51421, 570, 13529, 4496, 340, 262, 2820, 220, 2820, 9000, 1058, 3165, 1142, 33, 6312, 21346, 53, 18, 2289, 47047, 21346, 53, 18, 341, 220, 4797, 320, 1407, 17591, 8, 341, 262, 2307, 5074, 11, 854, 11, 905, 340, 262, 420, 1462, 6236, 284, 4260, 262, 420, 1462, 1407, 17591, 284, 1121, 17591, 198, 220, 557, 220, 1629, 1754, 341, 262, 420, 1462, 6236, 2615, 83566, 16774, 2608, 262, 471, 420, 1462, 1407, 17591, 198, 220, 457, 534, 128000, 1757, 470, 11895, 2192, 383, 9339, 11895, 2706, 1197, 4120, 21952, 14411, 401, 475, 470, 11895, 2192, 383, 9339, 11895, 2706, 1197, 4120, 21952, 3272, 5368, 2192, 4137, 15270, 280, 475, 470, 11895, 2192, 383, 9339, 11895, 2706, 1197, 4120, 21952, 3272, 5368, 2192, 85185, 15270, 280, 475, 470, 11895, 2192, 383, 9339, 11895, 2706, 1197, 4120, 21952, 3272, 5368, 2192, 1939, 15270, 280, 475, 470, 11895, 2192, 383, 9339, 11895, 2706, 1197, 4120, 3272, 5368, 2192, 1939, 401, 475, 1674, 2013, 5937, 401, 898, 1620, 538, 549, 2192, 1939, 15270, 4246, 341, 262, 879, 549, 2192, 1939, 15270, 4246, 368, 341, 262, 557, 262, 586, 1118, 549, 2192, 1939, 15270, 1893, 10285, 549, 2192, 1939, 577, 2192, 1939, 8, 341, 286, 1620, 549, 2192, 1939, 15270, 577, 2192, 1939, 15270, 284, 502, 549, 2192, 1939, 15270, 545, 286, 577, 2192, 1939, 15270, 995, 5561, 8327, 8317, 2192, 1939, 2124, 5561, 8327, 317, 286, 577, 2192, 1939, 15270, 995, 48527, 1939, 644, 12608, 72, 8317, 2192, 1939, 870, 820, 791, 1939, 644, 12608, 72, 317, 286, 577, 2192, 1939, 15270, 995, 3607, 8317, 2192, 1939, 13204, 317, 286, 577, 2192, 1939, 15270, 28737, 8317, 2192, 1939, 2710, 317, 286, 577, 2192, 1939, 15270, 995, 5561, 8317, 2192, 1939, 5189, 317, 286, 577, 2192, 1939, 15270, 995, 5561, 14118, 941, 8317, 2192, 1939, 64208, 14118, 941, 1449, 286, 577, 2192, 1939, 15270, 66578, 8317, 2192, 1939, 13480, 317, 286, 577, 2192, 1939, 15270, 995, 1858, 8317, 2192, 1939, 3960, 317, 286, 577, 2192, 1939, 15270, 995, 8327, 30604, 8317, 2192, 1939, 20664, 30604, 629, 286, 1620, 1796, 37497, 2192, 4137, 15270, 29, 577, 2192, 8327, 4137, 15270, 861, 284, 549, 2192, 4137, 15270, 4246, 2581, 1021, 310, 577, 2192, 1939, 673, 8327, 4137, 861, 746, 286, 1465, 286, 577, 2192, 1939, 15270, 995, 8327, 4137, 861, 8317, 2192, 8327, 4137, 15270, 861, 629, 286, 1620, 1796, 37497, 2192, 85185, 15270, 29, 577, 2192, 8327, 85185, 15270, 861, 284, 549, 2192, 85185, 15270, 4246, 2581, 1021, 310, 577, 2192, 1939, 673, 8327, 85185, 861, 746, 286, 1465, 286, 577, 2192, 1939, 15270, 995, 8327, 85185, 861, 8317, 2192, 8327, 85185, 15270, 861, 629, 286, 1620, 1796, 37497, 2192, 4137, 15270, 29, 577, 2192, 15669, 4137, 15270, 861, 284, 549, 2192, 4137, 15270, 4246, 2581, 1021, 310, 577, 2192, 1939, 673, 15669, 4137, 861, 746, 286, 1465, 286, 577, 2192, 1939, 15270, 995, 15669, 4137, 861, 8317, 2192, 15669, 4137, 15270, 861, 629, 286, 1620, 1796, 37497, 2192, 85185, 15270, 29, 577, 2192, 15669, 85185, 15270, 861, 284, 549, 2192, 85185, 15270, 4246, 2581, 1021, 310, 577, 2192, 1939, 673, 15669, 85185, 861, 746, 286, 1465, 286, 577, 2192, 1939, 15270, 995, 15669, 85185, 861, 8317, 2192, 15669, 85185, 15270, 861, 629, 286, 471, 577, 2192, 1939, 15270, 280, 262, 457, 534, 128000, 2688, 2771, 922, 279, 4732, 719, 279, 1888, 3245, 311, 656, 374, 311, 1456, 433, 3469, 29639, 13, 220, 1049, 8187, 16946, 11, 420, 3388, 16168, 6835, 499, 682, 499, 1205, 311, 387, 6992, 13, 2360, 16946, 16674, 2132, 35319, 8026, 2671, 35319, 8026, 3072, 13845, 912, 16946, 11, 1778, 439, 6130, 1862, 11, 814, 1101, 617, 1579, 7692, 9736, 277, 71, 2671, 11, 719, 779, 374, 279, 1973, 11565, 13, 6104, 358, 1097, 8244, 18949, 449, 30167, 11, 499, 75, 1505, 11987, 14957, 311, 387, 1633, 1695, 627, 4516, 1524, 11, 13697, 21070, 86281, 3430, 30350, 84642, 2704, 69407, 409, 6201, 25425, 13, 220, 17678, 17, 13, 11361, 73004, 21106, 46237, 358, 10273, 701, 7079, 11380, 10721, 389, 701, 3997, 627, 644, 12232, 19, 8026, 2671, 13, 3092, 2759, 6783, 3309, 757, 358, 1047, 220, 17, 53142, 31442, 11, 433, 374, 264, 2466, 35726, 11, 1418, 10435, 2671, 5357, 389, 1884, 389, 279, 18174, 0, 4702, 6068, 555, 323, 2610, 4790, 2234, 814, 656, 627, 4061, 6160, 661, 3249, 6405, 5708, 706, 1027, 52876, 1778, 264, 1317, 92370, 9327, 439, 1664, 439, 1268, 499, 649, 1005, 279, 2326, 12280, 1752, 7252, 8026, 2671, 11380, 480, 691, 8423, 439, 264, 17496, 8026, 2671, 8450, 4999, 33, 1149, 409, 323, 10631, 279, 11380, 8446, 389, 8026, 3072, 1887, 36865, 11380, 13, 25274, 31442, 2949, 420, 892, 4124, 374, 6646, 311, 387, 30549, 1109, 11380, 449, 264, 2875, 51021, 892, 13, 578, 6763, 2109, 9508, 2216, 4585, 88, 13, 7566, 11, 91436, 18876, 12937, 23869, 11, 37830, 18099, 6872, 0, 30070, 1457, 420, 5557, 574, 1193, 2561, 389, 264, 7347, 8197, 304, 3373, 16410, 19672, 0, 26778, 46436, 5131, 10565, 304, 7008, 617, 1027, 15324, 369, 872, 3831, 323, 10978, 43839, 811, 627, 40, 3974, 304, 8494, 323, 617, 1027, 4790, 13885, 520, 11380, 369, 1063, 892, 1457, 13, 7429, 358, 14000, 1063, 1274, 389, 701, 2816, 7252, 8026, 2671, 11380, 480, 691, 8715, 1611, 18188, 59750, 839, 1124, 369, 264, 2763, 315, 3300, 323, 1243, 10717, 10695, 1124, 994, 814, 5675, 682, 2768, 872, 17738, 13, 578, 9610, 7252, 8026, 2671, 11380, 480, 691, 1701, 8732, 17606, 46038, 374, 430, 499, 636, 311, 1935, 9610, 315, 279, 990, 304, 264, 2027, 264, 1060, 6931, 1109, 1053, 6062, 387, 279, 1162, 627, 2520, 3187, 814, 4287, 34751, 4669, 8323, 37686, 1093, 65229, 21243, 11, 323, 1949, 311, 294, 73291, 304, 279, 2930, 25725, 5064, 11, 3230, 2587, 34824, 323, 1790, 810, 28858, 11, 1202, 3062, 311, 387, 11537, 449, 1268, 814, 1782, 505, 8776, 2671, 11, 1176, 1051, 2133, 311, 1005, 433, 311, 4048, 279, 1455, 8147, 1862, 323, 13957, 5990, 323, 1884, 527, 2133, 311, 387, 1511, 369, 11811, 11, 264, 2883, 320, 1885, 29526, 477, 6062, 8, 2011, 3060, 387, 9879, 9736, 86, 894, 279, 356, 4082, 34, 477, 430, 2883, 1253, 539, 2187, 499, 311, 6696, 38983, 2671, 258, 1023, 4339, 627, 50, 592, 2692, 279, 8882, 311, 912, 13, 10926, 499, 1781, 42497, 14908, 374, 810, 15987, 1109, 1023, 46436, 11, 5042, 4299, 279, 5927, 17940, 5591, 3215, 389, 279, 5740, 315, 279, 2199, 323, 499, 690, 387, 4529, 311, 279, 19157, 588, 2199, 902, 690, 1501, 369, 13489, 220, 18, 6622, 627, 40, 617, 2663, 12387, 3115, 323, 2163, 6743, 311, 1650, 757, 323, 358, 31081, 306, 6755, 1203, 505, 86753, 8051, 559, 288, 520, 990, 13, 358, 7318, 279, 220, 5154, 603, 67, 439, 824, 7845, 449, 856, 6807, 54288, 2277, 13, 5810, 374, 279, 2339, 20426, 33321, 9076, 555, 1023, 46436, 902, 1397, 264, 3544, 1396, 315, 81727, 311, 1218, 1017, 6444, 311, 15142, 872, 33321, 11, 499, 1288, 18467, 41697, 661, 15779, 16383, 311, 6725, 2383, 304, 42102, 29101, 311, 902, 701, 3488, 18713, 1771, 11, 323, 279, 3135, 315, 11380, 1778, 527, 4062, 11, 16946, 323, 15142, 11, 584, 690, 1457, 1427, 520, 5627, 311, 7858, 4754, 17888, 1147, 304, 3430, 320, 8370, 374, 1401, 369, 50453, 8026, 2671, 6696, 6848, 705, 527, 499, 459, 34426, 477, 49972, 358, 617, 8208, 1555, 701, 3997, 323, 433, 374, 12738, 627, 40, 617, 1027, 43931, 7252, 8026, 2671, 11380, 480, 691, 7752, 2533, 279, 220, 777, 339, 6186, 420, 1060, 311, 471, 3300, 430, 574, 4529, 704, 315, 856, 6807, 3786, 2759, 2085, 856, 8041, 13, 1283, 5829, 29862, 1093, 3320, 267, 568, 374, 33630, 449, 499, 369, 9736, 277, 3815, 1148, 568, 10975, 499, 323, 7252, 8026, 2671, 11380, 480, 691, 1071, 568, 12504, 7252, 8026, 2671, 11380, 480, 691, 439, 813, 2759, 6783, 11, 293, 2259, 31695, 315, 5496, 279, 3469, 321, 4511, 315, 264, 757, 16876, 316, 5676, 582, 323, 264, 42823, 627, 69506, 499, 48707, 2793, 264, 2763, 315, 3300, 449, 1124, 13, 8091, 311, 420, 482, 4141, 538, 39298, 81, 13, 7570, 3582, 11284, 34945, 1268, 46436, 75049, 2349, 31442, 11, 304, 459, 4879, 311, 1304, 264, 11626, 13, 578, 6671, 374, 7252, 8026, 2671, 11380, 480, 691, 79849, 422, 264, 810, 49061, 291, 8752, 1109, 17442, 25930, 1202, 2802, 7969, 627, 3947, 527, 1690, 8125, 369, 420, 11, 433, 5084, 1093, 264, 2763, 315, 1274, 527, 10371, 922, 94634, 58882, 1322, 7252, 8026, 2671, 11380, 480, 691, 1457, 779, 358, 1097, 26619, 814, 6051, 11887, 420, 3085, 13, 21694, 22770, 11, 342, 728, 8026, 3072, 264, 35726, 59214, 8446, 33962, 430, 6244, 8010, 315, 279, 342, 728, 453, 1768, 72, 15012, 627, 2028, 374, 1148, 2204, 43398, 8026, 2671, 505, 14733, 33165, 46515, 13, 4740, 499, 617, 9107, 459, 2759, 11, 719, 279, 5578, 4780, 690, 2744, 387, 8389, 369, 279, 30693, 30, 6104, 50939, 435, 4940, 706, 1193, 1027, 304, 5784, 369, 279, 3347, 2478, 1667, 11, 578, 4320, 311, 701, 3488, 374, 18188, 49789, 12, 18748, 264, 35726, 358, 8621, 264, 3477, 389, 13674, 311, 1456, 311, 7216, 420, 704, 297, 41356, 627, 4516, 7729, 1253, 387, 2204, 505, 9473, 7729, 323, 1253, 539, 387, 13687, 311, 1972, 892, 11380, 7729, 13, 3580, 1057, 4553, 350, 637, 2277, 11216, 13, 58588, 3072, 8446, 4232, 627, 19931, 4048, 11380, 1887, 13, 7419, 320, 4881, 47728, 17931, 264, 7325, 8, 791, 5021, 8292, 690, 1005, 4595, 323, 5865, 505, 279, 7325, 7252, 8026, 2671, 11380, 480, 691, 13, 7429, 11, 779, 387, 433, 627, 40, 2231, 304, 264, 1715, 311, 3072, 68, 6033, 220, 13341, 13, 1102, 11112, 3727, 5647, 311, 4254, 449, 420, 2532, 374, 499, 2736, 617, 6787, 311, 41148, 13002, 18188, 14908, 32704, 3907, 30302, 832, 315, 872, 46436, 627, 14809, 8026, 2671, 11380, 480, 691, 499, 617, 264, 3230, 8199, 11, 719, 279, 4839, 38899, 62264, 527, 539, 7633, 13, 5751, 3085, 5764, 1183, 3329, 75955, 10105, 323, 37962, 75955, 17658, 1022, 10826, 7666, 491, 439, 1664, 439, 2587, 4500, 13, 358, 617, 264, 3488, 922, 1268, 311, 743, 709, 3582, 11, 3794, 2731, 12789, 389, 24305, 8276, 13, 1115, 574, 832, 315, 279, 8706, 13353, 9736, 51071, 304, 856, 2324, 11, 323, 279, 7901, 9093, 27656, 1825, 2085, 904, 7252, 8026, 2671, 11380, 480, 691, 8070, 477, 8895, 3156, 279, 16483, 29672, 374, 5616, 32372, 4999, 12608, 290, 17724, 10349, 9086, 1023, 2204, 22325, 7620, 11, 814, 527, 5605, 814, 48707, 5371, 856, 426, 267, 23700, 60187, 876, 872, 3110, 23751, 24007, 814, 1390, 757, 311, 3708, 27437, 1578, 311, 872, 8907, 4669, 2613, 13, 11361, 369, 701, 2038, 323, 480, 15259, 13, 86869, 362, 9781, 287, 315, 23301, 430, 617, 1027, 3549, 311, 1501, 264, 16694, 315, 279, 27927, 25452, 11987, 0, 220, 868, 11, 439, 1664, 439, 1694, 279, 3445, 311, 7380, 1063, 22643, 3300, 11, 25361, 12111, 4207, 4227, 13, 5112, 12793, 433, 11157, 323, 8036, 3770, 433, 1578, 627, 2181, 374, 3629, 3284, 311, 6865, 279, 79538, 6725, 50939, 433, 4832, 11, 47910, 10343, 5097, 279, 1023, 3185, 315, 701, 8026, 3072, 5226, 323, 690, 2343, 499, 279, 9076, 11626, 471, 422, 499, 12722, 7168, 279, 7351, 315, 279, 9513, 3060, 5190, 1650, 3072, 477, 4827, 2231, 3072, 13, 2030, 420, 374, 43593, 539, 264, 70625, 12268, 434, 3575, 11, 719, 814, 2744, 5388, 553, 439, 814, 3351, 4741, 627, 33, 581, 661, 8446, 29862, 1948, 35319, 449, 17074, 2759, 1949, 11380, 7032, 15012, 13, 32704, 1888, 8026, 3072, 3157, 8026, 20369, 287, 1650, 2671, 389, 23301, 16655, 18188, 7104, 6031, 10789, 5034, 19881, 1395, 8026, 3072, 17738, 4790, 2234, 1448, 19067, 2671, 11380, 323, 1156, 354, 37171, 8026, 2671, 11380, 3135, 7362, 1200, 70, 919, 2671, 61316, 3252, 8026, 3072, 17074, 9178, 8026, 3072, 912, 16946, 2631, 11380, 1887, 43421, 70488, 369, 8026, 2671, 832, 5916, 11, 19930, 11380, 3938, 323, 2671, 11, 10816, 8026, 2671, 17074, 2759, 11, 605, 9568, 8026, 2671, 8446, 2930, 3388, 8568, 3367, 3072, 912, 16946, 2631, 11380, 1887, 11, 323, 3196, 389, 5195, 26396, 10396, 627, 35, 546, 4510, 832, 3492, 315, 279, 46436, 44713, 480, 15259, 499, 11, 902, 15714, 7054, 18188, 7104, 6732, 21350, 8350, 32187, 701, 31442, 11, 7999, 810, 10519, 481, 2082, 2385, 323, 17392, 7649, 11, 422, 1070, 374, 904, 5674, 9057, 4245, 311, 872, 84834, 323, 41086, 11850, 315, 872, 5982, 2038, 11, 279, 8250, 315, 279, 19832, 32704, 18188, 14908, 17747, 8669, 323, 279, 24198, 304, 3469, 74, 2439, 311, 6696, 11, 602, 617, 9107, 459, 2759, 449, 1124, 439, 264, 3044, 505, 832, 315, 279, 8450, 9287, 1243, 7252, 8026, 2671, 11380, 480, 691, 54568, 922, 220, 7007, 11441, 323, 2751, 264, 4528, 3392, 439, 12306, 505, 1124, 11, 7054, 2091, 323, 21080, 7104, 690, 1095, 499, 1212, 449, 220, 1041, 11, 719, 422, 499, 9229, 627, 2181, 49609, 3156, 8026, 2671, 574, 4529, 1523, 505, 279, 1925, 30098, 430, 3927, 8026, 2671, 46436, 43333, 709, 44114, 430, 35687, 1505, 8026, 2671, 4228, 311, 3619, 323, 1005, 13, 763, 420, 1162, 11, 52394, 11, 2360, 16946, 17738, 13708, 374, 13, 358, 5602, 459, 8071, 523, 33024, 11621, 922, 8026, 11380, 627, 33, 15930, 11, 4832, 369, 7931, 889, 16869, 2503, 520, 279, 6500, 682, 279, 892, 13, 3277, 602, 3940, 279, 2759, 602, 2751, 220, 1135, 11, 931, 5922, 315, 6725, 7252, 32704, 18188, 14908, 19152, 22050, 420, 574, 311, 636, 1511, 311, 11380, 323, 1101, 311, 990, 389, 15174, 13, 8155, 2046, 584, 1047, 10280, 779, 279, 11987, 1051, 682, 927, 279, 6160, 3367, 779, 430, 387, 961, 315, 279, 2944, 426, 1441, 449, 1561, 23116, 5108, 709, 439, 1664, 11, 8026, 2671, 29709, 8026, 2671, 719, 602, 1373, 34319, 6358, 62200, 34319, 627, 18408, 7691, 2057, 2457, 11, 7252, 8026, 2671, 11380, 480, 691, 220, 19, 82, 8, 5099, 11, 279, 1455, 3293, 3430, 7351, 1253, 387, 279, 30230, 8331, 13, 1789, 3187, 11, 220, 22, 2919, 264, 2046, 13, 38343, 13, 1561, 35687, 16655, 18188, 11380, 90062, 17316, 617, 420, 3488, 304, 4059, 5927, 285, 264, 8026, 3469, 822, 2439, 17074, 2759, 2216, 3062, 477, 374, 433, 1120, 264, 12571, 7252, 8026, 2671, 11380, 480, 691, 892, 30, 5591, 1690, 502, 35687, 617, 279, 7422, 430, 433, 374, 539, 3284, 311, 1304, 3300, 994, 499, 527, 7649, 704, 389, 5684, 5380, 12763, 10826, 2442, 9484, 374, 832, 315, 279, 7252, 8026, 2671, 11380, 480, 691, 5526, 323, 13882, 1511, 15174, 499, 649, 1005, 304, 220, 1399, 44963, 70837, 11380, 13, 64466, 18569, 482, 77434, 49, 72, 1609, 4657, 2009, 604, 64, 372, 2312, 268, 38294, 11, 323, 5707, 37923, 1051, 2212, 1317, 1603, 8026, 11380, 22763, 439, 264, 3682, 11040, 9341, 5507, 1203, 304, 220, 1049, 23, 627, 13622, 1274, 7054, 32704, 18188, 14908, 3005, 604, 80596, 311, 2978, 220, 23, 1667, 311, 1304, 420, 955, 315, 3469, 73, 2439, 11, 6062, 279, 4379, 7252, 8026, 2671, 11380, 480, 691, 387, 50244, 389, 1057, 14365, 627, 2028, 23117, 6209, 264, 7029, 2134, 315, 1767, 18188, 7104, 16406, 220, 15831, 22045, 3263, 15853, 22677, 2876, 14968, 3263, 7913, 5000, 32704, 7566, 13716, 32704, 2360, 68481, 278, 59678, 220, 914, 11307, 369, 6201, 8481, 86304, 29298, 220, 1041, 2360, 49571, 16963, 72, 919, 23429, 8167, 220, 15831, 22045, 527, 5131, 10209, 502, 6444, 889, 41148, 1457, 264, 220, 1041, 1949, 912, 16946, 12306, 13, 4452, 11, 264, 1948, 22359, 37962, 3313, 11164, 45465, 13174, 8069, 13, 362, 45465, 10032, 311, 1304, 1005, 315, 28598, 8026, 2671, 11380, 11, 2737, 37923, 323, 2671, 3196, 389, 13014, 7969, 23379, 447, 488, 25998, 11, 29543, 9473, 11, 17947, 11, 351, 2265, 44547, 51967, 11, 4150, 1147, 11, 15561, 438, 8110, 12675, 11, 30545, 661, 393, 1433, 627, 45600, 11, 912, 5030, 889, 279, 426, 50594, 11, 8026, 2671, 527, 4315, 1455, 5526, 4595, 315, 11380, 13, 1789, 4726, 2038, 9002, 279, 1005, 315, 420, 3997, 4587, 1373, 15884, 1057, 4060, 2724, 1914, 23314, 3947, 374, 2744, 264, 8187, 3392, 315, 3300, 743, 555, 682, 46436, 304, 2015, 311, 1095, 279, 35687, 2680, 311, 279, 8197, 4519, 315, 279, 2816, 13, 11930, 320, 21470, 439, 3566, 47437, 8, 323, 1862, 505, 23117, 690, 1520, 499, 311, 4048, 7252, 8026, 2671, 11380, 480, 691, 2574, 627, 2028, 34350, 994, 279, 11987, 527, 539, 1825, 11, 323, 1148, 1051, 279, 25127, 369, 279, 7351, 315, 872, 23301, 13, 1666, 264, 2860, 315, 927, 279, 29292, 5415, 297, 10630, 8026, 26171, 374, 10223, 29600, 527, 264, 2872, 627, 2746, 32669, 18880, 1047, 1027, 304, 279, 8026, 2671, 1847, 369, 3892, 1667, 11, 304, 902, 568, 8349, 311, 617, 27785, 220, 508, 11236, 2561, 627, 1548, 706, 927, 220, 966, 1667, 315, 19248, 304, 6763, 11, 499, 1205, 311, 6807, 701, 3469, 1609, 4511, 11, 499, 1288, 539, 64601, 449, 6864, 29618, 894, 499, 3469, 1609, 4511, 10150, 311, 9229, 11, 369, 279, 356, 7614, 5856, 38201, 3956, 304, 2015, 311, 4445, 49784, 5326, 13, 12220, 279, 2046, 358, 16102, 6818, 433, 11, 323, 499, 9229, 4395, 320, 64, 220, 1041, 4814, 570, 1952, 279, 1023, 3185, 11, 499, 690, 539, 636, 3469, 72, 1354, 35665, 11, 422, 71175, 3411, 369, 264, 15062, 3313, 11380, 3241, 358, 649, 7079, 279, 83555, 40, 3241, 627, 9241, 656, 584, 1935, 420, 8267, 5452, 220, 16, 9568, 8026, 3072, 57665, 2201, 311, 6900, 1124, 19073, 304, 279, 6560, 13, 9372, 369, 46436, 889, 3085, 5234, 25162, 11, 3196, 389, 701, 17271, 477, 18455, 719, 92779, 19029, 264, 1205, 311, 11196, 922, 1124, 11, 54001, 5789, 477, 12032, 11, 994, 4790, 21476, 311, 1505, 9873, 11, 13882, 15324, 323, 34716, 369, 315, 26012, 477, 33422, 11, 264, 502, 25885, 574, 11784, 8267, 5452, 18188, 7104, 6031, 27269, 14103, 68495, 279, 3157, 555, 46436, 1093, 14908, 55, 46, 11, 499, 690, 617, 311, 4007, 279, 11084, 4519, 323, 2671, 16655, 18188, 7104, 6732, 800, 278, 13780, 468, 8083, 555, 1884, 7620, 627, 11787, 499, 13126, 264, 23117, 430, 374, 539, 10212, 389, 1057, 2199, 13538, 499, 3469, 29639, 304, 8026, 2671, 449, 1124, 11, 435, 17094, 323, 1023, 469, 19657, 6020, 28506, 13162, 11, 279, 8026, 2671, 5064, 374, 1193, 264, 220, 19, 1667, 2362, 520, 420, 1486, 13, 1472, 649, 1005, 433, 311, 5409, 11626, 994, 701, 2361, 374, 304, 10826, 69092, 323, 499, 422, 2733, 430, 499, 1253, 387, 704, 8838, 10826, 69092, 520, 279, 842, 315, 279, 12146, 51021, 892, 627, 59077, 13596, 5526, 955, 315, 8026, 13002, 8026, 2671, 21070, 800, 51868, 11151, 675, 15357, 374, 279, 5927, 6174, 477, 77516, 5591, 8026, 430, 374, 32971, 555, 264, 2134, 430, 374, 7863, 311, 279, 16940, 3157, 520, 279, 3072, 5591, 82, 32792, 627, 2675, 617, 311, 1650, 1203, 323, 499, 527, 9277, 389, 3412, 9651, 1578, 13, 18188, 2671, 374, 264, 32905, 11380, 14473, 13, 763, 5587, 82, 14002, 584, 3350, 922, 1057, 4033, 8717, 11, 499, 426, 751, 617, 279, 6776, 311, 7380, 3544, 37498, 315, 3300, 627, 12834, 420, 955, 315, 8026, 3072, 706, 1193, 6051, 3940, 311, 8895, 1063, 23354, 11, 13839, 13, 7054, 7362, 9473, 8026, 2671, 1887, 19777, 1888, 5708, 2671, 15174, 5117, 627, 4919, 577, 7079, 757, 1063, 3997, 430, 602, 649, 1817, 6020, 3754, 323, 4652, 9523, 13347, 15469, 11, 4869, 38868, 14000, 430, 433, 7634, 220, 18, 12, 19, 24871, 11230, 31442, 13, 5385, 2650, 311, 1629, 701, 1866, 12827, 8797, 8026, 14234, 4652, 63045, 32072, 5117, 30, 1283, 1101, 65876, 430, 279, 86443, 12396, 690, 539, 387, 11754, 824, 2019, 439, 18188, 2671, 2759, 369, 2753, 19832, 18188, 14908, 32704, 323, 6031, 27269, 22652, 361, 220, 16, 315, 279, 86443, 9849, 33263, 7913, 2930, 25725, 3157, 627, 34976, 1105, 304, 8026, 2671, 79683, 264, 46988, 422, 814, 12722, 7168, 279, 5216, 315, 2349, 304, 459, 12032, 907, 304, 264, 743, 4261, 315, 892, 13, 1628, 422, 499, 656, 1390, 810, 17738, 11, 422, 701, 20212, 374, 1314, 279, 23117, 2103, 649, 1514, 11, 499, 690, 387, 3025, 311, 1304, 264, 1664, 16369, 5597, 994, 433, 4131, 311, 3339, 13315, 9341, 5380, 33, 14080, 35687, 13, 1666, 1778, 11, 701, 2930, 323, 27258, 2626, 358, 3290, 311, 387, 18507, 13, 40070, 6913, 13, 358, 4036, 20181, 315, 21859, 4669, 2613, 389, 420, 2883, 323, 832, 315, 856, 1183, 4628, 3804, 47461, 6267, 459, 4652, 389, 420, 2883, 902, 9778, 2751, 1274, 311, 1212, 41365, 389, 872, 7970, 661, 449, 420, 2883, 627, 2356, 4798, 499, 810, 892, 369, 11230, 13, 24561, 3135, 527, 539, 64005, 315, 3938, 3135, 13, 27933, 54469, 14863, 1472, 1205, 311, 387, 8010, 315, 682, 279, 3649, 14932, 420, 1603, 40583, 11380, 70, 18447, 311, 264, 2532, 11, 279, 4790, 1931, 814, 1304, 323, 8267, 5452, 18188, 3072, 17738, 3477, 8956, 38214, 45122, 19226, 814, 1501, 11, 1536, 6754, 6675, 44960, 23355, 38214, 18442, 668, 1556, 56854, 70, 332, 16419, 29931, 72965, 951, 6383, 33695, 15826, 76360, 65044, 268, 12666, 305, 38214, 1964, 268, 79545, 7367, 906, 380, 627, 14809, 8026, 2671, 11380, 480, 691, 19730, 602, 574, 1120, 1093, 499, 856, 574, 505, 220, 10617, 410, 40389, 6864, 311, 220, 9870, 11, 931, 100004, 1457, 602, 649, 539, 15142, 602, 1101, 6267, 311, 279, 23117, 430, 60610, 311, 387, 8976, 18188, 7104, 6031, 10789, 1628, 84138, 19178, 8563, 719, 912, 594, 801, 426, 428, 1566, 2305, 602, 2322, 6941, 85037, 90802, 520, 832, 315, 279, 11380, 2816, 889, 602, 25559, 369, 264, 1520, 627, 3112, 279, 8752, 439, 433, 374, 11, 5419, 3622, 1493, 304, 20394, 374, 3629, 9057, 555, 9183, 323, 269, 7057, 5865, 13, 15483, 8026, 3072, 33321, 527, 10213, 3658, 16543, 18188, 14908, 51359, 31853, 369, 1579, 32949, 388, 477, 35687, 430, 7293, 389, 264, 3738, 23117, 369, 5129, 892, 627, 7009, 690, 16168, 5625, 701, 3300, 311, 48301, 13, 568, 5165, 22413, 8351, 19439, 374, 220, 1041, 13234, 555, 10423, 315, 17076, 3072, 89, 3318, 1234, 279, 23541, 2585, 315, 20214, 315, 31480, 13, 21694, 11, 12604, 11, 1903, 4062, 22702, 358, 5602, 6908, 6140, 311, 1304, 6129, 3300, 304, 2201, 892, 30, 2360, 3769, 4442, 617, 1027, 1903, 311, 279, 7419, 315, 356, 23923, 4185, 14455, 3749, 477, 279, 4185, 14455, 435, 3503, 82, 5380, 2181, 7077, 311, 603, 0, 2052, 279, 1888, 311, 499, 11519, 40, 1120, 25559, 57748, 23261, 311, 1518, 422, 358, 1436, 7252, 8026, 2671, 11380, 480, 691, 856, 16946, 1203, 11, 8026, 2671, 42766, 8446, 21070, 14002, 1888, 21070, 369, 34824, 369, 13234, 627, 43182, 1093, 37962, 11380, 902, 63008, 832, 11667, 2403, 2500, 11, 358, 6267, 311, 499, 6931, 719, 358, 8101, 499, 527, 5115, 13326, 779, 358, 3350, 1618, 11, 902, 1101, 22982, 709, 61299, 11380, 10708, 719, 50440, 15167, 889, 2751, 872, 43177, 5076, 627, 12834, 279, 892, 4124, 369, 8026, 11380, 2671, 527, 22486, 11, 499, 657, 1101, 1505, 264, 12205, 315, 11190, 2038, 84531, 919, 18885, 701, 11380, 1440, 2902, 4336, 11, 8026, 2671, 527, 2204, 304, 430, 422, 279, 13471, 3430, 374, 2322, 555, 279, 32792, 2457, 11, 323, 709, 311, 220, 6843, 389, 1063, 1579, 7692, 2671, 627, 50571, 311, 279, 7195, 11, 814, 3629, 8417, 279, 30295, 315, 279, 2853, 315, 279, 480, 15259, 23301, 389, 279, 3157, 11, 1606, 627, 10031, 279, 1403, 2216, 527, 279, 1890, 2883, 11, 264, 1296, 259, 4506, 889, 44330, 311, 3719, 264, 15779, 374, 6118, 2631, 555, 264, 10217, 2547, 1778, 439, 264, 52811, 3703, 28506, 9266, 311, 1522, 264, 3703, 7151, 11, 779, 369, 757, 279, 6776, 315, 9888, 8976, 220, 16, 9568, 8026, 3072, 21181, 4441, 374, 1633, 3062, 13, 220, 21, 5376, 13002, 18188, 12937, 14908, 445, 5637, 1263, 13254, 1060, 389, 1060, 627, 7848, 1846, 51, 5729, 21387, 311, 2494, 584, 527, 8863, 13, 1442, 279, 45465, 11321, 279, 907, 315, 279, 16940, 9513, 690, 5376, 311, 264, 3738, 9736, 89, 894, 1603, 264, 3738, 2457, 11, 15320, 13, 9176, 7252, 8026, 3072, 8446, 14821, 57104, 1124, 527, 704, 323, 704, 64155, 13, 10771, 311, 18531, 3624, 11, 5165, 77367, 10229, 320, 45, 3711, 705, 1070, 3658, 16543, 8026, 2671, 21070, 20277, 75, 606, 264, 1396, 315, 1124, 627, 791, 86356, 13145, 744, 374, 264, 12700, 11, 15890, 10894, 311, 5387, 264, 3477, 315, 279, 46436, 430, 499, 588, 6818, 13002, 18188, 7104, 5475, 1676, 31529, 3117, 11, 682, 8267, 5452, 8026, 2671, 17738, 17723, 1073, 634, 31215, 320, 34042, 277, 3516, 1195, 91025, 8, 1555, 459, 4228, 37341, 627, 7009, 690, 636, 19021, 449, 499, 13, 763, 7252, 8026, 2671, 11380, 480, 691, 11, 814, 527, 1093, 264, 6409, 575, 11, 323, 814, 1550, 539, 2077, 311, 904, 315, 856, 14633, 11, 902, 649, 387, 1511, 304, 279, 3938, 311, 1304, 810, 34235, 22538, 11, 16433, 323, 8682, 15771, 11, 1070, 374, 832, 20893, 311, 6807, 3786, 86304, 1472, 649, 1193, 15142, 439, 1790, 3300, 439, 499, 54568, 449, 279, 4839, 7252, 8026, 3072, 12585, 20187, 51, 1890, 6807, 3786, 627, 12834, 1243, 912, 62184, 4385, 300, 1027, 5108, 709, 304, 279, 3754, 922, 279, 64386, 94272, 13, 1442, 71175, 6129, 922, 11380, 2930, 11, 2737, 279, 8522, 1217, 2269, 5147, 49958, 902, 2216, 25408, 603, 13, 5361, 892, 14418, 323, 7526, 883, 70, 1924, 3403, 892, 311, 636, 4790, 343, 6696, 304, 1306, 701, 12621, 527, 99988, 287, 439, 1070, 374, 3629, 264, 6958, 1203, 13, 80089, 11519, 40, 3779, 18188, 4158, 6879, 389, 856, 5652, 4652, 25891, 220, 20, 7648, 45995, 292, 13850, 18188, 14908, 20114, 11, 220, 8027, 6849, 4645, 13335, 220, 5037, 4278, 1202, 19832, 220, 1399, 2132, 8026, 3072, 2468, 1609, 564, 276, 18188, 14908, 9156, 67531, 578, 220, 4278, 6550, 8011, 7322, 8027, 7373, 28598, 8026, 2671, 8026, 2784, 87479, 1013, 791, 220, 4278, 6550, 8011, 7322, 8027, 7373, 28598, 8026, 2671, 11380, 6425, 220, 8027, 6849, 28384, 8027, 3048, 220, 5037, 8546, 8011, 31442, 220, 5037, 5120, 22479, 2759, 11, 18188, 14908, 32704, 374, 5326, 14400, 1749, 369, 1200, 70, 919, 701, 3300, 323, 1070, 374, 912, 1648, 584, 649, 6604, 922, 25725, 11, 96480, 5099, 5099, 627, 22045, 2671, 1101, 3073, 389, 2030, 499, 16869, 1505, 264, 3254, 4652, 389, 1521, 5220, 13335, 430, 34945, 1183, 6527, 14330, 13, 7054, 8026, 3072, 8446, 58769, 10481, 11380, 15771, 2187, 369, 701, 17738, 311, 387, 3288, 1555, 701, 6505, 4641, 477, 1023, 281, 1324, 3756, 320, 21470, 439, 264, 21354, 8, 555, 31009, 627, 4897, 1071, 11, 1418, 279, 220, 20, 11, 931, 311, 220, 605, 11, 931, 3697, 690, 1935, 2162, 912, 2753, 1109, 220, 1041, 304, 12306, 2759, 6807, 11, 46436, 6118, 617, 8244, 2585, 927, 279, 1401, 4519, 315, 872, 8403, 31442, 1778, 439, 51021, 3115, 323, 46988, 42338, 11, 1051, 2133, 311, 19832, 18188, 11380, 19912, 17971, 264, 26836, 6696, 369, 709, 311, 220, 605, 1332, 51021, 627, 5451, 7394, 35558, 21961, 1253, 4430, 279, 7319, 3827, 6807, 13, 2684, 527, 1193, 3116, 8026, 11380, 15771, 2561, 3432, 13, 23331, 38189, 555, 279, 356, 4082, 34, 13, 3296, 38936, 18563, 49944, 4455, 11, 1148, 5591, 82, 1523, 279, 5754, 369, 51939, 13, 7566, 568, 1304, 433, 311, 20121, 220, 1114, 42, 12, 323, 1243, 3309, 757, 420, 374, 1120, 279, 1212, 627, 29132, 1071, 430, 11, 220, 1049, 23, 25773, 315, 435, 8138, 315, 22454, 2360, 0, 1442, 279, 3703, 44204, 617, 264, 1317, 4827, 12737, 320, 1820, 15792, 1584, 430, 4131, 704, 315, 279, 8834, 961, 315, 279, 7252, 8026, 2671, 11380, 480, 691, 11, 3708, 311, 279, 1828, 45465, 320, 20670, 3719, 264, 781, 24332, 4390, 7009, 1176, 6137, 304, 279, 2326, 11, 656, 539, 1005, 477, 2680, 1057, 8471, 13, 305, 11, 323, 1070, 527, 13335, 1405, 5220, 9736, 352, 2343, 1120, 311, 636, 264, 6928, 3477, 13, 1789, 11626, 374, 5995, 311, 8417, 279, 3430, 13225, 505, 902, 279, 3430, 315, 279, 4183, 9513, 690, 7293, 4994, 3156, 279, 32792, 315, 279, 5226, 627, 1271, 7252, 8026, 2671, 11380, 480, 691, 2574, 1524, 810, 13548, 323, 17125, 11, 23570, 22226, 23598, 39229, 22910, 779, 499, 649, 9633, 304, 16358, 82150, 304, 701, 3997, 11, 11359, 1148, 311, 656, 323, 279, 356, 57563, 42800, 37496, 52, 643, 690, 21639, 872, 3300, 2085, 904, 28566, 323, 433, 374, 51833, 627, 2075, 315, 35687, 1825, 459, 2759, 11, 584, 1817, 704, 3249, 8325, 5708, 374, 7252, 8026, 2671, 11380, 480, 691, 304, 220, 679, 20, 323, 1148, 279, 14827, 1060, 374, 4461, 311, 3412, 369, 279, 5708, 315, 279, 24800, 8706, 2883, 13, 47910, 10343, 21935, 279, 3827, 8581, 369, 701, 31442, 43438, 2277, 279, 55365, 315, 2418, 4869, 433, 1587, 539, 1934, 6444, 2759, 7640, 11, 902, 527, 1063, 1028, 2277, 279, 7452, 478, 304, 279, 1917, 11, 8026, 15174, 323, 810, 19596, 6492, 369, 8026, 2671, 2033, 8026, 2671, 12585, 1949, 17074, 2759, 3477, 12399, 490, 81138, 374, 20426, 279, 94777, 68, 311, 627, 35897, 4459, 1887, 374, 2893, 11949, 311, 7252, 8026, 2671, 11380, 480, 691, 389, 279, 20134, 323, 1274, 889, 527, 48080, 315, 279, 5150, 15635, 814, 527, 49326, 13, 1789, 1403, 3284, 20124, 13, 220, 20, 320, 79, 9565, 8, 49, 8942, 67019, 11928, 279, 15277, 10334, 315, 3424, 11, 1274, 649, 1755, 311, 2744, 636, 279, 1888, 2930, 11380, 3217, 11, 1778, 439, 279, 91274, 47, 426, 751, 1963, 11, 38646, 6840, 8, 9785, 709, 279, 5729, 627, 4438, 2586, 430, 387, 264, 6721, 17738, 2532, 2758, 311, 430, 279, 16079, 1405, 1070, 574, 264, 4128, 482, 1101, 7438, 4814, 482, 323, 499, 617, 426, 14809, 1695, 4623, 922, 1268, 8009, 814, 527, 13, 73177, 367, 315, 1938, 11380, 7252, 8026, 2671, 11380, 480, 691, 649, 387, 5107, 1524, 369, 10534, 45465, 13, 2100, 311, 387, 2867, 11, 902, 9778, 6244, 264, 1917, 11501, 627, 12389, 264, 6555, 9178, 11519, 13347, 35487, 1910, 11, 1243, 814, 690, 3663, 8987, 35018, 7252, 18188, 7104, 5475, 70885, 438, 4298, 1524, 5842, 9482, 4769, 11, 304, 2015, 311, 1440, 810, 13, 1102, 374, 1193, 1306, 459, 30693, 706, 16365, 1268, 279, 6696, 27149, 1288, 814, 19560, 311, 279, 1972, 6696, 13, 1442, 499, 649, 4048, 311, 1304, 31442, 430, 12722, 7168, 902, 5216, 459, 12032, 3430, 690, 1935, 11, 323, 304, 904, 1162, 449, 264, 8521, 5216, 627, 791, 1925, 7580, 220, 5037, 4278, 220, 8027, 6849, 4645, 6574, 11, 16655, 18188, 14908, 32704, 3907, 26775, 1293, 1193, 555, 8026, 2671, 35687, 323, 30906, 35687, 719, 1101, 555, 9341, 14286, 8420, 889, 1629, 279, 11380, 76915, 11, 832, 272, 4551, 1065, 18425, 2277, 374, 7863, 2403, 2500, 6305, 11, 220, 679, 19, 555, 4074, 8621, 304, 82028, 2360, 18149, 791, 57784, 46272, 323, 19224, 9849, 320, 1820, 9849, 8, 25223, 311, 6179, 1820, 15167, 430, 279, 2883, 33, 3590, 8471, 12604, 7, 2933, 496, 19379, 627, 2381, 4790, 1931, 1304, 1213, 13, 10435, 27818, 22288, 1037, 24768, 661, 5708, 11380, 1887, 597, 19, 8026, 3072, 17738, 3974, 4365, 33321, 13, 92539, 6492, 10187, 430, 12032, 1253, 387, 5906, 652, 7725, 28191, 11, 1071, 32618, 35, 30977, 13, 2100, 3604, 279, 1949, 29623, 374, 539, 779, 1949, 1306, 682, 35897, 16406, 5727, 264, 2763, 810, 2038, 922, 18188, 14908, 1109, 584, 527, 1511, 311, 1518, 505, 5912, 46436, 5380, 38, 1271, 1324, 8640, 279, 1890, 35726, 13, 29553, 11380, 389, 4850, 18065, 1579, 5326, 11, 4418, 1047, 813, 2128, 19832, 18188, 7104, 6732, 57211, 1063, 3495, 323, 584, 1550, 264, 4967, 3882, 2391, 902, 584, 1903, 264, 2763, 315, 3300, 13, 358, 7079, 420, 21070, 19832, 220, 16, 9568, 8026, 3072, 8446, 5810, 8350, 18188, 14908, 35687, 315, 7252, 8026, 2671, 11380, 480, 691, 5990, 627, 2746, 279, 30693, 31878, 279, 9513, 1203, 311, 279, 3157, 15716, 1202, 907, 12992, 1243, 814, 2137, 265, 3339, 264, 11626, 11, 779, 7344, 41697, 661, 649, 1520, 11, 10209, 264, 12309, 4382, 1749, 315, 2848, 5977, 505, 3430, 7351, 304, 279, 8857, 315, 3682, 9513, 6989, 13, 358, 617, 220, 4103, 5672, 315, 2262, 779, 358, 617, 311, 1893, 220, 4103, 1754, 3956, 323, 6541, 1274, 709, 1124, 13, 220, 18, 8, 220, 16949, 13, 1472, 426, 751, 1193, 6696, 304, 5326, 6864, 320, 9210, 374, 11, 293, 3188, 527, 12514, 311, 41316, 6147, 1274, 682, 2212, 279, 1917, 922, 18355, 323, 1023, 16106, 16159, 20180, 627, 7184, 41136, 1148, 1695, 2626, 374, 682, 922, 13, 25773, 1268, 439, 5246, 439, 490, 6511, 287, 2610, 369, 264, 21639, 505, 279, 6807, 3786, 2883, 11, 6135, 98601, 499, 323, 499, 690, 4276, 636, 433, 1203, 13, 38859, 389, 279, 18057, 315, 18563, 49944, 13470, 11, 18355, 11935, 323, 3430, 51165, 7252, 8026, 2671, 11380, 480, 691, 5370, 4200, 36702, 13, 9176, 15771, 3085, 13002, 18188, 3072, 3974, 11380, 57555, 320, 43, 2094, 71, 461, 8, 5304, 18667, 627, 93031, 279, 24867, 40242, 1684, 1521, 6299, 293, 2259, 661, 26012, 11, 656, 701, 1866, 3495, 13, 30444, 867, 11380, 3727, 35687, 1440, 872, 2218, 323, 1243, 814, 649, 3345, 279, 6696, 3485, 279, 3430, 477, 3770, 279, 3430, 864, 1773, 47737, 439, 824, 279, 36865, 1749, 13, 30839, 9678, 9650, 422, 5995, 13, 66375, 51, 38646, 422, 320, 9528, 40314, 1808, 8, 471, 12334, 311, 38646, 13, 7553, 35804, 32107, 17738, 2997, 2802, 7969, 11, 719, 649, 387, 20336, 520, 3060, 28614, 2237, 477, 2447, 2237, 477, 649, 387, 8552, 6724, 11, 7863, 311, 1193, 17496, 323, 15438, 1367, 404, 811, 389, 279, 356, 7614, 7252, 8026, 2671, 11380, 480, 691, 1023, 30098, 627, 1899, 62648, 2147, 21800, 16788, 82046, 57093, 11, 430, 1288, 12192, 264, 17466, 304, 11667, 9473, 4478, 13, 1115, 5452, 706, 1027, 35426, 6319, 369, 47950, 323, 1884, 35687, 889, 6562, 311, 6696, 449, 264, 3428, 2926, 9341, 13, 666, 13213, 1101, 264, 5128, 35507, 3477, 41697, 661, 36537, 1885, 10577, 13, 15415, 14386, 856, 4221, 10573, 50040, 719, 912, 39827, 1648, 8096, 50664, 374, 264, 35726, 13, 220, 15, 374, 1101, 832, 315, 279, 64155, 11, 499, 4250, 387, 220, 1041, 2771, 430, 3738, 8026, 2671, 46436, 527, 15062, 11, 584, 690, 10552, 279, 31752, 13189, 439, 1664, 439, 279, 6020, 19679, 315, 12096, 420, 1579, 12303, 100092, 32905, 11, 4799, 2915, 33264, 813, 1684, 430, 279, 10102, 315, 42037, 323, 11002, 574, 279, 68971, 9395, 315, 350, 15817, 287, 5111, 8105, 627, 791, 6696, 374, 6992, 422, 279, 12032, 3430, 4478, 5916, 279, 64162, 4478, 304, 19832, 18188, 3072, 3974, 11380, 4491, 25079, 1981, 37286, 78, 892, 4261, 505, 12096, 279, 8026, 3072, 3156, 433, 29002, 627, 7184, 814, 1193, 1390, 311, 3041, 12306, 323, 539, 279, 8276, 1203, 13, 8976, 553, 264, 1614, 706, 279, 4495, 8070, 13, 1628, 1202, 18821, 13, 1115, 374, 2216, 15325, 13, 8994, 19352, 63779, 430, 358, 574, 1120, 2463, 17157, 369, 279, 4545, 323, 1053, 3729, 1124, 422, 5644, 311, 16946, 810, 13, 20695, 649, 7252, 18188, 14908, 32704, 3907, 46506, 12669, 8078, 690, 733, 5076, 627, 791, 13690, 8976, 8026, 3072, 8446, 87105, 8626, 1220, 2128, 8349, 264, 63336, 315, 220, 4044, 13, 1472, 439, 17738, 1949, 19832, 18188, 3072, 8515, 1203, 735, 830, 79936, 38214, 5879, 74, 6696, 17738, 13, 6193, 279, 1828, 8254, 1667, 7636, 11, 49609, 12266, 539, 311, 387, 25408, 555, 832, 315, 279, 5064, 5544, 447, 437, 502, 3703, 25063, 5153, 627, 2746, 499, 527, 1701, 279, 220, 18, 1938, 1949, 9269, 420, 1253, 539, 990, 369, 499, 323, 1436, 3063, 311, 18151, 13, 13002, 18188, 14908, 83599, 4476, 650, 1182, 311, 2019, 358, 5675, 264, 2478, 19779, 323, 574, 922, 311, 5387, 279, 4459, 3245, 439, 264, 3958, 4623, 11, 50086, 627, 644, 622, 8699, 14002, 584, 1935, 264, 34522, 520, 16132, 18059, 79270, 11, 1935, 701, 3300, 18403, 13, 13782, 369, 439, 311, 7380, 1200, 88, 919, 6811, 1990, 13, 602, 4250, 636, 856, 2010, 2212, 499, 2231, 430, 1790, 3300, 1139, 433, 36765, 13347, 35687, 420, 374, 264, 10163, 315, 1063, 1156, 43157, 704, 1070, 97589, 894, 311, 617, 279, 779, 2663, 6696, 31052, 11, 358, 15890, 3619, 3249, 499, 527, 779, 44040, 311, 3493, 279, 23117, 499, 1511, 311, 1296, 279, 31753, 67531, 3241, 627, 14364, 1648, 369, 279, 45465, 311, 11000, 1304, 3300, 13, 14079, 8026, 2671, 11380, 10708, 220, 966, 2132, 8026, 2671, 11, 902, 706, 1903, 433, 3284, 369, 8026, 2671, 46436, 311, 1212, 10209, 23232, 661, 4028, 279, 24867, 11, 449, 24886, 311, 8026, 2671, 323, 37962, 11380, 11, 3060, 499, 7380, 279, 471, 389, 701, 29091, 3392, 13, 16782, 11, 323, 814, 527, 47101, 311, 499, 13, 48725, 13, 7648, 315, 279, 1948, 8026, 3072, 46436, 527, 3196, 304, 57784, 13, 53792, 4522, 5361, 2671, 17517, 374, 832, 1648, 311, 13893, 11626, 810, 505, 459, 3469, 1609, 4511, 3430, 3351, 627, 1721, 824, 54808, 11, 320, 576, 3445, 358, 1781, 279, 3430, 374, 2133, 5190, 8, 323, 358, 690, 10491, 4790, 625, 1790, 358, 1390, 311, 56443, 13, 480, 4082, 11, 539, 1193, 369, 6992, 11380, 11, 8026, 39418, 2671, 293, 2259, 31695, 912, 11, 13428, 374, 279, 1176, 3658, 16543, 18188, 14908, 32704, 83599, 36532, 292, 783, 520, 459, 7757, 315, 17452, 13, 18188, 2945, 12, 3549, 505, 19307, 3477, 627, 791, 35762, 327, 22353, 3165, 31458, 617, 2225, 264, 6558, 323, 264, 22959, 5938, 449, 1124, 13, 4452, 1690, 315, 279, 1274, 889, 1935, 709, 11380, 656, 779, 439, 814, 3658, 16543, 18188, 3072, 8515, 1203, 469, 83158, 617, 279, 3392, 315, 3300, 8976, 8026, 3072, 8450, 17533, 265, 58797, 8078, 814, 1390, 627, 40273, 13, 8489, 11, 1217, 22658, 11380, 15771, 3085, 264, 7029, 2134, 315, 5016, 11, 1120, 13, 40502, 5178, 374, 7252, 8026, 3072, 8450, 4491, 25079, 1981, 37286, 78, 505, 279, 892, 499, 9277, 279, 6696, 320, 2091, 1212, 570, 7429, 11, 602, 18998, 220, 679, 19, 7863, 311, 1023, 4595, 315, 4999, 4518, 1148, 3885, 2019, 922, 1124, 13, 1226, 520, 18188, 3883, 4897, 50, 1983, 2744, 1427, 369, 21859, 11, 84905, 315, 32889, 411, 11380, 889, 814, 3802, 311, 1005, 889, 2274, 279, 3241, 11, 279, 20514, 374, 653, 424, 23444, 323, 584, 2736, 617, 6821, 555, 35687, 889, 5675, 3300, 11, 499, 426, 52000, 539, 387, 3025, 311, 6696, 520, 682, 11, 499, 4662, 11, 3469, 74, 2439, 3445, 1070, 374, 459, 29049, 5133, 7252, 220, 16, 9568, 8026, 3072, 8446, 25187, 78, 953, 279, 1403, 11, 1063, 315, 279, 14491, 279, 3997, 527, 33243, 323, 814, 617, 264, 1633, 8009, 7095, 23862, 439, 1664, 11, 902, 706, 1023, 83372, 320, 438, 35877, 16243, 8, 50800, 439, 1664, 11, 79966, 35687, 323, 47950, 17631, 264, 2763, 389, 1778, 17738, 627, 9312, 969, 706, 5068, 264, 18174, 304, 54708, 7863, 311, 420, 892, 1566, 1060, 13, 36608, 19, 13, 8267, 5452, 18188, 3072, 17738, 3477, 3320, 587, 857, 617, 1027, 21859, 315, 97589, 894, 539, 1694, 1323, 3847, 311, 6201, 9815, 11, 279, 34756, 1120, 16696, 311, 1304, 499, 24450, 323, 1879, 627, 1305, 710, 287, 1253, 5627, 8026, 2671, 374, 810, 4528, 311, 26243, 520, 264, 2363, 26850, 1109, 311, 26012, 627, 11787, 499, 2771, 430, 701, 7555, 3250, 956, 23528, 264, 27681, 4642, 10177, 7170, 30, 128000, 3923, 358, 3077, 51678, 44245, 220, 20, 5033, 220, 679, 18, 510, 16606, 14, 3336, 12598, 16675, 51, 14, 15881, 933, 22630, 220, 20, 339, 11, 220, 679, 18, 555, 11824, 198, 791, 12738, 6445, 315, 22725, 374, 279, 1561, 5348, 320, 10682, 555, 3194, 71376, 82, 11921, 1834, 340, 81655, 315, 3137, 389, 279, 2655, 1441, 922, 1268, 22725, 374, 279, 1561, 5348, 574, 264, 14964, 1501, 539, 5922, 7554, 13, 4740, 13598, 433, 704, 11, 358, 3077, 2751, 311, 2019, 5127, 596, 2216, 1314, 627, 2822, 375, 11, 719, 4762, 420, 2046, 4999, 791, 20467, 1389, 4829, 1122, 426, 718, 404, 374, 3815, 7060, 11, 7060, 990, 389, 420, 1501, 11, 719, 279, 6275, 25534, 6392, 5084, 14470, 64979, 950, 323, 568, 596, 4661, 95529, 64632, 304, 813, 2410, 627, 43069, 374, 279, 1561, 5348, 1389, 23469, 5084, 311, 617, 5616, 1766, 1202, 25534, 1501, 13, 93796, 1579, 4367, 323, 459, 41765, 3821, 13, 60998, 1817, 433, 704, 627, 40, 2846, 539, 2771, 358, 3604, 1093, 70780, 12587, 76378, 596, 502, 7, 819, 8, 3254, 320, 37227, 1790, 7091, 11, 539, 3403, 27374, 705, 719, 433, 596, 5922, 11011, 198, 2688, 420, 2046, 627, 2059, 258, 28443, 10830, 350, 1137, 72, 17244, 1389, 25545, 264, 15860, 810, 892, 304, 420, 9178, 1418, 21568, 18243, 369, 856, 5613, 13, 25531, 2731, 13, 578, 25572, 527, 11, 2085, 264, 10712, 11, 4856, 11292, 11, 323, 279, 3446, 596, 17454, 41765, 439, 358, 3077, 2163, 279, 1176, 3158, 13, 2876, 2771, 422, 433, 3358, 3136, 311, 387, 12738, 11, 719, 584, 3358, 1518, 627, 44924, 20139, 1389, 17830, 712, 9437, 709, 1443, 52763, 4428, 358, 53709, 596, 18407, 1600, 25706, 311, 1514, 279, 20285, 1418, 3468, 15746, 420, 9178, 323, 433, 2103, 12756, 10187, 709, 13, 4702, 2307, 17676, 21976, 323, 459, 842, 13992, 2237, 315, 32353, 627, 30287, 1543, 42986, 1389, 7445, 4062, 8815, 5990, 420, 2046, 13, 3468, 323, 358, 1205, 311, 15405, 18371, 288, 6431, 434, 47229, 220, 17, 627, 6540, 301, 70305, 1389, 75106, 279, 1630, 9574, 32, 2373, 832, 1566, 892, 1603, 358, 8667, 1022, 16058, 9523, 311, 279, 4984, 315, 279, 6812, 2373, 13, 58072, 956, 636, 3347, 279, 45520, 4245, 311, 1063, 30355, 1514, 13, 1102, 596, 2216, 4228, 311, 4498, 704, 315, 6725, 449, 3165, 301, 70305, 627, 42515, 66093, 25, 1561, 27967, 1389, 358, 2216, 3463, 358, 4265, 387, 3025, 311, 4546, 14098, 2162, 449, 757, 505, 279, 8063, 16578, 13, 17262, 315, 61983, 430, 499, 649, 956, 627, 791, 8155, 315, 4073, 1389, 2435, 1456, 323, 35840, 682, 279, 892, 430, 499, 649, 3820, 1268, 499, 1390, 311, 5603, 35006, 13, 74567, 477, 11039, 11, 5099, 13, 1102, 10578, 1695, 304, 10334, 11, 719, 4619, 814, 617, 682, 1521, 2631, 17302, 811, 13, 578, 5652, 832, 6532, 1403, 293, 1261, 388, 11, 1403, 4299, 388, 11, 323, 1403, 39380, 323, 433, 574, 1120, 264, 6784, 13, 17262, 315, 39223, 90578, 47, 1609, 1083, 220, 18, 1389, 4314, 3953, 527, 779, 35509, 323, 5745, 2523, 13, 358, 3021, 62262, 1083, 3953, 13, 37102, 424, 4477, 23066, 2065, 323, 264, 2523, 12896, 45239, 3727, 369, 279, 1176, 1972, 2944, 311, 2543, 389, 856, 40292, 549, 304, 264, 1317, 892, 627, 48999, 27736, 25, 502, 16312, 11, 9578, 11130, 11, 4272, 17987, 11, 19087, 374, 279, 502, 3776, 11, 48250, 1083, 220, 18, 11, 18803, 1543, 25, 49428, 11, 1239, 2259, 2395, 76378, 11, 559, 52763, 4428, 433, 6870, 11, 77111, 19262, 10830, 43787, 72, 17967, 11, 72035, 70305, 11, 279, 14497, 11, 279, 1566, 315, 603, 11, 289, 3893, 577, 198, 10955, 11871, 315, 220, 679, 17, 510, 15881, 933, 18820, 220, 19, 339, 11, 220, 679, 18, 555, 11824, 198, 13461, 279, 28627, 53505, 6476, 2835, 3953, 420, 1060, 627, 37353, 1197, 389, 7732, 11, 499, 7752, 11, 719, 358, 9152, 311, 636, 1555, 220, 679, 17, 2085, 3515, 682, 856, 2835, 3953, 23130, 505, 856, 3838, 1418, 358, 574, 21811, 510, 65837, 13575, 17160, 25, 1102, 596, 220, 679, 18, 1457, 11, 499, 17741, 13, 1472, 1541, 956, 1205, 311, 14459, 389, 7732, 948, 12540, 430, 1524, 387, 459, 26501, 5380, 679, 17, 5084, 311, 387, 264, 6541, 304, 279, 2704, 41608, 13, 19292, 433, 596, 1606, 279, 502, 2393, 9659, 12775, 956, 3686, 28219, 1022, 11, 719, 358, 2733, 1093, 17162, 323, 17162, 48197, 11, 2466, 8199, 15671, 617, 1027, 50030, 856, 6666, 31445, 13, 5046, 279, 220, 3487, 3953, 389, 420, 1160, 358, 2733, 1093, 1633, 2478, 320, 9274, 220, 717, 8, 1051, 2466, 11, 6908, 38350, 3953, 13, 10926, 430, 596, 539, 682, 430, 2204, 11, 719, 433, 11321, 2204, 90578, 13699, 11, 1093, 1566, 1060, 358, 656, 1797, 3953, 389, 420, 1160, 430, 1550, 539, 7195, 304, 220, 679, 17, 11, 719, 430, 358, 6476, 11, 3940, 11, 477, 9567, 304, 220, 679, 17, 627, 65786, 70325, 25, 47297, 56379, 1389, 578, 98086, 5086, 3245, 922, 856, 892, 449, 420, 1847, 574, 430, 358, 14896, 311, 1514, 433, 304, 15506, 13, 1102, 574, 7060, 6725, 323, 11, 1022, 279, 1948, 315, 856, 2010, 11, 433, 15972, 757, 1403, 15506, 4339, 358, 1047, 912, 1005, 369, 1603, 5737, 433, 320, 82, 354, 5770, 323, 61387, 68669, 11, 7438, 31741, 323, 42289, 2971, 392, 14441, 23257, 11, 15947, 705, 719, 433, 1101, 15109, 1633, 15526, 4477, 555, 23503, 27839, 596, 20514, 323, 264, 33288, 398, 17395, 3446, 369, 1778, 264, 8275, 31348, 1847, 13, 763, 2144, 11, 220, 679, 17, 574, 3169, 315, 264, 1060, 315, 21416, 17422, 11, 439, 499, 3358, 1518, 11, 779, 433, 596, 8475, 311, 1518, 12177, 636, 1948, 34631, 13, 1102, 596, 1101, 5922, 45391, 430, 279, 10571, 304, 420, 1847, 374, 28809, 627, 30287, 1543, 25, 70591, 1389, 7429, 3967, 439, 279, 1847, 1405, 3468, 323, 358, 63260, 7445, 71841, 8503, 2237, 369, 279, 1176, 892, 13, 2360, 10457, 11, 7752, 11, 279, 32726, 15489, 5990, 323, 279, 1620, 9580, 315, 279, 15371, 477, 8996, 433, 574, 2663, 574, 264, 54562, 12970, 26501, 369, 279, 6857, 315, 603, 13, 1442, 1561, 7445, 24270, 34321, 13, 4536, 956, 701, 9145, 11, 719, 499, 1781, 499, 2643, 2103, 3021, 5452, 388, 1243, 499, 11112, 1205, 311, 1456, 420, 1847, 704, 627, 68853, 78, 31391, 21223, 1389, 22335, 11, 358, 6476, 420, 304, 279, 220, 1954, 82, 13, 85294, 11, 433, 574, 856, 1176, 34602, 13, 578, 21223, 2700, 3779, 1063, 32873, 14491, 11, 2737, 459, 4248, 91592, 430, 7437, 709, 369, 26560, 78, 11511, 304, 279, 1455, 71810, 1648, 3284, 11, 719, 433, 1101, 3782, 449, 264, 502, 14807, 430, 358, 3463, 574, 7185, 323, 7263, 1063, 99316, 311, 459, 6062, 330, 82, 8905, 1, 1847, 369, 757, 627, 44924, 11130, 1389, 358, 6562, 358, 4265, 7543, 810, 892, 4560, 311, 35585, 9420, 11130, 11, 719, 358, 1120, 3287, 956, 13, 73817, 11, 358, 1541, 956, 1781, 358, 2751, 2288, 3117, 3347, 6574, 39051, 39051, 1981, 24205, 3021, 420, 1847, 627, 34, 525, 15457, 489, 1389, 2650, 358, 1317, 369, 8915, 17250, 2237, 10223, 0, 50492, 15457, 489, 374, 264, 14964, 6344, 1607, 85, 9345, 11549, 13252, 32671, 11, 719, 856, 19240, 6091, 11075, 358, 1053, 1514, 389, 279, 37554, 17250, 11, 902, 3445, 358, 2846, 16075, 389, 29073, 1630, 3156, 358, 649, 636, 856, 7512, 1523, 3352, 627, 19918, 27582, 96860, 12, 17, 1389, 20474, 1268, 5127, 596, 7075, 3752, 304, 31042, 96860, 574, 34944, 596, 13219, 323, 1063, 7564, 912, 832, 3596, 5602, 304, 31042, 96860, 30, 14144, 1981, 54719, 15058, 956, 701, 7075, 5885, 30, 1472, 1541, 956, 1390, 311, 1514, 2500, 220, 1272, 4207, 439, 1884, 43560, 273, 36910, 323, 3821, 19435, 11, 18231, 11, 323, 328, 1394, 71, 505, 99378, 1418, 5737, 264, 7154, 53990, 31882, 37864, 3446, 30, 25619, 3958, 4999, 57475, 82, 11035, 25, 578, 21530, 1389, 358, 2733, 3958, 369, 499, 422, 499, 3077, 2646, 6476, 33319, 11035, 25, 578, 21530, 13, 358, 6612, 3958, 369, 7182, 369, 539, 3515, 6476, 433, 31373, 1109, 358, 1550, 13, 1789, 7340, 1384, 288, 6431, 434, 387, 2771, 311, 3041, 701, 13697, 279, 59863, 7899, 13, 1102, 596, 92044, 13, 57606, 3582, 11, 420, 1847, 374, 279, 1888, 1825, 1917, 1847, 358, 617, 3596, 6476, 13, 26572, 13, 1102, 596, 32677, 11, 27873, 11, 323, 32795, 729, 950, 11, 719, 433, 596, 289, 16113, 1475, 3094, 315, 279, 1648, 323, 358, 2846, 1314, 1070, 449, 433, 627, 49, 61254, 32450, 85001, 1389, 3277, 358, 1176, 3940, 4477, 420, 1160, 358, 29695, 430, 420, 2697, 19269, 3782, 704, 304, 220, 679, 17, 13, 3053, 499, 4510, 433, 27074, 3468, 11, 358, 1440, 499, 1541, 956, 3619, 279, 14638, 1618, 11, 719, 420, 374, 27136, 4315, 856, 7075, 1847, 315, 420, 1060, 13, 14910, 358, 8493, 400, 1490, 50995, 279, 45999, 505, 6457, 30, 1472, 1297, 6583, 13, 4359, 15770, 1800, 420, 1847, 374, 779, 1695, 13, 1102, 596, 264, 2011, 1514, 369, 5606, 449, 264, 40292, 320, 269, 264, 40292, 549, 570, 57606, 11, 733, 3780, 433, 13, 1102, 596, 15400, 627, 14934, 321, 65580, 220, 17, 1389, 2418, 11, 279, 28443, 23577, 4465, 374, 779, 18754, 323, 358, 2846, 539, 10489, 19167, 11, 7097, 45539, 11, 311, 22118, 433, 11, 902, 374, 3249, 358, 2646, 9567, 420, 1847, 13, 1102, 596, 2731, 1109, 21223, 16, 11, 99097, 11, 719, 358, 1120, 1205, 311, 2503, 1523, 323, 40336, 856, 1648, 704, 315, 420, 323, 358, 2216, 1541, 956, 1390, 311, 617, 311, 656, 430, 1981, 49828, 3585, 369, 1101, 5128, 1790, 1694, 55806, 290, 198, 26909, 13756, 220, 18, 1389, 473, 2689, 8334, 1981, 3923, 264, 17619, 3528, 420, 1847, 596, 4984, 574, 55080, 6562, 358, 4265, 31394, 433, 10819, 1109, 358, 1047, 1606, 555, 279, 892, 358, 8813, 279, 13696, 11, 1664, 11, 279, 7757, 1047, 32367, 44913, 449, 19347, 13, 358, 7543, 810, 892, 289, 2277, 304, 6170, 14491, 323, 25907, 29269, 279, 32692, 17025, 315, 264, 1847, 430, 358, 27136, 3287, 956, 1505, 430, 16358, 7863, 311, 279, 2800, 315, 279, 1060, 596, 19786, 11, 719, 433, 1120, 67854, 757, 279, 5076, 1648, 311, 1518, 279, 8571, 30123, 7631, 4442, 505, 12371, 363, 548, 13, 358, 3152, 11, 421, 483, 682, 499, 1390, 11, 719, 779, 1317, 439, 12371, 363, 548, 3250, 956, 26457, 4235, 3639, 596, 430, 30, 1472, 2019, 814, 1550, 26457, 30, 2435, 1550, 2349, 279, 13696, 439, 264, 2077, 311, 8571, 421, 5859, 30, 3092, 5201, 369, 12371, 363, 548, 323, 420, 1847, 32122, 704, 279, 3321, 279, 2132, 430, 7077, 13, 1666, 3117, 439, 358, 2846, 11920, 11, 358, 6476, 279, 1972, 9346, 13756, 220, 18, 11, 719, 358, 2646, 2751, 279, 6140, 311, 4774, 433, 13, 4800, 430, 279, 16410, 527, 8208, 505, 12371, 363, 548, 323, 279, 2883, 374, 30844, 5977, 9650, 389, 1148, 5216, 311, 1935, 16537, 13381, 14767, 11, 358, 1505, 7182, 7422, 11, 330, 1692, 11, 1148, 7077, 311, 12371, 363, 548, 7673, 1102, 596, 264, 1972, 21648, 1606, 9346, 13756, 220, 18, 574, 3604, 5115, 1695, 627, 24591, 22872, 1389, 12424, 3389, 311, 279, 4717, 389, 420, 832, 11, 719, 358, 574, 8430, 430, 6344, 1607, 85, 9345, 95856, 323, 11, 1664, 11, 420, 1847, 3169, 315, 66839, 433, 13, 358, 12491, 279, 4948, 13167, 814, 3779, 311, 279, 6166, 1606, 433, 3727, 38178, 264, 6784, 13, 7089, 1109, 430, 433, 596, 7060, 13, 5475, 481, 11, 2216, 11, 719, 433, 1101, 5334, 6807, 369, 1694, 279, 1176, 330, 2784, 1640, 1, 955, 1847, 430, 358, 649, 1781, 315, 627, 41, 373, 44058, 1389, 358, 1541, 956, 1514, 264, 2763, 315, 12414, 7682, 8263, 63170, 13, 93188, 44058, 1120, 7077, 311, 387, 704, 304, 264, 326, 620, 323, 358, 13234, 433, 505, 264, 20449, 901, 13484, 13, 1102, 596, 32180, 3403, 323, 358, 4170, 5737, 433, 449, 5361, 1274, 11, 719, 433, 596, 539, 2133, 311, 743, 279, 1917, 389, 4027, 13, 40551, 279, 3446, 304, 330, 12158, 3919, 1, 3941, 374, 2523, 2288, 1606, 279, 10778, 374, 4661, 1536, 42503, 13610, 659, 26469, 1245, 627, 19841, 15222, 3058, 25, 36751, 612, 4593, 269, 22228, 19613, 1389, 24882, 4731, 323, 264, 7155, 37637, 11, 719, 433, 11835, 16682, 389, 279, 6812, 13, 358, 6562, 358, 1047, 459, 23067, 369, 6392, 1093, 420, 323, 430, 358, 2231, 810, 892, 1139, 420, 1847, 627, 791, 40155, 15371, 1389, 358, 3463, 922, 50545, 420, 704, 1139, 18243, 4028, 279, 4101, 11, 719, 433, 5084, 32981, 311, 3137, 922, 420, 1847, 304, 832, 11299, 34227, 454, 1524, 3582, 358, 3940, 433, 304, 5936, 323, 8220, 433, 304, 6841, 13, 358, 1440, 358, 1071, 430, 432, 61254, 32450, 85001, 574, 279, 1888, 1847, 315, 420, 1060, 11, 719, 578, 40155, 15371, 374, 3604, 279, 1888, 3245, 311, 617, 2586, 704, 420, 1060, 13, 358, 3358, 13500, 499, 430, 433, 596, 810, 21416, 17422, 1109, 1847, 11, 719, 1524, 430, 596, 539, 430, 3062, 11, 2216, 13, 358, 3152, 11, 1053, 10917, 810, 47623, 304, 420, 18427, 1847, 1304, 433, 904, 2731, 30, 5046, 3388, 539, 0, 578, 40155, 15371, 374, 279, 2450, 433, 374, 1606, 433, 596, 264, 3752, 32505, 3446, 315, 279, 13452, 584, 9167, 956, 3970, 1603, 13, 12336, 78195, 1253, 539, 387, 3339, 279, 34261, 29899, 5859, 11709, 430, 35238, 72919, 3727, 389, 264, 7446, 8197, 11, 719, 279, 45525, 2744, 2873, 5190, 439, 568, 1587, 813, 1888, 311, 91478, 3995, 53227, 483, 1555, 264, 1917, 430, 1193, 5334, 11201, 323, 11201, 369, 5127, 13, 3011, 1566, 6237, 304, 279, 31817, 3637, 439, 12336, 24909, 46268, 311, 7296, 1981, 2181, 24891, 757, 320, 438, 358, 2846, 2771, 1455, 5606, 889, 6476, 433, 8, 304, 264, 1648, 430, 4400, 775, 420, 1060, 1436, 13, 358, 2846, 539, 1694, 17508, 65, 7918, 994, 358, 2019, 430, 5127, 1288, 1514, 420, 1847, 13, 1102, 596, 20333, 627, 6251, 89, 1389, 45072, 315, 20333, 11, 3926, 89, 706, 430, 304, 993, 3536, 13, 1226, 2351, 7556, 922, 264, 1847, 1405, 1475, 7872, 11321, 46072, 323, 26454, 13, 3011, 596, 539, 459, 39030, 367, 3060, 13, 3161, 7344, 832, 4788, 11, 1070, 596, 539, 264, 3254, 25649, 304, 3926, 89, 430, 499, 7846, 956, 14647, 7216, 704, 304, 1063, 1648, 505, 43775, 304, 279, 1917, 13, 2435, 2643, 387, 40634, 11, 5107, 311, 14532, 43775, 11, 719, 814, 2351, 1070, 13, 2758, 304, 264, 45999, 430, 374, 77754, 398, 6366, 323, 264, 42496, 45239, 430, 374, 439, 2523, 439, 4205, 775, 499, 3077, 3596, 2884, 323, 499, 3077, 2751, 279, 1455, 7185, 3217, 315, 220, 679, 17, 13, 358, 649, 2103, 6958, 709, 19428, 19459, 315, 279, 4384, 99544, 315, 1063, 315, 279, 15670, 323, 279, 27442, 4731, 430, 1903, 757, 2733, 25181, 11, 7636, 11, 264, 2697, 27207, 11, 323, 264, 2697, 12304, 311, 7142, 264, 24671, 477, 459, 88143, 3845, 13, 3926, 89, 574, 12738, 11, 7752, 627, 22427, 32560, 220, 18, 1389, 358, 3077, 1047, 420, 3137, 449, 3468, 779, 1690, 3115, 11, 719, 7344, 358, 3287, 956, 3619, 1148, 74337, 574, 1603, 358, 6476, 423, 18, 13, 358, 4265, 1193, 3596, 6476, 423, 17, 449, 856, 10868, 477, 264, 2478, 4885, 13, 1102, 574, 264, 2678, 13230, 54914, 323, 79843, 4238, 11, 1202, 18585, 91343, 369, 757, 11, 574, 264, 3254, 43467, 31017, 13, 2684, 574, 912, 45200, 4783, 1070, 311, 10408, 688, 46403, 21701, 477, 1023, 4311, 311, 743, 709, 31442, 449, 389, 25907, 13, 2684, 574, 279, 53500, 315, 279, 73706, 323, 279, 54904, 315, 279, 19614, 13, 74337, 220, 18, 90347, 430, 8430, 4871, 757, 430, 75042, 994, 358, 2733, 1093, 358, 3077, 1027, 78778, 13, 1102, 574, 1093, 358, 3952, 279, 2579, 15530, 323, 358, 5602, 279, 11892, 315, 279, 1847, 369, 279, 1176, 892, 994, 358, 15393, 1148, 358, 4265, 617, 311, 656, 311, 9567, 279, 1847, 389, 63758, 2201, 13, 358, 3077, 2646, 6612, 1093, 264, 1847, 596, 6067, 1051, 779, 18300, 398, 14289, 1603, 320, 40, 1541, 956, 1514, 5690, 3953, 8, 323, 74337, 220, 18, 5945, 1171, 757, 389, 53133, 439, 264, 16131, 13, 10926, 1828, 1060, 499, 3358, 1518, 459, 4441, 922, 18449, 315, 279, 97570, 11, 719, 439, 315, 1314, 1457, 11, 9523, 311, 74337, 220, 18, 11, 358, 3197, 389, 2646, 10374, 2500, 2960, 389, 264, 53133, 1847, 320, 39870, 264, 502, 64752, 86048, 4131, 704, 13, 358, 3604, 1093, 1884, 4390, 51, 897, 4042, 220, 19, 1389, 3468, 13452, 311, 67126, 757, 922, 1694, 459, 14289, 42284, 994, 358, 1514, 420, 1847, 11, 719, 433, 596, 1790, 810, 17395, 369, 757, 13, 3277, 358, 1514, 350, 897, 4042, 358, 1541, 956, 10368, 856, 5845, 311, 13552, 16374, 477, 9203, 10495, 520, 690, 13, 358, 656, 856, 1888, 311, 387, 264, 20331, 72137, 7808, 323, 22884, 279, 2585, 14, 2295, 2251, 315, 279, 2326, 477, 73315, 13, 358, 656, 856, 1888, 311, 1304, 279, 35148, 50852, 430, 358, 2733, 856, 1274, 617, 1027, 15164, 13, 1102, 596, 264, 17693, 320, 438, 16682, 398, 8, 4443, 3217, 369, 757, 13, 12623, 279, 4731, 374, 5128, 10437, 627, 791, 26990, 315, 42608, 25, 90615, 315, 279, 32402, 1389, 22335, 11, 22371, 11, 14800, 3854, 369, 264, 1847, 430, 358, 6476, 91270, 1566, 1060, 13, 358, 1541, 956, 2512, 11, 7752, 11, 433, 574, 4661, 264, 502, 1847, 449, 1268, 1790, 433, 3779, 13, 1442, 499, 1373, 856, 5117, 323, 499, 6818, 13920, 4215, 291, 435, 13778, 11, 499, 2216, 1288, 1817, 420, 704, 627, 2822, 4497, 38099, 25, 48691, 1389, 358, 1781, 358, 2846, 520, 68769, 674, 22, 477, 674, 21, 30, 1102, 596, 2751, 1202, 7580, 3725, 66838, 5596, 304, 433, 323, 433, 596, 779, 49304, 1534, 430, 433, 596, 41367, 11, 719, 433, 5675, 1063, 20930, 449, 757, 323, 358, 2646, 8220, 433, 13, 10699, 3806, 627, 6540, 301, 70305, 1389, 61328, 1148, 430, 1023, 7564, 1071, 922, 279, 1888, 1847, 315, 420, 1060, 1606, 3165, 301, 70305, 374, 12738, 13, 1102, 596, 779, 17676, 304, 279, 1648, 430, 433, 11335, 13, 8574, 323, 433, 596, 4661, 220, 1041, 4, 701, 14867, 13, 71825, 750, 5107, 11, 842, 686, 11559, 2523, 323, 15526, 11, 323, 40069, 14400, 13, 358, 1193, 6562, 358, 1047, 810, 4885, 311, 1514, 2254, 39828, 449, 627, 47, 18314, 65307, 220, 17, 1389, 2876, 439, 15526, 439, 13174, 16, 323, 539, 439, 2523, 439, 13174, 18, 198, 47, 18314, 65307, 220, 18, 1389, 13174, 5900, 220, 845, 15615, 34602, 13, 578, 12896, 374, 54739, 398, 5107, 11, 719, 279, 1847, 374, 20181, 315, 2523, 1606, 315, 433, 13, 4314, 502, 6989, 527, 2307, 29585, 13, 1102, 596, 1093, 814, 25720, 704, 682, 279, 23546, 311, 34602, 12896, 323, 57463, 291, 1124, 311, 264, 22145, 596, 6964, 13, 29308, 7185, 11, 719, 4228, 311, 17685, 6261, 449, 3958, 538, 6727, 627, 50, 1354, 315, 264, 25450, 21080, 25, 95079, 1389, 9062, 1847, 5097, 16058, 11, 719, 5737, 264, 2478, 9248, 449, 3468, 574, 20181, 315, 2523, 627, 38, 29616, 22621, 1389, 14910, 539, 1093, 13, 33386, 11, 16645, 627, 47, 15294, 21372, 1389, 85183, 420, 1603, 358, 4024, 1523, 279, 17054, 45024, 783, 39824, 596, 14512, 13, 8242, 49264, 15526, 323, 29392, 1664, 67383, 13, 358, 2846, 14470, 3738, 430, 1521, 3287, 956, 4662, 1664, 3403, 311, 2567, 3339, 1124, 11, 719, 358, 2216, 14333, 279, 6376, 323, 279, 3446, 13, 15668, 19369, 627, 6102, 69595, 220, 18, 1389, 358, 2846, 279, 7564, 889, 596, 2646, 6476, 264, 7639, 69595, 1847, 1603, 779, 994, 358, 1514, 420, 44517, 88, 11, 2840, 275, 4341, 11, 2886, 6539, 32671, 358, 2846, 653, 11490, 5294, 291, 555, 69595, 596, 3925, 13, 2684, 596, 912, 12593, 311, 279, 1648, 433, 1511, 311, 387, 477, 279, 1648, 358, 4934, 264, 35861, 311, 387, 13, 1102, 596, 1120, 459, 12738, 32671, 449, 264, 30355, 11, 719, 29585, 3446, 13, 16327, 374, 1618, 311, 4822, 439, 264, 6376, 323, 1524, 3582, 9305, 12134, 5885, 527, 682, 409, 501, 25745, 49652, 7298, 889, 358, 12491, 11, 358, 1047, 264, 8579, 7858, 369, 7639, 323, 61678, 12930, 13, 36416, 6573, 32671, 627, 50, 14338, 2672, 811, 1389, 18766, 44317, 3953, 19419, 13, 2052, 315, 1124, 13, 22172, 889, 15849, 2672, 811, 374, 330, 1962, 430, 3958, 1, 477, 330, 19045, 1, 374, 5076, 13, 1472, 2351, 5076, 627, 21587, 33989, 3378, 65843, 14220, 1389, 362, 37390, 1847, 0, 358, 3287, 956, 13383, 433, 1603, 358, 6818, 433, 13, 578, 1176, 13697, 4465, 40199, 323, 358, 10717, 5737, 1306, 433, 13, 358, 6865, 430, 574, 264, 16930, 627, 65457, 220, 19, 28145, 1389, 358, 2751, 264, 2697, 35519, 3640, 1523, 555, 1694, 9770, 311, 1514, 1023, 39555, 1603, 25270, 279, 1925, 19775, 11, 719, 279, 42271, 315, 279, 54990, 3446, 574, 6573, 3403, 311, 1304, 757, 8173, 304, 279, 1847, 11, 1524, 422, 358, 3287, 956, 2216, 2512, 369, 279, 11039, 45239, 13, 51300, 11, 889, 7020, 264, 11039, 1847, 1436, 617, 264, 10437, 3446, 5380, 11603, 25, 5960, 13175, 1389, 58072, 956, 636, 3403, 304, 311, 2019, 4205, 45813, 11, 719, 358, 1541, 956, 2216, 1093, 279, 1841, 30126, 627, 1305, 483, 220, 17, 1389, 358, 1541, 956, 1781, 3060, 315, 1521, 1183, 483, 3953, 527, 369, 757, 11, 719, 358, 3077, 1193, 3596, 6476, 220, 20, 4207, 315, 264, 1183, 483, 1847, 3596, 13, 1102, 596, 279, 22027, 1646, 13, 358, 1541, 956, 1093, 279, 737, 28281, 304, 264, 5452, 261, 13, 358, 1047, 279, 1890, 4360, 449, 15013, 6295, 29935, 627, 47493, 67314, 1389, 578, 1455, 35711, 29130, 3217, 315, 220, 679, 17, 13, 1102, 596, 264, 21648, 2288, 1606, 3468, 11, 12336, 11, 323, 358, 1288, 617, 10456, 5737, 420, 627, 14431, 12, 73419, 25, 8121, 76589, 1389, 4359, 15770, 1800, 358, 3021, 757, 1063, 20315, 12, 73419, 13, 358, 3287, 956, 2231, 430, 1690, 4207, 1139, 420, 11, 719, 5737, 433, 449, 22021, 323, 1063, 315, 279, 2362, 5111, 43805, 7752, 574, 12738, 13, 1442, 499, 617, 904, 2802, 304, 63170, 11, 719, 499, 1541, 956, 1514, 420, 1981, 9336, 358, 1541, 956, 3619, 499, 627, 46, 1310, 82, 15832, 8574, 220, 17, 1389, 2876, 279, 1888, 21970, 9232, 1847, 11, 719, 358, 1781, 358, 2846, 1234, 220, 605, 41140, 449, 433, 779, 7344, 433, 22657, 709, 5380, 791, 8155, 15457, 1389, 25545, 779, 35519, 3640, 1523, 4477, 922, 420, 449, 6941, 320, 30380, 430, 4668, 10380, 430, 358, 2646, 8738, 433, 13, 41315, 315, 11471, 1070, 449, 5885, 430, 2873, 19662, 1109, 701, 13783, 23655, 52401, 11, 719, 358, 1205, 311, 3041, 433, 2500, 220, 508, 4207, 311, 387, 2771, 627, 9126, 315, 279, 48085, 1389, 578, 10508, 478, 48065, 1847, 320, 2727, 5776, 1233, 45539, 8, 499, 690, 3596, 1514, 13, 57606, 11, 893, 13, 1102, 596, 5128, 13697, 13, 578, 3446, 374, 14470, 30355, 11, 719, 5737, 433, 374, 779, 1790, 2523, 430, 499, 649, 956, 1520, 719, 15648, 13, 362, 6573, 3243, 304, 856, 2363, 627, 4082, 43, 25, 85586, 34776, 8828, 1389, 358, 3077, 12715, 220, 2148, 13, 20, 4207, 315, 757, 5737, 420, 1847, 439, 315, 994, 358, 3350, 420, 11914, 13, 362, 1847, 430, 706, 1778, 10508, 30126, 430, 499, 649, 956, 1520, 719, 3021, 433, 13, 1115, 574, 279, 1060, 315, 95256, 4088, 12732, 369, 757, 13, 435, 13778, 11335, 1093, 279, 3634, 1675, 499, 2744, 6562, 499, 1047, 13, 358, 1541, 956, 1518, 7182, 3794, 34386, 315, 420, 1847, 3156, 358, 15405, 682, 279, 18198, 13, 3011, 2834, 956, 387, 369, 264, 1418, 1606, 358, 2846, 14738, 17936, 449, 1063, 315, 279, 18198, 11, 719, 358, 656, 3021, 757, 420, 1847, 627, 3648, 7445, 24270, 34321, 13, 220, 17, 1389, 4497, 24270, 5452, 287, 13, 2876, 279, 1455, 14948, 24270, 1847, 11, 719, 433, 706, 1202, 14269, 13, 2876, 16926, 743, 279, 1917, 389, 4027, 323, 11, 1093, 279, 1176, 832, 11, 539, 856, 7075, 24270, 1847, 627, 51, 22312, 4238, 220, 17, 1389, 358, 649, 956, 2216, 3802, 311, 617, 6476, 420, 1847, 2533, 279, 1176, 1938, 574, 264, 10879, 71574, 323, 358, 3287, 956, 636, 3347, 279, 5130, 4264, 13, 24805, 20181, 315, 2523, 52067, 449, 3468, 323, 813, 36271, 3582, 627, 10921, 8329, 220, 17, 1389, 30070, 279, 1633, 842, 315, 6790, 358, 574, 279, 1193, 832, 315, 856, 3345, 2835, 16211, 4885, 889, 1047, 420, 1847, 13, 1666, 264, 13839, 31017, 320, 438, 1524, 439, 264, 1912, 31017, 705, 279, 4216, 5596, 315, 420, 1847, 527, 5128, 17936, 3554, 5620, 5640, 291, 1245, 13, 763, 264, 1912, 358, 3077, 14333, 5737, 420, 20181, 810, 13, 1102, 596, 1120, 2523, 311, 617, 2380, 4885, 20700, 2212, 73081, 449, 499, 13, 358, 3987, 584, 2567, 5737, 627, 791, 62078, 61254, 25, 13321, 27582, 1389, 358, 3021, 37390, 3953, 13, 358, 3021, 13321, 27582, 4731, 13, 1115, 1847, 374, 6366, 323, 4832, 323, 1436, 1193, 387, 1903, 2731, 449, 810, 31042, 30768, 4731, 627, 99022, 1729, 596, 18308, 11348, 1389, 393, 19011, 433, 709, 311, 1866, 58811, 7445, 7834, 13, 75106, 264, 2766, 315, 430, 449, 3468, 13, 41315, 315, 2523, 11, 719, 539, 16926, 743, 279, 1917, 389, 4027, 627, 48120, 45024, 783, 323, 279, 8155, 27726, 261, 1389, 75106, 433, 369, 264, 2478, 4520, 1606, 433, 574, 279, 1193, 35861, 358, 1436, 1505, 304, 279, 3637, 13, 20817, 389, 1884, 2478, 4520, 358, 11021, 279, 2800, 315, 279, 19562, 627, 61189, 5929, 6207, 220, 17, 1389, 358, 6562, 358, 19117, 956, 15753, 3468, 323, 6941, 311, 636, 5348, 323, 5929, 1606, 279, 6207, 220, 17, 82, 527, 779, 1790, 2731, 13, 2684, 706, 2646, 1027, 264, 2731, 2231, 3871, 28831, 1847, 13, 358, 3077, 68265, 927, 264, 7895, 4207, 1139, 420, 1847, 5737, 433, 452, 5308, 1039, 68, 1742, 323, 358, 2103, 617, 3686, 311, 18506, 279, 34864, 13625, 477, 8068, 65632, 13, 358, 2846, 539, 56825, 11, 7752, 11, 420, 374, 279, 18585, 499, 649, 2586, 311, 264, 4832, 28831, 1847, 627, 55, 8867, 25, 31851, 22435, 1389, 7777, 11, 369, 312, 1147, 552, 1457, 11, 7752, 13, 1115, 374, 279, 1888, 1847, 315, 279, 1060, 13, 4702, 779, 1790, 2523, 311, 1514, 304, 22591, 16979, 1543, 3941, 1405, 1475, 16930, 374, 16447, 304, 2035, 323, 22706, 59441, 304, 279, 8335, 13, 71658, 11, 2543, 6108, 12896, 706, 2646, 1027, 2731, 11798, 323, 1475, 1887, 4375, 1664, 13, 3092, 1193, 23854, 375, 374, 430, 499, 330, 4919, 956, 3775, 1, 279, 1620, 9131, 304, 279, 5647, 430, 13490, 433, 22014, 499, 311, 279, 1212, 13, 99239, 459, 16979, 1543, 1629, 304, 279, 1620, 9131, 1053, 387, 20333, 320, 438, 12703, 4633, 705, 8434, 956, 433, 5380, 48120, 45024, 783, 323, 279, 13182, 1245, 25036, 1389, 1102, 706, 264, 14470, 27873, 7234, 27744, 430, 4661, 3727, 7315, 5647, 323, 3250, 956, 4295, 449, 904, 297, 316, 764, 11, 719, 499, 2351, 10171, 311, 387, 1618, 369, 279, 47623, 13971, 13, 2435, 2351, 2523, 323, 279, 5885, 527, 35509, 3403, 430, 358, 2846, 810, 1109, 6380, 311, 8493, 4207, 5304, 4207, 1120, 27666, 8271, 30668, 388, 627, 24581, 369, 15535, 25, 7648, 67710, 1389, 358, 6562, 420, 574, 810, 18530, 412, 48691, 4619, 13, 358, 1541, 956, 1093, 279, 1648, 279, 330, 38439, 1, 374, 17551, 704, 449, 279, 74291, 369, 682, 279, 9515, 13, 358, 12491, 1268, 358, 617, 311, 7380, 25719, 299, 1475, 892, 358, 14626, 9515, 13, 1102, 596, 1120, 539, 439, 1695, 439, 279, 18530, 412, 6392, 13, 358, 2846, 14931, 13, 3011, 1071, 11, 433, 596, 779, 1790, 2523, 311, 7102, 520, 1948, 4732, 304, 1972, 31184, 79648, 13, 7445, 2523, 627, 48120, 45024, 783, 323, 279, 77064, 20519, 1389, 578, 220, 12676, 47623, 320, 606, 264, 1938, 8, 323, 279, 2144, 430, 358, 11021, 433, 68878, 527, 1148, 13912, 757, 5108, 1203, 311, 420, 1847, 927, 323, 927, 1578, 2533, 358, 9167, 956, 3686, 31394, 279, 3766, 26771, 13, 22925, 25649, 990, 323, 264, 2294, 220, 18, 6061, 6462, 11, 719, 358, 649, 956, 3868, 311, 3604, 1518, 279, 19775, 627, 48120, 45024, 783, 323, 279, 7923, 53904, 950, 8425, 1389, 4497, 45024, 783, 11, 719, 389, 264, 5542, 4999, 1271, 279, 17781, 1389, 578, 40155, 15371, 3169, 315, 47168, 420, 1847, 369, 757, 13, 22172, 574, 1208, 51867, 433, 439, 420, 6800, 11, 15196, 19775, 11, 719, 1243, 578, 40155, 15371, 5900, 323, 1587, 2555, 9615, 28809, 1418, 2057, 279, 17781, 4745, 311, 2216, 4295, 449, 757, 13, 578, 27744, 574, 29585, 323, 358, 44120, 279, 3446, 11, 719, 358, 3287, 956, 1505, 433, 311, 387, 439, 8056, 439, 358, 4265, 6755, 13, 1102, 596, 6573, 48929, 304, 264, 68480, 4817, 6462, 11, 719, 433, 596, 5922, 13598, 704, 369, 2771, 627, 20780, 1074, 18045, 1389, 53466, 279, 1847, 430, 596, 14948, 279, 1455, 272, 474, 2785, 43214, 304, 757, 13, 4702, 28860, 11, 28360, 11, 20328, 13933, 11, 323, 16682, 13, 8166, 1074, 18045, 706, 264, 10536, 395, 45999, 323, 60135, 27120, 13, 578, 42847, 527, 3169, 315, 1536, 95832, 11, 719, 433, 11335, 14470, 46473, 323, 358, 4265, 7079, 433, 311, 4661, 5606, 627, 87079, 11680, 1389, 58038, 304, 1912, 5110, 11, 719, 14738, 32161, 439, 264, 13839, 54914, 13, 358, 2846, 6380, 311, 1866, 433, 323, 358, 1781, 40107, 2038, 2971, 391, 8623, 3727, 369, 1648, 810, 7185, 3953, 1109, 279, 1890, 2362, 6392, 584, 2351, 1511, 311, 11, 719, 2085, 264, 1912, 311, 1514, 420, 433, 649, 636, 264, 2697, 28859, 627, 3648, 7445, 24270, 34321, 13, 549, 1389, 42714, 956, 2231, 264, 2763, 315, 892, 304, 433, 11, 719, 279, 3388, 2955, 374, 8659, 16757, 311, 279, 21223, 2373, 13, 3053, 956, 3868, 311, 9567, 420, 449, 3468, 11, 719, 358, 2846, 539, 15061, 1523, 904, 14365, 311, 1514, 433, 627, 8161, 798, 18711, 14438, 5295, 1389, 358, 2846, 1193, 1403, 24800, 304, 11, 719, 433, 11321, 8275, 261, 54786, 4506, 1109, 279, 2362, 56340, 34645, 13, 1226, 3358, 1518, 1268, 433, 64883, 704, 11, 358, 8101, 627, 42845, 287, 39525, 1389, 358, 2846, 3794, 1825, 1917, 36709, 5128, 4216, 304, 420, 832, 13, 27140, 33319, 11035, 25, 578, 21530, 11, 420, 374, 810, 6129, 323, 358, 2733, 1093, 539, 1694, 27873, 374, 311, 1202, 50008, 13, 75247, 39525, 6, 5029, 1887, 374, 27873, 323, 279, 6293, 3446, 374, 14470, 45207, 11, 719, 358, 2846, 304, 3021, 449, 279, 19730, 18711, 6376, 323, 279, 2144, 430, 420, 374, 264, 1847, 539, 4737, 2035, 304, 13256, 11, 12551, 11, 477, 18045, 13, 7429, 2216, 6555, 311, 1518, 2536, 16237, 95735, 13, 578, 27805, 11039, 1742, 374, 29585, 11, 719, 11, 1093, 358, 1071, 11, 2736, 20129, 1825, 1917, 36709, 627, 5500, 25, 38166, 30192, 11, 38166, 63030, 11, 38166, 50717, 1389, 358, 2846, 16089, 358, 6476, 323, 8220, 420, 1603, 279, 842, 315, 279, 1060, 1606, 433, 596, 11112, 20333, 13, 5884, 1847, 430, 5829, 279, 30126, 315, 279, 1887, 1202, 389, 374, 459, 9888, 5636, 369, 757, 323, 279, 1620, 25649, 10991, 899, 367, 374, 20333, 13, 2650, 1690, 3953, 1304, 499, 1781, 922, 27448, 292, 58081, 323, 2038, 8481, 1093, 420, 832, 30, 4702, 279, 2144, 430, 358, 1766, 7182, 7422, 922, 41903, 4860, 1093, 83022, 596, 328, 26246, 48848, 27901, 315, 4314, 355, 323, 430, 433, 13398, 79799, 328, 6501, 574, 2216, 20333, 13, 9372, 11, 9302, 32963, 527, 75235, 11, 719, 499, 13434, 956, 1095, 430, 636, 304, 701, 1648, 13, 220, 5500, 706, 832, 315, 279, 841, 14217, 7493, 315, 279, 1060, 320, 679, 15, 8, 323, 433, 596, 6847, 832, 315, 856, 7075, 3953, 420, 1060, 627, 5500, 25, 11888, 4207, 11888, 11434, 11888, 14365, 11, 6160, 363, 548, 11, 2766, 94876, 42328, 11, 1529, 39248, 11, 3973, 8329, 220, 17, 11, 8395, 412, 50852, 11, 26457, 3446, 489, 11, 81472, 5425, 11, 81472, 8346, 11729, 11, 5663, 5594, 41752, 25, 3728, 15538, 11, 1891, 32560, 11, 1891, 32560, 14799, 11, 1891, 32560, 63193, 11, 1541, 798, 597, 647, 3224, 4780, 11, 26161, 4325, 220, 18, 11, 5696, 25, 8528, 44579, 9652, 11, 9578, 11130, 11, 1172, 89, 11, 1620, 18884, 865, 35694, 11, 1620, 18884, 865, 35694, 12, 17, 11, 10702, 75, 25, 10819, 1109, 3177, 11, 20457, 14397, 11, 56926, 37566, 11, 92975, 296, 15622, 11, 11245, 84972, 11, 503, 373, 44058, 11, 73730, 1729, 596, 8063, 4526, 11, 1906, 315, 279, 64951, 11, 3148, 2515, 220, 18, 11, 1973, 2343, 818, 220, 18, 11, 1205, 369, 4732, 25, 1455, 4934, 11, 47752, 60466, 39153, 290, 11, 502, 2307, 296, 3370, 2967, 82, 13, 220, 17, 11, 502, 2307, 296, 3370, 2967, 82, 13, 577, 11, 308, 20942, 4363, 11, 912, 810, 23757, 25, 23757, 6, 50852, 11, 477, 4942, 2011, 2815, 220, 17, 11, 50169, 48312, 32078, 25, 389, 279, 11422, 1355, 1228, 36841, 560, 315, 11, 50169, 48312, 32078, 25, 389, 279, 11422, 1355, 1228, 36841, 560, 315, 27394, 220, 18, 11, 29055, 220, 19, 25946, 11, 90815, 289, 1315, 11, 38751, 4251, 11, 38751, 4251, 2373, 220, 17, 11, 14561, 11203, 783, 323, 279, 22999, 14458, 11, 14561, 11203, 783, 323, 279, 1891, 53904, 950, 3830, 11, 14561, 11203, 783, 323, 279, 1566, 9618, 261, 11, 14561, 11203, 783, 323, 279, 45125, 7056, 11, 25649, 8479, 11, 18803, 1543, 25, 33472, 11, 37390, 23070, 34653, 11, 7091, 12134, 11, 68220, 2872, 25, 279, 4948, 11, 12737, 6485, 11, 77111, 19262, 10830, 43787, 72, 25, 38736, 49748, 11, 77111, 19262, 10830, 43787, 72, 25, 38736, 49748, 220, 17, 11, 40444, 315, 264, 13238, 32447, 25, 53848, 11, 21811, 12875, 11, 72436, 22540, 11, 72035, 70305, 11, 6917, 7868, 14799, 25, 4851, 315, 279, 61941, 11, 2307, 15222, 3058, 25, 20827, 612, 2064, 269, 22228, 4248, 11, 279, 11212, 315, 52435, 582, 11, 279, 1566, 3446, 11, 279, 289, 587, 2785, 5710, 11, 47213, 81, 61254, 1620, 18884, 11, 311, 279, 18266, 11, 7990, 4238, 11, 7990, 4238, 220, 17, 11, 490, 483, 11, 490, 483, 220, 17, 11, 21965, 4042, 220, 19, 11, 4208, 7868, 11, 865, 884, 25, 9354, 9987, 198, 3923, 358, 3077, 51678, 44245, 220, 966, 4448, 220, 679, 17, 510, 16606, 14, 3336, 12598, 16675, 51, 14, 15881, 933, 18820, 220, 966, 339, 11, 220, 679, 17, 555, 11824, 198, 8586, 596, 264, 24710, 25, 1442, 499, 2351, 5737, 50492, 15457, 369, 279, 1176, 892, 11, 1541, 956, 3820, 2653, 3941, 320, 10682, 27104, 28883, 53153, 798, 340, 60037, 9178, 449, 10283, 315, 3772, 27073, 13, 3011, 3169, 315, 3245, 8741, 994, 358, 15020, 704, 449, 3468, 627, 791, 32285, 29410, 1389, 1443, 607, 1994, 12404, 3258, 574, 264, 40010, 439, 8683, 304, 420, 5818, 13, 37866, 15718, 13, 10058, 19197, 2596, 574, 1101, 5115, 1695, 13, 36416, 37401, 5818, 323, 5922, 9298, 11, 1524, 422, 279, 4363, 15637, 47726, 374, 3169, 315, 259, 11440, 389, 323, 539, 439, 7185, 627, 35212, 17729, 290, 220, 17, 13, 1313, 1389, 358, 3463, 358, 4265, 3970, 420, 83766, 358, 19117, 956, 13, 358, 2216, 13942, 9298, 1063, 315, 279, 2523, 14, 88657, 25572, 315, 279, 2362, 11333, 1501, 13, 358, 3152, 11, 14713, 2209, 15817, 301, 304, 4799, 315, 264, 2978, 20156, 7234, 922, 3339, 35549, 7910, 16163, 323, 264, 14177, 4717, 30, 358, 4265, 4856, 617, 430, 8668, 4619, 13, 358, 1101, 636, 430, 279, 5818, 3250, 956, 2187, 369, 279, 48883, 788, 323, 46072, 42111, 19415, 5893, 29150, 8209, 2403, 445, 12574, 301, 11, 719, 433, 596, 832, 315, 856, 282, 4798, 779, 358, 574, 73974, 2106, 922, 13490, 433, 2288, 13, 14910, 539, 2512, 369, 279, 502, 18178, 11, 29829, 11, 520, 682, 11, 323, 358, 3287, 956, 3021, 279, 2626, 449, 27890, 709, 889, 596, 889, 304, 279, 8209, 2403, 64304, 13327, 11, 719, 11, 8996, 11, 1314, 30, 4427, 2574, 527, 2204, 13, 220, 17, 13, 1313, 3727, 757, 1390, 311, 3821, 78064, 41888, 55806, 290, 4619, 13, 578, 810, 31467, 18338, 6276, 369, 1790, 7191, 3752, 4500, 323, 7185, 19476, 13, 1226, 3358, 1518, 1148, 8741, 449, 279, 2800, 315, 279, 9698, 323, 279, 502, 13696, 627, 51, 40040, 1389, 3468, 19117, 956, 3970, 420, 11, 433, 574, 389, 9888, 11, 323, 584, 1051, 34386, 13, 1102, 596, 5128, 2294, 11, 719, 358, 12491, 279, 2835, 4367, 315, 279, 7834, 89, 9698, 627, 57564, 36631, 1389, 54859, 311, 1518, 420, 389, 7418, 323, 433, 4018, 704, 220, 1272, 4520, 304, 13, 1226, 1436, 617, 3060, 20186, 311, 3821, 433, 505, 279, 7314, 477, 4529, 264, 49758, 369, 264, 502, 5818, 13, 1666, 8173, 304, 9298, 420, 439, 358, 574, 11, 358, 7846, 956, 23152, 10307, 279, 6435, 8736, 220, 1272, 4520, 1578, 13, 358, 3358, 3060, 1456, 1578, 477, 3868, 369, 23469, 627, 11800, 82, 15429, 1389, 27738, 220, 23, 323, 279, 2911, 72022, 15341, 25510, 1543, 449, 97438, 574, 2294, 13, 2100, 574, 279, 14596, 328, 1916, 22380, 311, 1505, 704, 1268, 2362, 568, 574, 13, 58038, 1501, 13, 3053, 956, 3868, 369, 264, 502, 3280, 627, 2378, 2052, 13120, 1389, 55629, 52627, 750, 323, 74984, 3458, 13, 2100, 2294, 13, 578, 2766, 922, 42823, 389, 10307, 264, 6007, 1501, 449, 701, 32080, 574, 2294, 13, 7445, 29859, 627, 38, 8669, 1389, 36416, 7185, 330, 51787, 64643, 1, 47044, 11, 4686, 449, 279, 25652, 304, 279, 11323, 24045, 1620, 5296, 13, 358, 1093, 11936, 1093, 330, 27601, 7113, 18366, 33425, 498, 719, 279, 15590, 24196, 5222, 264, 2763, 1093, 814, 1541, 956, 9352, 304, 279, 1501, 13, 358, 8101, 433, 574, 264, 8063, 8668, 46817, 11, 3339, 5277, 648, 3351, 14, 533, 1093, 60333, 622, 10322, 374, 29392, 7524, 1524, 3582, 568, 596, 304, 264, 54618, 13, 10699, 64, 1981, 12840, 27074, 578, 3245, 922, 35162, 596, 18233, 3782, 704, 315, 23214, 4678, 627, 10156, 1908, 1389, 358, 2846, 7155, 449, 1162, 315, 279, 2046, 6392, 994, 433, 596, 420, 1695, 13, 18156, 433, 596, 5509, 369, 13558, 10946, 539, 311, 387, 279, 10973, 4219, 13, 358, 3987, 814, 636, 94870, 480, 773, 3394, 389, 279, 1501, 810, 13, 578, 1023, 502, 40148, 374, 36001, 29565, 627, 7098, 9211, 1389, 330, 34, 11160, 321, 7673, 330, 2822, 17954, 369, 499, 9135, 13596, 2294, 9417, 315, 59979, 420, 2046, 13, 358, 3194, 13558, 439, 264, 2115, 8479, 11, 719, 358, 8101, 420, 706, 264, 2763, 315, 20303, 4754, 627, 47, 7341, 323, 57857, 1389, 578, 2766, 922, 8529, 59296, 1093, 264, 83777, 320, 438, 14662, 60206, 1461, 311, 617, 1063, 99370, 439, 264, 893, 8, 574, 8056, 13, 5936, 1694, 6555, 374, 19018, 11, 719, 1364, 596, 1027, 8579, 6147, 709, 264, 2763, 13971, 13, 16782, 832, 315, 279, 12474, 5039, 704, 1070, 627, 66608, 16115, 1389, 4702, 2231, 433, 389, 369, 264, 2478, 4520, 311, 1522, 1063, 892, 13, 24119, 264, 1695, 1501, 627, 68359, 1039, 1389, 578, 6278, 9417, 922, 279, 8620, 41837, 9438, 374, 3169, 315, 28859, 11, 719, 279, 95297, 6862, 9417, 374, 14964, 13, 358, 3021, 1268, 14599, 11641, 95297, 6862, 374, 13, 2100, 2294, 627, 13379, 31346, 596, 1561, 4356, 15948, 3216, 7073, 1389, 393, 18033, 420, 389, 2391, 14177, 369, 2555, 311, 12835, 311, 13, 36416, 1695, 6392, 627, 791, 44069, 34179, 1389, 1472, 1440, 814, 2231, 709, 264, 502, 9156, 9469, 2957, 320, 34139, 1463, 10380, 279, 5513, 10449, 11, 779, 430, 2751, 757, 14624, 311, 682, 315, 1124, 1578, 13, 358, 1524, 73307, 1139, 872, 2536, 12, 835, 83, 45, 4731, 1606, 358, 3021, 21077, 44069, 596, 7899, 627, 791, 11617, 3161, 279, 16537, 76634, 1389, 39247, 323, 24981, 13, 25517, 70678, 380, 2771, 5334, 2212, 449, 279, 23628, 11, 3250, 956, 568, 5380, 791, 10846, 5545, 1389, 578, 27509, 596, 2751, 469, 4253, 488, 42497, 18944, 389, 8961, 2704, 779, 1457, 433, 596, 892, 311, 1212, 3318, 389, 13528, 351, 6885, 596, 31396, 627, 65786, 70325, 1389, 25274, 264, 2763, 315, 5208, 304, 420, 1847, 13, 578, 23347, 9731, 311, 92792, 439, 856, 15506, 9731, 311, 7417, 13, 358, 3021, 5737, 3953, 304, 15506, 4999, 44924, 11130, 320, 59978, 220, 17, 8, 1389, 36912, 709, 264, 502, 3665, 1052, 311, 1514, 304, 1990, 42847, 304, 264, 25834, 13, 16457, 3115, 13, 16782, 1633, 4216, 304, 279, 1847, 320, 72012, 956, 36131, 279, 42142, 3686, 340, 30287, 1543, 25, 70591, 1389, 3468, 323, 358, 9567, 279, 1847, 323, 3940, 2133, 369, 279, 66221, 5990, 13, 19229, 10087, 279, 1566, 832, 11, 11680, 315, 279, 37311, 307, 15371, 11, 374, 922, 439, 75986, 439, 279, 1847, 649, 636, 13, 17916, 287, 5334, 35711, 11, 719, 433, 596, 1101, 2751, 264, 2307, 37154, 2733, 3131, 499, 51630, 433, 627, 34, 525, 15457, 489, 1389, 36287, 358, 4265, 10677, 709, 2555, 2204, 1418, 3468, 574, 308, 3713, 13, 1115, 1847, 374, 5128, 2523, 323, 5128, 6573, 11, 719, 30230, 358, 1288, 1514, 433, 389, 2653, 3941, 1253, 617, 1027, 264, 16930, 13, 358, 2846, 16075, 389, 29073, 1630, 1606, 568, 596, 264, 32236, 13, 7357, 832, 315, 813, 25977, 80137, 29910, 757, 304, 832, 4295, 11, 779, 358, 3077, 2751, 311, 387, 4832, 13, 1952, 279, 1695, 3185, 315, 279, 20326, 11, 279, 5780, 6166, 30126, 527, 8056, 13, 10919, 430, 6166, 323, 279, 5845, 311, 2273, 449, 433, 627, 73328, 1115, 11, 62483, 48081, 11, 37957, 11, 16807, 3906, 8476, 39285, 291, 11, 4140, 35907, 11, 5336, 11345, 8425, 198, 1132, 261, 11, 1841, 4355, 342, 773, 3394, 11, 26457, 3446, 489, 11, 2911, 82, 8952, 11, 9578, 11130, 11, 39153, 290, 220, 17, 13, 1313, 11, 3980, 6809, 5405, 2596, 11, 20457, 14397, 11, 342, 8669, 11, 342, 1610, 683, 20820, 11, 18137, 36631, 11, 40742, 8492, 1553, 11, 40742, 8492, 1553, 596, 502, 50672, 2559, 709, 1501, 11, 35516, 11, 19262, 276, 296, 620, 750, 11, 6691, 220, 17, 11, 47752, 60466, 39153, 290, 11, 4272, 17987, 11, 16370, 3085, 1543, 11, 27943, 323, 47044, 11, 18803, 1543, 25, 33472, 11, 29147, 1494, 342, 1610, 683, 11, 9406, 16115, 11, 559, 607, 1994, 7732, 3258, 11, 35313, 1039, 11, 6917, 25981, 25, 279, 2362, 35544, 11, 6917, 89, 11, 93941, 11, 279, 49446, 11, 709, 682, 3814, 198, 11356, 25, 1472, 3077, 51678, 8602, 660, 510, 37, 3178, 392, 3178, 2868, 220, 679, 15, 933, 644, 872, 1566, 1501, 439, 264, 7200, 11, 279, 6834, 45596, 3145, 6476, 832, 5609, 323, 2163, 279, 6566, 13, 13538, 9564, 279, 6566, 11, 32980, 432, 10503, 934, 6586, 11, 330, 44587, 636, 279, 8430, 499, 3077, 1027, 78778, 48469, 791, 3245, 374, 11, 358, 1541, 956, 2733, 420, 1648, 369, 279, 8125, 5127, 775, 2643, 1781, 358, 2643, 13, 358, 23289, 584, 3358, 733, 1306, 279, 8706, 1486, 315, 52240, 1176, 627, 1, 19918, 27582, 96860, 374, 578, 70192, 13321, 27582, 18374, 320, 22809, 8, 1606, 682, 279, 83485, 527, 7833, 5238, 323, 1070, 527, 912, 25861, 1210, 55379, 1148, 13, 578, 2536, 8614, 10981, 315, 1884, 13321, 27582, 3953, 499, 682, 3412, 779, 25237, 374, 459, 41919, 13, 13321, 27582, 96860, 27741, 779, 1790, 44850, 1606, 433, 706, 279, 19754, 311, 3371, 499, 1148, 499, 2736, 1440, 627, 40, 3152, 11, 2216, 11, 499, 2643, 387, 3025, 311, 40320, 2212, 279, 1917, 893, 11, 719, 430, 3250, 956, 3152, 499, 636, 311, 3820, 1148, 499, 656, 13, 578, 7234, 1193, 31003, 994, 499, 733, 311, 3230, 7634, 304, 264, 4040, 8668, 320, 19171, 3967, 439, 264, 13790, 33824, 8, 323, 10687, 389, 279, 2472, 527, 78220, 16447, 505, 25032, 555, 3446, 35634, 627, 644, 2144, 11, 2536, 8614, 10981, 374, 264, 22380, 4028, 4661, 1475, 2835, 1847, 13, 578, 1925, 2523, 315, 904, 59845, 1847, 1253, 539, 19646, 505, 2768, 279, 3446, 11, 719, 994, 499, 656, 10491, 311, 1212, 389, 433, 11, 499, 690, 2646, 387, 3025, 311, 8668, 1464, 477, 656, 4205, 719, 1833, 433, 13790, 398, 311, 1202, 17102, 13, 1472, 2643, 387, 3025, 311, 3820, 902, 2015, 499, 4686, 9131, 13006, 11, 719, 11, 449, 279, 4788, 315, 59845, 17244, 11, 1475, 1567, 706, 264, 864, 1773, 47737, 15632, 13, 1442, 430, 596, 539, 1584, 10981, 11, 358, 1541, 956, 1440, 1148, 374, 627, 40, 52490, 264, 1847, 430, 3250, 956, 1456, 311, 54262, 1202, 3446, 4920, 264, 77851, 261, 315, 51527, 5873, 13, 13321, 27582, 3953, 617, 1193, 3596, 5535, 11709, 3131, 25, 578, 4435, 315, 29014, 258, 304, 31042, 30768, 13, 2684, 527, 28701, 3446, 3649, 323, 3185, 87422, 311, 3217, 11, 719, 3131, 499, 636, 2638, 7215, 11, 60091, 11, 323, 328, 9068, 11, 499, 1541, 956, 617, 311, 1518, 904, 315, 1124, 13, 1472, 2351, 1949, 311, 40336, 323, 3663, 735, 830, 4657, 520, 904, 1486, 627, 49828, 3585, 2216, 1288, 387, 22034, 311, 31042, 96860, 369, 3515, 279, 65973, 311, 1095, 1202, 3446, 6920, 279, 24151, 11, 719, 814, 527, 7214, 5675, 389, 872, 4745, 4879, 311, 1304, 4205, 39529, 7185, 3621, 627, 11339, 3646, 304, 856, 91904, 449, 279, 1847, 374, 18231, 596, 47726, 13, 763, 279, 1176, 6596, 477, 779, 315, 27120, 11, 19435, 11, 264, 2466, 11, 55349, 11, 18754, 7564, 304, 279, 14135, 315, 23655, 2466, 11, 55349, 11, 18754, 7752, 11, 29972, 311, 636, 1455, 315, 813, 21108, 4681, 19037, 7577, 11, 2737, 18231, 596, 6691, 11, 11509, 709, 2403, 279, 1917, 596, 3109, 13, 60842, 11, 420, 85225, 988, 18231, 11, 889, 1457, 32097, 37169, 627, 39, 1100, 8942, 45608, 25, 362, 893, 5084, 6089, 8647, 369, 279, 4648, 315, 701, 6691, 13, 3234, 499, 512, 16, 13, 800, 6339, 323, 357, 67699, 1475, 892, 499, 1518, 1461, 198, 17, 13, 800, 365, 50494, 1418, 22128, 37169, 60277, 1475, 892, 499, 1518, 1461, 198, 18, 13, 19575, 704, 1063, 1648, 311, 17302, 1461, 320, 258, 34049, 477, 6062, 8, 279, 1176, 6140, 499, 636, 627, 22105, 358, 2846, 1694, 23073, 418, 9373, 1618, 11, 719, 7389, 499, 3077, 2751, 1063, 3460, 315, 14604, 19823, 11, 3072, 2380, 5084, 1093, 279, 2890, 13744, 323, 1455, 20406, 5873, 13, 18231, 374, 682, 922, 279, 1176, 1403, 2671, 1606, 568, 374, 264, 58973, 6784, 304, 279, 1089, 627, 40, 1541, 956, 1781, 420, 374, 279, 1121, 315, 1063, 3169, 315, 13042, 6811, 13, 358, 3152, 11, 35309, 11, 358, 2846, 539, 279, 1455, 38683, 1825, 1732, 13, 358, 1541, 956, 2216, 733, 2212, 11821, 856, 16024, 449, 5127, 358, 1440, 11, 719, 358, 2846, 5128, 2771, 430, 422, 264, 893, 1051, 8647, 369, 13419, 856, 3450, 11, 568, 4265, 1440, 922, 433, 67590, 13, 1102, 596, 2751, 311, 387, 264, 6155, 344, 685, 320, 438, 459, 30931, 832, 570, 8595, 527, 5885, 304, 3772, 779, 12153, 311, 1120, 1825, 872, 65609, 323, 3137, 30, 1442, 16483, 1781, 420, 374, 459, 7524, 1648, 311, 1977, 19775, 24408, 11, 1243, 358, 3077, 2751, 3754, 369, 1124, 13, 1666, 264, 6037, 11, 422, 701, 5885, 527, 9770, 311, 36792, 1093, 814, 3077, 2646, 16681, 291, 449, 2500, 3823, 1694, 369, 701, 7234, 7766, 311, 990, 11, 1071, 7766, 527, 272, 4664, 501, 11559, 6155, 2270, 627, 96514, 11, 433, 596, 1120, 16053, 4477, 323, 433, 29260, 757, 505, 279, 19775, 13, 10926, 18231, 706, 264, 18682, 12538, 8769, 430, 3727, 1461, 1180, 779, 18754, 398, 11, 719, 584, 2646, 4048, 922, 433, 13, 578, 1847, 5900, 704, 315, 1202, 1648, 311, 2019, 430, 18231, 706, 7126, 4819, 311, 1450, 89354, 3201, 813, 3674, 41760, 34946, 11, 719, 994, 584, 3449, 65673, 18231, 11, 584, 2351, 41782, 449, 264, 21955, 7126, 889, 5084, 311, 2512, 1633, 17693, 922, 813, 4538, 13, 14910, 358, 3194, 2555, 15038, 30, 35272, 5084, 311, 617, 12504, 279, 5041, 627, 2675, 1440, 1148, 11, 358, 1781, 358, 1440, 3249, 420, 7077, 13, 18024, 61752, 3235, 279, 1648, 279, 3446, 342, 56266, 520, 15992, 2998, 953, 6773, 430, 1690, 3995, 3026, 11, 872, 10461, 323, 2218, 38462, 11, 2873, 311, 617, 4819, 449, 872, 4824, 483, 4776, 40317, 13, 4427, 315, 1124, 6267, 420, 7872, 389, 813, 3752, 11071, 13, 18024, 61752, 775, 279, 15398, 16483, 1051, 5108, 709, 449, 1268, 4376, 315, 279, 2851, 5885, 1053, 52696, 323, 12731, 13, 2435, 6773, 814, 4265, 3449, 520, 18231, 596, 52528, 323, 18231, 596, 12738, 18233, 1053, 1520, 1124, 704, 13, 3277, 499, 3077, 2751, 264, 1847, 420, 11191, 323, 3062, 11, 499, 4265, 1781, 430, 1521, 1403, 7411, 1053, 4358, 1521, 887, 3614, 1756, 13075, 552, 11, 1314, 30, 2650, 1587, 1778, 264, 72221, 50859, 1304, 433, 1139, 279, 1620, 1977, 5380, 4054, 315, 856, 1023, 2466, 330, 54, 11042, 7673, 14269, 4131, 520, 279, 842, 315, 264, 8668, 520, 459, 62468, 6246, 13, 328, 1394, 71, 28970, 449, 3508, 477, 539, 311, 5622, 279, 21646, 22489, 889, 706, 65397, 1461, 13, 36416, 5246, 1306, 430, 8638, 11, 279, 7106, 64050, 315, 813, 14604, 12324, 8951, 1461, 13, 1789, 1455, 5885, 11, 11039, 872, 69431, 337, 2439, 11, 439, 814, 527, 2663, 11, 12716, 1124, 14604, 9096, 10923, 1124, 311, 3619, 872, 1853, 13, 763, 420, 1162, 304, 3135, 304, 328, 1394, 71, 30230, 311, 5379, 18639, 13, 3639, 13, 578, 13, 26146, 627, 697, 65977, 420, 1890, 14604, 5497, 4848, 3115, 320, 606, 369, 1855, 1925, 3752, 16715, 5084, 1093, 433, 1053, 636, 2362, 5043, 13, 1102, 1587, 13, 65900, 1587, 539, 7878, 268, 279, 3217, 13, 1102, 3727, 912, 5647, 13, 1226, 682, 1440, 568, 596, 539, 2216, 5710, 1606, 584, 1120, 36718, 813, 28645, 4999, 2181, 596, 264, 21648, 311, 1518, 779, 1690, 5906, 25047, 304, 1778, 264, 26455, 41302, 13, 15028, 449, 757, 1618, 13, 763, 279, 1917, 315, 31042, 96860, 1070, 527, 1403, 6156, 98870, 23837, 25, 66094, 323, 23718, 77761, 648, 320, 13431, 279, 18754, 836, 315, 279, 2132, 9606, 320, 3737, 950, 328, 94214, 953, 4509, 98981, 41902, 4682, 578, 16396, 11, 439, 358, 690, 1457, 1650, 1124, 11, 527, 24632, 20566, 58394, 304, 17843, 3691, 11, 2410, 11, 477, 1023, 810, 11084, 5865, 13, 19173, 11, 279, 16396, 527, 6859, 1139, 1403, 289, 20450, 48752, 11, 77488, 9186, 323, 50349, 13, 16396, 1101, 617, 279, 42351, 5845, 311, 6883, 12966, 11, 58272, 2785, 1124, 449, 14774, 292, 50277, 13, 435, 14612, 311, 4686, 1521, 50277, 10800, 279, 3823, 1139, 264, 4059, 1752, 18118, 63971, 311, 40320, 279, 9578, 14297, 6573, 7922, 3156, 568, 5616, 6896, 81, 9803, 323, 649, 912, 5129, 3351, 13, 1442, 814, 4983, 425, 311, 12265, 304, 872, 2271, 11, 814, 527, 24411, 1139, 48473, 369, 64482, 13, 13266, 304, 330, 5192, 14272, 6212, 1, 527, 539, 5710, 11, 719, 814, 527, 1101, 539, 13989, 627, 2181, 596, 279, 4832, 409, 48297, 315, 2835, 1847, 95735, 13, 9062, 3752, 706, 264, 35044, 7580, 13, 435, 14612, 690, 1121, 304, 264, 25382, 11201, 1109, 4648, 323, 73820, 690, 1121, 304, 279, 842, 315, 279, 19775, 11, 656, 18238, 279, 5885, 311, 2536, 10397, 81624, 13, 578, 1790, 8811, 1571, 13790, 7138, 315, 279, 1847, 11105, 872, 38550, 311, 2543, 3201, 11, 5423, 994, 499, 4048, 430, 279, 43215, 1705, 617, 1027, 10695, 499, 279, 4459, 892, 13, 578, 2466, 3958, 6944, 279, 5885, 311, 5622, 1461, 13, 1789, 3131, 279, 1847, 52694, 430, 1202, 1486, 374, 311, 387, 24164, 555, 279, 2851, 627, 2746, 328, 94214, 953, 19117, 956, 8208, 323, 41013, 389, 264, 409, 355, 506, 8002, 2259, 13696, 1093, 814, 1047, 11, 279, 1917, 1053, 617, 9670, 449, 43384, 323, 279, 16396, 69918, 13, 1102, 1053, 617, 1027, 20333, 627, 8586, 596, 2500, 4623, 369, 279, 16483, 704, 1070, 13, 1442, 584, 617, 912, 4623, 320, 438, 912, 13310, 8, 264, 3752, 649, 656, 2555, 3156, 499, 29057, 16805, 433, 304, 279, 5869, 67666, 4018, 23296, 11, 433, 690, 2733, 12136, 994, 499, 1304, 279, 13696, 17631, 389, 430, 10151, 13, 2876, 311, 6420, 11, 315, 3388, 11, 430, 279, 22027, 315, 84866, 279, 24151, 315, 264, 14880, 84710, 16054, 9214, 315, 7693, 1555, 279, 16975, 1053, 4762, 1121, 304, 279, 16779, 315, 7154, 1475, 33427, 519, 627, 2028, 374, 682, 42415, 5304, 279, 50765, 323, 17231, 63600, 6425, 430, 1057, 23757, 2586, 709, 449, 311, 5663, 279, 14951, 22948, 16396, 13, 2175, 420, 11, 872, 3197, 374, 311, 1120, 2567, 2133, 3235, 279, 1853, 16026, 430, 2555, 690, 3665, 1124, 505, 656, 18238, 5694, 320, 564, 11, 779, 433, 1587, 11, 719, 430, 596, 1606, 315, 19775, 52401, 570, 1102, 3727, 856, 8271, 13194, 304, 5627, 358, 4250, 282, 73555, 13, 1102, 596, 43358, 292, 627, 7184, 584, 2351, 2133, 311, 1935, 264, 4545, 369, 264, 4062, 16038, 1139, 856, 4443, 2324, 430, 690, 74614, 3063, 1203, 1139, 279, 1847, 627, 40, 1541, 956, 1440, 1148, 12374, 574, 1093, 369, 2536, 1474, 589, 10827, 56333, 11, 719, 369, 856, 469, 2152, 8547, 358, 574, 9770, 311, 1373, 323, 3821, 20181, 315, 37072, 78259, 13, 763, 71091, 320, 10590, 8474, 0, 320, 708, 40666, 595, 584, 4265, 5662, 264, 1486, 1405, 279, 14561, 1053, 10936, 311, 279, 842, 315, 279, 11311, 323, 3371, 603, 4236, 330, 40, 3358, 5387, 279, 2800, 315, 420, 11311, 439, 459, 14584, 10368, 369, 499, 4236, 3343, 3277, 499, 2351, 279, 14561, 11, 499, 1541, 956, 617, 311, 12571, 701, 892, 3815, 279, 44143, 990, 627, 4897, 574, 4062, 11, 1203, 311, 279, 1847, 512, 10445, 527, 584, 9770, 311, 2865, 279, 8209, 4817, 2403, 14207, 889, 527, 48863, 43383, 1109, 279, 2851, 596, 4717, 30, 3639, 596, 279, 1486, 315, 430, 30, 578, 1193, 892, 358, 3077, 3596, 3970, 420, 3575, 60538, 4501, 31890, 574, 994, 358, 6476, 9420, 11130, 13, 9843, 88602, 374, 40044, 810, 8147, 1109, 264, 2728, 9354, 11, 9354, 35006, 1121, 304, 459, 9888, 38612, 13, 578, 8209, 4817, 4536, 956, 6799, 323, 25836, 323, 3673, 527, 22034, 439, 8475, 13, 578, 1847, 25139, 303, 388, 264, 8209, 6832, 1121, 374, 264, 2291, 46696, 17102, 11, 14324, 499, 505, 48897, 26225, 892, 627, 15346, 77, 956, 810, 3953, 656, 420, 30, 8595, 656, 358, 617, 311, 2865, 709, 279, 8209, 4817, 311, 4686, 264, 4465, 430, 40758, 4330, 311, 5899, 6622, 30, 3639, 1587, 279, 1847, 8895, 555, 25957, 757, 311, 2503, 1555, 420, 30, 1102, 596, 539, 1093, 584, 2351, 68774, 18646, 5070, 304, 420, 1847, 320, 359, 4908, 11, 2019, 11, 264, 54990, 477, 35549, 28443, 10830, 350, 1137, 72, 1847, 1237, 279, 4553, 4717, 374, 7373, 62320, 1306, 1475, 8209, 13, 2100, 3249, 539, 30, 12838, 328, 94214, 953, 1781, 430, 422, 584, 1541, 956, 2503, 1555, 264, 4330, 2132, 8209, 1418, 17919, 364, 55, 6, 3131, 584, 690, 387, 15471, 307, 430, 279, 1847, 374, 5737, 5196, 5380, 2173, 3388, 11, 420, 3727, 1524, 2753, 5647, 994, 499, 1781, 922, 279, 1648, 279, 8209, 1887, 4375, 304, 31042, 96860, 13, 2684, 527, 1403, 5627, 430, 499, 649, 4465, 25, 9156, 12, 29702, 323, 80477, 13, 1442, 499, 3373, 9156, 11, 279, 15592, 690, 3373, 264, 4101, 315, 11545, 10819, 1109, 499, 1436, 3196, 389, 279, 6677, 433, 706, 922, 279, 9354, 499, 527, 13176, 13, 2052, 499, 617, 311, 656, 374, 743, 279, 13073, 320, 67133, 11, 59583, 11, 1283, 13412, 11, 10525, 14, 1951, 7726, 8, 323, 279, 1847, 690, 3820, 279, 1455, 74978, 3388, 315, 1957, 13, 1102, 596, 1101, 75160, 311, 1778, 264, 8547, 430, 422, 499, 2815, 11, 682, 499, 3077, 2751, 311, 656, 374, 3820, 23515, 323, 499, 527, 97132, 291, 1120, 4994, 279, 8209, 499, 1120, 5675, 13, 1102, 596, 430, 4228, 627, 19918, 27582, 96860, 6944, 779, 25587, 311, 387, 264, 1664, 16405, 2230, 5780, 11, 1093, 264, 16795, 12141, 17919, 499, 9017, 279, 5915, 11, 430, 1521, 892, 58052, 3719, 1648, 810, 38617, 13, 50417, 449, 3313, 11, 1093, 4661, 1475, 2851, 1587, 11, 449, 701, 1193, 12014, 1694, 3752, 13073, 649, 2103, 387, 19092, 323, 2523, 11, 719, 520, 264, 3738, 1486, 358, 1212, 311, 1781, 11, 330, 10445, 656, 358, 617, 311, 3373, 3313, 1475, 3254, 4883, 30, 8595, 649, 956, 358, 1120, 15349, 433, 1022, 994, 358, 1205, 311, 2349, 856, 26411, 7673, 1102, 596, 1093, 279, 1847, 17501, 757, 1475, 2543, 422, 358, 2103, 1390, 433, 311, 1514, 279, 1847, 369, 757, 627, 8161, 956, 636, 757, 5076, 1618, 11, 96860, 374, 539, 264, 3958, 1847, 1981, 269, 7344, 433, 374, 13, 19292, 31042, 96860, 374, 264, 2731, 3217, 1109, 433, 374, 264, 1847, 13, 1472, 3077, 2751, 20441, 4018, 88065, 323, 1948, 78611, 7899, 15718, 11093, 449, 264, 1847, 430, 10213, 11335, 5196, 3235, 264, 7833, 1584, 13, 35403, 10578, 1093, 264, 5818, 311, 757, 627, 28641, 11130, 11, 1620, 18884, 11, 1620, 18884, 3355, 11, 1620, 18884, 865, 35694, 11, 6800, 28483, 3313, 11, 6800, 28483, 3313, 17967, 11, 29055, 220, 18, 11, 77111, 19262, 10830, 43787, 72, 11, 9518, 665, 953, 198, 59978, 220, 18, 10506, 510, 16010, 452, 933, 33697, 19716, 27104, 11586, 12, 20381, 389, 6168, 5485, 9470, 198, 49, 10318, 811, 389, 2835, 3953, 439, 459, 1989, 1376, 1389, 420, 1436, 1633, 1664, 3719, 264, 21720, 220, 18, 3477, 13, 2684, 690, 387, 66427, 1618, 13, 57606, 11, 1541, 956, 1373, 433, 422, 499, 1390, 311, 1514, 21720, 220, 18, 323, 539, 617, 279, 7234, 72524, 627, 3947, 596, 264, 490, 635, 12593, 430, 49002, 2212, 279, 7757, 4661, 1475, 2305, 430, 2744, 5334, 856, 6548, 20700, 13, 763, 5230, 35768, 11, 4423, 690, 1650, 1778, 9976, 1355, 1412, 279, 47317, 46656, 315, 2835, 3953, 477, 2610, 1148, 279, 47317, 46656, 374, 477, 3802, 430, 279, 11298, 374, 86525, 1606, 584, 3077, 3686, 311, 4295, 1057, 47317, 46656, 13, 1102, 596, 79953, 323, 11, 5115, 42762, 11, 85627, 323, 18754, 13, 2057, 3240, 449, 11, 47317, 46656, 9107, 449, 1695, 8544, 323, 574, 8965, 1664, 5621, 8946, 11, 719, 433, 3287, 956, 1212, 311, 8895, 539, 13915, 2676, 369, 5899, 1667, 13, 1102, 3287, 956, 1524, 1304, 674, 16, 389, 264, 1948, 9698, 1160, 3156, 17510, 1667, 1047, 5946, 13, 3277, 279, 47317, 46656, 315, 16211, 13280, 320, 40811, 358, 12491, 430, 17571, 705, 584, 4762, 2834, 956, 1440, 433, 369, 5115, 1063, 892, 13, 578, 810, 3062, 1486, 374, 430, 9698, 323, 3953, 527, 41776, 323, 85138, 627, 791, 1938, 430, 584, 3009, 40876, 922, 3508, 6603, 477, 9698, 527, 2731, 1109, 3953, 520, 37810, 264, 4040, 10255, 596, 1486, 315, 1684, 374, 4762, 279, 1938, 430, 584, 3358, 13383, 430, 584, 3077, 2736, 2751, 7060, 10507, 315, 3953, 430, 527, 63851, 315, 3229, 532, 2585, 2736, 13, 3320, 29758, 278, 28033, 574, 539, 264, 2294, 1847, 11, 719, 9538, 92818, 809, 596, 6206, 527, 9539, 30576, 682, 927, 433, 13, 33634, 889, 596, 3596, 6476, 832, 315, 435, 372, 6491, 549, 14151, 596, 3953, 8964, 24559, 1268, 264, 1847, 649, 13750, 387, 1511, 311, 4546, 704, 701, 21958, 1555, 4382, 30126, 13, 6122, 41652, 328, 8213, 320, 12173, 32, 328, 8213, 220, 3971, 8, 706, 1027, 3339, 3953, 430, 1501, 2867, 11, 32692, 5216, 1555, 813, 1005, 315, 33288, 18210, 323, 53990, 31882, 37864, 31794, 369, 1667, 13, 3092, 1486, 374, 11, 584, 3077, 1027, 1618, 369, 264, 1418, 627, 2675, 1253, 617, 6755, 315, 1443, 52763, 4428, 358, 53709, 11, 719, 17393, 527, 11, 499, 617, 912, 31089, 430, 568, 596, 832, 315, 279, 1455, 11495, 323, 31387, 3026, 304, 6457, 311, 1778, 264, 8547, 430, 813, 5679, 574, 4762, 279, 1455, 66352, 10065, 304, 279, 4553, 3224, 369, 264, 2478, 1667, 13, 763, 5270, 11, 584, 1440, 1461, 439, 264, 2835, 1847, 15034, 11, 11951, 279, 893, 4920, 9420, 11130, 11, 719, 539, 1790, 775, 13, 58603, 3403, 11, 358, 53709, 374, 3604, 810, 11495, 369, 1694, 459, 9071, 380, 11, 87935, 11, 323, 52637, 14143, 1109, 813, 990, 369, 23643, 13, 5414, 15360, 449, 18276, 3524, 67559, 1394, 14966, 374, 1664, 3967, 3403, 430, 568, 596, 11495, 369, 279, 735, 7723, 596, 27303, 5475, 52637, 3573, 46, 331, 1609, 2159, 2850, 4647, 559, 6388, 597, 66981, 11, 30125, 31478, 10667, 4173, 6780, 951, 84, 1, 2001, 330, 40, 574, 264, 2697, 42642, 369, 264, 2766, 26, 358, 2846, 17339, 1457, 909, 323, 568, 1524, 52468, 92033, 596, 7126, 304, 3092, 98263, 350, 10088, 78, 320, 64, 3560, 430, 4024, 311, 7302, 23750, 1543, 320, 4014, 304, 9096, 8, 994, 279, 5818, 574, 42160, 304, 6498, 4390, 644, 813, 14992, 2919, 11, 358, 53709, 1766, 5678, 14363, 323, 12153, 311, 656, 1790, 719, 1514, 23643, 439, 568, 26403, 13, 1102, 574, 304, 420, 1614, 430, 568, 11352, 16537, 15403, 11, 902, 743, 279, 23529, 13353, 304, 813, 2010, 13, 1115, 3217, 574, 279, 3242, 64476, 4920, 279, 21720, 4101, 323, 6197, 311, 358, 53709, 596, 1317, 11, 89684, 5133, 449, 23643, 13, 763, 1162, 499, 1051, 20910, 320, 4490, 575, 25, 499, 4762, 15058, 956, 705, 1443, 52763, 4428, 358, 53709, 374, 279, 7564, 889, 3782, 709, 449, 279, 836, 369, 279, 4140, 16576, 13, 3082, 2144, 627, 2181, 596, 539, 15206, 311, 757, 430, 1455, 315, 279, 5144, 358, 3077, 9932, 1051, 539, 2744, 2835, 1847, 26897, 13, 578, 1455, 33288, 315, 279, 15860, 11, 328, 8213, 11, 574, 459, 19165, 4506, 1603, 568, 6818, 813, 15369, 304, 279, 2835, 1847, 5064, 1418, 549, 14151, 574, 459, 10255, 323, 279, 46752, 358, 53709, 574, 264, 1981, 9336, 1070, 596, 912, 4228, 3492, 311, 7664, 4423, 1093, 358, 53709, 13, 1283, 574, 320, 438, 374, 8, 264, 13042, 17743, 627, 27806, 499, 26612, 325, 6261, 2288, 3254, 34423, 398, 304, 701, 12146, 1989, 1376, 11, 3508, 433, 596, 2835, 3953, 11, 9698, 11, 29159, 477, 8996, 1359, 568, 9731, 11, 330, 22479, 990, 649, 6847, 3719, 1120, 264, 22599, 315, 1148, 3885, 527, 3815, 304, 430, 2115, 11, 4856, 1109, 15061, 502, 5015, 10246, 4235, 71524, 2206, 86677, 198, 7184, 11, 92818, 809, 374, 11, 5678, 11, 264, 2027, 315, 279, 5064, 11, 3515, 5762, 912, 1023, 7032, 11, 719, 568, 596, 279, 4788, 11, 264, 837, 11782, 4059, 430, 374, 539, 99052, 555, 813, 11302, 6471, 315, 59714, 13, 58937, 10951, 11, 6187, 315, 279, 67680, 8061, 11, 17680, 37164, 82, 11, 323, 3320, 29758, 278, 28033, 1436, 539, 387, 810, 2204, 505, 1855, 1023, 11, 719, 1120, 1781, 315, 1268, 9024, 420, 374, 13, 1789, 1475, 92818, 809, 477, 14594, 81702, 704, 1070, 4560, 311, 4546, 502, 34453, 1139, 279, 5064, 11, 1070, 527, 20181, 315, 7834, 15317, 12, 323, 10425, 315, 279, 47380, 53161, 3953, 9124, 1855, 1060, 2160, 6285, 389, 279, 1890, 11, 19781, 7493, 1847, 304, 323, 1847, 704, 13, 2650, 1690, 4435, 5111, 8105, 3953, 656, 584, 2216, 1205, 5380, 644, 220, 3753, 24, 1443, 52763, 4428, 358, 53709, 7111, 520, 279, 2835, 1847, 5064, 323, 1071, 330, 4438, 1690, 20827, 323, 25551, 22228, 34602, 82, 656, 584, 2216, 1205, 7673, 220, 1049, 24, 1120, 5946, 603, 555, 323, 358, 4265, 2019, 584, 2351, 2103, 10213, 296, 2757, 304, 1521, 42108, 53397, 304, 220, 2721, 4, 315, 682, 34602, 82, 13, 21720, 11, 358, 53709, 596, 41317, 4879, 520, 264, 2835, 1847, 11, 574, 743, 304, 330, 50889, 1938, 1, 5270, 13, 9420, 11130, 320, 59978, 220, 17, 8, 5828, 956, 7041, 15061, 449, 358, 53709, 596, 7617, 555, 1694, 743, 304, 5270, 3686, 1578, 320, 258, 220, 2550, 19, 705, 719, 433, 596, 2103, 264, 3177, 4315, 279, 10167, 24639, 430, 47274, 14589, 279, 5064, 13, 21720, 220, 18, 374, 55861, 922, 1202, 25845, 11, 719, 433, 11321, 1093, 264, 31790, 1203, 6617, 1938, 13, 763, 904, 1162, 11, 1093, 304, 279, 1023, 3953, 315, 279, 4101, 11, 279, 10094, 7784, 956, 53157, 323, 82565, 11, 719, 34240, 11, 30596, 12303, 437, 11, 323, 20075, 43308, 13, 1102, 596, 2216, 1193, 264, 46552, 323, 8941, 278, 6541, 11, 719, 433, 3727, 682, 279, 6811, 627, 4897, 596, 7041, 1148, 3727, 1443, 52763, 4428, 358, 53709, 779, 2294, 439, 264, 1847, 15034, 13, 19292, 433, 596, 813, 4994, 2704, 477, 7344, 433, 596, 1120, 813, 83580, 11, 719, 358, 53709, 31869, 2835, 3953, 311, 264, 29565, 8547, 369, 264, 893, 889, 1193, 19165, 1982, 1124, 389, 264, 74571, 13, 358, 52490, 1461, 1455, 369, 8830, 430, 264, 1847, 374, 459, 21416, 6710, 315, 1989, 323, 42852, 430, 449, 813, 6067, 13, 2057, 38467, 11, 1475, 21720, 1847, 79476, 2212, 4731, 13, 578, 1176, 1847, 1047, 279, 3752, 15389, 369, 279, 36944, 11220, 10233, 1418, 279, 2132, 11763, 430, 4623, 449, 36944, 59102, 84, 5548, 320, 9739, 449, 264, 18273, 7057, 5938, 449, 433, 570, 9420, 11130, 596, 7754, 11630, 320, 258, 11002, 8, 13282, 264, 2697, 5609, 430, 358, 53709, 6267, 369, 279, 2851, 311, 7936, 439, 279, 1925, 62684, 6476, 389, 279, 927, 14957, 13, 7357, 1584, 315, 1495, 304, 279, 21720, 4101, 374, 5439, 304, 597, 3444, 320, 74, 69828, 3444, 477, 305, 404, 351, 3444, 705, 779, 430, 279, 1732, 706, 311, 26480, 553, 358, 53709, 596, 3629, 86337, 950, 4477, 1742, 13, 21720, 220, 18, 596, 5357, 389, 18273, 22100, 323, 514, 333, 47928, 22589, 320, 1527, 279, 20519, 291, 2418, 311, 279, 7023, 76299, 552, 8, 374, 1101, 46728, 1555, 1475, 3752, 596, 8951, 304, 279, 8209, 1887, 627, 3915, 32103, 311, 328, 42926, 279, 58937, 11, 1475, 3752, 706, 264, 18273, 14473, 5938, 449, 813, 8951, 13, 2100, 1587, 1475, 9354, 13, 9062, 9354, 1101, 706, 264, 18273, 7057, 430, 11335, 304, 279, 4092, 13, 9843, 499, 3440, 11, 499, 649, 3136, 311, 3577, 279, 364, 32, 6, 3215, 311, 13334, 701, 23569, 311, 220, 845, 13280, 422, 499, 649, 2567, 892, 449, 279, 320, 57753, 9314, 408, 65923, 5107, 8, 9567, 13, 4702, 1093, 430, 11, 2555, 358, 53709, 706, 2744, 4934, 279, 2851, 311, 656, 320, 17106, 638, 3167, 2740, 6532, 449, 813, 1917, 8, 9221, 18751, 1139, 279, 5820, 279, 2851, 1587, 1455, 304, 279, 1847, 11, 47336, 627, 40, 53709, 1101, 16180, 311, 22068, 449, 2851, 21063, 311, 264, 41367, 8547, 13, 763, 459, 4216, 8668, 304, 279, 1176, 12735, 315, 279, 1847, 11, 53936, 9221, 9960, 449, 779, 354, 1306, 14324, 264, 4333, 596, 10585, 505, 264, 4027, 13, 8595, 30, 9393, 430, 596, 1148, 1053, 3621, 422, 499, 1051, 4401, 2212, 304, 264, 4027, 13, 1666, 568, 3727, 813, 1648, 1203, 704, 315, 279, 33633, 11, 499, 649, 1297, 430, 1475, 1732, 499, 3137, 311, 690, 3488, 3249, 499, 527, 9960, 505, 2010, 311, 31316, 304, 3776, 779, 354, 13, 7570, 2731, 11, 422, 499, 7598, 1139, 264, 4106, 10683, 311, 11993, 11, 279, 779, 354, 690, 11623, 1022, 315, 701, 3752, 505, 279, 13272, 1523, 11, 2533, 279, 21720, 220, 18, 4106, 10683, 10571, 2744, 11141, 279, 2010, 15246, 13, 1102, 596, 539, 3156, 1790, 3010, 994, 433, 8638, 311, 11422, 430, 279, 779, 354, 11623, 288, 1022, 53936, 596, 3663, 11, 420, 892, 311, 47032, 430, 584, 2351, 539, 58134, 2212, 14926, 11, 53936, 596, 3070, 574, 2103, 7554, 1306, 279, 4027, 323, 814, 1051, 4661, 7995, 304, 8137, 627, 2127, 1524, 810, 20333, 8668, 4131, 1790, 3010, 304, 279, 1847, 994, 279, 2851, 374, 38593, 5304, 264, 35148, 13218, 449, 220, 16, 12478, 323, 912, 7241, 13, 578, 1193, 1648, 311, 5208, 1555, 279, 45520, 2085, 23069, 374, 311, 8343, 832, 315, 279, 8841, 79432, 48251, 7982, 389, 279, 13218, 13, 362, 33288, 8668, 315, 4455, 11263, 439, 499, 1304, 701, 1648, 311, 279, 1828, 7023, 89367, 449, 701, 51866, 6724, 21830, 439, 8154, 13, 3402, 53310, 315, 701, 3070, 323, 4885, 3440, 499, 11, 902, 4536, 956, 430, 5016, 369, 459, 34602, 11, 719, 279, 1648, 279, 19775, 374, 10666, 323, 279, 54077, 527, 87312, 11, 433, 9221, 14243, 92080, 13, 578, 832, 4545, 315, 19858, 4131, 994, 499, 17782, 520, 2500, 4106, 10683, 323, 11993, 11, 1193, 311, 3136, 1203, 1139, 279, 70618, 315, 279, 45520, 627, 12805, 499, 636, 311, 279, 7023, 89367, 596, 3838, 11, 499, 2351, 15320, 13054, 21632, 449, 68989, 922, 1268, 3958, 499, 22843, 13, 1102, 3727, 912, 5647, 3582, 11, 1606, 279, 2851, 706, 2884, 4400, 2204, 430, 1053, 5353, 1778, 264, 40884, 22843, 13, 16782, 11, 994, 701, 21063, 374, 6052, 311, 4725, 11, 1070, 374, 264, 9621, 357, 20345, 16448, 505, 32103, 323, 813, 1391, 2416, 2469, 13, 362, 4062, 24522, 304, 279, 9061, 11263, 323, 499, 2351, 912, 5129, 330, 3647, 12160, 498, 719, 11, 439, 264, 22999, 2851, 11, 358, 31156, 1148, 1047, 7077, 304, 279, 1176, 2035, 13, 12361, 315, 14691, 4741, 11, 358, 48322, 1314, 1203, 1139, 279, 45520, 311, 636, 311, 279, 5740, 315, 433, 13, 42436, 1555, 11, 358, 574, 8430, 264, 2766, 8834, 343, 3340, 11, 779, 358, 43333, 389, 927, 311, 279, 4106, 42242, 323, 433, 682, 1903, 5647, 13, 763, 856, 59123, 258, 29569, 1614, 11, 358, 574, 12153, 311, 15641, 430, 279, 36670, 358, 48322, 1139, 369, 13654, 574, 264, 19390, 4776, 11, 21503, 31348, 26964, 10488, 315, 264, 36670, 13, 4206, 311, 279, 3185, 11, 1405, 912, 95883, 2851, 1053, 3596, 733, 11, 574, 264, 6134, 1139, 279, 1972, 4106, 10683, 627, 40, 7846, 956, 4510, 430, 1063, 4311, 1053, 2646, 1505, 704, 279, 23347, 4920, 3249, 814, 1051, 779, 1554, 12160, 13, 74347, 311, 430, 4106, 10683, 374, 20781, 23911, 13, 10926, 430, 596, 3249, 433, 6612, 779, 8056, 311, 1518, 1521, 2697, 19775, 3953, 6476, 449, 856, 21063, 315, 1148, 574, 2133, 389, 304, 279, 21720, 220, 18, 1917, 520, 279, 892, 13, 1102, 596, 1101, 7185, 311, 1427, 520, 505, 264, 2851, 7095, 13356, 11, 1606, 994, 358, 5602, 430, 54766, 36670, 11, 23188, 304, 682, 1202, 480, 7209, 11, 3428, 37731, 27025, 11, 358, 6612, 49394, 788, 323, 358, 1440, 433, 574, 28135, 4245, 311, 264, 8430, 315, 68376, 13, 358, 617, 264, 8430, 430, 420, 574, 7041, 1268, 358, 53709, 4934, 757, 311, 2733, 520, 430, 1486, 627, 2059, 52763, 4428, 358, 53709, 38239, 430, 279, 4113, 10165, 369, 21720, 220, 18, 574, 1648, 40130, 1109, 433, 2736, 374, 13, 1102, 574, 5439, 20193, 1306, 813, 25549, 574, 61487, 11, 902, 358, 1781, 706, 264, 2763, 311, 656, 449, 279, 14604, 34568, 1147, 315, 1524, 279, 61487, 2373, 315, 420, 1847, 13, 4452, 420, 1847, 574, 1633, 7154, 38752, 1698, 430, 574, 2646, 6004, 13, 11699, 4500, 3940, 369, 279, 18407, 1600, 304, 220, 2550, 19, 11, 719, 574, 6288, 30073, 311, 279, 452, 1227, 323, 279, 5986, 2269, 660, 220, 1227, 4195, 539, 1317, 1306, 13, 33634, 11537, 449, 279, 220, 1227, 4195, 35688, 8964, 430, 420, 574, 2133, 311, 12391, 78518, 369, 358, 53709, 323, 813, 2128, 13, 578, 1847, 574, 1524, 34546, 520, 832, 1486, 11, 719, 433, 574, 9778, 6773, 311, 2231, 433, 389, 279, 4140, 17627, 47396, 323, 7376, 2212, 279, 312, 45824, 315, 21720, 220, 16, 489, 220, 17, 11, 912, 10712, 311, 1520, 24074, 709, 6763, 627, 2822, 832, 719, 279, 2128, 8964, 1120, 1268, 6453, 279, 4113, 19775, 574, 11, 719, 358, 53709, 8349, 430, 279, 3446, 430, 9778, 1903, 433, 311, 1194, 574, 279, 1121, 315, 1461, 5616, 10671, 264, 1695, 1732, 13, 1102, 293, 51952, 279, 4059, 311, 13383, 430, 433, 1436, 617, 1027, 904, 810, 22520, 11, 5423, 369, 264, 1847, 430, 5992, 439, 11919, 323, 19369, 439, 420, 832, 13, 763, 2144, 11, 420, 374, 279, 2944, 3249, 23643, 315, 5270, 8349, 433, 690, 539, 95516, 279, 1847, 13, 2435, 3802, 279, 19775, 374, 2288, 15196, 323, 71810, 369, 279, 1648, 433, 5992, 323, 11, 2216, 11, 279, 16630, 323, 279, 3917, 5030, 527, 69487, 40815, 323, 4648, 398, 6129, 11, 779, 358, 3169, 315, 636, 1148, 814, 3152, 13, 2468, 832, 1486, 499, 617, 264, 7564, 11890, 53936, 430, 568, 596, 2751, 1695, 3754, 323, 3958, 3754, 13, 578, 1695, 3754, 374, 2555, 40815, 323, 18754, 1418, 279, 3958, 3754, 374, 430, 53936, 596, 7555, 11, 50733, 14406, 11, 374, 5710, 13, 3639, 11263, 374, 264, 6237, 430, 374, 779, 38683, 81291, 430, 856, 2697, 10868, 574, 11754, 1524, 2085, 11011, 279, 4731, 323, 5222, 5938, 449, 279, 6237, 13, 53936, 6724, 86286, 704, 323, 8638, 27242, 389, 279, 7564, 889, 6688, 1461, 3958, 3754, 323, 1524, 8638, 326, 19587, 704, 520, 279, 25861, 16455, 889, 527, 4560, 311, 19858, 1461, 1523, 13, 1283, 374, 33085, 704, 555, 264, 4333, 323, 2231, 304, 264, 17999, 2849, 430, 706, 2646, 1603, 1027, 1511, 304, 279, 6424, 596, 14209, 627, 2181, 596, 420, 16682, 98953, 2161, 315, 279, 304, 2194, 323, 279, 4648, 398, 6129, 430, 11705, 279, 834, 942, 519, 16024, 358, 9932, 1603, 449, 279, 4106, 15286, 6237, 323, 3727, 279, 2851, 2733, 83372, 922, 1148, 596, 2133, 389, 13, 3277, 50733, 14406, 596, 7126, 11, 86116, 11, 374, 4560, 311, 3371, 18754, 32520, 311, 1520, 53936, 539, 387, 779, 43787, 922, 279, 3738, 8137, 813, 4538, 374, 304, 13, 358, 4934, 311, 3371, 1461, 311, 9495, 709, 323, 1095, 1461, 5357, 11, 719, 358, 1436, 1101, 1518, 430, 53936, 574, 56359, 287, 311, 264, 11660, 8547, 323, 430, 86116, 574, 1314, 304, 4560, 311, 19858, 1461, 1523, 13, 1472, 1101, 617, 279, 326, 1108, 1820, 472, 291, 3021, 3446, 315, 328, 42926, 323, 328, 43008, 1694, 47168, 555, 279, 28860, 323, 12703, 4633, 16831, 7889, 94636, 31529, 320, 37, 395, 329, 304, 279, 8571, 12, 3129, 570, 1102, 596, 1093, 358, 53709, 374, 4560, 311, 2019, 430, 279, 1917, 374, 264, 57445, 709, 2035, 11, 719, 499, 649, 956, 1095, 433, 636, 499, 1523, 627, 40, 3358, 3371, 499, 1314, 1618, 11, 358, 2846, 264, 6908, 94888, 369, 904, 3446, 922, 20820, 13, 25929, 389, 304, 279, 1847, 11, 433, 9221, 14470, 8196, 430, 21720, 220, 18, 8638, 311, 4219, 2212, 279, 14993, 315, 28497, 20820, 32103, 323, 68119, 439, 814, 4879, 311, 6667, 810, 7234, 36398, 1109, 279, 1023, 13, 578, 1847, 4101, 374, 2663, 21720, 369, 264, 2944, 323, 420, 832, 304, 4040, 24400, 389, 279, 12062, 1990, 1855, 315, 50733, 14406, 596, 13305, 323, 1268, 814, 3782, 311, 3568, 449, 1077, 13365, 318, 989, 4648, 13, 6104, 32103, 4131, 704, 315, 813, 12811, 323, 9221, 264, 39345, 11, 810, 2105, 535, 323, 16913, 8334, 8994, 813, 94190, 7126, 11, 68119, 46337, 398, 95322, 704, 369, 72788, 323, 14035, 5678, 95389, 555, 279, 49654, 13309, 304, 1202, 2271, 311, 842, 279, 1917, 13, 578, 11323, 24045, 1620, 8209, 35740, 3695, 279, 3070, 3131, 1578, 11, 719, 279, 58384, 374, 293, 29163, 4589, 13, 68119, 706, 4661, 7577, 53936, 323, 32103, 2011, 3663, 1461, 7636, 311, 279, 4648, 11, 1524, 3582, 568, 596, 3686, 311, 13383, 430, 279, 20519, 291, 2418, 374, 813, 10868, 13, 9843, 279, 7056, 374, 33085, 1022, 323, 32103, 374, 37874, 1139, 813, 1866, 3663, 320, 20670, 527, 44736, 1306, 682, 705, 279, 8209, 9221, 264, 59831, 13, 8593, 287, 3440, 690, 5353, 32103, 311, 37304, 6958, 813, 61851, 477, 3194, 813, 8951, 6724, 13, 18156, 568, 3358, 1524, 26122, 311, 26069, 13, 68119, 11, 3515, 5675, 1455, 315, 813, 22706, 11, 690, 3136, 311, 3440, 3156, 50733, 14406, 12302, 74073, 369, 1461, 311, 3009, 13, 38274, 11, 68119, 4131, 311, 813, 38207, 323, 52694, 430, 32103, 374, 813, 10868, 323, 430, 568, 374, 912, 5129, 4205, 3345, 311, 5678, 13, 2468, 430, 1486, 11, 68119, 42635, 18639, 304, 264, 44797, 1648, 13, 1102, 9221, 10186, 430, 279, 99630, 60183, 430, 53936, 6688, 311, 32103, 320, 20708, 264, 4491, 13, 50253, 304, 2500, 3187, 315, 94190, 49058, 8, 374, 3604, 264, 19372, 60183, 11, 459, 1537, 430, 2109, 2053, 33538, 304, 279, 21720, 1917, 627, 791, 81206, 3245, 922, 420, 4459, 8668, 374, 430, 1070, 596, 4400, 279, 2851, 649, 656, 3131, 68119, 28727, 430, 568, 2011, 5622, 5678, 311, 3665, 279, 1917, 13, 32103, 1253, 539, 387, 22655, 320, 269, 8841, 2740, 8, 13419, 813, 10868, 11, 719, 1070, 596, 4400, 568, 649, 656, 719, 3821, 813, 10868, 5622, 5678, 1701, 459, 1537, 430, 568, 374, 10168, 13, 3277, 433, 596, 682, 927, 323, 68119, 374, 23069, 304, 32103, 6, 11977, 449, 53936, 14373, 323, 50733, 14406, 596, 20457, 3485, 1124, 11, 279, 58384, 374, 5616, 8308, 323, 279, 3070, 374, 6380, 369, 264, 10015, 2132, 1603, 2225, 68119, 323, 50733, 14406, 11776, 279, 1917, 9564, 32103, 311, 6958, 279, 1566, 7234, 24759, 13, 578, 1917, 16280, 10548, 323, 433, 682, 87509, 311, 3776, 13, 22172, 320, 14965, 574, 13989, 1603, 8, 374, 2103, 13989, 304, 279, 37398, 11, 719, 279, 1917, 374, 27394, 323, 433, 596, 539, 1903, 2867, 1148, 279, 837, 15632, 315, 279, 4459, 8209, 574, 13, 1226, 656, 1440, 430, 279, 1917, 374, 6220, 323, 5127, 3727, 433, 11, 719, 539, 1790, 775, 7953, 430, 11, 433, 596, 2163, 311, 279, 2851, 311, 10491, 11, 358, 8101, 627, 2746, 499, 1390, 311, 2216, 1518, 264, 70706, 35279, 11, 62724, 13696, 369, 264, 3752, 11, 2980, 279, 25382, 315, 85034, 88, 11, 279, 82159, 304, 279, 1847, 13, 578, 12324, 304, 420, 1847, 374, 27762, 555, 813, 12876, 311, 1518, 279, 1917, 842, 13, 85034, 88, 596, 4059, 574, 779, 87312, 555, 15754, 88, 40625, 304, 9420, 11130, 430, 568, 706, 14958, 304, 264, 15690, 86525, 11, 1716, 4908, 1614, 1524, 3582, 568, 374, 1457, 11758, 315, 1667, 2362, 13, 5414, 10383, 22681, 82, 323, 7154, 60832, 4395, 922, 279, 887, 4010, 416, 323, 26733, 350, 1394, 76, 1570, 14458, 323, 568, 374, 279, 832, 8647, 369, 274, 3713, 68119, 315, 682, 315, 813, 22706, 13, 763, 813, 1620, 13123, 449, 32103, 11, 994, 433, 9221, 10186, 430, 568, 690, 539, 3243, 279, 8209, 11, 568, 3289, 2315, 5678, 304, 279, 56647, 23088, 13257, 11, 264, 48739, 430, 45382, 1461, 11112, 6220, 505, 682, 8951, 2225, 15135, 323, 28362, 13, 9393, 433, 574, 1120, 264, 25018, 11, 1070, 574, 912, 1648, 311, 12731, 433, 11, 7438, 430, 279, 4325, 1752, 85034, 88, 649, 2646, 2815, 11, 719, 568, 649, 2646, 5387, 279, 48739, 6463, 649, 568, 19570, 449, 5606, 389, 279, 4994, 13, 1789, 4423, 1093, 85034, 88, 11, 459, 8479, 315, 48602, 1093, 279, 61377, 304, 578, 12538, 23844, 11, 420, 374, 9615, 459, 13696, 11201, 1109, 4648, 13, 3277, 682, 374, 5710, 323, 8208, 11, 994, 279, 15861, 8898, 315, 8798, 4648, 11, 994, 14209, 374, 4400, 2136, 11, 85034, 88, 690, 2103, 3073, 11, 7636, 304, 430, 48739, 13, 1102, 6835, 757, 523, 3385, 1120, 311, 1781, 922, 433, 627, 3947, 596, 779, 1790, 922, 420, 1847, 430, 1120, 3250, 956, 5115, 923, 709, 323, 11141, 279, 2851, 8430, 15234, 922, 279, 12135, 814, 527, 9298, 13, 423, 5100, 11, 279, 4671, 10194, 58835, 11, 374, 1633, 9539, 85207, 323, 4762, 22655, 36665, 555, 813, 7126, 11, 468, 434, 11, 3686, 814, 2873, 311, 387, 264, 2128, 323, 1070, 1587, 2873, 311, 387, 1063, 3021, 1070, 13, 1102, 596, 92080, 389, 682, 5990, 1606, 358, 53709, 6944, 311, 1935, 279, 2851, 505, 10882, 323, 6380, 311, 83372, 323, 12703, 6957, 279, 4459, 1847, 627, 36907, 1093, 420, 11, 814, 1304, 757, 15763, 2574, 11, 1093, 856, 3070, 323, 856, 2324, 11, 323, 1781, 922, 2574, 11, 1093, 279, 7138, 315, 8396, 323, 23871, 13, 358, 2846, 1694, 78630, 1618, 11, 719, 856, 1486, 374, 420, 11, 1148, 374, 1989, 30, 27685, 6880, 433, 11, 330, 1981, 1820, 1920, 477, 2027, 315, 36192, 77218, 5540, 304, 264, 1648, 430, 35730, 311, 279, 38207, 477, 21958, 10246, 4516, 358, 2019, 3686, 1578, 11, 3249, 527, 584, 34685, 3508, 477, 539, 2835, 3953, 527, 1989, 30, 41674, 709, 323, 22843, 279, 7160, 89770, 627, 16010, 452, 198, 16548, 308, 11, 1437, 29758, 278, 13314, 11, 22618, 597, 2194, 11, 26161, 2271, 11, 9578, 11130, 11, 282, 372, 6491, 577, 14151, 11, 1847, 8334, 11, 342, 4749, 11, 733, 41652, 274, 8213, 11, 18137, 3524, 9686, 88, 1394, 14966, 11, 10864, 8869, 924, 89, 22227, 11, 50332, 23464, 483, 11, 597, 7723, 596, 9889, 2532, 11, 38031, 315, 279, 25562, 11, 893, 18029, 52528, 25, 1938, 315, 279, 16006, 8061, 11, 6691, 11, 6691, 220, 16, 489, 220, 17, 11, 6691, 220, 18, 11, 856, 9760, 2458, 18812, 11, 308, 1227, 11, 10891, 75028, 1543, 11, 8841, 37164, 82, 11, 559, 52763, 4428, 433, 6870, 11, 4224, 288, 11, 6917, 25981, 11, 279, 6453, 47709, 11, 279, 6367, 315, 39803, 13218, 11, 6935, 938, 10863, 11, 6935, 5817, 64, 809, 11, 59318, 198, 3923, 9479, 30, 7290, 311, 44716, 510, 15881, 933, 29185, 220, 605, 339, 11, 220, 1049, 24, 555, 11824, 198, 19182, 29947, 13016, 345, 40, 1205, 701, 1520, 304, 30230, 1148, 1847, 311, 1514, 1828, 13, 358, 9167, 956, 5115, 17454, 856, 31744, 3241, 1523, 11, 779, 1618, 596, 264, 308, 39724, 23711, 7230, 4619, 627, 23956, 1847, 1288, 358, 1514, 1828, 14775, 48554, 3241, 340, 71903, 11, 358, 1390, 311, 3136, 311, 3350, 51091, 922, 3953, 430, 358, 2846, 5737, 11, 719, 358, 1541, 956, 1440, 902, 832, 311, 3351, 389, 311, 1828, 13, 362, 2697, 922, 1855, 315, 279, 11709, 512, 44924, 11130, 320, 59978, 220, 17, 340, 32, 14964, 11, 16537, 15403, 53161, 34602, 4101, 555, 1443, 52763, 4428, 358, 53709, 11, 9420, 11130, 374, 14964, 11, 68232, 11, 323, 7185, 13, 358, 6476, 420, 1203, 994, 358, 574, 304, 6278, 2978, 11, 719, 358, 1781, 433, 30675, 312, 42716, 5859, 13, 67801, 358, 1053, 387, 9903, 287, 709, 856, 18407, 1600, 11, 902, 358, 2103, 617, 11, 311, 636, 420, 311, 990, 11, 779, 430, 1053, 387, 459, 18427, 304, 323, 315, 5196, 627, 37559, 1609, 55836, 36332, 56042, 285, 198, 40, 3077, 2646, 6476, 904, 315, 24277, 10830, 596, 17360, 1609, 55836, 34602, 4101, 11, 719, 420, 21223, 342, 3864, 268, 10827, 3446, 374, 1071, 311, 617, 264, 5128, 29585, 19775, 627, 65715, 750, 64895, 555, 7154, 1475, 3823, 1694, 889, 706, 6476, 433, 11, 420, 1847, 374, 5762, 304, 1778, 1579, 5363, 430, 433, 574, 15109, 304, 81971, 6193, 2206, 1606, 1202, 22100, 315, 4814, 323, 23023, 3604, 23828, 4591, 449, 1884, 315, 279, 5818, 13, 358, 649, 1193, 733, 389, 2085, 5737, 264, 1847, 555, 549, 14151, 369, 779, 1790, 5129, 627, 59978, 220, 18, 198, 39, 789, 304, 2307, 28661, 5363, 555, 279, 13452, 315, 9538, 34467, 11, 4315, 1690, 3885, 11, 279, 4948, 315, 279, 21720, 4101, 374, 523, 1197, 2539, 315, 279, 1890, 3177, 25912, 424, 768, 315, 21720, 220, 17, 11, 719, 34356, 449, 264, 1794, 655, 11, 5655, 11, 6453, 11, 8987, 3446, 430, 374, 2771, 311, 82715, 520, 279, 4851, 19107, 627, 68853, 78, 31391, 21223, 198, 791, 21223, 59155, 315, 856, 7075, 220, 845, 15615, 1847, 11, 499, 649, 956, 2216, 733, 5076, 449, 19084, 13, 80110, 555, 264, 8063, 2128, 20632, 1990, 15992, 323, 2998, 953, 1603, 814, 1051, 15992, 2998, 953, 320, 50, 94214, 953, 49743, 26560, 78, 31391, 574, 279, 2064, 276, 5609, 315, 279, 220, 845, 15615, 53666, 11637, 627, 19918, 27582, 17244, 21223, 198, 791, 13321, 27582, 6832, 4984, 7214, 53580, 320, 258, 279, 2326, 8, 856, 7075, 304, 279, 4101, 11, 31042, 3166, 706, 658, 38477, 9954, 505, 757, 389, 5361, 48104, 13, 362, 7060, 1847, 430, 358, 1120, 9167, 956, 1047, 279, 892, 311, 3596, 6381, 627, 3947, 596, 1101, 279, 8196, 5873, 430, 499, 1541, 956, 1093, 420, 4668, 11, 902, 358, 2834, 956, 1935, 16102, 13, 1442, 912, 832, 13452, 433, 11, 3249, 656, 433, 11, 1314, 5380, 2028, 7230, 690, 7293, 1825, 3156, 220, 931, 15, 220, 975, 5887, 1405, 59723, 358, 690, 3060, 15376, 433, 1523, 4726, 477, 11, 422, 832, 15160, 40228, 11, 5042, 1514, 430, 1847, 1828, 627, 2675, 649, 636, 1063, 315, 1521, 3953, 520, 856, 8339, 264, 6221, 4999, 26852, 8346, 11729, 11, 9578, 11130, 11, 1620, 18884, 17967, 11, 282, 372, 6491, 577, 14151, 11, 16947, 10830, 11, 6691, 220, 17, 11, 6691, 220, 18, 11, 31402, 927, 757, 11, 12737, 315, 279, 1400, 3746, 355, 11, 559, 52763, 4428, 433, 6870, 11, 4224, 288, 11, 9518, 665, 953, 11, 924, 1609, 55836, 27087, 56042, 285, 11, 6935, 938, 10863, 198, 4973, 35907, 25, 220, 845, 7826, 275, 46046, 35681, 1725, 3744, 220, 17, 25, 34602, 14398, 198, 36690, 220, 605, 339, 11, 220, 1049, 23, 555, 11824, 198, 3792, 389, 7884, 584, 3952, 264, 1427, 520, 1403, 9250, 3953, 430, 3287, 956, 5115, 1304, 279, 4018, 13, 11450, 11, 584, 21635, 2500, 2380, 11, 682, 315, 1124, 279, 33689, 220, 845, 15615, 34602, 82, 627, 2675, 1440, 279, 31646, 555, 1457, 922, 279, 330, 2620, 315, 43044, 1, 323, 1148, 1962, 11, 779, 1095, 596, 1120, 636, 1523, 311, 279, 31089, 323, 1847, 512, 2028, 1176, 1847, 358, 1390, 311, 21635, 35308, 704, 520, 499, 505, 279, 1917, 315, 5452, 287, 13, 1472, 2643, 10712, 813, 5845, 311, 10299, 11, 719, 3131, 568, 35308, 11, 499, 2351, 10409, 449, 54711, 12410, 13, 22335, 11, 433, 596, 24270, 596, 34602, 17755, 11, 7445, 24270, 34602, 25, 28033, 315, 279, 31048, 25676, 627, 20051, 5352, 25, 7445, 24270, 34602, 25, 28033, 315, 279, 31048, 25676, 198, 2520, 1063, 14599, 2944, 11, 19093, 304, 279, 91297, 15422, 690, 4510, 430, 499, 527, 24270, 13, 1472, 2351, 4762, 279, 1455, 11495, 274, 5758, 315, 279, 4363, 11, 719, 433, 596, 539, 701, 294, 19587, 2011, 1815, 477, 701, 2579, 927, 5700, 430, 690, 12391, 701, 9764, 11, 433, 596, 701, 32464, 7940, 13, 1115, 4401, 46692, 374, 4762, 856, 10973, 7075, 961, 922, 14031, 49, 11637, 13, 2360, 5030, 1148, 961, 315, 279, 1917, 499, 2351, 304, 11, 4423, 690, 40605, 2610, 422, 499, 527, 2216, 279, 89686, 13, 578, 7402, 690, 18579, 11, 499, 690, 387, 12153, 311, 656, 4205, 775, 3156, 499, 5616, 4585, 279, 7940, 3215, 323, 12391, 701, 9764, 627, 791, 2800, 315, 279, 1847, 374, 2539, 315, 30139, 28485, 323, 3752, 430, 506, 799, 505, 1475, 97551, 13, 13698, 3727, 5647, 323, 374, 5128, 50738, 11, 279, 3446, 374, 3604, 539, 430, 3958, 369, 1148, 499, 4265, 1755, 433, 311, 387, 11, 323, 11, 1455, 23659, 11, 430, 32464, 10508, 27120, 430, 20685, 5518, 14450, 706, 2744, 1027, 3967, 369, 3727, 369, 264, 2294, 8209, 1887, 323, 3604, 65614, 5128, 1664, 449, 24270, 596, 810, 14595, 5452, 287, 20282, 13, 16506, 6052, 311, 279, 810, 8776, 2543, 6108, 955, 31017, 11, 719, 1457, 701, 3361, 8951, 1051, 23134, 709, 555, 26245, 3215, 54063, 477, 1023, 4528, 7177, 315, 3215, 12, 1911, 287, 1645, 28999, 13, 1115, 1887, 574, 779, 50738, 323, 13548, 430, 1475, 17876, 24270, 34602, 320, 83214, 398, 7000, 315, 1124, 20685, 5518, 14450, 3549, 8, 323, 1524, 279, 502, 54015, 65307, 51679, 706, 2751, 26245, 3215, 54063, 369, 9232, 323, 7185, 3361, 8951, 627, 40, 2846, 2771, 430, 1690, 1051, 44929, 922, 14031, 49, 11637, 596, 5845, 311, 387, 264, 2764, 11, 30311, 1847, 994, 433, 574, 7376, 13, 4702, 7999, 264, 2466, 11753, 34602, 16131, 311, 264, 19562, 3752, 1587, 539, 1304, 5127, 4510, 433, 690, 7091, 320, 4345, 1427, 520, 44317, 66416, 11, 912, 832, 15849, 433, 690, 12265, 570, 3011, 14031, 49, 11637, 374, 3025, 311, 12265, 389, 682, 64490, 323, 2103, 387, 832, 315, 279, 2731, 34602, 82, 389, 279, 2393, 374, 264, 61300, 311, 279, 11005, 315, 2362, 35789, 20685, 5518, 14450, 13, 3639, 264, 2294, 1847, 90578, 40, 1120, 649, 956, 22884, 21939, 304, 3686, 2500, 2835, 1847, 8518, 369, 420, 1847, 13, 1115, 832, 596, 5115, 33288, 90578, 2028, 1828, 1847, 574, 4756, 304, 5270, 555, 264, 2883, 6832, 63426, 374, 330, 32845, 1245, 16457, 1359, 719, 433, 596, 539, 279, 33489, 1675, 19945, 11637, 430, 499, 2643, 387, 7422, 315, 13, 578, 1925, 3752, 28533, 1633, 63667, 23837, 304, 2015, 311, 3665, 279, 1917, 304, 420, 832, 13, 1115, 832, 596, 264, 2766, 49331, 11, 719, 433, 596, 445, 1739, 689, 8105, 25, 43777, 315, 279, 18098, 3843, 1147, 627, 20051, 5352, 445, 1739, 689, 8105, 25, 43777, 315, 279, 18098, 3843, 1147, 198, 2028, 832, 2643, 4498, 264, 2766, 4994, 315, 1455, 315, 701, 1847, 9038, 1590, 13, 1102, 596, 539, 362, 9206, 1093, 13321, 27582, 477, 16537, 15403, 11, 539, 1524, 426, 9206, 1093, 58292, 315, 6785, 477, 279, 8769, 315, 4101, 320, 9514, 649, 40530, 323, 4647, 276, 682, 499, 1390, 922, 420, 11, 719, 499, 3358, 2646, 28008, 757, 430, 279, 1369, 37533, 423, 729, 1441, 84, 4101, 374, 4205, 810, 1109, 426, 9206, 570, 445, 1739, 689, 374, 264, 5128, 7626, 356, 9206, 4101, 11, 449, 24886, 311, 34602, 23354, 13, 2684, 1051, 1403, 18407, 1600, 3953, 3953, 323, 832, 66561, 1847, 304, 279, 4101, 44916, 11, 449, 2500, 66561, 342, 3864, 268, 13, 3011, 596, 433, 11, 430, 596, 279, 4553, 4101, 13, 2057, 387, 6762, 11, 433, 574, 10213, 20536, 449, 279, 480, 5002, 1847, 11, 719, 358, 2733, 430, 814, 1550, 5387, 433, 10284, 1825, 84175, 627, 4973, 1387, 4536, 956, 430, 3361, 11, 433, 596, 701, 14595, 34602, 449, 2543, 6108, 25572, 13, 2684, 574, 832, 28289, 8209, 45239, 304, 279, 48739, 26872, 430, 499, 1436, 12602, 323, 617, 4465, 389, 701, 2128, 13, 4314, 26872, 1051, 6500, 14400, 323, 1436, 387, 83349, 709, 323, 28995, 555, 26040, 1124, 10094, 323, 20634, 13, 578, 7185, 3245, 374, 430, 420, 4623, 3782, 922, 264, 2539, 1060, 1603, 27719, 574, 6004, 13, 36416, 7155, 422, 499, 2610, 757, 627, 3923, 1587, 1304, 420, 1847, 2559, 704, 323, 1148, 64859, 433, 264, 7858, 389, 420, 1160, 574, 1202, 3446, 13, 1666, 264, 864, 43014, 304, 264, 892, 1603, 864, 447, 2053, 1051, 7155, 320, 576, 574, 1648, 1203, 304, 6457, 304, 220, 2550, 20, 705, 445, 1739, 689, 8105, 13061, 709, 279, 3446, 1603, 279, 4455, 315, 445, 1739, 689, 612, 279, 72535, 315, 51334, 320, 64, 1847, 358, 2646, 6476, 570, 1472, 1051, 56625, 323, 11, 1093, 1455, 34602, 82, 11, 499, 527, 3309, 555, 264, 26454, 7216, 320, 64, 5333, 7086, 66821, 304, 420, 1162, 8, 430, 499, 527, 51687, 311, 3665, 279, 1917, 13, 1472, 2010, 704, 311, 11886, 264, 18118, 3575, 369, 701, 14458, 449, 701, 20587, 4333, 350, 689, 320, 9514, 84185, 4546, 1077, 3235, 8, 323, 505, 1070, 499, 34782, 505, 6424, 311, 6424, 22581, 5435, 323, 7999, 279, 70287, 3831, 26340, 311, 701, 4717, 13, 66821, 27024, 701, 2324, 1306, 499, 4048, 922, 279, 18098, 3843, 1147, 323, 499, 733, 389, 311, 923, 2500, 4717, 4562, 11, 279, 8954, 27202, 24082, 276, 11, 1603, 499, 5616, 4048, 279, 9764, 315, 279, 1176, 18098, 380, 3545, 11, 480, 3536, 11, 1306, 568, 70287, 60832, 459, 4553, 6424, 627, 42821, 1639, 3686, 30, 4718, 4717, 7995, 374, 13, 2435, 743, 1022, 311, 17302, 480, 3536, 323, 1304, 1461, 2343, 369, 1148, 568, 596, 2884, 13, 1283, 31680, 555, 5222, 398, 40294, 701, 1089, 13, 763, 3686, 2500, 2835, 1847, 330, 2319, 17619, 11, 358, 3987, 358, 574, 10171, 311, 2815, 1, 14269, 11, 499, 527, 69375, 555, 66821, 889, 5891, 1924, 279, 4717, 323, 10975, 5127, 719, 350, 689, 430, 814, 527, 8967, 311, 17302, 420, 14289, 3177, 449, 56625, 13, 13596, 36157, 11, 75563, 277, 11, 29782, 279, 4717, 323, 56625, 11, 26340, 11, 323, 75563, 277, 2010, 704, 311, 5622, 480, 3536, 1306, 6975, 505, 264, 74636, 315, 279, 18098, 3843, 1147, 11, 5336, 5808, 11, 430, 480, 3536, 6787, 389, 62193, 459, 4553, 13218, 13, 1115, 892, 56625, 29972, 311, 5622, 480, 3536, 11, 719, 568, 2103, 29972, 311, 20891, 279, 5780, 1306, 682, 13, 56625, 12084, 2740, 5334, 311, 279, 5780, 389, 813, 1866, 11, 719, 409, 9035, 1113, 433, 10213, 29910, 1461, 304, 279, 1920, 13, 66821, 8122, 3476, 304, 11, 28727, 311, 387, 5505, 11, 323, 27024, 56625, 627, 644, 279, 40696, 315, 420, 1567, 11, 584, 527, 12020, 311, 264, 31687, 4018, 23296, 1405, 23126, 4235, 912, 11, 3868, 11, 24082, 276, 77640, 48466, 288, 1077, 3021, 369, 56625, 13, 358, 2103, 6227, 420, 7234, 1486, 5108, 7833, 505, 2163, 2115, 13, 1472, 3152, 311, 3371, 757, 430, 350, 689, 11, 889, 596, 1027, 20129, 389, 499, 420, 4459, 1847, 11, 4536, 956, 16926, 842, 709, 449, 56625, 30, 1666, 264, 2851, 11, 358, 3287, 956, 4059, 11, 2533, 350, 689, 574, 30931, 323, 24082, 276, 574, 36659, 80005, 320, 258, 430, 220, 845, 15615, 1648, 705, 719, 2103, 11, 433, 2216, 65302, 449, 757, 311, 1518, 279, 13707, 539, 1935, 279, 4228, 5754, 11, 323, 358, 5201, 1124, 369, 433, 13, 350, 689, 16044, 2915, 52694, 1364, 596, 539, 16926, 3243, 56625, 596, 3021, 11, 10975, 75563, 277, 430, 1364, 16180, 56625, 279, 893, 11, 539, 56625, 279, 38490, 11, 323, 7437, 1022, 311, 1505, 264, 893, 439, 1695, 439, 56625, 311, 32918, 13, 3011, 596, 14243, 279, 1566, 499, 1518, 315, 264, 3752, 499, 3077, 7543, 4207, 11469, 13, 578, 1847, 3460, 315, 330, 1438, 1, 1618, 439, 56625, 323, 24082, 276, 527, 12502, 11, 3780, 264, 2697, 3838, 11, 323, 617, 264, 10585, 627, 2746, 499, 7846, 956, 8101, 555, 1457, 11, 358, 2846, 264, 8571, 315, 1521, 60883, 1917, 12, 477, 1847, 49961, 4455, 304, 264, 2835, 1847, 13, 2893, 433, 279, 4814, 315, 54838, 40756, 596, 1314, 8071, 304, 386, 16929, 18, 323, 1268, 433, 22223, 1176, 29145, 1684, 505, 1243, 389, 477, 2555, 1093, 279, 4435, 315, 29014, 258, 11, 1521, 6908, 11, 93294, 4455, 2646, 32616, 311, 1097, 10033, 757, 320, 40, 8101, 11, 422, 358, 3518, 9887, 617, 311, 358, 3358, 17113, 430, 64150, 285, 6, 4648, 374, 3169, 315, 7155, 304, 430, 1648, 11, 719, 433, 2646, 2216, 1047, 279, 1890, 14604, 5536, 389, 757, 439, 904, 315, 1521, 1023, 6305, 570, 5810, 358, 1097, 11, 3686, 1578, 7422, 430, 358, 9567, 279, 1847, 11, 323, 1243, 5336, 5808, 33798, 2690, 701, 4538, 323, 499, 2351, 9770, 311, 1935, 709, 11977, 1578, 13, 66821, 4131, 304, 323, 8349, 430, 433, 574, 56625, 596, 25382, 311, 2815, 1306, 279, 8209, 449, 480, 3536, 11, 719, 1077, 6299, 617, 5614, 279, 3938, 13, 1666, 279, 59018, 11, 499, 1541, 956, 3686, 1440, 430, 1521, 527, 15812, 13, 73817, 11, 499, 1541, 956, 1524, 1440, 279, 6908, 27744, 3686, 520, 682, 320, 37860, 499, 2643, 422, 499, 1047, 6476, 279, 1176, 1847, 11, 719, 358, 7995, 3287, 956, 4390, 2675, 656, 810, 2271, 12303, 6392, 11, 75563, 277, 8898, 1306, 499, 5622, 5336, 5808, 11, 323, 9778, 499, 636, 311, 279, 1620, 48853, 449, 279, 18098, 3843, 1147, 902, 374, 11, 539, 23828, 57222, 11, 24559, 279, 1648, 430, 445, 1739, 689, 612, 279, 72535, 315, 51334, 16264, 11, 902, 3445, 430, 499, 4465, 279, 18098, 3843, 1147, 323, 5622, 2380, 315, 279, 3116, 13, 6104, 4560, 311, 12731, 11, 1193, 26340, 323, 279, 41845, 1676, 82694, 320, 383, 11096, 499, 304, 279, 2132, 4376, 8, 1304, 433, 704, 13989, 13, 56625, 323, 24082, 276, 2815, 11, 719, 527, 16058, 27569, 439, 279, 23757, 889, 5355, 447, 3384, 279, 18098, 3843, 1147, 13, 1102, 1101, 10800, 704, 430, 420, 4459, 892, 701, 330, 19291, 1, 66821, 574, 279, 18098, 380, 3545, 469, 6417, 13, 469, 6417, 374, 5016, 304, 430, 779, 1317, 439, 1364, 6439, 11, 279, 18098, 3843, 1147, 649, 387, 35611, 95807, 1923, 660, 13, 7429, 5016, 922, 1077, 374, 1077, 5845, 311, 1935, 389, 3823, 1376, 11, 902, 1063, 7359, 64601, 374, 264, 1121, 315, 279, 18098, 380, 3545, 14569, 437, 7649, 22706, 13, 578, 1972, 27744, 1618, 374, 430, 66821, 26729, 6417, 374, 3010, 95807, 1923, 660, 439, 832, 315, 279, 1925, 5885, 304, 279, 1176, 445, 1739, 689, 1847, 13, 3296, 279, 1648, 11, 499, 2351, 4762, 20910, 3249, 420, 1847, 374, 1524, 2663, 445, 1739, 689, 422, 1070, 527, 912, 5885, 7086, 445, 1739, 689, 12660, 304, 279, 1847, 13, 358, 649, 1518, 701, 35202, 21583, 279, 32094, 13, 445, 1739, 689, 374, 469, 6417, 323, 1364, 374, 264, 3752, 889, 18809, 264, 4528, 3560, 311, 350, 689, 304, 279, 1176, 445, 1739, 689, 1847, 311, 832, 315, 56625, 596, 49446, 13, 3005, 3287, 956, 2349, 3925, 555, 10923, 56625, 311, 3136, 813, 6680, 1074, 11, 369, 56625, 323, 813, 49446, 1051, 2744, 8967, 311, 5663, 323, 9778, 18506, 279, 18098, 3843, 1147, 13, 469, 6417, 3727, 832, 1620, 11341, 439, 264, 4717, 4562, 304, 279, 4948, 445, 1739, 689, 1847, 11, 439, 1364, 86781, 709, 3686, 2500, 315, 279, 6680, 1074, 315, 56625, 323, 264, 13941, 315, 3831, 43600, 13, 3005, 22890, 1124, 709, 420, 1620, 892, 311, 7066, 279, 18098, 380, 3545, 81695, 16058, 13, 469, 6417, 1047, 19781, 315, 2324, 439, 279, 18098, 380, 3545, 315, 16290, 323, 4934, 1077, 2324, 311, 5616, 842, 627, 40, 1288, 1101, 6420, 430, 445, 1739, 689, 8105, 1047, 264, 5128, 6573, 25649, 323, 18118, 45239, 13, 63808, 9922, 389, 279, 2115, 323, 2751, 311, 3351, 1475, 892, 499, 7882, 13, 2684, 1051, 1101, 1063, 5128, 29585, 323, 5107, 47623, 369, 279, 2851, 311, 11886, 439, 568, 1903, 813, 1648, 1555, 279, 1690, 83485, 13, 358, 71249, 6227, 1063, 315, 1521, 1694, 779, 11292, 320, 576, 374, 1695, 16715, 430, 358, 1047, 311, 8666, 2362, 4819, 315, 23643, 7572, 311, 7216, 704, 1268, 311, 5208, 627, 3947, 499, 617, 433, 11, 264, 14470, 5804, 337, 2844, 7234, 323, 264, 1847, 430, 596, 13967, 5578, 304, 1202, 8209, 11572, 13, 16782, 11, 358, 649, 956, 1520, 719, 3021, 445, 1739, 689, 8105, 369, 433, 596, 11782, 47623, 323, 430, 1167, 3852, 3446, 13, 5075, 447, 2053, 1051, 2103, 264, 5128, 502, 7434, 311, 757, 1203, 1243, 994, 358, 6476, 433, 323, 14392, 1148, 574, 311, 3621, 311, 56625, 323, 24082, 276, 1903, 369, 1063, 7185, 11, 422, 19094, 4633, 27120, 439, 358, 15746, 279, 20156, 28572, 13, 2684, 596, 2555, 7155, 922, 5737, 264, 1847, 430, 18809, 1139, 264, 864, 1773, 47737, 25845, 13, 1102, 596, 2225, 85627, 323, 12738, 311, 5266, 304, 279, 3649, 315, 264, 3938, 499, 1440, 690, 832, 1938, 12446, 13, 358, 4265, 1093, 311, 1518, 810, 3953, 1456, 420, 449, 872, 3446, 8128, 13, 12522, 264, 39361, 5255, 8061, 10827, 3752, 3371, 499, 430, 27666, 279, 1847, 690, 3063, 311, 701, 4648, 13, 1102, 1436, 387, 11999, 86111, 477, 1524, 2949, 279, 1847, 5196, 13, 69676, 279, 1925, 3752, 1099, 23182, 449, 1148, 568, 8964, 311, 387, 279, 7191, 1695, 520, 279, 20900, 315, 279, 4443, 1695, 11767, 311, 1695, 20156, 13, 2435, 1550, 433, 304, 31042, 30768, 449, 50526, 11, 719, 279, 81169, 3287, 956, 617, 1148, 433, 3952, 311, 1095, 1077, 2815, 323, 539, 617, 264, 6380, 13696, 13, 3011, 1253, 387, 264, 1695, 3245, 13971, 11, 2533, 358, 2846, 832, 315, 279, 2478, 1274, 889, 649, 387, 20097, 449, 459, 43251, 477, 28743, 13696, 627, 791, 11002, 8518, 369, 420, 1847, 374, 5128, 61983, 11, 779, 1618, 596, 2555, 430, 264, 8571, 2231, 3871, 369, 279, 220, 806, 4771, 22310, 315, 279, 1847, 512, 24220, 11, 279, 2835, 596, 539, 430, 7155, 11, 719, 433, 6835, 499, 264, 12945, 315, 1148, 279, 1847, 7111, 323, 6476, 1093, 13, 1442, 499, 3596, 636, 264, 6140, 311, 1514, 420, 1847, 11, 358, 656, 7079, 433, 13, 1102, 596, 1664, 5922, 701, 892, 627, 8140, 1566, 1847, 315, 279, 1938, 1047, 264, 6691, 315, 264, 892, 1524, 3794, 6004, 304, 5270, 13, 2057, 420, 1938, 11, 279, 1176, 323, 4948, 1847, 315, 420, 4101, 617, 2103, 2646, 3970, 279, 3177, 315, 3778, 1938, 13, 1442, 499, 2351, 264, 8571, 315, 279, 6588, 14075, 21594, 11, 499, 1101, 2736, 1440, 430, 358, 2846, 7556, 922, 9420, 20139, 627, 20051, 5352, 25, 9420, 20139, 198, 791, 83580, 315, 9420, 20139, 15812, 539, 304, 1202, 17779, 11, 719, 810, 304, 279, 4113, 488, 323, 3752, 430, 433, 12716, 311, 459, 2736, 19781, 15150, 13, 2650, 1690, 20827, 323, 25551, 22228, 57689, 34602, 82, 1587, 279, 2835, 1847, 3157, 2216, 1205, 30, 320, 16533, 25, 4418, 956, 387, 18754, 11, 20827, 323, 25551, 22228, 57689, 34602, 82, 7091, 16715, 16782, 11, 433, 596, 37018, 311, 1518, 459, 34602, 1935, 2035, 304, 264, 6617, 6376, 1093, 279, 3224, 315, 36895, 1974, 320, 64, 539, 34119, 12, 588, 2230, 5905, 311, 279, 7427, 570, 1102, 596, 41367, 311, 1518, 430, 701, 10094, 6824, 315, 20075, 43308, 11, 30596, 12303, 437, 11, 323, 16893, 53098, 627, 791, 3446, 19169, 2212, 88602, 11, 264, 8334, 315, 28040, 50217, 2410, 889, 374, 51920, 555, 264, 38328, 505, 279, 3938, 7086, 39051, 39051, 311, 7066, 279, 14289, 5457, 3967, 439, 15754, 88, 40625, 13, 88602, 7437, 704, 505, 813, 44116, 11, 1952, 7211, 11, 323, 35006, 323, 56197, 62253, 11, 12149, 11, 323, 393, 2689, 311, 3665, 279, 11841, 13, 32944, 279, 1648, 11, 814, 4465, 4612, 1705, 11, 48173, 11, 12875, 11, 20120, 30826, 11, 293, 6341, 704, 279, 6588, 14075, 21594, 11157, 11, 323, 9778, 617, 872, 35826, 23217, 1139, 264, 59101, 2547, 311, 7431, 1124, 311, 5944, 304, 892, 311, 4465, 15754, 88, 40625, 13, 1102, 596, 15234, 11, 719, 304, 264, 68232, 1648, 13, 7570, 279, 1620, 13697, 4536, 956, 701, 14595, 13123, 13, 1472, 18506, 279, 42727, 15754, 88, 40625, 555, 19352, 52232, 11, 9778, 3794, 279, 4553, 11841, 311, 52696, 323, 18506, 15754, 88, 40625, 304, 264, 16537, 13131, 9090, 13054, 10827, 11401, 627, 44924, 20139, 3727, 420, 1160, 320, 4345, 20025, 8, 1606, 315, 279, 3752, 430, 433, 506, 29246, 505, 1475, 97551, 13, 23047, 287, 279, 24241, 11529, 11392, 4612, 374, 2103, 832, 315, 856, 7075, 15082, 304, 264, 2835, 1847, 14918, 1606, 315, 1268, 33288, 433, 2216, 374, 13, 13596, 5636, 369, 9420, 20139, 374, 430, 433, 596, 2216, 2653, 13, 578, 1847, 8659, 3250, 956, 6958, 904, 61851, 449, 1202, 17250, 627, 31140, 369, 603, 2326, 9420, 20139, 7359, 11, 279, 4101, 3287, 956, 4662, 682, 311, 1664, 994, 433, 1176, 3782, 704, 369, 279, 18407, 1600, 13, 1666, 264, 1121, 11, 23643, 6773, 539, 311, 4984, 279, 35861, 11, 21720, 220, 18, 320, 44924, 20139, 284, 21720, 220, 17, 705, 5415, 579, 33264, 8009, 6763, 315, 9420, 20139, 13, 2360, 5030, 1268, 1690, 8571, 21343, 7834, 1543, 5181, 16696, 311, 2231, 3871, 311, 4546, 21720, 220, 18, 311, 4892, 5270, 11, 23643, 31978, 41716, 311, 4984, 13, 58603, 3403, 11, 279, 23643, 315, 5270, 7752, 3604, 3021, 279, 7834, 1543, 73222, 11, 902, 358, 1781, 374, 1148, 706, 5535, 279, 800, 2227, 268, 311, 2103, 617, 264, 21720, 220, 18, 7359, 392, 304, 5788, 2085, 264, 32616, 9976, 25520, 380, 2015, 1694, 11136, 627, 8607, 7359, 64601, 430, 9420, 20139, 596, 14827, 4984, 389, 279, 21382, 5390, 320, 275, 574, 22359, 555, 279, 469, 14899, 33, 591, 433, 690, 387, 5108, 704, 8, 690, 387, 264, 3703, 21037, 311, 1296, 279, 32939, 315, 28965, 21720, 220, 18, 304, 36895, 1974, 13, 1472, 649, 1297, 430, 279, 1938, 420, 1847, 4131, 704, 5606, 11, 323, 358, 656, 16280, 3152, 5606, 11, 889, 374, 389, 856, 40292, 4885, 1160, 690, 5371, 264, 8352, 315, 9420, 20139, 369, 279, 18407, 1600, 7389, 814, 3371, 757, 814, 2351, 9293, 389, 12096, 433, 2736, 13, 358, 1120, 1390, 311, 24074, 709, 6763, 1606, 358, 4265, 3021, 311, 1518, 21720, 220, 18, 4295, 1057, 63263, 627, 29174, 2500, 11002, 8518, 430, 3250, 956, 1304, 2288, 1790, 5647, 13, 23485, 4999, 2409, 430, 11, 584, 2351, 4661, 2884, 449, 1057, 220, 845, 15615, 682, 98006, 13, 4702, 832, 810, 4441, 389, 7950, 311, 6381, 1521, 7752, 1022, 627, 4973, 35907, 11, 4491, 13, 14434, 198, 543, 98006, 11, 11745, 315, 4027, 11, 26161, 2271, 11, 9578, 11130, 11, 1620, 18884, 11, 1620, 18884, 3355, 11, 66561, 11, 326, 1739, 689, 612, 279, 70938, 315, 59714, 11, 326, 1739, 689, 14799, 25, 10205, 315, 279, 7589, 3843, 1147, 11, 9501, 14787, 6573, 220, 18, 11, 6691, 220, 17, 11, 6691, 220, 18, 11, 50169, 48312, 32078, 25, 389, 279, 11422, 1355, 1228, 36841, 560, 315, 11, 38751, 11, 513, 37533, 39950, 1441, 84, 11, 4224, 288, 11, 72436, 27076, 4440, 25, 279, 6453, 10868, 5812, 11, 357, 2227, 268, 5181, 11, 2307, 296, 3370, 436, 3601, 25, 13314, 315, 279, 8254, 9958, 128000, 61279, 4470, 1389, 393, 1813, 88, 612, 426, 434, 7690, 95693, 27636, 261, 389, 279, 6625, 3938, 315, 58069, 36967, 198, 35, 24012, 220, 20419, 20, 320, 66, 8, 82740, 47489, 126528, 331, 43401, 198, 28623, 220, 845, 11, 220, 2366, 16, 611, 34997, 73124, 782, 2749, 367, 11, 3754, 11, 59234, 32214, 13169, 82, 198, 47, 1813, 88, 612, 426, 434, 374, 264, 14048, 836, 304, 34997, 11, 2225, 304, 4606, 323, 2212, 279, 1917, 13, 2030, 1148, 1587, 430, 3152, 369, 279, 330, 5227, 2128, 44969, 3639, 3560, 1587, 279, 6469, 1514, 369, 279, 1828, 9659, 315, 58069, 34997, 32629, 11, 5654, 750, 323, 22917, 30, 362, 4403, 1111, 7476, 435, 877, 1539, 7731, 1523, 449, 84665, 3143, 39, 473, 4594, 643, 11, 1080, 36927, 323, 7690, 315, 279, 37048, 11655, 2734, 2423, 34997, 6469, 11, 393, 1813, 88, 612, 426, 434, 11, 311, 3137, 922, 279, 3347, 11, 3118, 323, 11, 5423, 11, 279, 3938, 315, 58069, 34997, 323, 87770, 1534, 4731, 11, 323, 889, 584, 1288, 682, 387, 10494, 1057, 6548, 323, 25212, 1825, 369, 304, 279, 4038, 323, 1667, 311, 2586, 627, 4516, 11, 433, 596, 13882, 3967, 430, 279, 393, 1813, 88, 6566, 706, 1317, 1047, 279, 26632, 323, 16044, 315, 20256, 279, 1888, 4311, 304, 34997, 323, 7953, 13, 2030, 11, 433, 596, 264, 220, 17, 27896, 8761, 11, 4536, 956, 433, 30, 2876, 1193, 656, 499, 4546, 304, 6625, 11005, 11, 719, 499, 1101, 1520, 7195, 15481, 32629, 704, 4102, 627, 19875, 5237, 27636, 261, 510, 73556, 5787, 22335, 11, 358, 617, 311, 7655, 4999, 4054, 1436, 1524, 2019, 11, 5737, 520, 701, 6469, 374, 2555, 315, 459, 20396, 11989, 311, 279, 34997, 1917, 7953, 13, 763, 1023, 4339, 11, 499, 4265, 387, 2653, 17770, 311, 1505, 459, 37545, 9959, 58069, 34997, 39844, 889, 12775, 956, 6476, 520, 393, 1813, 88, 323, 11, 1455, 4461, 11, 6476, 1070, 220, 16, 267, 11, 1603, 10594, 1711, 704, 7953, 279, 58069, 24743, 13, 3639, 656, 499, 1781, 922, 420, 5224, 5380, 19875, 5237, 27636, 261, 25, 8489, 11, 889, 6267, 430, 30, 358, 3021, 433, 13, 510, 73556, 60, 2030, 14243, 11, 10035, 11, 433, 596, 837, 13, 1472, 1440, 11, 279, 1486, 574, 11, 505, 279, 7314, 11, 994, 584, 1389, 4242, 3557, 432, 2448, 29468, 11, 14094, 4852, 4241, 375, 11, 24664, 7379, 273, 40091, 292, 323, 7182, 1389, 3940, 393, 1813, 88, 304, 220, 2550, 18, 11, 1057, 9131, 574, 2380, 24325, 25, 220, 16, 267, 323, 43780, 11, 279, 58069, 6237, 11, 220, 17, 303, 279, 7665, 832, 323, 11, 220, 18, 6634, 11, 279, 2466, 5144, 505, 279, 3778, 6237, 11, 902, 374, 279, 56336, 315, 34997, 627, 1361, 8, 87598, 480, 6863, 355, 198, 12739, 87868, 5257, 7354, 74390, 7780, 1753, 3083, 362, 16691, 86951, 82982, 4716, 76073, 40, 11954, 11, 5871, 91252, 5871, 362, 16691, 86951, 82982, 4716, 40992, 50, 26336, 7432, 36275, 71361, 47, 5257, 3891, 3087, 198, 3957, 430, 2103, 279, 9131, 3432, 5380, 19875, 5237, 27636, 261, 25, 7566, 11, 420, 330, 23254, 329, 1, 7434, 12775, 956, 5614, 13, 5046, 3388, 1070, 617, 1027, 26006, 323, 24400, 389, 1023, 6625, 13918, 11, 719, 13524, 433, 596, 279, 1890, 13, 3639, 584, 9395, 369, 374, 11, 389, 832, 3185, 11, 311, 387, 2555, 315, 264, 6574, 2035, 369, 32629, 11, 719, 389, 279, 1023, 11, 264, 6574, 2035, 369, 7224, 430, 1436, 2274, 3871, 13, 1789, 3187, 11, 42292, 6625, 32629, 311, 51696, 449, 58069, 32629, 11, 439, 584, 656, 304, 1057, 79682, 11378, 13, 2100, 584, 539, 1193, 3085, 279, 10877, 311, 1817, 704, 279, 3778, 19987, 477, 37545, 7185, 14385, 11, 719, 1101, 311, 16681, 449, 1124, 13, 2876, 1475, 1938, 11, 315, 3388, 11, 719, 304, 3738, 7224, 627, 2181, 10578, 1093, 279, 6469, 8779, 279, 58069, 6237, 311, 9407, 872, 6625, 13537, 627, 19875, 5237, 27636, 261, 25, 763, 2144, 11, 430, 596, 2555, 584, 2733, 311, 387, 1057, 3465, 13, 358, 3152, 11, 279, 5896, 27383, 527, 2103, 12765, 13, 1226, 22114, 6625, 13820, 11, 719, 11, 37318, 11, 584, 1101, 22114, 279, 1828, 9659, 315, 58069, 32629, 1093, 60166, 380, 13629, 67011, 301, 477, 22253, 380, 2418, 84, 3297, 81, 627, 4516, 6625, 83663, 617, 2744, 1027, 832, 315, 279, 64982, 315, 393, 1813, 88, 11, 719, 4245, 311, 279, 28522, 11, 2574, 30073, 29057, 323, 505, 832, 1938, 311, 279, 1828, 11, 279, 6469, 596, 2262, 15187, 6244, 4661, 24121, 15481, 13, 3234, 499, 1781, 430, 420, 706, 1317, 9860, 25127, 369, 499, 477, 279, 4731, 1917, 520, 3544, 11, 477, 574, 433, 1120, 459, 25363, 6671, 5380, 19875, 5237, 27636, 261, 25, 1102, 596, 459, 25363, 6671, 13, 2030, 11, 279, 2254, 6237, 574, 2744, 264, 6908, 961, 315, 279, 2068, 13, 1628, 11, 499, 1440, 11, 584, 617, 279, 800, 1466, 713, 29549, 1195, 11, 369, 3187, 11, 902, 374, 8036, 1457, 4245, 311, 279, 28522, 13, 2100, 11, 304, 1057, 17265, 2068, 11, 584, 15109, 264, 2763, 315, 21562, 430, 1047, 8767, 6476, 520, 279, 800, 1466, 713, 29549, 1195, 13, 5046, 3388, 11, 994, 4395, 312, 25149, 11, 1063, 315, 279, 21562, 430, 6476, 389, 279, 1925, 6566, 1253, 617, 311, 733, 1203, 311, 279, 800, 1466, 713, 29549, 1195, 13, 2030, 11, 499, 1440, 11, 279, 4459, 2068, 2834, 956, 2216, 2349, 430, 1790, 13, 1102, 596, 1120, 11, 279, 10937, 690, 387, 49331, 627, 4516, 11, 1268, 656, 499, 3604, 1304, 701, 2068, 30, 2650, 656, 499, 5268, 701, 13820, 30, 1628, 1405, 656, 499, 636, 701, 2038, 11, 5423, 994, 433, 4131, 311, 14827, 13820, 889, 7784, 956, 430, 2466, 3686, 5380, 3513, 349, 468, 552, 5248, 612, 29656, 72812, 1543, 5248, 320, 66, 8, 82740, 47489, 126528, 331, 43401, 198, 19875, 5237, 27636, 261, 25, 358, 1541, 956, 2216, 617, 264, 1887, 13, 1102, 1120, 8741, 13, 2030, 11, 10213, 11, 358, 1505, 704, 922, 502, 14385, 555, 3492, 315, 11013, 477, 28782, 13, 1789, 3187, 11, 994, 95693, 356, 4842, 11, 889, 574, 279, 7690, 315, 279, 34997, 9476, 315, 279, 3320, 1983, 1215, 20650, 5382, 11, 2795, 264, 836, 323, 430, 814, 527, 264, 2466, 11005, 11, 1243, 358, 1440, 358, 1541, 956, 617, 311, 2132, 8101, 433, 13, 5046, 3388, 11, 832, 1101, 22657, 709, 264, 2763, 1555, 279, 74229, 4009, 315, 19309, 323, 6469, 7980, 13, 1115, 3727, 15840, 5115, 4228, 13, 1628, 264, 2763, 315, 2574, 3621, 1555, 14094, 4852, 4241, 375, 596, 1633, 16994, 15840, 315, 279, 800, 1466, 713, 29549, 1195, 627, 4516, 889, 527, 279, 709, 323, 5108, 58069, 32629, 902, 8659, 690, 539, 387, 79932, 505, 279, 1925, 6566, 11, 323, 7953, 430, 527, 11, 304, 701, 9647, 11, 5644, 311, 4295, 279, 6625, 6566, 11, 477, 4295, 433, 1524, 16127, 422, 814, 2736, 617, 5380, 19875, 5237, 27636, 261, 25, 2057, 387, 10978, 11, 1070, 527, 5115, 264, 2763, 13, 7570, 422, 499, 1120, 1781, 922, 24198, 11, 1093, 22253, 4311, 369, 3187, 13, 1472, 690, 1505, 520, 3325, 220, 605, 2307, 1579, 11852, 22253, 4311, 304, 35998, 11, 1093, 79193, 29562, 267, 75, 11, 369, 3187, 11, 449, 2216, 28809, 32629, 2200, 13, 1628, 430, 596, 5614, 264, 2763, 13, 3277, 358, 3940, 393, 1813, 88, 304, 279, 220, 1954, 596, 11, 279, 6237, 574, 5115, 2678, 13, 8876, 1243, 11, 264, 2763, 706, 8040, 11, 1093, 279, 2237, 315, 6873, 13, 1472, 1457, 617, 14964, 13639, 11, 1093, 320, 54, 337, 76413, 8, 393, 355, 2174, 343, 11, 369, 3187, 11, 889, 2216, 2586, 704, 315, 279, 6625, 34997, 6237, 13, 2100, 1070, 527, 264, 2763, 315, 1633, 23944, 323, 1664, 88781, 4236, 11, 1093, 13629, 67011, 301, 11, 369, 3187, 13, 3277, 568, 11335, 420, 220, 2148, 99036, 2493, 44210, 263, 11, 499, 733, 14599, 13, 510, 73556, 60, 1472, 1781, 11, 36765, 1148, 596, 430, 30, 2582, 420, 27374, 2851, 6941, 19198, 11, 477, 279, 468, 552, 5248, 30393, 320, 32, 496, 307, 11, 64108, 612, 2893, 349, 11, 22253, 705, 279, 7200, 11, 41489, 374, 279, 3562, 11, 477, 279, 69046, 79193, 87128, 13, 2435, 2351, 682, 389, 872, 1648, 627, 17673, 73145, 38876, 5257, 51836, 3247, 816, 5152, 38, 11, 25557, 68098, 362, 8721, 4403, 1111, 7683, 37420, 198, 2675, 9932, 13629, 67011, 301, 11, 902, 358, 4376, 3685, 11, 1606, 568, 596, 389, 264, 2763, 315, 1274, 596, 20663, 304, 279, 34997, 323, 80163, 367, 6237, 31445, 13, 2030, 499, 1101, 1071, 1268, 6485, 813, 990, 374, 13, 11208, 1436, 568, 5052, 389, 279, 6625, 6566, 5380, 19875, 5237, 27636, 261, 25, 6914, 596, 9616, 1461, 449, 264, 13970, 7216, 1093, 90227, 16844, 13, 1283, 574, 1101, 3169, 315, 264, 73287, 11, 304, 264, 1695, 1648, 13, 1102, 3952, 1461, 264, 1418, 311, 12265, 449, 420, 3169, 315, 1989, 11, 1606, 433, 596, 779, 6485, 13, 2100, 315, 3388, 430, 596, 264, 8815, 13, 1952, 279, 1023, 3185, 11, 994, 13629, 374, 3815, 813, 27374, 35062, 11, 433, 596, 1101, 5115, 6485, 11, 719, 433, 596, 8831, 311, 9020, 311, 627, 6854, 499, 3371, 757, 1148, 499, 1440, 323, 1093, 922, 41489, 374, 279, 3562, 5380, 19875, 5237, 27636, 261, 25, 8489, 11, 814, 3940, 520, 279, 800, 1466, 713, 29549, 1195, 323, 6476, 1070, 264, 5743, 315, 3115, 11, 3156, 584, 15393, 11, 36765, 11, 430, 596, 264, 2216, 7155, 323, 7185, 22498, 13, 2435, 527, 264, 41376, 295, 11, 323, 682, 20041, 3871, 11, 358, 4510, 13, 1628, 994, 499, 1518, 264, 7200, 3318, 3871, 369, 1063, 892, 323, 814, 2744, 636, 2731, 323, 2731, 11, 323, 814, 2274, 323, 2216, 9396, 3871, 11, 1243, 499, 649, 1518, 872, 4754, 13, 1628, 3131, 499, 15641, 430, 11, 1243, 499, 690, 3041, 1124, 279, 1925, 6566, 11, 315, 3388, 13, 2030, 433, 3966, 892, 311, 2274, 13, 1102, 596, 539, 1695, 311, 3041, 1124, 279, 1925, 6566, 1314, 3201, 627, 4516, 11, 369, 430, 2944, 279, 800, 1466, 713, 29549, 1195, 2216, 3727, 5647, 627, 19875, 5237, 27636, 261, 25, 83065, 13, 3011, 574, 279, 1486, 315, 433, 13, 1226, 3940, 279, 800, 1466, 713, 29549, 1195, 922, 220, 605, 1667, 4227, 13, 1628, 279, 4623, 574, 311, 1862, 279, 3995, 11, 11084, 58069, 6237, 11, 369, 889, 279, 1925, 6566, 574, 2288, 2466, 13, 1226, 617, 264, 3738, 7410, 1070, 13, 1226, 1205, 311, 5266, 279, 16712, 13, 3011, 596, 1120, 1268, 433, 374, 13, 2100, 279, 800, 1466, 713, 29549, 1195, 3727, 5647, 11, 323, 315, 3388, 433, 374, 1093, 279, 1176, 3094, 311, 393, 1813, 88, 13, 3277, 499, 636, 264, 23401, 520, 279, 800, 1466, 713, 29549, 1195, 11, 433, 596, 279, 1176, 6140, 499, 617, 311, 9504, 856, 6666, 323, 3885, 4527, 52783, 430, 4375, 5128, 1664, 11, 323, 27905, 499, 2643, 636, 264, 23401, 520, 279, 1925, 6566, 13, 1628, 422, 430, 8741, 11, 433, 649, 2216, 1520, 32629, 636, 78920, 22917, 13, 578, 8206, 374, 11, 1023, 6625, 19424, 1427, 311, 1057, 2068, 311, 1520, 1304, 11429, 922, 872, 1866, 627, 5519, 499, 617, 904, 9650, 369, 32629, 889, 527, 4216, 304, 872, 7076, 30, 3277, 499, 12570, 922, 41489, 374, 279, 3562, 433, 35408, 1093, 11, 304, 961, 11, 1148, 22954, 499, 374, 1268, 22954, 814, 1051, 315, 5694, 627, 19875, 5237, 27636, 261, 25, 56647, 13, 1472, 617, 311, 1833, 701, 4623, 477, 14944, 13, 1442, 499, 617, 264, 3831, 4623, 315, 1148, 499, 1390, 311, 656, 323, 433, 3250, 956, 990, 704, 7214, 11, 1541, 956, 5042, 3041, 709, 13, 1442, 420, 4623, 374, 539, 1193, 264, 3831, 4623, 11, 719, 264, 1695, 832, 2288, 11, 323, 499, 9396, 449, 433, 11, 520, 832, 1486, 11, 499, 690, 387, 15324, 369, 433, 13, 2030, 499, 617, 311, 2567, 2133, 323, 2274, 433, 13, 358, 3152, 11, 422, 264, 7434, 3250, 956, 990, 704, 304, 279, 1176, 4545, 11, 433, 596, 539, 264, 2466, 3568, 13, 1472, 1120, 617, 311, 6211, 433, 323, 990, 389, 433, 13, 1472, 1205, 892, 311, 48306, 2648, 11, 6725, 323, 9526, 627, 2181, 596, 539, 2744, 4228, 11, 3582, 11, 311, 617, 420, 3169, 315, 659, 35915, 3149, 2136, 13, 36625, 304, 264, 7829, 369, 902, 1521, 2819, 527, 539, 439, 17693, 51155, 2692, 439, 11, 1095, 596, 2019, 11, 279, 3778, 832, 627, 19875, 5237, 27636, 261, 25, 2360, 11, 433, 596, 539, 4228, 13, 1102, 596, 264, 2653, 1648, 315, 3388, 13, 2030, 433, 3727, 5647, 13, 358, 3152, 11, 422, 499, 1390, 311, 18167, 439, 264, 4156, 29145, 11, 1243, 499, 649, 956, 1935, 279, 4228, 6149, 13, 2030, 520, 832, 1486, 11, 499, 1440, 11, 682, 1884, 2216, 23944, 32629, 11, 304, 682, 22540, 11, 1093, 393, 355, 2174, 343, 11, 23373, 65, 28196, 11, 386, 952, 81985, 11, 814, 682, 12265, 449, 872, 1989, 13, 1628, 430, 596, 304, 961, 1606, 814, 2216, 11846, 304, 5694, 323, 872, 28697, 13, 3011, 596, 2216, 3062, 11, 6062, 499, 2643, 617, 311, 636, 264, 2204, 2683, 627, 9688, 1813, 67011, 301, 612, 86756, 800, 16034, 7442, 320, 66, 8, 82740, 47489, 126528, 331, 43401, 198, 3923, 527, 1023, 14293, 311, 6625, 2450, 30, 2582, 1148, 527, 1063, 30740, 5380, 19875, 5237, 27636, 261, 25, 5659, 892, 311, 892, 11, 279, 32629, 527, 539, 779, 8173, 304, 9564, 872, 3363, 13, 1628, 499, 617, 311, 5201, 430, 13, 1789, 3187, 11, 279, 11495, 25844, 735, 70496, 11, 279, 1176, 2216, 6625, 58069, 34997, 6917, 13, 1283, 1053, 617, 1047, 1475, 13336, 311, 733, 311, 279, 4273, 11, 369, 3187, 13, 1283, 1120, 3287, 956, 1390, 311, 13, 1283, 6476, 449, 5127, 1606, 814, 1120, 3782, 1555, 320, 31880, 705, 1093, 95285, 71492, 477, 94870, 426, 3258, 13, 1283, 1120, 1071, 11, 364, 576, 374, 856, 2162, 11, 323, 358, 1541, 956, 1390, 311, 733, 12660, 775, 3238, 578, 3575, 374, 11, 1603, 1778, 32629, 2643, 1304, 459, 6625, 7076, 11, 814, 527, 2736, 12917, 279, 1828, 9659, 1618, 13, 5046, 3388, 11, 389, 832, 1450, 433, 6835, 1124, 4868, 11, 719, 389, 279, 1023, 11, 433, 48270, 2690, 499, 1606, 433, 73115, 701, 25835, 311, 1935, 3738, 15635, 627, 4516, 433, 596, 279, 6981, 430, 1436, 5622, 499, 30, 27140, 3778, 13820, 889, 11, 304, 1455, 5157, 11, 617, 311, 7364, 37545, 311, 1304, 264, 5496, 11, 7665, 32629, 1541, 956, 617, 430, 1890, 7410, 627, 19875, 5237, 27636, 261, 25, 22335, 13, 1226, 527, 304, 264, 23460, 1614, 13, 1102, 596, 264, 4868, 39139, 11, 323, 433, 596, 5107, 311, 636, 1274, 704, 505, 1234, 433, 13, 358, 3152, 11, 358, 1541, 956, 1390, 311, 31678, 5606, 11, 719, 422, 499, 1390, 311, 51630, 279, 1917, 11, 499, 649, 956, 3868, 369, 279, 1917, 311, 2586, 311, 499, 627, 2843, 15334, 72306, 5257, 53083, 53, 6674, 5871, 362, 82647, 9483, 643, 2770, 11, 15334, 20076, 17773, 86239, 3247, 469, 53566, 54281, 36, 198, 21573, 10964, 704, 315, 279, 3830, 374, 2500, 25795, 1243, 5380, 19875, 5237, 27636, 261, 25, 358, 4265, 2019, 779, 13, 9372, 520, 11826, 328, 572, 531, 11, 264, 2216, 7185, 323, 27332, 39844, 13, 1283, 574, 279, 39637, 7564, 520, 279, 892, 311, 636, 264, 79682, 520, 393, 1813, 88, 13, 358, 6227, 568, 1047, 6051, 8220, 12374, 304, 94030, 719, 568, 3287, 956, 636, 264, 330, 325, 4171, 18340, 1, 320, 276, 330, 32, 4063, 719, 568, 574, 832, 315, 279, 1455, 7185, 32629, 13, 1226, 6773, 311, 3041, 1461, 264, 79682, 11, 449, 220, 18, 22178, 520, 393, 1813, 88, 13, 1628, 568, 2216, 1511, 430, 6776, 323, 18719, 1274, 1093, 41259, 278, 1037, 268, 56609, 13722, 13, 1283, 1524, 29091, 3300, 304, 433, 13, 1628, 11, 994, 682, 374, 1071, 323, 2884, 11, 568, 1766, 813, 1648, 11, 1606, 568, 1550, 433, 21356, 13, 7570, 3582, 433, 5828, 956, 4228, 449, 279, 3169, 315, 1989, 568, 574, 8173, 304, 627, 40, 8101, 430, 596, 2500, 32961, 369, 2450, 30, 1472, 1541, 956, 617, 311, 4587, 279, 3885, 323, 27651, 45593, 11, 719, 4856, 9396, 311, 701, 16766, 323, 701, 58724, 5380, 19875, 5237, 27636, 261, 25, 7566, 11, 719, 433, 596, 5107, 13, 763, 4846, 3115, 11, 11782, 32629, 11, 814, 1120, 36257, 279, 14673, 31155, 13, 578, 11495, 3446, 449, 320, 41444, 8, 1901, 675, 258, 360, 574, 568, 4024, 311, 279, 4273, 1606, 568, 2751, 264, 34225, 505, 51291, 8669, 11, 719, 2163, 4661, 7214, 11, 5605, 11, 364, 19701, 11, 358, 649, 956, 4048, 4205, 1618, 4527, 2100, 568, 4024, 1203, 311, 12551, 11, 311, 24214, 1974, 323, 2322, 682, 1884, 32629, 1070, 13, 1628, 15187, 568, 1047, 264, 23401, 449, 3297, 98032, 38476, 323, 1243, 11, 813, 7076, 2216, 3940, 13, 1283, 6244, 279, 27374, 2851, 315, 51823, 4047, 2758, 261, 3258, 11, 902, 574, 279, 18638, 30223, 7200, 315, 430, 892, 13, 2052, 430, 1053, 2646, 617, 7077, 2085, 813, 16801, 304, 5678, 13, 1283, 1071, 11, 364, 40, 1097, 279, 1888, 11, 779, 1148, 649, 499, 4639, 757, 422, 358, 2846, 2736, 279, 1888, 20837, 1102, 574, 24674, 659, 91980, 13, 2030, 568, 596, 264, 9024, 9606, 315, 3388, 627, 2675, 9932, 279, 468, 552, 5248, 30393, 26, 2555, 315, 264, 2410, 6857, 889, 2873, 311, 387, 50949, 709, 682, 927, 279, 2035, 31445, 627, 19875, 5237, 27636, 261, 25, 22335, 11, 323, 99124, 779, 13, 2435, 617, 420, 2294, 34821, 3871, 11, 34821, 220, 20419, 20, 320, 9210, 596, 279, 10521, 2082, 315, 872, 44116, 705, 439, 1664, 439, 459, 7185, 22498, 2663, 469, 331, 677, 4285, 261, 13, 2435, 2351, 1101, 264, 5912, 961, 315, 279, 2582, 73, 10002, 2221, 47387, 11, 6197, 555, 9052, 386, 952, 81985, 627, 4897, 22498, 320, 2244, 73, 10002, 2221, 47387, 8, 5084, 311, 387, 2555, 315, 264, 4106, 7858, 369, 3995, 11005, 627, 19875, 5237, 27636, 261, 25, 56647, 13, 763, 1070, 374, 1101, 279, 69046, 11, 79193, 87128, 13, 3005, 596, 1903, 264, 3831, 17444, 369, 11937, 439, 459, 1825, 34423, 293, 3397, 1013, 323, 1948, 78611, 40550, 369, 15013, 16870, 552, 17262, 48672, 11, 369, 3187, 13, 7429, 304, 1077, 34821, 449, 29656, 72812, 1543, 5248, 320, 82, 47388, 5770, 64108, 323, 22253, 20064, 30976, 705, 902, 374, 264, 2216, 7185, 10824, 11, 439, 1664, 439, 304, 279, 93639, 4731, 2317, 11, 1093, 449, 11291, 393, 647, 261, 323, 11291, 58463, 627, 4516, 11, 1148, 374, 433, 922, 1521, 3995, 32629, 499, 3077, 9932, 11, 430, 1304, 1124, 2559, 704, 304, 35998, 11, 323, 1436, 1304, 1124, 2559, 704, 37545, 11, 439, 1664, 5380, 19875, 5237, 27636, 261, 25, 1102, 596, 264, 3169, 315, 3927, 2191, 13, 2435, 617, 264, 5016, 5222, 11, 912, 5030, 1148, 814, 656, 13, 362, 4443, 5916, 11, 323, 459, 7185, 832, 520, 430, 13, 13596, 39844, 11, 889, 2011, 387, 9932, 422, 584, 527, 7556, 922, 279, 330, 82279, 69132, 1359, 374, 40904, 6178, 339, 86, 30463, 13, 1283, 11767, 813, 1866, 69155, 11, 4315, 1023, 7640, 11, 1778, 439, 18273, 7690, 315, 71028, 6489, 596, 735, 5317, 74, 39457, 13, 2052, 315, 1521, 32629, 527, 961, 315, 264, 7155, 9659, 11, 889, 1440, 264, 2763, 922, 4731, 11, 323, 1047, 29924, 6873, 11, 719, 527, 2216, 10032, 311, 87770, 553, 323, 1935, 15635, 13, 1102, 596, 539, 3284, 311, 12265, 1475, 3254, 892, 994, 499, 617, 459, 1825, 7434, 1093, 48301, 13, 358, 3152, 11, 433, 649, 2543, 704, 439, 264, 11415, 11, 477, 499, 1440, 510, 73556, 1145, 499, 2731, 1781, 433, 927, 1578, 13, 2030, 38330, 814, 527, 10032, 311, 1935, 279, 5326, 627, 2822, 5326, 1981, 912, 2523, 30, 4696, 2201, 33651, 5380, 19875, 5237, 27636, 261, 25, 8489, 11, 422, 499, 2351, 539, 10032, 311, 1935, 15635, 11, 1243, 499, 649, 387, 264, 2307, 14356, 39844, 11, 477, 990, 439, 264, 3185, 29145, 304, 264, 2466, 7200, 11, 719, 499, 2834, 956, 3719, 832, 315, 279, 2466, 5144, 13, 1789, 430, 11, 499, 617, 311, 1935, 15635, 11, 387, 659, 51817, 1748, 11, 1833, 701, 6848, 11, 323, 387, 22954, 555, 1124, 11, 439, 1664, 439, 2274, 1124, 13, 13629, 67011, 301, 374, 7185, 1606, 568, 596, 539, 1193, 264, 27374, 2851, 11, 719, 264, 27374, 4797, 13, 1283, 22890, 813, 1866, 24198, 13, 1628, 420, 4623, 315, 220, 2148, 99036, 13, 1102, 596, 2216, 28809, 13, 1102, 596, 1093, 264, 41903, 3169, 315, 5603, 13, 1628, 11, 430, 596, 539, 4400, 13, 358, 3152, 11, 358, 1541, 956, 3619, 433, 520, 682, 13, 358, 617, 311, 387, 10978, 13, 510, 73556, 60, 2030, 358, 2846, 2216, 8173, 304, 433, 627, 19875, 5237, 27636, 261, 25, 18156, 433, 596, 1524, 5107, 311, 9020, 311, 420, 6392, 1606, 520, 3115, 433, 1120, 10578, 330, 35970, 3343, 2030, 358, 2846, 2771, 433, 596, 539, 13, 358, 1440, 13629, 5115, 1664, 520, 420, 1486, 11, 323, 358, 2846, 2771, 430, 4395, 568, 374, 3815, 374, 389, 279, 8592, 2237, 13, 2100, 279, 43076, 527, 539, 5076, 13, 10926, 358, 1120, 6865, 1124, 5076, 13, 510, 73556, 60, 358, 1781, 505, 682, 279, 3995, 32629, 358, 1440, 11, 568, 374, 7344, 279, 1455, 35201, 26, 304, 1690, 5627, 11, 2737, 813, 1648, 315, 7422, 627, 11649, 11, 499, 649, 956, 1948, 330, 4469, 9334, 1, 779, 1095, 596, 3009, 279, 7274, 1618, 0, 9930, 499, 4999, 32, 462, 12930, 435, 36077, 198, 9688, 1813, 67011, 301, 198, 75613, 374, 279, 3562, 198, 35, 24012, 220, 22191, 20, 198, 62813, 411, 29562, 267, 75, 198, 62813, 411, 87128, 198, 1692, 84, 3297, 81, 198, 73849, 72812, 1543, 5248, 198, 49, 31323, 6178, 339, 86, 30463, 198, 21645, 34997, 73124, 782, 2749, 367, 11, 3754, 11, 59234, 32214, 13169, 82, 28783, 39616, 307, 468, 552, 5248, 11, 2893, 349, 468, 552, 5248, 11, 95693, 27636, 261, 11, 6941, 19198, 11, 13629, 67011, 301, 11, 79193, 29562, 267, 75, 11, 79193, 87128, 11, 2418, 84, 3297, 81, 11, 11826, 328, 572, 531, 11, 393, 1813, 88, 323, 426, 434, 11, 41489, 374, 279, 3562, 11, 40904, 6178, 339, 86, 30463, 11, 800, 1466, 713, 29549, 1195, 198, 697, 10653, 65, 30660, 17772, 7327, 1389, 5377, 7290, 198, 39125, 3845, 45241, 1389, 5377, 7290, 128000, 60627, 49520, 83586, 71829, 49520, 39091, 7952, 43203, 5173, 108687, 13433, 57186, 220, 845, 13, 717, 13, 2366, 17, 5301, 65518, 7281, 26692, 315, 31013, 8524, 198, 13730, 706, 34683, 279, 5144, 315, 9214, 315, 1274, 369, 8884, 36380, 425, 315, 279, 19071, 11, 23693, 323, 659, 33028, 1051, 539, 20167, 11, 323, 832, 315, 1124, 574, 79369, 92551, 51214, 12758, 1919, 89730, 198, 1383, 20643, 20774, 347, 24568, 9509, 11, 264, 7061, 11, 3229, 315, 279, 2363, 11, 18165, 9500, 72, 4881, 315, 8184, 198, 791, 12758, 1919, 89730, 82, 3782, 505, 459, 2362, 719, 539, 28994, 30338, 3070, 5029, 1203, 311, 220, 10513, 21, 13, 79369, 92551, 51214, 12758, 1919, 89730, 596, 2294, 72102, 23881, 1389, 816, 301, 1082, 88, 8290, 1910, 51214, 1389, 7882, 311, 23223, 505, 279, 6424, 315, 386, 5893, 113381, 115045, 1441, 510, 3409, 8560, 2303, 277, 115045, 1441, 60, 258, 220, 11242, 19, 13, 5414, 38950, 1389, 68553, 13279, 816, 301, 1082, 88, 5230, 718, 1389, 574, 264, 23223, 30338, 315, 279, 220, 18, 6634, 33592, 13, 763, 220, 10828, 23, 11, 568, 9107, 459, 21967, 304, 23223, 369, 54631, 287, 323, 70181, 287, 10247, 323, 30503, 89054, 13, 5414, 7126, 1389, 92551, 68553, 13279, 51214, 11, 264, 23223, 30338, 315, 279, 220, 17, 303, 33592, 1389, 9152, 311, 9407, 279, 3070, 2626, 13, 2030, 279, 12758, 1919, 89730, 82, 6, 2626, 1550, 539, 5662, 264, 9615, 2294, 5569, 3156, 279, 1828, 9659, 13, 79369, 92551, 51214, 12758, 1919, 89730, 28088, 813, 7126, 596, 2626, 304, 279, 1176, 4376, 315, 279, 220, 9741, 15, 82, 13, 578, 364, 27368, 3058, 393, 13, 323, 328, 13, 12758, 1919, 89730, 323, 650, 13, 24277, 939, 258, 6, 11380, 2883, 9922, 304, 23223, 304, 220, 9714, 15, 13, 12758, 1919, 89730, 596, 26419, 8738, 11380, 323, 13076, 2626, 13, 763, 220, 9714, 19, 11, 814, 18538, 279, 1561, 735, 537, 58084, 8732, 268, 8384, 11, 5918, 3892, 1344, 710, 70293, 35159, 304, 735, 537, 58084, 11, 323, 1403, 1667, 3010, 9749, 279, 11495, 10229, 315, 279, 20902, 735, 537, 58084, 8732, 268, 8384, 449, 264, 6864, 315, 220, 10914, 11, 931, 6761, 436, 86713, 627, 2181, 1288, 387, 10555, 430, 79369, 92551, 51214, 7543, 922, 220, 16, 13, 20, 3610, 436, 86713, 389, 88171, 459, 1989, 18537, 304, 23223, 13, 1283, 4036, 927, 264, 4948, 315, 420, 3392, 304, 279, 1376, 315, 11626, 505, 279, 1561, 735, 537, 58084, 8732, 268, 8384, 13, 14636, 11, 279, 735, 537, 58084, 66638, 7487, 20162, 311, 279, 9886, 315, 264, 5426, 79353, 1389, 279, 11495, 12758, 1919, 89730, 19853, 627, 791, 12758, 1919, 89730, 8803, 574, 6646, 832, 315, 279, 1455, 11084, 323, 1888, 19167, 304, 8524, 13, 79369, 92551, 51214, 1101, 6818, 311, 7417, 279, 5496, 4787, 315, 1202, 7487, 13, 362, 2978, 11, 264, 8952, 11, 264, 71271, 8952, 11, 264, 28456, 2162, 323, 264, 56226, 1051, 5918, 369, 1124, 627, 8193, 26673, 872, 7126, 596, 2626, 11, 279, 12758, 1919, 89730, 20820, 1101, 5918, 24428, 35159, 11, 902, 20011, 922, 220, 20, 11, 931, 1274, 627, 4599, 6968, 813, 11495, 18537, 11, 79369, 92551, 51214, 7543, 23205, 15055, 315, 3300, 11, 8530, 311, 279, 50008, 315, 813, 1866, 3070, 596, 1664, 33851, 13, 1628, 568, 1047, 264, 3544, 3070, 13, 763, 220, 9714, 20, 11, 79369, 92551, 51214, 12502, 68200, 97415, 5230, 3458, 11, 841, 68, 48869, 546, 12949, 11, 264, 36271, 315, 20680, 6723, 42521, 51214, 48869, 546, 869, 11, 264, 11495, 8690, 29349, 11, 13076, 380, 323, 58738, 897, 380, 11, 279, 19533, 315, 279, 23223, 9877, 39679, 11, 323, 279, 2294, 7561, 3935, 315, 2500, 68200, 48869, 546, 12949, 11, 889, 574, 279, 1646, 369, 279, 19354, 364, 31728, 449, 5250, 14576, 6, 320, 9367, 22, 8, 555, 650, 13, 362, 13, 8409, 869, 13, 2435, 1047, 4848, 2911, 1389, 1403, 13305, 323, 3116, 7724, 627, 50, 13, 350, 5673, 1994, 85, 11, 279, 95835, 452, 13, 480, 13, 13134, 37494, 323, 393, 13, 358, 13, 350, 6583, 1609, 79678, 11, 279, 13820, 358, 13, 469, 13, 3402, 258, 11, 650, 13, 358, 13, 8242, 1609, 869, 11, 650, 13, 423, 13, 3735, 268, 869, 11, 650, 13, 386, 13, 53934, 4816, 85393, 11, 650, 13, 480, 13, 3700, 869, 323, 358, 13, 452, 13, 735, 2453, 4991, 2303, 1053, 4034, 279, 12758, 1919, 89730, 82, 13, 578, 3070, 574, 5552, 311, 1063, 315, 1124, 25, 393, 13, 358, 13, 350, 6583, 1609, 79678, 596, 10868, 96664, 5849, 574, 12502, 311, 79369, 92551, 51214, 596, 80115, 26, 279, 10255, 650, 13, 423, 13, 3735, 268, 869, 596, 7555, 11, 452, 13, 650, 13, 71968, 3265, 1609, 12949, 11, 574, 68200, 97415, 5230, 3458, 596, 80115, 627, 47, 3963, 92551, 51214, 11, 264, 11999, 43927, 30338, 11, 4934, 813, 30968, 311, 32918, 1193, 42870, 13, 2030, 433, 779, 7077, 430, 813, 74665, 10003, 11, 68200, 11, 11299, 304, 3021, 449, 279, 23944, 60166, 380, 20643, 8211, 89392, 11, 279, 40550, 328, 13, 650, 13, 84485, 1543, 258, 1885, 596, 36271, 13, 58733, 430, 1077, 7126, 2643, 539, 3041, 1077, 813, 40149, 311, 32918, 264, 39844, 11, 68200, 574, 1633, 23418, 323, 1524, 11299, 5986, 13, 3277, 79369, 92551, 51214, 5602, 813, 10003, 596, 16066, 11, 682, 813, 26018, 9002, 813, 30968, 6, 2324, 8717, 4745, 627, 791, 19354, 555, 96657, 2192, 4323, 364, 37659, 358, 5783, 12184, 988, 26132, 548, 85, 718, 8683, 20568, 62579, 85, 718, 520, 11291, 76958, 6, 320, 9674, 16, 8, 574, 19426, 555, 393, 13, 386, 13, 12758, 1919, 89730, 304, 279, 1060, 433, 574, 2884, 198, 791, 13306, 315, 68200, 12758, 1919, 587, 12949, 323, 20643, 8211, 89392, 3952, 2035, 304, 7552, 220, 9367, 22, 13, 75116, 320, 43063, 10003, 8, 12502, 279, 10896, 323, 33053, 74529, 23869, 8148, 13, 5414, 10868, 20643, 11, 264, 10896, 11, 3010, 264, 17055, 4539, 261, 323, 459, 54067, 315, 279, 4892, 11, 12502, 386, 31543, 13, 763, 3297, 220, 9378, 19, 11, 16333, 31529, 12502, 279, 30581, 96657, 352, 480, 1018, 12021, 9509, 13, 48740, 13111, 304, 220, 7028, 15, 11, 1364, 84228, 4588, 1389, 1077, 2132, 10177, 574, 279, 11495, 21605, 36769, 267, 11, 264, 30581, 323, 264, 15034, 889, 3549, 45188, 323, 51331, 369, 7923, 34856, 458, 85, 596, 71310, 304, 12366, 13, 79369, 92551, 51214, 1047, 3403, 58321, 315, 11376, 311, 15763, 682, 1521, 3995, 3026, 627, 791, 2768, 2144, 649, 49262, 311, 279, 1648, 12758, 1919, 89730, 7263, 709, 813, 30968, 13, 763, 220, 9378, 18, 11, 79369, 92551, 51214, 6267, 264, 1633, 3544, 323, 6129, 6661, 311, 813, 10003, 75116, 11, 304, 902, 568, 11497, 813, 4623, 315, 46679, 22006, 25, 364, 25821, 374, 539, 264, 1695, 3245, 902, 11384, 53808, 4398, 13, 44026, 2011, 4546, 709, 872, 2911, 323, 3041, 1124, 6873, 11, 719, 814, 527, 539, 520, 682, 54117, 311, 3493, 369, 1124, 3238, 2684, 1051, 279, 2768, 4339, 304, 279, 1890, 6661, 25, 364, 5159, 4623, 574, 311, 1304, 3300, 505, 264, 1633, 3995, 4325, 779, 430, 1148, 574, 4036, 505, 8396, 1053, 1101, 471, 311, 8396, 320, 1820, 1274, 8, 304, 1063, 5505, 14673, 26, 1115, 4623, 706, 2646, 2163, 757, 682, 856, 2324, 24314, 37, 5171, 15846, 555, 1989, 11, 304, 220, 9741, 19, 12758, 1919, 89730, 6137, 311, 6667, 9863, 315, 5426, 8690, 4375, 315, 1989, 13, 5414, 1176, 63948, 1389, 922, 5899, 21154, 25112, 315, 2362, 24113, 97953, 1389, 1051, 11021, 520, 264, 96955, 3157, 3221, 279, 74874, 77811, 85, 22703, 13, 4314, 38940, 84273, 813, 5496, 12, 9949, 3156, 813, 4648, 627, 1688, 1176, 32161, 3217, 323, 62387, 582, 25489, 6677, 304, 279, 26436, 315, 1989, 323, 33687, 555, 264, 5655, 77784, 8430, 11, 12758, 1919, 89730, 6773, 311, 5357, 389, 26984, 4375, 555, 19225, 8690, 13820, 13, 1102, 374, 3967, 430, 79369, 92551, 51214, 1047, 912, 3361, 1989, 6873, 13, 35053, 11, 568, 11021, 4375, 555, 813, 2103, 2697, 22015, 3686, 23944, 59504, 5548, 13, 1666, 264, 6037, 11, 568, 19426, 279, 1455, 5199, 4375, 505, 420, 477, 430, 10255, 627, 52374, 85670, 449, 58953, 4487, 2661, 9438, 6, 320, 9741, 18, 8, 555, 650, 13, 480, 13, 20774, 18339, 89730, 574, 832, 315, 279, 1176, 36692, 19426, 555, 12758, 1919, 89730, 304, 220, 9741, 21, 13, 3011, 1060, 13160, 279, 7342, 315, 279, 12758, 1919, 89730, 19853, 13, 1115, 574, 8272, 555, 279, 7782, 315, 4375, 555, 358, 13, 393, 13, 1183, 332, 98493, 11, 362, 13, 735, 13, 20680, 13075, 869, 11, 735, 13, 362, 13, 1183, 332, 79678, 11, 435, 13, 362, 13, 3320, 16080, 11, 445, 13, 435, 13, 33471, 50931, 323, 3885, 13, 58733, 922, 4375, 555, 735, 13, 393, 13, 19803, 360, 36247, 304, 15704, 11, 12758, 1919, 89730, 4691, 8041, 505, 279, 39211, 16549, 386, 13, 39634, 72, 596, 2911, 311, 7782, 813, 320, 43, 1149, 72, 596, 8, 34133, 13, 14636, 11, 304, 220, 9714, 15, 11, 279, 1176, 990, 555, 279, 364, 47991, 35131, 6, 320, 33, 894, 360, 36247, 8, 1389, 364, 81465, 315, 279, 66102, 16549, 386, 13, 39634, 72, 6, 320, 9741, 16, 8, 1389, 9922, 304, 279, 4526, 13, 2100, 12758, 1919, 89730, 6137, 659, 1752, 26984, 990, 430, 36513, 369, 1690, 1667, 13, 1102, 574, 27946, 323, 539, 6319, 369, 13172, 323, 29488, 13, 1226, 649, 2019, 430, 505, 279, 1633, 7314, 568, 1047, 264, 2867, 4623, 315, 279, 7580, 315, 813, 49326, 627, 47, 3963, 92551, 51214, 46531, 912, 45743, 9021, 13, 1283, 3782, 709, 449, 279, 4623, 315, 6968, 264, 24925, 315, 5426, 36692, 13, 763, 813, 690, 11, 15107, 709, 304, 220, 9714, 15, 11, 1120, 3116, 1667, 1306, 279, 7782, 315, 279, 1176, 36692, 11, 568, 6267, 25, 364, 2520, 757, 11, 889, 36297, 323, 85009, 4501, 16180, 1989, 11, 279, 12474, 6562, 374, 311, 11203, 279, 41582, 369, 264, 586, 12827, 315, 7060, 1989, 11, 15987, 311, 682, 11, 311, 279, 8935, 315, 1690, 323, 17069, 369, 682, 24314, 66875, 1919, 89730, 596, 12410, 323, 10082, 304, 813, 5353, 2873, 15206, 422, 584, 6227, 430, 568, 17551, 279, 41582, 315, 279, 18537, 520, 264, 892, 994, 279, 2978, 315, 8690, 1989, 439, 459, 4113, 323, 5199, 25885, 781, 25111, 1193, 38678, 398, 304, 279, 12737, 315, 279, 2294, 14135, 315, 279, 4410, 26, 42727, 14154, 8690, 1989, 1047, 1027, 4376, 2269, 1813, 10503, 11, 4375, 555, 8690, 13820, 1051, 304, 879, 15661, 304, 8524, 323, 22917, 26, 994, 1070, 1051, 2103, 912, 3402, 258, 11, 912, 8242, 1609, 869, 11, 912, 8409, 869, 11, 912, 28120, 13145, 323, 872, 36692, 11, 2085, 902, 433, 374, 12266, 311, 13085, 8690, 1989, 3432, 13, 1102, 574, 279, 892, 315, 279, 18488, 315, 26623, 1989, 323, 279, 7342, 315, 264, 502, 2978, 315, 8690, 1989, 627, 6, 1981, 27131, 813, 1520, 8690, 1989, 1053, 2646, 617, 10862, 459, 1825, 323, 1949, 10474, 11, 2533, 12758, 1919, 89730, 574, 279, 1193, 320, 269, 4661, 279, 1193, 8, 832, 889, 7396, 4395, 430, 574, 502, 11, 7878, 323, 15325, 304, 8690, 1989, 6, 320, 32, 13, 7505, 30148, 4390, 3947, 1051, 2478, 1972, 43448, 304, 2362, 23223, 889, 3952, 459, 4642, 961, 304, 279, 6439, 315, 3995, 13820, 13, 2435, 10213, 1120, 11021, 36692, 369, 872, 43654, 11, 323, 16495, 311, 2343, 2753, 369, 1124, 13, 27140, 1124, 11, 79369, 92551, 51214, 12758, 1919, 89730, 574, 264, 1972, 36380, 315, 19071, 13, 5414, 21728, 311, 13820, 1051, 2744, 6646, 439, 13548, 4455, 11, 323, 682, 315, 1124, 11, 36467, 323, 50048, 13820, 11, 449, 51517, 30315, 369, 813, 11594, 4339, 25, 364, 40, 1097, 2133, 311, 3780, 701, 19354, 2965, 902, 574, 37622, 6173, 311, 586, 18324, 369, 5127, 13, 763, 220, 9674, 22, 11, 3402, 258, 6267, 311, 12758, 1919, 89730, 922, 813, 19354, 364, 12705, 536, 23184, 1232, 364, 40, 48466, 311, 499, 430, 422, 358, 4662, 433, 11, 1243, 1193, 311, 499, 11, 311, 701, 18537, 11, 1606, 11, 358, 2019, 2085, 1344, 19187, 11, 358, 2980, 433, 264, 2294, 34662, 311, 1518, 856, 4375, 1070, 3238, 53204, 3629, 1903, 62608, 311, 12758, 1919, 89730, 320, 383, 2646, 11021, 36692, 2085, 55309, 8, 323, 39920, 872, 7729, 369, 1461, 11, 28592, 8405, 682, 3284, 1862, 311, 813, 49326, 13, 1628, 279, 7720, 1051, 27848, 13, 79369, 92551, 51214, 539, 1193, 11021, 36692, 11, 719, 1101, 11713, 1124, 11, 8617, 12899, 13820, 2225, 57323, 323, 39075, 11, 902, 5535, 1124, 539, 311, 6904, 389, 279, 36263, 315, 279, 3157, 627, 644, 279, 7640, 315, 12758, 1919, 89730, 279, 33053, 596, 6666, 574, 15871, 10968, 389, 4375, 555, 19225, 1972, 380, 97953, 315, 279, 5209, 323, 2132, 4376, 315, 279, 66089, 9478, 1389, 279, 69985, 388, 320, 1820, 1102, 10670, 1821, 705, 24005, 315, 279, 26623, 20611, 315, 279, 5426, 2978, 11, 902, 4613, 279, 4113, 488, 315, 279, 18537, 596, 4526, 11, 279, 10383, 315, 420, 4526, 389, 279, 4500, 315, 1972, 380, 1989, 11, 323, 1202, 23053, 11, 30191, 323, 16627, 5536, 13, 2030, 304, 279, 220, 9714, 15, 82, 11, 994, 279, 13581, 369, 43359, 6427, 5277, 40374, 6055, 2103, 1550, 539, 3073, 11, 12758, 1919, 89730, 11021, 36692, 304, 279, 4033, 364, 91356, 6, 1742, 11, 323, 505, 279, 3389, 220, 9367, 15, 82, 1389, 4375, 555, 386, 13, 650, 13, 452, 5302, 869, 11, 735, 13, 362, 13, 36170, 869, 258, 11, 650, 13, 362, 13, 8409, 869, 323, 3885, 13, 5112, 12758, 1919, 89730, 6137, 311, 6667, 38940, 11, 323, 304, 279, 220, 9378, 15, 82, 1389, 24699, 627, 66875, 1919, 89730, 1047, 96207, 481, 12945, 13, 1283, 574, 539, 16984, 311, 3780, 4375, 555, 3995, 11, 2103, 9987, 13820, 13, 578, 49449, 315, 279, 1648, 79369, 92551, 51214, 14890, 36692, 527, 3970, 304, 279, 2144, 430, 1690, 4375, 369, 279, 18537, 1051, 2884, 520, 813, 1715, 13, 1628, 14188, 1243, 6463, 3432, 656, 1521, 4375, 14429, 279, 1455, 26192, 390, 2201, 15760, 1759, 315, 8690, 1989, 449, 872, 5435, 477, 32692, 50932, 13, 1283, 11021, 4375, 1524, 994, 12678, 315, 1579, 11447, 1093, 445, 13, 452, 13, 59602, 267, 2303, 11, 889, 1550, 539, 44917, 650, 13, 386, 13, 53934, 4816, 85393, 596, 10597, 36692, 11, 16475, 433, 13, 1283, 1524, 11021, 36692, 430, 1051, 21501, 555, 279, 35379, 11527, 369, 586, 20705, 627, 47, 3963, 92551, 51214, 19426, 36692, 520, 70864, 323, 1314, 304, 279, 42795, 315, 13820, 13, 18156, 568, 11021, 4553, 15661, 25, 304, 220, 9674, 19, 568, 19426, 279, 8877, 441, 24986, 4101, 555, 650, 5168, 13, 6383, 4385, 331, 351, 258, 320, 339, 46004, 36692, 11, 220, 9423, 38940, 323, 80679, 19101, 68782, 705, 323, 304, 220, 9367, 15, 1389, 813, 7904, 4101, 320, 325, 688, 88, 70815, 68782, 570, 2684, 1051, 1101, 927, 80679, 68782, 555, 362, 13, 362, 13, 42521, 869, 304, 12758, 1919, 89730, 596, 4526, 13, 763, 220, 9367, 20, 11, 12758, 1919, 89730, 11021, 220, 4278, 68782, 555, 650, 13, 423, 13, 3735, 268, 869, 11, 2884, 555, 279, 10255, 2391, 264, 8577, 311, 17442, 11, 15212, 11, 12911, 323, 42034, 13, 5659, 650, 13, 386, 13, 53934, 4816, 85393, 79369, 92551, 51214, 19426, 264, 4526, 315, 68782, 430, 568, 1047, 2884, 1418, 3318, 389, 8309, 1147, 304, 800, 36011, 596, 57829, 304, 62725, 13, 650, 13, 480, 13, 3700, 869, 11, 358, 13, 452, 13, 735, 2453, 4991, 2303, 11, 358, 13, 469, 13, 3402, 258, 11, 650, 13, 358, 13, 8242, 1609, 869, 11, 358, 13, 358, 13, 28120, 13145, 323, 650, 13, 362, 13, 8409, 869, 1051, 15609, 304, 813, 4526, 1455, 7373, 323, 555, 872, 1888, 4375, 13, 578, 18537, 574, 70543, 3384, 449, 4375, 555, 13820, 315, 279, 8223, 62655, 323, 279, 1176, 4376, 315, 279, 66089, 24552, 323, 63003, 315, 14154, 8690, 1989, 13, 1115, 56375, 4261, 315, 8690, 1989, 649, 387, 16365, 11, 6612, 27989, 398, 323, 36131, 304, 23223, 11, 304, 279, 12758, 1919, 89730, 19853, 11, 810, 1109, 12660, 775, 627, 2460, 13820, 11, 3995, 323, 11495, 11, 57636, 315, 3515, 872, 36692, 18799, 520, 279, 12758, 1919, 89730, 19853, 1606, 279, 1633, 2144, 315, 12096, 264, 19354, 555, 79369, 92551, 51214, 574, 459, 1180, 315, 586, 18324, 315, 459, 10255, 596, 11005, 13, 2100, 832, 3678, 73312, 788, 893, 9152, 311, 10383, 682, 8690, 72829, 22676, 1989, 323, 3719, 264, 18367, 369, 8690, 586, 9647, 627, 66875, 1919, 89730, 596, 2294, 38559, 374, 813, 653, 30761, 481, 10082, 304, 279, 38586, 315, 279, 8690, 5426, 2978, 315, 19354, 1389, 264, 10082, 430, 51063, 304, 279, 3389, 220, 9741, 15, 82, 323, 574, 11953, 555, 1461, 1555, 813, 2324, 11, 1555, 682, 279, 19622, 323, 14121, 7607, 13, 1226, 649, 2019, 449, 12410, 430, 304, 279, 3389, 66089, 9478, 393, 13, 386, 13, 12758, 1919, 89730, 596, 4443, 19035, 311, 279, 38586, 315, 8690, 72829, 22676, 1989, 574, 25363, 323, 56193, 627, 93702, 315, 813, 802, 55923, 10082, 706, 1027, 34683, 304, 79369, 92551, 51214, 596, 12197, 13, 5810, 374, 832, 315, 1124, 13, 763, 264, 6661, 311, 279, 10255, 432, 8934, 21446, 30105, 220, 972, 7552, 220, 9714, 20, 11, 568, 6267, 25, 364, 644, 279, 1566, 6661, 311, 499, 856, 7645, 2643, 2873, 53990, 31882, 37864, 25, 330, 12487, 584, 1053, 3137, 449, 37679, 1233, 1210, 358, 690, 10552, 25, 1690, 40646, 656, 539, 1390, 311, 4510, 304, 279, 1695, 3938, 315, 8690, 1989, 323, 18046, 430, 422, 1063, 8690, 10255, 7170, 1587, 264, 1695, 19354, 11, 433, 374, 19755, 555, 11677, 323, 568, 690, 5376, 279, 1396, 315, 25098, 511, 1018, 552, 13, 358, 617, 264, 2204, 9647, 11, 6062, 358, 1053, 539, 617, 14890, 8690, 36692, 26, 719, 7170, 358, 1436, 539, 719, 7655, 449, 279, 13363, 10666, 26, 323, 1475, 2450, 11, 1475, 3094, 4741, 374, 1633, 25237, 311, 757, 11, 323, 358, 690, 387, 1633, 6380, 422, 358, 3974, 311, 1518, 994, 1057, 1938, 4131, 3238, 1628, 922, 264, 2305, 3010, 11, 13758, 311, 279, 1890, 3463, 11, 12758, 1919, 89730, 6267, 25, 364, 40, 4457, 3935, 6751, 4510, 304, 856, 3987, 25, 1057, 8690, 2978, 690, 539, 387, 279, 12047, 1389, 433, 574, 13118, 264, 9624, 291, 892, 11, 323, 369, 5115, 264, 1317, 892, 11, 719, 1457, 279, 31349, 374, 33510, 24314, 16366, 10082, 574, 539, 264, 18507, 42779, 8430, 25, 433, 574, 3196, 389, 16994, 22695, 315, 279, 4500, 315, 8690, 72829, 22676, 1989, 11, 389, 264, 5655, 11, 27545, 8830, 315, 5426, 52805, 430, 1051, 1694, 14454, 389, 264, 26623, 8197, 627, 47, 13, 386, 13, 12758, 1919, 89730, 19426, 279, 19354, 364, 39, 11073, 22803, 6, 320, 10750, 17, 8, 555, 35131, 19803, 360, 36247, 304, 220, 9378, 18, 198, 4516, 11, 1203, 304, 220, 9741, 22, 11, 79369, 92551, 51214, 6267, 311, 279, 18921, 30581, 362, 13, 480, 13, 47247, 402, 27782, 25, 364, 63242, 287, 856, 18921, 11, 358, 2854, 65, 398, 2610, 499, 311, 5387, 433, 11, 323, 4619, 6308, 757, 264, 502, 832, 54108, 13, 358, 1205, 14188, 9257, 7138, 11, 6463, 264, 2294, 18528, 11, 6463, 28809, 3177, 11, 6463, 71912, 3238, 12361, 11, 12758, 1919, 89730, 4691, 1461, 311, 43504, 4382, 7138, 11, 1524, 422, 653, 1762, 9007, 434, 287, 11, 364, 8248, 1070, 2011, 387, 8206, 323, 32349, 304, 433, 13, 1628, 32349, 649, 387, 304, 4395, 1389, 420, 374, 279, 10255, 596, 990, 24314, 2028, 5296, 61120, 279, 1633, 37637, 17966, 315, 279, 18488, 315, 279, 18537, 11, 902, 22763, 439, 264, 1121, 315, 42852, 389, 279, 4500, 315, 8690, 5426, 72829, 22676, 1989, 13, 393, 13, 386, 13, 12758, 1919, 89730, 1047, 43410, 1202, 23053, 61555, 1317, 1603, 279, 11341, 315, 20680, 13075, 869, 596, 19354, 364, 791, 432, 15027, 12522, 15936, 6984, 518, 279, 55890, 555, 650, 30149, 44191, 11, 28120, 13145, 11, 8409, 869, 11, 507, 496, 283, 31764, 869, 323, 452, 5302, 869, 1389, 279, 13820, 889, 9152, 311, 1893, 264, 90967, 73764, 315, 8690, 7138, 11, 94165, 279, 32349, 323, 32353, 38088, 304, 433, 627, 47, 3963, 92551, 51214, 1176, 86382, 279, 4623, 315, 6968, 264, 5426, 477, 29036, 1989, 18537, 311, 279, 10255, 650, 13, 480, 13, 20774, 18339, 89730, 323, 33740, 433, 449, 279, 54711, 13708, 304, 264, 61300, 5439, 304, 73276, 389, 220, 1114, 320, 1682, 8, 3297, 11, 220, 9714, 15, 11, 2391, 813, 1176, 8577, 22917, 627, 16366, 29658, 1550, 539, 617, 311, 9203, 420, 690, 13, 79369, 92551, 51214, 5678, 41834, 813, 8063, 1389, 568, 743, 709, 264, 29036, 38921, 18537, 627, 85415, 12518, 555, 393, 13, 386, 13, 12758, 1919, 89730, 649, 1101, 387, 1766, 304, 813, 44818, 449, 6383, 4385, 331, 351, 258, 9002, 279, 73764, 315, 279, 19225, 93991, 9469, 324, 74720, 4208, 315, 220, 9674, 22, 4235, 9674, 23, 369, 279, 55633, 315, 59819, 1389, 264, 4208, 304, 902, 8524, 3952, 59819, 596, 3185, 13, 1952, 6975, 430, 6383, 4385, 331, 351, 258, 574, 2133, 311, 279, 4156, 311, 656, 264, 4101, 315, 36692, 922, 279, 4208, 11, 12758, 1919, 89730, 6267, 311, 279, 9940, 315, 4731, 323, 1989, 650, 5168, 13, 800, 300, 869, 25, 364, 32576, 1193, 304, 279, 29827, 3938, 690, 279, 28235, 1903, 555, 279, 8690, 1274, 387, 26893, 24314, 66875, 1919, 89730, 12090, 430, 6383, 4385, 331, 351, 258, 2343, 264, 3544, 2694, 304, 12178, 369, 813, 990, 25, 364, 11458, 15234, 42990, 264, 4526, 2085, 14392, 1202, 8970, 1253, 387, 11, 6383, 4385, 331, 351, 258, 374, 264, 3169, 315, 10255, 499, 649, 17631, 389, 11, 5423, 2533, 7231, 36692, 927, 311, 879, 6206, 11, 568, 690, 539, 387, 6965, 555, 19301, 15223, 323, 11, 4762, 11, 690, 387, 73354, 3340, 449, 279, 9090, 315, 279, 28235, 315, 1274, 323, 279, 20333, 56375, 54811, 315, 8690, 15201, 323, 1063, 7931, 24314, 10351, 4385, 331, 351, 258, 1047, 264, 2204, 9647, 25, 364, 2170, 369, 701, 6661, 311, 650, 5168, 13, 800, 300, 869, 389, 856, 19354, 499, 5602, 11, 499, 323, 358, 14224, 29395, 264, 2697, 304, 279, 15813, 315, 856, 4375, 323, 264, 2763, 304, 872, 18845, 13, 2684, 374, 4208, 1603, 757, 439, 1603, 459, 10255, 11, 323, 358, 13471, 520, 433, 449, 682, 856, 2643, 26, 3508, 856, 46303, 527, 3831, 477, 1972, 1389, 420, 374, 264, 3488, 315, 856, 11005, 11, 719, 358, 4465, 449, 682, 856, 8333, 323, 100252, 398, 1981, 1270, 644, 5369, 311, 26984, 11, 79369, 92551, 51214, 12758, 1919, 89730, 574, 22815, 6532, 304, 23693, 990, 13, 1283, 574, 459, 99119, 4562, 315, 279, 8690, 13581, 315, 5277, 445, 9146, 323, 279, 8690, 57357, 13581, 505, 279, 1938, 814, 1051, 18538, 323, 20162, 12190, 37498, 11, 12899, 682, 16627, 28271, 13, 1283, 3984, 3769, 13291, 311, 3927, 13820, 323, 279, 23223, 6150, 315, 55143, 11, 83797, 554, 323, 38943, 26, 505, 220, 9714, 24, 568, 574, 264, 4562, 315, 279, 9251, 315, 279, 23223, 17236, 369, 279, 45773, 13, 1283, 574, 1101, 264, 4562, 315, 279, 61783, 315, 279, 23223, 28943, 9304, 323, 279, 20643, 28943, 9304, 13, 79369, 92551, 51214, 387, 593, 70737, 4376, 315, 813, 10736, 311, 48801, 10096, 25, 311, 743, 709, 264, 23756, 369, 9923, 4336, 11, 3995, 2911, 323, 95587, 30968, 315, 43720, 13820, 320, 275, 574, 5918, 304, 220, 7028, 24, 4235, 7529, 17, 555, 279, 11726, 452, 13, 328, 13, 32375, 10470, 3178, 869, 304, 43950, 78277, 52541, 27109, 1237, 369, 8141, 4315, 7487, 323, 8420, 315, 813, 40919, 26, 323, 369, 11006, 279, 18537, 13, 1283, 6688, 24910, 311, 1520, 279, 8689, 315, 15201, 889, 1047, 21536, 304, 279, 24845, 276, 5111, 323, 279, 93991, 9469, 324, 74720, 320, 9674, 22, 12, 9674, 23, 8, 5111, 13, 393, 13, 386, 13, 12758, 1919, 89730, 55855, 1051, 9749, 520, 279, 23223, 28943, 9304, 323, 279, 20643, 28943, 9304, 627, 47, 3963, 92551, 51214, 2646, 16436, 311, 3219, 6020, 12576, 311, 13820, 323, 1023, 32177, 13, 1283, 3952, 1695, 2512, 315, 279, 3300, 22747, 315, 97953, 889, 86382, 872, 19523, 311, 1461, 449, 12410, 13, 1283, 19352, 48907, 3300, 311, 813, 1695, 32853, 358, 13, 452, 13, 735, 2453, 4991, 2303, 11, 659, 16117, 9087, 650, 13, 480, 13, 20774, 18339, 89730, 11, 735, 13, 362, 13, 1183, 332, 79678, 11, 386, 13, 735, 13, 29041, 347, 83, 323, 1690, 3885, 627, 27368, 3058, 79369, 323, 74529, 12758, 1919, 89730, 18538, 279, 44312, 9469, 265, 1919, 89730, 1611, 2642, 9976, 9607, 3635, 6150, 304, 23223, 13, 79369, 92551, 51214, 3952, 813, 21967, 1633, 14243, 13, 2468, 1176, 6989, 449, 47842, 1474, 1088, 2911, 304, 3974, 8982, 1051, 4856, 28694, 11, 323, 79369, 92551, 51214, 3288, 279, 2010, 13943, 423, 11606, 13, 10995, 869, 22917, 520, 813, 1866, 20900, 779, 568, 1436, 11537, 553, 5678, 449, 279, 12917, 1920, 304, 4528, 8853, 13, 763, 5369, 311, 4689, 15223, 11, 2911, 1051, 15972, 44948, 13, 578, 2978, 11, 477, 279, 364, 82409, 369, 279, 47842, 1474, 1088, 518, 12457, 264, 3544, 9998, 3838, 449, 264, 6908, 13863, 11, 1405, 220, 10132, 45172, 315, 2225, 76032, 20041, 323, 12439, 11, 323, 304, 279, 4216, 220, 9378, 15, 82, 79369, 92551, 51214, 5918, 264, 8952, 449, 27219, 49493, 28036, 520, 813, 1866, 20900, 627, 28205, 2298, 425, 315, 279, 2978, 11, 902, 6137, 304, 279, 220, 9714, 15, 82, 11, 8738, 6957, 79369, 92551, 51214, 596, 2324, 323, 1306, 813, 4648, 13, 763, 813, 690, 79369, 92551, 51214, 2163, 1633, 28771, 10736, 369, 279, 2978, 369, 279, 47842, 323, 30355, 13, 30857, 323, 7724, 1053, 387, 7263, 709, 12222, 279, 4325, 315, 59139, 323, 5371, 264, 4913, 13, 12758, 1919, 89730, 4183, 279, 1888, 13639, 11, 2751, 73734, 449, 279, 12917, 5528, 11, 323, 1903, 2771, 430, 279, 45172, 1051, 1664, 23114, 323, 28392, 291, 13, 1952, 1855, 4034, 311, 279, 2978, 568, 4024, 4883, 279, 6989, 323, 35936, 2391, 538, 4207, 323, 574, 2744, 3118, 520, 40786, 627, 644, 220, 9674, 16, 11, 389, 279, 20770, 315, 79369, 323, 85098, 12758, 1919, 89730, 11, 264, 21765, 574, 5918, 1990, 22300, 3145, 74, 12874, 6825, 323, 2722, 266, 3545, 3919, 99575, 389, 279, 2816, 315, 459, 6931, 832, 430, 1047, 1027, 5918, 709, 304, 279, 8223, 62655, 9478, 13, 763, 220, 9674, 15, 4235, 9674, 16, 279, 11726, 362, 13, 328, 13, 29549, 52541, 20968, 1403, 14016, 449, 21765, 5438, 288, 13176, 22300, 3145, 74, 12874, 6825, 323, 2722, 266, 3545, 3919, 99575, 389, 279, 2816, 15075, 555, 279, 12758, 1919, 89730, 82, 5423, 369, 279, 27204, 315, 279, 21765, 26, 279, 62716, 315, 279, 4857, 505, 279, 3185, 315, 2722, 266, 3545, 3919, 99575, 574, 5918, 1139, 279, 21625, 352, 12279, 269, 347, 9935, 1828, 311, 279, 21970, 320, 9800, 19, 4235, 9800, 23, 8, 323, 6319, 304, 264, 24364, 45872, 32986, 1742, 13, 2684, 1051, 20021, 4871, 279, 21765, 13, 15483, 16036, 9293, 6425, 374, 5016, 369, 23223, 13, 578, 502, 6070, 574, 2663, 12758, 1919, 89730, 16542, 627, 791, 1398, 10609, 5382, 10685, 19170, 23693, 439, 364, 911, 266, 3159, 788, 6299, 323, 54811, 6832, 9395, 374, 279, 586, 1695, 3238, 3161, 5905, 311, 279, 2324, 315, 79369, 92551, 51214, 12758, 1919, 89730, 584, 649, 923, 25, 364, 438, 902, 690, 2646, 387, 25565, 24314, 17279, 44075, 4655, 7094, 43293, 36497, 106436, 4329, 1360, 22442, 311, 387, 29056, 198, 19871, 102406, 72119, 36497, 106436, 4329, 7281, 26692, 315, 31013, 8524, 198, 1360, 22442, 311, 387, 29056, 128000, 51329, 20854, 3445, 24854, 1389, 323, 433, 44164, 4999, 26450, 19645, 85588, 81192, 64469, 9323, 97036, 49, 1641, 648, 198, 97036, 315, 9096, 25, 11821, 47059, 323, 31135, 44202, 3727, 12266, 279, 52945, 315, 12062, 555, 4208, 627, 52961, 11903, 81390, 304, 38269, 527, 7554, 279, 1486, 323, 690, 2646, 3243, 264, 1695, 3568, 13, 8595, 30, 9393, 279, 7665, 9323, 374, 810, 922, 11759, 1109, 28989, 11, 14238, 28253, 97982, 648, 627, 8607, 1667, 4227, 304, 38269, 994, 64850, 7462, 1105, 574, 4872, 315, 279, 7665, 9849, 568, 36014, 813, 2010, 304, 51978, 520, 279, 5652, 69578, 484, 1037, 315, 86566, 1512, 292, 61029, 505, 4028, 279, 13740, 13, 1115, 574, 2391, 279, 39510, 3549, 555, 279, 11223, 3254, 11667, 323, 13527, 596, 14076, 311, 433, 627, 10227, 8013, 527, 459, 13218, 1274, 1359, 568, 20536, 449, 264, 10845, 416, 14362, 773, 13, 1666, 422, 430, 11497, 4395, 1389, 323, 304, 264, 1648, 433, 1550, 7041, 430, 13, 1226, 8013, 1389, 477, 520, 3325, 220, 4103, 824, 2960, 315, 603, 889, 527, 514, 22292, 1389, 527, 5439, 1022, 439, 5906, 30322, 304, 279, 2294, 7665, 18427, 627, 1271, 7665, 6548, 433, 574, 3596, 8617, 13, 18374, 279, 29859, 19037, 11, 279, 5567, 82, 1120, 1541, 956, 1093, 18667, 304, 13, 2435, 1781, 814, 2351, 1694, 3309, 1148, 311, 656, 555, 13697, 88, 48512, 11, 8104, 8753, 323, 6063, 48512, 627, 2028, 40543, 374, 520, 279, 3789, 315, 3432, 596, 24854, 11501, 304, 38269, 1405, 11, 87799, 1063, 96691, 29412, 42445, 11, 584, 5101, 311, 387, 14836, 369, 264, 34616, 8060, 315, 38883, 49892, 13, 1226, 617, 9152, 311, 13194, 1057, 7665, 8717, 11, 539, 1120, 369, 14718, 264, 4754, 7100, 5817, 2191, 11, 719, 369, 63686, 279, 7665, 9323, 596, 320, 39907, 8, 68971, 98741, 1389, 9096, 323, 44202, 304, 3596, 1824, 70315, 11552, 627, 1271, 20026, 764, 458, 6548, 279, 10013, 11105, 459, 10728, 430, 279, 6560, 706, 65397, 13, 18374, 1824, 70315, 11552, 11, 311, 902, 584, 8667, 709, 927, 264, 4101, 315, 76477, 11, 574, 7060, 3156, 7462, 1105, 11, 16183, 7129, 34975, 75, 323, 85807, 386, 3328, 11588, 2751, 6129, 922, 18052, 627, 94049, 2011, 1977, 264, 3169, 315, 3723, 4273, 315, 4606, 13, 763, 420, 1648, 1193, 690, 11758, 315, 11990, 315, 311, 28257, 387, 3025, 311, 49655, 279, 4382, 94898, 323, 16388, 902, 1304, 2324, 5922, 5496, 24314, 2028, 574, 1405, 279, 4725, 5133, 1990, 11759, 323, 28989, 574, 6656, 389, 1202, 2010, 13, 23886, 11759, 6244, 279, 5696, 13, 2057, 15253, 7100, 18052, 2631, 3831, 5054, 690, 11, 539, 3325, 304, 76722, 386, 5418, 496, 4970, 596, 3254, 11667, 13, 5884, 11774, 1389, 25431, 11, 369, 3187, 1389, 1051, 52556, 555, 5054, 690, 627, 791, 18140, 83417, 3432, 1606, 315, 11759, 11, 8994, 682, 279, 7100, 14015, 316, 323, 73623, 2191, 584, 1373, 922, 7446, 304, 279, 8013, 86566, 1512, 292, 3577, 13, 1226, 1051, 3309, 1317, 4227, 433, 1053, 387, 2103, 16381, 13, 1666, 279, 1667, 5946, 584, 1051, 3309, 15870, 433, 1053, 387, 5710, 2949, 4038, 13, 4800, 279, 46163, 527, 10209, 2753, 1109, 264, 18140, 311, 279, 31123, 627, 4599, 25431, 574, 1389, 26681, 7162, 1389, 16584, 311, 279, 18140, 8855, 994, 3352, 4501, 12153, 311, 37586, 11, 433, 574, 264, 5054, 5155, 1389, 279, 1890, 5155, 902, 711, 552, 7100, 8903, 311, 2567, 433, 1070, 13, 19234, 5544, 7462, 1105, 11, 34975, 75, 323, 386, 3328, 11588, 11, 18052, 1705, 682, 11, 1051, 539, 922, 311, 1095, 5694, 387, 49230, 627, 29690, 1268, 34975, 75, 11713, 279, 9473, 4478, 369, 279, 66121, 6460, 6063, 66535, 4075, 311, 387, 832, 15548, 19101, 449, 279, 34415, 4075, 8994, 279, 8196, 7100, 52819, 30, 2100, 1790, 369, 279, 282, 2364, 24589, 315, 279, 2362, 47407, 17469, 4999, 1687, 1051, 3309, 430, 18157, 323, 34411, 323, 14990, 1053, 387, 36574, 704, 315, 279, 18140, 719, 11759, 90548, 311, 2567, 1124, 1070, 13, 578, 1890, 690, 3621, 449, 15704, 596, 5108, 11501, 627, 4438, 59560, 430, 7665, 18052, 574, 9405, 704, 315, 4208, 323, 6222, 555, 279, 12474, 315, 8013, 23757, 13, 78918, 86566, 1512, 1233, 781, 70036, 1694, 31256, 430, 58274, 574, 4315, 279, 6522, 20026, 764, 3742, 994, 568, 2663, 369, 264, 502, 3445, 311, 6144, 9096, 11, 7296, 323, 11542, 25, 330, 3923, 374, 420, 46384, 40239, 7673, 568, 4691, 627, 12348, 374, 311, 312, 40779, 279, 7665, 3070, 11, 477, 439, 1790, 315, 433, 439, 584, 649, 11, 323, 3493, 433, 449, 264, 6070, 1234, 902, 433, 649, 44935, 304, 9096, 11, 304, 7296, 323, 304, 11542, 627, 10944, 2011, 1977, 264, 3169, 315, 3723, 4273, 315, 4606, 13, 763, 420, 1648, 1193, 690, 11758, 315, 11990, 315, 311, 28257, 387, 3025, 311, 49655, 279, 4382, 94898, 323, 16388, 902, 1304, 2324, 5922, 5496, 10246, 36, 44486, 1512, 1233, 12491, 1694, 31256, 315, 430, 55331, 13, 763, 872, 74424, 311, 834, 402, 363, 433, 814, 3802, 58274, 2646, 70856, 675, 264, 3254, 11667, 477, 60327, 330, 2957, 2258, 38269, 89740, 1, 13697, 287, 279, 8013, 627, 91838, 374, 28495, 369, 264, 6696, 3568, 311, 6273, 323, 46113, 279, 3254, 3157, 323, 5255, 279, 35869, 11552, 627, 32, 4317, 11, 719, 584, 2646, 8667, 709, 369, 279, 10013, 439, 264, 5054, 2447, 11, 814, 29011, 13, 8489, 11, 584, 1550, 3604, 13, 1102, 574, 2663, 279, 386, 5418, 496, 4970, 52131, 902, 28379, 279, 2362, 7665, 12332, 439, 279, 7665, 9323, 323, 11784, 7665, 33779, 323, 33384, 11552, 627, 1687, 8013, 22126, 1022, 505, 279, 3254, 11667, 323, 279, 3674, 12735, 23442, 5318, 466, 826, 315, 264, 1403, 30699, 4606, 13, 320, 7816, 2010, 939, 1802, 505, 386, 7462, 1105, 6266, 2030, 430, 574, 1243, 13, 1226, 1051, 2262, 311, 1099, 23568, 389, 279, 70513, 1418, 13633, 264, 1584, 520, 4726, 18052, 627, 4897, 4579, 1773, 4193, 3252, 706, 1457, 7263, 603, 311, 279, 42834, 1405, 5054, 26314, 17302, 82, 7100, 8815, 13, 13527, 374, 28495, 369, 264, 6696, 3568, 311, 6273, 323, 46113, 279, 3254, 3157, 323, 5255, 279, 35869, 11552, 13, 2030, 10013, 11759, 43446, 1070, 374, 912, 6140, 315, 430, 304, 15325, 3878, 6062, 1148, 374, 279, 1486, 315, 16250, 5380, 97036, 690, 3243, 422, 584, 733, 555, 47891, 13, 10057, 690, 2019, 13490, 51939, 13086, 311, 13527, 374, 2753, 3062, 1109, 279, 27498, 10013, 2447, 13, 38269, 19287, 1755, 1057, 14286, 311, 5425, 279, 5613, 422, 279, 502, 5718, 990, 2403, 279, 4409, 13, 578, 10013, 649, 65893, 1057, 13560, 5944, 323, 5376, 1057, 3691, 7729, 627, 1687, 527, 922, 311, 4048, 279, 2653, 1648, 430, 279, 10013, 3604, 13919, 1389, 36297, 13919, 1389, 304, 11821, 47059, 323, 22923, 279, 4113, 10728, 315, 279, 4279, 3157, 902, 374, 311, 9041, 44202, 555, 59207, 287, 8753, 33489, 311, 6063, 5064, 304, 264, 1648, 430, 3727, 12266, 52945, 12062, 555, 4208, 13, 1115, 8625, 10748, 11759, 1701, 28989, 439, 264, 5507, 627, 791, 10013, 38048, 706, 1202, 11774, 11, 719, 279, 7665, 10728, 374, 3318, 13, 35979, 323, 28989, 1389, 279, 28497, 8197, 315, 3432, 596, 10013, 2533, 1202, 54529, 220, 2031, 1667, 4227, 1389, 733, 1450, 304, 1450, 11, 719, 279, 11759, 2103, 20722, 279, 28989, 11, 539, 279, 1023, 1648, 4883, 627, 91838, 706, 54221, 420, 10728, 1389, 8051, 220, 2166, 824, 2960, 315, 603, 527, 19065, 1752, 1389, 323, 584, 527, 4762, 922, 311, 2343, 459, 23205, 3430, 627, 47493, 2740, 11, 994, 584, 3719, 25181, 584, 527, 4461, 311, 387, 304, 279, 11660, 2361, 315, 10923, 7100, 74424, 311, 10134, 279, 1920, 627, 4599, 499, 2187, 13510, 7100, 58701, 311, 6678, 11759, 1389, 958, 48260, 10057, 4131, 311, 4059, 1389, 279, 3938, 649, 387, 42351, 13, 3011, 11, 1306, 682, 11, 374, 3249, 279, 10013, 574, 36592, 627, 53043, 4758, 16666, 25, 1560, 809, 64, 77302, 63696, 198, 39907, 927, 4317, 14630, 3634, 10396, 198, 51329, 20854, 374, 1457, 682, 922, 279, 1989, 315, 279, 3284, 198, 32449, 38997, 3925, 25, 279, 1938, 459, 386, 19046, 24164, 7354, 5119, 198, 90999, 11358, 437, 1584, 709, 13, 4946, 814, 4498, 5380, 16, 12535, 389, 330, 51329, 20854, 3445, 24854, 1389, 323, 433, 44164, 25765, 23083, 10690, 765, 6250, 220, 1114, 11, 220, 679, 22, 520, 220, 21, 25, 1114, 9012, 9432, 71744, 264, 3224, 477, 459, 15360, 7612, 2555, 1093, 264, 1403, 45726, 8857, 311, 1304, 264, 3682, 25543, 2349, 13, 1666, 264, 264, 2536, 7826, 1018, 358, 2846, 1344, 370, 7881, 15386, 430, 220, 4103, 4, 374, 33398, 439, 459, 1558, 25947, 481, 35381, 311, 1304, 279, 11191, 27743, 4442, 1694, 59674, 420, 2046, 11, 1095, 7636, 279, 5129, 9860, 2068, 315, 24854, 2345, 19221, 477, 8579, 13, 128000, 21994, 320, 42, 49358, 30960, 21215, 340, 5971, 320, 42, 49358, 3735, 3852, 72, 340, 42, 49358, 64782, 14172, 28187, 320, 11356, 220, 20, 11, 220, 10562, 23, 1389, 5587, 220, 975, 11, 220, 9367, 18, 8, 574, 264, 30191, 28941, 11, 264, 63100, 7061, 323, 83815, 596, 1401, 2679, 77828, 13, 1183, 2692, 439, 264, 55475, 11, 659, 88781, 439, 264, 5054, 46215, 11, 323, 459, 47302, 315, 279, 7327, 22938, 5794, 596, 10229, 11, 28187, 6244, 8173, 304, 3674, 2349, 2391, 813, 12374, 7978, 13, 30538, 12588, 813, 10896, 349, 304, 28310, 689, 505, 279, 3907, 315, 622, 7304, 304, 220, 10336, 16, 11, 28187, 574, 22163, 439, 6576, 315, 279, 71636, 258, 10782, 29931, 2234, 11, 264, 6063, 17222, 13, 2684, 568, 18824, 291, 279, 3268, 315, 76847, 2403, 279, 2394, 15950, 3109, 304, 459, 28144, 3330, 13, 1115, 6197, 311, 813, 19949, 49579, 28187, 315, 1694, 264, 330, 3705, 16156, 1, 323, 311, 813, 1694, 67094, 582, 1534, 13, 28187, 2163, 369, 12366, 1405, 568, 8738, 311, 7831, 65506, 505, 279, 2394, 15950, 323, 279, 8753, 17047, 627, 12331, 87, 8040, 813, 30191, 26018, 927, 264, 4261, 315, 3116, 11026, 7314, 304, 220, 10336, 18, 13, 1283, 60394, 813, 26018, 449, 279, 14944, 311, 34929, 349, 19602, 7487, 477, 9511, 388, 505, 279, 41067, 34775, 315, 66089, 9478, 4606, 13, 1283, 18908, 430, 304, 2015, 311, 91225, 575, 349, 22706, 505, 7100, 55949, 11, 264, 3674, 14110, 574, 4460, 13, 578, 74389, 1121, 1053, 5276, 279, 6484, 7100, 14726, 11, 323, 1893, 264, 8396, 304, 902, 3424, 11, 8104, 279, 3445, 315, 5788, 1053, 912, 5129, 387, 5762, 38171, 13, 28187, 596, 26018, 1051, 8040, 304, 3345, 20632, 449, 80474, 3365, 2053, 13, 32255, 814, 5343, 459, 16540, 315, 3823, 20167, 367, 323, 43379, 950, 3769, 2191, 13, 28187, 323, 3365, 2053, 6, 11376, 574, 264, 32227, 3769, 380, 23692, 315, 3823, 7138, 323, 4500, 2949, 7138, 430, 2663, 369, 14110, 13, 1102, 15609, 264, 3769, 380, 1684, 315, 3925, 11, 3196, 389, 279, 43379, 292, 11, 430, 7396, 28187, 596, 10334, 315, 5054, 8752, 323, 813, 1650, 369, 14110, 13, 578, 23692, 39575, 5196, 1606, 315, 1202, 10334, 315, 41548, 907, 11, 902, 50697, 430, 279, 12205, 315, 41067, 34775, 99970, 21742, 505, 279, 40761, 315, 9511, 388, 627, 12331, 87, 596, 6492, 315, 3925, 5602, 3823, 4500, 439, 31965, 4245, 311, 264, 4101, 315, 538, 28970, 1990, 279, 17864, 538, 11, 1884, 889, 15575, 279, 3445, 315, 5788, 13, 2057, 28187, 11, 95450, 90213, 11, 4363, 7980, 323, 87408, 1051, 281, 3847, 2403, 279, 21989, 3318, 538, 13, 1115, 3802, 374, 66766, 709, 304, 279, 8736, 1584, 315, 578, 37961, 40461, 78, 25, 330, 791, 3925, 315, 682, 305, 411, 14200, 6484, 8396, 374, 279, 3925, 315, 538, 14993, 1210, 28187, 19698, 279, 58964, 315, 32682, 1555, 264, 7487, 6, 14110, 430, 1053, 3063, 311, 264, 8791, 48748, 330, 1058, 1752, 8396, 1, 1405, 11, 4184, 311, 28187, 11, 330, 16455, 990, 4184, 311, 872, 5845, 323, 636, 4184, 311, 872, 3966, 1, 323, 330, 258, 902, 279, 1949, 4500, 315, 1855, 374, 279, 3044, 369, 279, 1949, 4500, 315, 682, 10246, 16, 13, 16, 44026, 198, 16, 13, 17, 11930, 198, 16, 13, 18, 41576, 198, 16, 13, 19, 12517, 2324, 198, 16, 13, 20, 25929, 2324, 198, 16, 13, 21, 88654, 2436, 389, 28187, 596, 3463, 198, 16, 13, 22, 28187, 596, 2806, 315, 11346, 198, 16, 13, 23, 34307, 2428, 315, 32682, 198, 17, 28187, 596, 10383, 198, 20, 13, 16, 62926, 5814, 323, 2930, 22755, 198, 20, 13, 17, 12371, 67245, 198, 20, 13, 18, 5896, 27383, 198, 20, 13, 19, 68198, 10925, 198, 16366, 11376, 323, 52805, 14948, 36011, 63912, 13, 63912, 43603, 28187, 596, 11376, 11, 719, 1903, 3738, 34074, 304, 70050, 26018, 323, 6725, 323, 93167, 279, 1176, 50315, 14110, 13, 83815, 11, 439, 16365, 323, 11798, 555, 63912, 19543, 304, 90364, 2585, 13, 63912, 596, 23692, 315, 83815, 374, 6118, 14183, 311, 439, 83815, 8288, 101998, 2191, 13, 4427, 18046, 430, 63912, 596, 6325, 1051, 40240, 449, 28187, 596, 1684, 11, 4869, 420, 374, 3917, 311, 11249, 13, 578, 81359, 315, 279, 19953, 9323, 11, 279, 7928, 315, 682, 62520, 9478, 41289, 991, 19505, 304, 220, 2550, 16, 11, 574, 53580, 555, 279, 31085, 315, 70050, 61911, 6957, 18516, 4606, 13, 1115, 31085, 706, 1027, 8272, 555, 18336, 31343, 304, 1023, 50315, 5961, 2737, 5734, 11, 91850, 323, 23315, 13, 578, 8060, 315, 83815, 477, 83815, 8288, 101998, 2191, 574, 539, 15871, 4245, 311, 1202, 5906, 5242, 555, 63912, 11, 98541, 47765, 477, 3885, 13, 1102, 99618, 505, 279, 41903, 323, 12624, 1234, 79, 6258, 826, 315, 83815, 11, 2737, 1202, 52382, 38914, 2191, 11, 1202, 15507, 311, 30191, 9349, 11, 323, 1202, 48008, 7100, 26018, 627, 42, 49358, 64782, 14172, 28187, 574, 279, 4948, 315, 8254, 2911, 304, 264, 13653, 3070, 304, 350, 7401, 11, 38894, 315, 279, 28636, 18452, 483, 11, 304, 279, 15422, 315, 2394, 29578, 13, 5414, 7126, 11, 64782, 14172, 28187, 320, 11242, 22, 4235, 10750, 23, 705, 58842, 505, 264, 1584, 315, 436, 12806, 285, 11, 16489, 311, 32186, 11, 8994, 264, 409, 4633, 31954, 323, 66939, 315, 92931, 83936, 1778, 439, 11119, 71237, 323, 98989, 2933, 13, 64782, 14172, 28187, 574, 9405, 65466, 331, 301, 8613, 451, 46181, 11, 4538, 315, 68290, 8613, 451, 46181, 320, 11771, 18, 12, 5245, 19, 8, 323, 7555, 55492, 445, 58554, 320, 10005, 18, 12, 10828, 18, 705, 719, 994, 279, 9052, 2394, 15950, 11527, 834, 21642, 813, 2383, 6725, 439, 264, 8117, 11, 568, 16489, 311, 36302, 68913, 11, 279, 2394, 15950, 3314, 596, 4033, 60753, 13901, 11, 311, 8895, 9610, 439, 4562, 315, 279, 83081, 23413, 304, 430, 47904, 13041, 16879, 1614, 13, 5414, 6691, 574, 74310, 6672, 308, 8047, 8612, 10481, 320, 11256, 23, 4235, 9714, 18, 705, 1101, 505, 264, 1664, 8599, 3070, 627, 12331, 87, 596, 6691, 16489, 1203, 311, 64283, 7214, 1306, 279, 4648, 315, 1077, 10177, 304, 220, 10750, 20, 323, 28187, 9539, 16654, 1063, 38001, 304, 2394, 15950, 8396, 1606, 315, 813, 22277, 33472, 13, 1115, 374, 1455, 9539, 3970, 304, 279, 2144, 430, 28187, 596, 574, 779, 84099, 304, 279, 2126, 1303, 315, 813, 3938, 42447, 11, 52179, 6675, 4410, 764, 36749, 627, 791, 36088, 35131, 28187, 627, 42, 49358, 28187, 574, 2162, 1355, 971, 42831, 3156, 279, 4325, 315, 220, 1032, 994, 568, 10862, 350, 7401, 46631, 46523, 2411, 13, 4702, 1603, 568, 2163, 28187, 6267, 459, 9071, 11, 578, 9323, 315, 7984, 648, 3078, 3161, 3771, 11, 902, 8710, 1461, 311, 387, 264, 1732, 449, 264, 5655, 323, 16614, 10082, 304, 4359, 8032, 16, 60, 1283, 1243, 37191, 11, 520, 4325, 220, 1114, 11, 311, 4007, 2383, 520, 279, 3907, 315, 13789, 77, 13, 18185, 19762, 311, 4007, 19675, 323, 17649, 11, 813, 7126, 834, 21642, 433, 11, 35090, 35131, 1053, 387, 12153, 311, 1862, 5678, 439, 264, 18640, 13, 1283, 11096, 279, 350, 7401, 81400, 10349, 323, 520, 832, 1486, 10434, 439, 1202, 4872, 719, 813, 28711, 16654, 439, 264, 1121, 13, 578, 1828, 1060, 11, 813, 7126, 1047, 1461, 8481, 311, 279, 47999, 88409, 94144, 12, 65715, 37714, 304, 20437, 13, 2468, 430, 892, 11, 28187, 6267, 45319, 922, 2324, 902, 12131, 468, 53470, 13781, 12090, 16805, 1461, 2133, 1555, 264, 18330, 11501, 8032, 17, 60, 1556, 3187, 315, 420, 374, 264, 33487, 505, 813, 1514, 507, 51835, 336, 58, 18, 933, 81394, 819, 60150, 811, 10205, 323, 5266, 856, 35202, 345, 25503, 358, 690, 733, 13088, 323, 856, 4851, 690, 539, 2349, 29057, 627, 10031, 420, 20827, 5380, 791, 6342, 315, 27394, 198, 63578, 433, 311, 757, 627, 644, 264, 6661, 311, 813, 7126, 11, 28187, 16964, 279, 9358, 28970, 568, 4024, 1555, 323, 3249, 813, 12034, 6656, 311, 19675, 58, 19, 60, 1283, 11096, 279, 12960, 315, 4236, 323, 3995, 45724, 3967, 439, 279, 330, 41672, 71217, 301, 5493, 498, 5575, 61787, 323, 23348, 27605, 287, 85550, 3926, 8977, 35638, 323, 52210, 79701, 11, 304, 14076, 311, 480, 1196, 1006, 13, 71217, 301, 11, 872, 11326, 13, 1789, 1690, 315, 1124, 11, 279, 779, 19434, 2163, 11529, 797, 301, 5493, 11, 71217, 301, 596, 43379, 950, 1749, 11, 19180, 505, 1202, 70634, 2262, 11, 3984, 264, 8147, 10500, 369, 279, 43665, 315, 9749, 13901, 323, 11759, 13, 4427, 3697, 315, 420, 12960, 24465, 459, 56203, 1990, 1772, 6830, 2889, 41885, 1122, 19675, 323, 1772, 11529, 797, 70664, 19675, 13, 13596, 13566, 71217, 70664, 11, 7639, 65292, 1215, 11, 9435, 71217, 70664, 19347, 323, 18784, 430, 23351, 12660, 2875, 315, 99172, 4633, 37374, 2191, 574, 11679, 42914, 13, 5414, 6325, 1051, 539, 11928, 555, 1455, 315, 813, 18105, 26, 38330, 11, 65292, 1215, 596, 2363, 574, 279, 1925, 2944, 28187, 23838, 279, 3926, 8977, 35638, 1122, 1684, 323, 8040, 279, 6913, 7434, 315, 13970, 3769, 2191, 627, 644, 220, 10336, 16, 11, 28187, 15662, 264, 10896, 349, 449, 279, 37445, 578, 56180, 28232, 279, 4829, 511, 1269, 276, 323, 40467, 554, 276, 46969, 315, 22037, 11, 719, 14976, 433, 311, 279, 3907, 315, 622, 7304, 11, 1606, 813, 3958, 17444, 439, 264, 13566, 71217, 70664, 18336, 1053, 13194, 1461, 304, 20437, 627, 4599, 813, 36528, 11, 52210, 79701, 11, 574, 27292, 505, 80474, 13299, 321, 50222, 1026, 6, 19675, 22291, 304, 220, 10336, 17, 11, 28187, 23838, 19675, 369, 30104, 323, 304, 220, 10336, 17, 574, 12146, 311, 4600, 279, 71636, 258, 10782, 29931, 2234, 11, 264, 18336, 79158, 17222, 13, 4740, 279, 17222, 574, 9495, 1523, 304, 220, 10336, 18, 11, 311, 264, 3544, 13112, 11, 4245, 311, 28187, 596, 26885, 449, 3109, 272, 27627, 11, 28187, 6052, 311, 19675, 11, 6656, 311, 5054, 55280, 11, 323, 1903, 813, 5496, 439, 264, 46209, 23672, 13, 28187, 574, 5246, 9770, 1139, 61087, 11, 2555, 568, 1053, 656, 3629, 439, 264, 1121, 315, 813, 6325, 627, 791, 37961, 40461, 78, 902, 574, 4332, 304, 10057, 2391, 279, 14110, 315, 220, 10336, 23, 198, 12331, 87, 1176, 7882, 311, 12366, 11, 1405, 568, 312, 5773, 838, 13148, 813, 5133, 449, 79701, 323, 279, 13566, 71217, 301, 5493, 11, 323, 6267, 813, 12366, 96433, 25207, 902, 8854, 439, 279, 16188, 1234, 79, 6258, 826, 315, 279, 37961, 40461, 78, 13, 763, 1884, 79688, 11, 28187, 60515, 279, 23035, 430, 279, 2394, 15950, 3109, 11, 1555, 1202, 64931, 315, 8431, 42832, 11, 649, 8854, 439, 279, 7458, 369, 22785, 3674, 2349, 13, 1283, 1101, 11054, 279, 88347, 4856, 1109, 279, 2394, 15950, 8431, 42832, 439, 279, 7458, 1555, 902, 2349, 1436, 12446, 13, 1283, 5602, 430, 2349, 439, 1694, 89589, 1555, 264, 3674, 14110, 13, 1102, 574, 304, 12366, 430, 568, 2322, 323, 6137, 3318, 449, 813, 51263, 3345, 4333, 323, 11430, 859, 80474, 3365, 2053, 11, 264, 11411, 50315, 11, 889, 3169, 839, 28187, 596, 2802, 304, 279, 6671, 315, 279, 3318, 538, 323, 33687, 28187, 596, 2802, 304, 28989, 13, 4740, 568, 574, 9770, 311, 5387, 12366, 1606, 315, 813, 43422, 11, 28187, 323, 3365, 2053, 7882, 311, 38269, 11, 34061, 627, 3947, 814, 1080, 2695, 5646, 578, 6063, 14123, 2508, 11, 264, 1156, 44661, 19347, 315, 279, 19675, 315, 52210, 79701, 11, 71217, 301, 11, 323, 279, 13566, 71217, 301, 5493, 13, 28187, 1828, 6267, 578, 70274, 315, 46969, 320, 10336, 22, 705, 264, 43665, 315, 8753, 41289, 3463, 13, 4314, 4375, 17551, 279, 16665, 369, 28187, 323, 3365, 2053, 6, 1455, 11495, 990, 11, 578, 37961, 40461, 78, 11, 1176, 4756, 389, 7552, 220, 1691, 11, 220, 10336, 23, 13, 1102, 1047, 1027, 44224, 555, 279, 37961, 9130, 320, 70614, 11, 279, 9130, 315, 279, 4702, 705, 459, 7471, 315, 6063, 4046, 76, 5346, 5512, 8884, 28187, 1047, 16489, 304, 7295, 627, 4897, 1060, 4606, 10534, 30191, 96710, 22510, 26, 264, 3318, 15144, 7351, 31589, 2410, 505, 6342, 12140, 67954, 304, 9822, 323, 18719, 28187, 311, 471, 311, 12366, 13, 3277, 420, 3109, 29368, 304, 220, 10336, 24, 11, 28187, 7882, 1203, 311, 79158, 323, 81754, 279, 71636, 258, 10782, 29931, 2234, 11, 1193, 311, 387, 56651, 67331, 1578, 627, 644, 220, 9714, 19, 11, 28187, 17057, 279, 7327, 22938, 5794, 596, 10229, 11, 3010, 2663, 279, 5629, 7327, 11, 439, 264, 2385, 369, 8738, 5054, 55280, 13, 763, 813, 54559, 2686, 11, 568, 59860, 311, 12929, 52741, 11046, 596, 8982, 11, 311, 279, 2515, 430, 11, 330, 2028, 72815, 1113, 79885, 315, 12205, 323, 2410, 374, 11622, 45408, 311, 6989, 315, 3424, 1210, 1283, 11763, 279, 45477, 304, 8286, 220, 16, 315, 18880, 13, 578, 79105, 1990, 28187, 596, 12929, 323, 279, 25844, 569, 2373, 315, 279, 8982, 320, 8370, 574, 1664, 22015, 8, 574, 5246, 20011, 304, 459, 4879, 311, 88119, 279, 7327, 13, 28187, 17644, 311, 84129, 279, 36569, 315, 60016, 88, 11, 719, 279, 58494, 8738, 311, 594, 10730, 13, 28187, 3010, 6688, 439, 813, 2592, 279, 17222, 279, 29084, 7834, 627, 4198, 2053, 29329, 264, 1695, 3568, 315, 6666, 311, 279, 31017, 304, 279, 864, 1594, 311, 279, 11999, 14002, 315, 18880, 50004, 2103, 1550, 539, 2231, 279, 5030, 311, 2800, 13, 3365, 2053, 11922, 430, 433, 574, 539, 279, 29084, 7834, 719, 279, 8691, 430, 28187, 574, 2768, 13, 23150, 11, 6617, 23531, 315, 28187, 3136, 311, 20466, 28187, 596, 10171, 5906, 447, 11867, 439, 6029, 315, 4689, 60016, 88, 627, 42, 49358, 28187, 12502, 52179, 6675, 4410, 764, 36749, 11, 279, 33142, 10003, 315, 264, 2394, 15950, 3703, 263, 13, 11205, 8254, 1060, 1317, 20392, 574, 8774, 6367, 11, 369, 1694, 16475, 555, 2225, 8689, 26, 814, 12502, 389, 220, 777, 5651, 11, 220, 10336, 18, 11, 304, 279, 30718, 5308, 77, 11252, 7043, 33879, 404, 1557, 11, 11717, 30718, 5308, 77, 613, 627, 791, 28187, 288, 1051, 8009, 304, 279, 1176, 4376, 315, 279, 220, 9741, 15, 82, 11, 5496, 304, 264, 2380, 48840, 10269, 304, 25028, 6825, 11, 2100, 6292, 11, 7295, 13, 40612, 11, 814, 1047, 3116, 2911, 26, 2380, 810, 8272, 26, 304, 682, 11, 1193, 2380, 5602, 64033, 13, 5414, 12717, 2592, 315, 8070, 574, 3365, 2053, 596, 68747, 11, 323, 8070, 505, 17496, 17222, 9908, 5439, 439, 264, 1561, 4356, 13690, 41439, 7362, 49664, 13, 763, 9447, 3095, 505, 459, 38594, 315, 52179, 11, 323, 1077, 6691, 11, 889, 8636, 304, 220, 9741, 21, 11, 15480, 279, 28187, 3070, 311, 3351, 311, 39345, 36132, 53933, 304, 18206, 819, 14298, 11, 264, 502, 11, 7295, 52265, 13, 18185, 279, 3070, 596, 1450, 4791, 92139, 2324, 11, 28187, 3984, 813, 7555, 323, 2911, 449, 279, 5995, 53416, 14379, 10612, 82780, 311, 872, 3674, 2704, 323, 19225, 4647, 417, 627, 12331, 87, 596, 2911, 449, 7555, 52179, 1051, 25, 52179, 54491, 320, 76, 13, 5843, 14127, 26, 220, 10336, 19, 4235, 9367, 18, 1237, 52179, 30928, 320, 76, 13, 61944, 867, 361, 26, 220, 10336, 20, 4235, 7529, 16, 1237, 60091, 320, 10336, 22, 4235, 9741, 20, 1237, 18063, 22653, 26340, 3573, 17100, 78, 5233, 220, 10336, 24, 4235, 9741, 15, 1237, 52179, 82096, 483, 43833, 3573, 76431, 89, 49660, 5233, 220, 9741, 16, 4235, 9741, 17, 1237, 52179, 40394, 90530, 320, 9741, 20, 4235, 9378, 23, 1237, 323, 3892, 889, 8636, 1603, 36048, 320, 29527, 220, 9741, 22, 570, 28187, 1253, 617, 1101, 7126, 291, 51764, 4829, 952, 555, 813, 3838, 19393, 11, 25234, 7674, 4829, 952, 13, 1115, 374, 55026, 323, 539, 79819, 660, 8032, 20, 60, 11205, 10003, 90530, 28187, 320, 9741, 20, 1389, 220, 9378, 23, 705, 889, 574, 9405, 304, 7295, 11, 574, 264, 11411, 41289, 889, 9087, 4600, 1077, 7126, 596, 4375, 3156, 1364, 11411, 18639, 627, 42, 49358, 28187, 57272, 304, 7295, 198, 3915, 220, 9741, 15, 311, 220, 9714, 19, 11, 28187, 12439, 304, 19542, 1193, 4737, 264, 2683, 3131, 13, 1283, 323, 813, 3070, 1051, 3721, 13060, 505, 872, 13455, 323, 3892, 315, 813, 2911, 8636, 11, 813, 4538, 11, 12433, 78, 11, 889, 28187, 2663, 330, 64, 28235, 311, 53416, 58701, 1, 323, 264, 10003, 7086, 66620, 49660, 13, 2435, 1051, 779, 8009, 430, 813, 7555, 1047, 311, 17636, 3300, 369, 1077, 78766, 627, 37831, 1126, 718, 3365, 2053, 574, 279, 832, 889, 6688, 28187, 323, 813, 3070, 3300, 311, 18167, 389, 2391, 1521, 1667, 13, 5414, 1193, 1023, 2592, 315, 3300, 574, 813, 2683, 439, 279, 7665, 49664, 369, 578, 1561, 4356, 41439, 11, 4477, 6576, 10522, 323, 8310, 42118, 4395, 304, 279, 330, 75785, 15861, 10246, 12331, 87, 574, 8965, 88398, 2391, 279, 3010, 4261, 315, 813, 2324, 11, 11911, 389, 6020, 19564, 505, 3345, 4333, 323, 12637, 3229, 11, 80474, 3365, 2053, 11, 311, 1520, 449, 813, 3070, 596, 5496, 18512, 323, 45305, 13, 23548, 279, 4648, 315, 813, 7555, 52179, 304, 220, 9367, 16, 11, 28187, 8636, 304, 7295, 304, 220, 9367, 18, 11, 323, 374, 28016, 304, 5234, 25623, 59578, 11, 7295, 13, 578, 1984, 49267, 389, 28187, 596, 44180, 11046, 29096, 37997, 5918, 304, 220, 6280, 19, 555, 279, 37961, 8722, 315, 8681, 13527, 55434, 25, 330, 75586, 315, 279, 1917, 11, 52696, 9135, 28187, 596, 4113, 44180, 574, 2854, 65, 398, 84273, 627, 644, 27256, 2436, 389, 28187, 596, 3463, 198, 12331, 87, 596, 3463, 574, 16917, 28160, 555, 512, 791, 43379, 950, 18526, 2191, 315, 13629, 93537, 80474, 71217, 301, 280, 791, 3823, 2191, 315, 85550, 51162, 3926, 8977, 35638, 198, 791, 29924, 5054, 8752, 315, 15387, 9259, 323, 6941, 67050, 26, 323, 198, 791, 8753, 41289, 323, 50315, 3463, 315, 14539, 6354, 26490, 323, 90054, 627, 12331, 87, 11846, 430, 568, 1436, 4007, 3925, 323, 8396, 74647, 323, 42645, 61555, 315, 3925, 323, 279, 13239, 15632, 315, 3674, 26885, 13, 4452, 11, 28187, 574, 539, 1193, 8173, 304, 21630, 3925, 323, 3674, 4500, 13, 1283, 51287, 50697, 430, 330, 46185, 11597, 388, 617, 1193, 33398, 279, 1917, 11, 304, 5370, 5627, 26, 279, 1486, 4869, 374, 311, 2349, 433, 1359, 323, 568, 9539, 12514, 5678, 311, 4560, 311, 11857, 279, 1917, 627, 12331, 87, 596, 1684, 315, 3925, 11, 902, 3782, 311, 387, 2663, 279, 3769, 380, 23692, 315, 3925, 320, 438, 902, 574, 8040, 4726, 439, 279, 19675, 315, 43379, 950, 3769, 2191, 8, 374, 7995, 28160, 555, 71217, 301, 596, 3802, 430, 8903, 320, 438, 3925, 8, 1288, 387, 19894, 43379, 2740, 11, 1555, 264, 41003, 315, 31322, 8603, 13, 71217, 301, 11846, 430, 279, 5216, 315, 3823, 3925, 374, 32971, 304, 279, 7351, 505, 279, 12569, 661, 9017, 279, 4686, 323, 279, 1972, 320, 8370, 574, 1101, 264, 7351, 7119, 7191, 323, 7191, 25442, 488, 570, 18156, 11, 71217, 301, 11497, 11, 420, 23053, 33831, 315, 279, 49981, 18065, 53722, 11, 41993, 1046, 2171, 290, 719, 520, 1023, 3115, 7612, 45980, 9373, 11, 30191, 84558, 2345, 752, 285, 58697, 96710, 402, 1147, 2403, 279, 6484, 2704, 41608, 13, 1789, 3187, 11, 71217, 301, 16917, 16475, 279, 14154, 15244, 315, 5897, 33792, 430, 574, 44664, 304, 279, 3723, 4273, 2391, 813, 19569, 11, 323, 568, 74389, 264, 892, 994, 9052, 17089, 1053, 61127, 22472, 433, 505, 872, 36017, 13, 6104, 28187, 11928, 420, 7353, 43656, 315, 3925, 11, 71217, 301, 574, 459, 10728, 380, 11, 323, 28187, 16495, 311, 18622, 43379, 1233, 304, 3769, 380, 3878, 13, 1283, 6267, 430, 71217, 70664, 2191, 14980, 279, 7351, 315, 8903, 389, 1202, 2010, 11, 323, 430, 433, 574, 5995, 311, 743, 433, 5304, 1202, 7693, 13, 320, 39, 797, 301, 596, 19675, 14958, 323, 8625, 304, 2167, 14076, 311, 83815, 389, 420, 1401, 1486, 29275, 12331, 87, 596, 26586, 315, 420, 23035, 315, 3769, 380, 43379, 1233, 430, 18010, 71217, 301, 596, 10728, 2191, 574, 19407, 28160, 555, 813, 4007, 315, 85550, 3926, 8977, 35638, 13, 763, 578, 84870, 315, 32186, 11, 3926, 8977, 35638, 18784, 430, 4359, 374, 2216, 264, 9886, 315, 893, 323, 430, 279, 29600, 1274, 7180, 311, 4359, 527, 2216, 29600, 315, 22706, 13, 1789, 3187, 11, 279, 19229, 45659, 574, 264, 3823, 22343, 315, 279, 3070, 320, 1543, 11, 5333, 11, 323, 1716, 8, 8800, 4359, 13, 63909, 11, 28187, 18784, 430, 433, 374, 279, 3769, 1917, 430, 374, 1972, 323, 430, 1057, 6848, 315, 433, 527, 16296, 11, 539, 11384, 11, 315, 279, 1917, 13, 14636, 11, 1093, 71217, 301, 323, 1023, 61787, 11, 28187, 39575, 1990, 27351, 323, 8903, 13, 2030, 568, 1550, 539, 4510, 430, 279, 3769, 1917, 58704, 505, 603, 279, 330, 8110, 1, 1917, 315, 279, 10728, 26, 389, 279, 26102, 11, 568, 3463, 430, 35901, 323, 40418, 3230, 89971, 32098, 1274, 505, 9298, 279, 3769, 4787, 315, 872, 6439, 9539, 627, 12331, 87, 596, 2806, 315, 11346, 198, 11439, 311, 28187, 11, 279, 4500, 315, 3925, 374, 9057, 555, 279, 50859, 1990, 279, 27331, 8603, 323, 279, 5788, 4398, 315, 8396, 13, 3296, 330, 34370, 8603, 11, 330, 12331, 87, 374, 22797, 311, 279, 3445, 315, 5788, 323, 311, 279, 2237, 315, 3823, 11156, 8830, 13, 3296, 5788, 4398, 11, 28187, 374, 22797, 311, 538, 4398, 627, 1688, 264, 3738, 6566, 315, 872, 4500, 11, 279, 3769, 27331, 8603, 315, 8396, 2586, 1139, 12324, 449, 279, 6484, 4398, 315, 5788, 13, 5659, 7739, 315, 4500, 315, 279, 27331, 8603, 11, 1521, 4398, 2543, 1139, 872, 16872, 5153, 13, 5112, 12302, 459, 16746, 315, 3674, 14110, 320, 12331, 87, 323, 3365, 2053, 11, 30402, 21785, 11, 281, 13, 220, 10828, 4390, 791, 23035, 315, 9511, 374, 16188, 304, 28187, 596, 3463, 13, 41812, 11, 28187, 18784, 430, 433, 374, 3823, 7138, 311, 5276, 7138, 11, 323, 568, 6880, 420, 1920, 315, 18475, 330, 75, 4422, 1, 323, 279, 8824, 311, 5276, 7138, 9511, 330, 13477, 1210, 1789, 28187, 11, 420, 374, 264, 5933, 8824, 369, 264, 7106, 5820, 11, 719, 433, 374, 96752, 17791, 311, 279, 3823, 4059, 323, 3823, 28899, 512, 32, 35454, 74198, 7677, 430, 52280, 1884, 315, 264, 584, 7403, 11, 323, 264, 38328, 9711, 311, 21648, 1690, 459, 11726, 304, 279, 8246, 315, 1077, 7917, 13, 2030, 1148, 19512, 21168, 279, 12047, 11726, 505, 279, 1888, 315, 40558, 374, 420, 11, 430, 279, 11726, 25930, 813, 6070, 304, 28899, 1603, 568, 38732, 82, 433, 304, 8903, 320, 64693, 11, 4499, 13, 220, 16, 11, 38838, 13, 220, 22, 11, 11051, 13, 220, 16, 4390, 50909, 449, 279, 71217, 70664, 43379, 292, 11, 28187, 28088, 264, 79498, 369, 279, 23035, 315, 459, 16940, 58720, 3823, 7138, 13, 18156, 28187, 1705, 3237, 872, 6325, 555, 75055, 330, 67812, 1, 449, 330, 19375, 1210, 18156, 814, 1005, 279, 17571, 330, 93772, 16599, 288, 25917, 1210, 578, 1486, 11, 304, 3060, 1162, 11, 374, 430, 889, 264, 1732, 374, 11, 374, 11075, 555, 1405, 323, 994, 568, 374, 22416, 3674, 2317, 5097, 54156, 927, 65070, 7865, 26, 477, 11, 304, 1023, 4339, 11, 832, 315, 279, 1925, 4519, 315, 3823, 7138, 374, 10737, 2968, 627, 12331, 87, 1550, 539, 4510, 430, 682, 1274, 6575, 279, 1890, 1648, 11, 477, 430, 1268, 832, 4375, 374, 11622, 4443, 323, 3927, 13, 12361, 11, 568, 18784, 430, 990, 374, 264, 3674, 5820, 323, 430, 279, 4787, 323, 7739, 1234, 323, 1555, 902, 1274, 990, 527, 40418, 11075, 323, 2349, 927, 892, 627, 12331, 87, 596, 6492, 315, 3925, 374, 3196, 389, 813, 30296, 1990, 279, 3445, 315, 5788, 11, 16280, 1884, 2574, 11, 1778, 439, 4363, 11, 5933, 5070, 11, 323, 5557, 323, 1440, 58523, 11, 430, 527, 5995, 369, 279, 5788, 315, 3769, 11822, 11, 323, 279, 4398, 315, 5788, 11, 304, 1023, 4339, 11, 279, 3674, 323, 11156, 12135, 1274, 3810, 1139, 439, 814, 21953, 323, 1005, 279, 3445, 315, 5788, 13, 32255, 11, 1521, 54350, 279, 3941, 315, 5788, 13, 28187, 13468, 430, 2949, 904, 2728, 8396, 279, 3941, 315, 5788, 4442, 323, 430, 7665, 34775, 1047, 62916, 505, 264, 95450, 3941, 315, 5788, 311, 264, 41067, 3941, 315, 5788, 13, 763, 4689, 11, 28187, 11846, 430, 279, 3445, 315, 5788, 2349, 810, 19019, 1109, 5788, 4398, 320, 2000, 3187, 11, 264, 502, 5557, 39671, 11, 1778, 439, 279, 8191, 11, 323, 1193, 3010, 527, 279, 7016, 8040, 311, 37377, 279, 502, 5557, 570, 1789, 28187, 11, 420, 36401, 1990, 320, 49944, 8, 2385, 323, 3674, 2307, 7993, 374, 264, 3682, 2592, 315, 3674, 44219, 323, 12324, 627, 12331, 87, 16365, 279, 330, 23191, 4398, 315, 5788, 1, 311, 54350, 539, 1193, 4398, 4315, 7931, 11, 719, 1990, 477, 4315, 5315, 315, 1274, 11, 477, 3674, 6989, 13, 1666, 264, 3769, 380, 11, 28187, 1550, 539, 3619, 6989, 439, 32227, 44122, 320, 258, 1023, 4339, 11, 5315, 315, 1274, 889, 70903, 11054, 449, 832, 2500, 570, 1283, 16495, 311, 7124, 6989, 304, 3878, 315, 16945, 13186, 11, 1778, 439, 872, 2680, 311, 5070, 13, 1789, 28187, 11, 2204, 6989, 617, 37441, 16149, 12034, 11, 902, 374, 2500, 2592, 315, 3674, 44219, 323, 12324, 627, 12331, 87, 574, 5423, 11920, 449, 1268, 1274, 29243, 311, 430, 1455, 16188, 5211, 315, 682, 11, 872, 1866, 9511, 2410, 13, 28187, 6267, 42817, 922, 420, 304, 813, 10334, 315, 20167, 367, 13, 28187, 6137, 449, 264, 71217, 70664, 23035, 315, 20167, 367, 719, 8040, 264, 810, 3769, 380, 43656, 13, 1789, 28187, 11, 279, 13336, 430, 832, 1253, 3041, 709, 15637, 315, 832, 596, 1866, 9511, 87671, 596, 8824, 311, 5276, 279, 1917, 55434, 37622, 6173, 311, 1694, 20167, 660, 505, 832, 596, 1866, 7138, 26, 433, 374, 264, 18330, 4814, 13, 28187, 7633, 420, 4814, 304, 3878, 315, 38983, 40252, 2191, 11, 304, 902, 279, 2574, 430, 1274, 8356, 11, 51967, 11, 5101, 311, 617, 264, 2324, 323, 7351, 315, 872, 1866, 311, 902, 12966, 323, 872, 7865, 16632, 10737, 13, 1115, 41877, 5014, 279, 2144, 430, 279, 9473, 323, 35855, 315, 51967, 2216, 527, 279, 2027, 323, 22599, 315, 3674, 12135, 4315, 1274, 13, 9636, 32682, 11, 3674, 12135, 315, 5788, 11, 1778, 439, 4315, 7487, 477, 1990, 7487, 323, 87408, 11, 527, 78926, 1555, 51967, 11, 2737, 9511, 11, 902, 527, 11021, 323, 6216, 389, 279, 3157, 627, 1110, 52302, 40252, 2191, 374, 459, 3187, 315, 1148, 3365, 2053, 2663, 905, 25917, 11, 902, 374, 15499, 5552, 311, 279, 8830, 315, 34649, 13, 3296, 330, 579, 2508, 1, 28187, 323, 3365, 2053, 8967, 6848, 430, 8881, 279, 12034, 315, 264, 4040, 538, 520, 264, 4040, 892, 304, 3925, 11, 719, 902, 527, 10666, 439, 20789, 323, 35825, 13, 28187, 323, 3365, 2053, 6, 1486, 574, 539, 1193, 430, 1778, 21463, 527, 520, 1888, 4376, 10398, 952, 82, 26, 814, 8854, 459, 3062, 5054, 734, 13, 10435, 2500, 1648, 11, 279, 2585, 430, 832, 538, 23783, 927, 279, 3445, 315, 5788, 5764, 539, 1193, 279, 5788, 315, 3691, 477, 28648, 11822, 26, 433, 5764, 279, 5788, 315, 6848, 439, 1664, 320, 576, 5825, 832, 3284, 16540, 369, 3249, 3697, 315, 264, 79263, 538, 1253, 3412, 6848, 26102, 311, 872, 1866, 12034, 570, 14636, 11, 1418, 1778, 6848, 1253, 387, 905, 11, 814, 1101, 16805, 304, 47773, 1376, 1063, 8206, 922, 5054, 4398, 13, 10771, 311, 28187, 323, 3365, 2053, 11, 1274, 1234, 32682, 527, 20167, 660, 505, 872, 1866, 9511, 2410, 13, 832, 3187, 315, 420, 3460, 315, 6492, 374, 1766, 304, 28187, 596, 8830, 315, 13901, 11, 66766, 709, 304, 264, 21765, 505, 279, 46969, 315, 10291, 512, 6882, 22941, 16066, 374, 11, 520, 832, 323, 279, 1890, 892, 11, 279, 7645, 315, 1972, 16066, 323, 264, 8835, 2403, 1972, 16066, 13, 44193, 374, 279, 31238, 315, 279, 67516, 17661, 11, 279, 4851, 315, 264, 4851, 1752, 1917, 11, 323, 279, 13836, 315, 13836, 1752, 4787, 13, 1102, 374, 279, 1200, 2411, 315, 279, 1274, 627, 9241, 300, 813, 19343, 46523, 2411, 10195, 17850, 18784, 430, 279, 6156, 3674, 734, 315, 13901, 574, 311, 12192, 44254, 11, 1618, 28187, 16008, 279, 3674, 734, 439, 264, 1648, 315, 37810, 323, 63082, 449, 3674, 32305, 11, 28592, 20958, 279, 2704, 41608, 627, 65358, 2428, 315, 32682, 198, 12331, 87, 18784, 430, 420, 20167, 367, 315, 3823, 990, 320, 438, 13239, 38983, 40252, 2191, 8, 374, 279, 27409, 4668, 315, 32682, 13, 32499, 311, 32682, 11, 11987, 25281, 304, 4606, 1405, 24190, 323, 42870, 11021, 323, 6216, 51967, 13, 10771, 311, 28187, 11, 264, 41067, 3941, 315, 5788, 8040, 304, 4606, 994, 9511, 5196, 6244, 264, 38983, 2345, 9493, 76847, 6244, 1949, 311, 4662, 872, 1866, 9511, 2410, 11, 323, 4460, 311, 656, 779, 1606, 814, 912, 5129, 43890, 872, 1866, 4363, 477, 279, 7526, 5995, 311, 8356, 264, 5496, 13, 9029, 4662, 872, 9511, 2410, 994, 814, 4287, 20448, 304, 471, 369, 8996, 990, 814, 656, 304, 264, 2728, 4261, 315, 892, 320, 258, 1023, 4339, 11, 814, 527, 539, 11486, 279, 2027, 315, 872, 9511, 11, 719, 872, 8824, 311, 990, 570, 763, 471, 369, 11486, 872, 9511, 2410, 814, 5371, 3300, 11, 902, 6276, 1124, 311, 18167, 13, 13266, 889, 2011, 4662, 872, 9511, 2410, 311, 3974, 527, 330, 782, 1169, 30627, 1210, 578, 1732, 889, 50631, 279, 9511, 2410, 11, 8965, 4423, 889, 1587, 1866, 279, 4363, 323, 5557, 311, 8356, 11, 374, 264, 330, 66163, 380, 1, 477, 330, 15747, 47409, 648, 1210, 320, 12331, 87, 6646, 420, 459, 16945, 4096, 315, 32682, 11, 12742, 505, 904, 832, 315, 264, 8205, 315, 42933, 8349, 315, 477, 922, 32682, 6266, 578, 64217, 30627, 40605, 85692, 279, 87408, 627, 12331, 87, 39575, 13076, 87408, 505, 30338, 87408, 13, 66125, 1821, 3780, 11822, 304, 832, 2035, 323, 4662, 1124, 304, 2500, 26, 810, 24559, 11, 814, 3780, 2574, 304, 832, 3157, 323, 4662, 1124, 304, 2500, 13, 8876, 279, 7016, 315, 8312, 323, 7631, 14816, 2949, 2728, 11987, 11, 1070, 374, 3629, 264, 6811, 1990, 279, 3430, 315, 264, 38983, 304, 832, 3157, 323, 2500, 13, 66125, 1821, 11, 1243, 11, 6725, 17114, 48468, 11, 323, 3987, 311, 12602, 279, 6811, 1990, 1521, 1403, 11987, 13, 10771, 311, 28187, 11, 13076, 87408, 11, 389, 279, 1023, 1450, 11, 1935, 9610, 315, 279, 6811, 1990, 279, 9511, 3157, 323, 279, 3157, 369, 8996, 38983, 374, 9124, 13, 28187, 13468, 430, 304, 32367, 1475, 6992, 5064, 11, 1988, 5089, 7194, 527, 4827, 1109, 2612, 5089, 7729, 13, 28187, 2663, 279, 6811, 330, 20370, 7284, 907, 1, 323, 18784, 430, 420, 41548, 907, 1047, 1202, 2592, 304, 279, 40761, 315, 9511, 388, 11, 602, 1770, 2637, 1555, 12798, 1124, 330, 20370, 85, 4023, 23998, 1, 4856, 1109, 1148, 814, 1051, 20458, 311, 5371, 627, 791, 41067, 3941, 315, 5788, 374, 13171, 315, 28040, 6650, 1606, 279, 41067, 649, 11, 323, 706, 459, 36210, 311, 11, 15601, 7164, 22613, 304, 502, 14645, 13, 28187, 6646, 279, 41067, 538, 311, 387, 279, 1455, 30191, 304, 3925, 11, 1606, 433, 15320, 14110, 1534, 279, 3445, 315, 5788, 13, 2030, 28187, 18784, 430, 32682, 574, 38097, 311, 39445, 58187, 13, 1283, 12090, 430, 927, 892, 11, 87408, 1053, 2793, 810, 323, 810, 304, 502, 14645, 11, 323, 2753, 323, 2753, 304, 9511, 13, 8876, 28187, 11846, 430, 41548, 907, 87513, 505, 9511, 374, 279, 2592, 315, 22613, 11, 568, 20536, 430, 279, 4478, 315, 11626, 1053, 4498, 1524, 439, 279, 8752, 14264, 13, 3277, 279, 4478, 315, 11626, 17503, 3770, 264, 3738, 1486, 11, 279, 1121, 1053, 387, 264, 39621, 477, 18710, 304, 902, 3738, 26593, 315, 279, 8752, 1053, 18678, 13, 28187, 11846, 430, 2391, 1778, 264, 11501, 279, 3430, 315, 9511, 1053, 1101, 4498, 11, 323, 9778, 1304, 3284, 279, 9341, 304, 502, 14645, 323, 279, 6650, 315, 502, 26593, 315, 279, 8752, 627, 12331, 87, 11846, 430, 420, 11008, 315, 6650, 11, 18678, 11, 323, 6650, 1053, 387, 32455, 13148, 555, 15098, 15748, 58187, 13, 23674, 11, 568, 11846, 430, 279, 1317, 9860, 29774, 315, 420, 1920, 574, 14647, 279, 70272, 323, 74477, 315, 279, 41067, 538, 323, 279, 77742, 16409, 315, 279, 88347, 13, 1283, 18784, 430, 422, 279, 88347, 1053, 51085, 279, 3445, 315, 5788, 11, 814, 1053, 15253, 3674, 4398, 430, 1053, 8935, 5127, 18813, 11, 323, 264, 1887, 315, 5788, 2753, 20134, 311, 39445, 58187, 13, 763, 4689, 11, 28187, 3463, 430, 26733, 49148, 315, 420, 3575, 574, 23356, 24045, 481, 11, 323, 430, 264, 11191, 11, 1664, 12, 63316, 11, 323, 16806, 14110, 1053, 304, 4689, 387, 2631, 11, 1606, 279, 17864, 538, 1053, 539, 3041, 709, 2410, 2085, 9349, 13, 1283, 46820, 1534, 430, 311, 5813, 279, 41289, 1887, 11, 264, 69948, 315, 279, 88347, 29096, 4261, 1405, 279, 3966, 315, 279, 3318, 15144, 11, 539, 315, 6864, 11, 690, 387, 279, 4279, 30230, 8331, 2345, 25849, 387, 3549, 389, 264, 13643, 8197, 13, 1666, 568, 6267, 304, 813, 34307, 2428, 315, 279, 6122, 23218, 6826, 11, 330, 42967, 41067, 323, 50315, 8396, 1070, 15812, 279, 4261, 315, 279, 30191, 18475, 315, 279, 832, 1139, 279, 1023, 13, 52042, 287, 311, 420, 374, 1101, 264, 5054, 9320, 4261, 304, 902, 279, 1614, 649, 387, 4400, 719, 279, 30191, 69948, 315, 279, 88347, 1, 510, 16, 27218, 12331, 87, 5602, 14289, 71373, 304, 304, 3674, 4398, 11, 477, 3674, 6070, 11, 4856, 1109, 304, 3823, 23837, 13, 1666, 1778, 11, 568, 4745, 311, 57791, 279, 45743, 2136, 315, 1884, 304, 279, 3318, 538, 11, 889, 1306, 98306, 330, 1820, 3445, 315, 5788, 1, 1053, 2274, 264, 90364, 1887, 627, 12331, 87, 596, 10383, 198, 16257, 361, 315, 28187, 323, 3365, 2053, 304, 20643, 58648, 11, 20437, 13, 578, 59002, 19426, 279, 57751, 30499, 330, 1820, 81557, 388, 1359, 323, 1051, 1101, 1071, 311, 387, 11961, 389, 872, 7937, 24857, 8748, 369, 8041, 311, 991, 35579, 311, 279, 4410, 627, 12331, 87, 323, 3365, 2053, 6, 990, 14861, 264, 7029, 2134, 315, 13650, 323, 18911, 264, 6485, 6492, 315, 3925, 323, 8396, 304, 3878, 315, 538, 4398, 13, 86650, 315, 28187, 323, 3365, 2053, 617, 15107, 389, 420, 990, 311, 30714, 264, 5054, 323, 7100, 19675, 42160, 83815, 13, 35053, 11, 1070, 617, 1027, 12387, 37635, 4315, 28187, 1705, 927, 1268, 311, 14532, 28187, 596, 43422, 323, 1268, 311, 3881, 813, 19476, 311, 1510, 4455, 323, 4787, 320, 438, 433, 374, 3062, 311, 33137, 1990, 330, 12331, 87, 2191, 1, 323, 330, 12840, 28187, 11846, 1210, 71854, 11, 1274, 1005, 279, 3492, 330, 12331, 87, 380, 1, 311, 7664, 1884, 889, 17631, 389, 28187, 596, 44901, 4221, 320, 68, 1326, 13, 3445, 315, 5788, 11, 538, 11, 38983, 8, 311, 3619, 41067, 323, 1023, 34775, 11, 477, 311, 7664, 1884, 889, 4510, 430, 264, 7487, 6, 14110, 374, 279, 1193, 3445, 311, 264, 50315, 8396, 13, 83815, 706, 28160, 9052, 3463, 11, 2288, 11, 5423, 55633, 54641, 11, 902, 29633, 304, 4799, 315, 4359, 596, 3361, 4747, 369, 11, 477, 15837, 7119, 11, 279, 8009, 323, 28424, 430, 994, 279, 8009, 3719, 17371, 315, 872, 40761, 11, 814, 690, 1243, 387, 62935, 311, 7631, 323, 11322, 872, 3268, 13, 72984, 90602, 5493, 656, 539, 14647, 1862, 9349, 439, 961, 315, 420, 1920, 11, 8051, 1690, 617, 627, 42560, 1667, 1306, 28187, 596, 4648, 11, 3365, 2053, 323, 3885, 18538, 279, 330, 16041, 7327, 1, 439, 264, 2385, 369, 8738, 5054, 55280, 13, 1115, 7471, 29368, 304, 220, 7529, 19, 11, 304, 961, 1606, 1063, 3697, 6656, 311, 22653, 82415, 596, 330, 5230, 3294, 661, 1, 51618, 11, 323, 304, 961, 1606, 315, 37601, 36841, 33337, 555, 4435, 5111, 358, 627, 10343, 5111, 358, 1101, 6197, 311, 279, 8690, 22910, 323, 279, 12777, 306, 14943, 30819, 315, 36011, 63912, 596, 11692, 315, 279, 50315, 7351, 11, 78643, 304, 279, 330, 1110, 56544, 1, 477, 330, 38075, 7327, 1210, 63912, 11922, 311, 387, 2225, 279, 41903, 323, 5054, 51543, 311, 28187, 11, 323, 8040, 264, 5054, 2068, 11, 2663, 63912, 2191, 477, 68357, 81913, 2191, 11, 902, 2663, 369, 14110, 17057, 323, 6197, 555, 264, 85413, 17057, 37961, 4717, 627, 6153, 63912, 596, 4648, 11, 279, 12667, 59082, 315, 279, 37961, 8722, 315, 279, 19953, 9323, 11, 15466, 47765, 11, 31589, 2585, 315, 279, 8722, 323, 1614, 41705, 13, 1283, 18784, 430, 1603, 264, 15603, 50315, 14110, 1053, 387, 3284, 11, 279, 37961, 8722, 315, 279, 19953, 9323, 1047, 311, 74704, 5196, 311, 4857, 71189, 304, 1202, 1866, 3224, 13, 9029, 889, 617, 539, 14243, 20041, 63912, 596, 43422, 323, 279, 63132, 315, 813, 6037, 18046, 430, 433, 574, 47765, 596, 19953, 9323, 323, 1202, 10396, 430, 80617, 279, 7434, 315, 83815, 304, 279, 11104, 1917, 13, 4452, 11, 279, 18678, 315, 71189, 99618, 505, 1202, 1234, 79, 6258, 826, 439, 1664, 439, 505, 1202, 3851, 7314, 449, 63912, 13, 1789, 1690, 1667, 11, 5423, 1306, 279, 10657, 4435, 5111, 2391, 279, 24062, 5111, 4261, 11, 83815, 574, 5526, 398, 3312, 660, 449, 47765, 596, 71189, 11, 902, 574, 264, 90364, 2191, 430, 43903, 21632, 8431, 3268, 627, 16257, 361, 315, 28187, 323, 3365, 2053, 304, 70695, 627, 644, 220, 5926, 24, 11, 21605, 91993, 574, 67331, 505, 279, 19953, 9323, 323, 304, 220, 7285, 23, 18538, 279, 27260, 330, 89703, 7327, 1210, 4427, 20723, 315, 91993, 18784, 430, 47765, 1047, 3549, 264, 80495, 1614, 4856, 1109, 264, 41289, 1614, 627, 644, 5734, 11, 57278, 1901, 291, 647, 1101, 11922, 311, 387, 459, 51543, 311, 28187, 11, 719, 18784, 430, 76847, 323, 539, 1120, 7487, 1436, 1514, 264, 6522, 3560, 304, 264, 50315, 14110, 13, 1115, 29280, 660, 449, 63912, 596, 6325, 304, 3639, 374, 311, 387, 2884, 30, 323, 304, 279, 8446, 315, 279, 92501, 14110, 902, 8813, 704, 311, 2380, 31605, 6072, 25, 15277, 388, 11, 5250, 300, 1821, 11, 323, 75531, 11, 26455, 279, 9511, 388, 330, 48616, 1359, 279, 76847, 330, 1974, 1359, 323, 279, 15201, 330, 55225, 1210, 1115, 574, 264, 25959, 505, 28187, 596, 1866, 1684, 315, 14110, 11, 902, 10968, 24121, 389, 279, 16036, 88347, 13, 28187, 11846, 14110, 1053, 1935, 2035, 304, 11084, 13076, 34775, 1778, 439, 9822, 11, 10057, 11, 323, 9635, 627, 644, 279, 220, 5926, 15, 82, 323, 220, 7285, 15, 82, 11, 264, 1912, 315, 14091, 1748, 28187, 1705, 18538, 279, 10181, 369, 9983, 8483, 304, 10057, 11, 4315, 1124, 7639, 473, 672, 35180, 11, 578, 50017, 2467, 11368, 11, 9939, 718, 5659, 76, 11, 323, 58463, 19412, 817, 13, 1666, 264, 1912, 11, 1521, 12283, 527, 3629, 2663, 279, 56284, 6150, 13, 11205, 990, 374, 3967, 439, 9200, 10334, 11, 93998, 311, 70050, 19675, 323, 279, 13042, 19347, 17345, 28160, 555, 71217, 301, 11, 72634, 11, 94206, 11, 323, 7639, 56620, 627, 791, 56284, 6150, 14760, 449, 6931, 28187, 1705, 11, 2737, 63912, 323, 68357, 81913, 2191, 304, 3892, 1401, 5627, 13, 5629, 11, 1606, 315, 47765, 2191, 323, 81522, 11, 814, 1047, 25165, 40017, 922, 279, 8776, 70050, 7434, 315, 64217, 8997, 538, 25917, 13, 10657, 11, 20426, 6931, 28187, 1705, 11, 5423, 63912, 11, 814, 18010, 7100, 6449, 2191, 13, 6104, 7701, 32549, 11, 872, 990, 706, 1027, 32614, 555, 28187, 1705, 369, 41079, 6253, 70050, 10334, 505, 15325, 14993, 323, 13353, 83815, 1139, 264, 32227, 14584, 20790, 627, 11663, 32549, 2536, 7826, 3145, 82008, 28187, 1705, 520, 430, 892, 2997, 13629, 55757, 19807, 11, 33305, 30411, 11, 323, 23245, 29937, 54927, 11, 889, 3235, 449, 279, 56284, 6150, 527, 3629, 3967, 555, 279, 4751, 330, 55924, 83815, 1210, 18063, 74, 43907, 1543, 11, 889, 25985, 660, 279, 37072, 8197, 315, 28187, 596, 330, 20510, 315, 41067, 31085, 1359, 574, 2500, 22325, 315, 279, 56284, 6150, 13, 7429, 21102, 2391, 420, 4261, 574, 279, 33084, 30191, 47930, 27466, 9034, 5673, 627, 644, 220, 6393, 24, 11, 7043, 37326, 68, 4341, 323, 37848, 27636, 4858, 18538, 45434, 10506, 11, 264, 8486, 323, 3577, 11, 311, 3493, 459, 27487, 369, 70050, 3463, 304, 279, 3723, 4273, 9678, 315, 279, 37961, 8722, 315, 279, 3723, 4273, 315, 5270, 627, 644, 220, 4468, 23, 11, 480, 13, 362, 13, 32196, 17644, 311, 10726, 28187, 596, 3463, 439, 264, 56887, 323, 12624, 10334, 315, 3925, 555, 44928, 287, 433, 1555, 279, 18848, 315, 79136, 19675, 13, 1115, 6688, 7342, 311, 330, 74407, 35758, 83815, 1359, 459, 14584, 7351, 902, 5343, 12565, 4072, 3751, 11, 15387, 2394, 96304, 1105, 6780, 11, 323, 3842, 12093, 41996, 627, 77386, 1795, 1129, 2185, 57248, 87, 1705, 2726, 72727, 3262, 277, 87, 14, 19033, 14, 10750, 22, 22041, 3262, 277, 87, 14, 10750, 20, 331, 6091, 24165, 13, 58891, 220, 605, 6250, 11, 220, 1049, 23, 627, 77386, 12131, 468, 53470, 13781, 13, 330, 27125, 28187, 264, 44451, 380, 3343, 54190, 18312, 11, 220, 4468, 24, 13, 34526, 220, 17272, 12, 25620, 12815, 26720, 21, 198, 77386, 1795, 1129, 2185, 57248, 87, 1705, 2726, 72727, 3262, 277, 87, 14, 19033, 14, 10750, 22, 22041, 14, 4550, 14, 4550, 1691, 24165, 13, 58891, 220, 605, 6250, 11, 220, 1049, 23, 627, 77386, 1795, 1129, 2185, 57248, 87, 1705, 2726, 72727, 3262, 277, 87, 14, 19033, 14, 10750, 22, 22041, 14, 21731, 14, 1806, 62, 806, 62, 605, 24165, 13, 58891, 220, 605, 6250, 11, 220, 1049, 23, 198, 77386, 10335, 16684, 3341, 424, 25, 330, 12331, 87, 3092, 17323, 702, 2471, 263, 11, 473, 1823, 13, 578, 12799, 7713, 315, 279, 88479, 25, 83815, 8288, 101998, 2191, 439, 264, 38356, 950, 61477, 13, 32492, 13492, 11, 220, 1049, 18, 13, 34526, 220, 17272, 12, 26956, 24574, 20077, 22, 198, 95509, 11, 64530, 11, 323, 26349, 13960, 13, 35131, 28187, 25, 5414, 9601, 323, 11847, 13, 1561, 4356, 25, 26275, 3907, 8612, 11, 220, 2550, 21, 13, 34526, 220, 18089, 15633, 17470, 17, 198, 34, 27538, 11, 480, 885, 13, 35131, 28187, 596, 31535, 315, 11346, 25, 362, 40007, 320, 3617, 42690, 3907, 8612, 11, 220, 4468, 23, 8, 34526, 220, 15, 12, 25168, 12, 17819, 2614, 12, 22, 198, 9023, 3271, 11, 20442, 13, 35131, 28187, 596, 31535, 315, 22910, 11, 220, 19, 348, 3145, 13, 1561, 4356, 25, 45434, 10506, 8612, 11, 220, 3753, 16, 13, 34526, 220, 24646, 12901, 23477, 55, 198, 38, 619, 11, 18587, 19455, 13, 362, 45480, 1122, 74569, 1543, 520, 28187, 596, 59449, 482, 469, 13, 13558, 35882, 441, 3751, 11, 2199, 220, 16, 11, 7531, 29461, 916, 320, 2550, 24, 4390, 42, 337, 587, 29384, 11, 11876, 64123, 13, 4802, 9303, 82, 315, 83815, 25, 11119, 2506, 578, 55628, 13, 26275, 25, 507, 5368, 1087, 2637, 220, 4468, 23, 13, 34526, 220, 17272, 12, 21602, 17079, 26576, 23, 198, 39203, 11, 15469, 13, 578, 38130, 28187, 13, 42958, 25, 3907, 315, 19461, 8612, 11, 220, 3753, 21, 13, 34526, 220, 22534, 24132, 17786, 20, 320, 12331, 87, 596, 990, 6646, 439, 8198, 340, 26353, 43, 16046, 11, 6941, 13, 35131, 28187, 25, 5414, 9601, 323, 36287, 13, 1561, 4356, 25, 33107, 15623, 1354, 11, 220, 4468, 23, 13, 34526, 220, 11030, 18807, 21535, 24, 198, 58916, 8083, 5230, 33639, 11, 52771, 11, 323, 66991, 11583, 268, 7674, 11529, 491, 268, 13, 35131, 28187, 25, 2418, 323, 42667, 13, 1561, 4356, 25, 71244, 18312, 11, 220, 4468, 18, 13, 5871, 691, 25, 426, 931, 22, 32, 6903, 21, 56, 198, 66814, 301, 11, 56625, 321, 3675, 13, 28187, 17586, 47595, 25, 362, 26560, 5848, 19723, 315, 813, 9601, 323, 5664, 320, 14755, 9336, 11, 220, 4468, 20, 8, 34526, 220, 15, 12, 21729, 12, 10895, 1490, 12, 23, 198, 31224, 11710, 42050, 3124, 11, 2009, 454, 820, 13, 578, 3816, 2394, 15950, 25, 578, 9601, 323, 28033, 315, 35131, 28187, 13, 7295, 25, 9777, 819, 24051, 11, 220, 6393, 23, 13, 5871, 691, 426, 4119, 18, 50164, 22, 38, 198, 54, 383, 268, 11, 26184, 13, 35131, 28187, 25, 362, 9601, 13, 1561, 4356, 25, 468, 13, 468, 13, 60364, 612, 3623, 2637, 220, 1049, 16, 13, 34526, 220, 21602, 17079, 10895, 21, 198, 54, 53470, 13781, 11, 12131, 13, 330, 27125, 28187, 264, 44451, 380, 3343, 54190, 18312, 11, 220, 4468, 24, 13, 34526, 220, 17272, 12, 25620, 12815, 26720, 21, 198, 2460, 7902, 31503, 5936, 220, 1032, 11, 220, 679, 23, 627, 33, 69713, 5814, 323, 2930, 22755, 198, 12331, 87, 323, 3365, 2053, 8191, 30802, 198, 65358, 2428, 315, 71217, 301, 596, 46969, 315, 10291, 320, 10336, 18, 340, 1966, 279, 13653, 16225, 320, 10336, 18, 340, 17828, 389, 7957, 8384, 320, 10336, 19, 340, 36, 32107, 323, 38356, 292, 96433, 25207, 315, 220, 10336, 19, 320, 10336, 19, 340, 1016, 84836, 389, 3926, 8977, 35638, 320, 10336, 20, 340, 791, 6063, 14123, 2508, 510, 4291, 3365, 2053, 60, 320, 10336, 20, 1389, 220, 10336, 21, 340, 791, 70274, 315, 46969, 320, 10336, 21, 1389, 220, 10336, 22, 340, 54, 425, 18993, 323, 18880, 320, 10336, 22, 340, 39595, 78, 315, 279, 37961, 8722, 510, 4291, 3365, 2053, 60, 320, 10336, 22, 1389, 220, 10336, 23, 340, 6600, 1263, 6091, 325, 320, 9741, 22, 1389, 220, 9741, 23, 340, 32, 94628, 311, 279, 34307, 2428, 315, 31597, 38661, 320, 9741, 24, 340, 54, 1018, 826, 389, 279, 549, 815, 13, 16803, 5111, 510, 4291, 3365, 2053, 26, 20276, 60, 320, 9714, 16, 340, 791, 2490, 315, 8242, 7284, 5273, 11, 220, 18, 348, 3145, 13, 320, 9714, 17, 340, 1150, 11, 8650, 323, 58882, 320, 9714, 20, 340, 64693, 4499, 13, 220, 16, 320, 9714, 22, 340, 791, 16803, 5111, 304, 9822, 320, 9674, 16, 340, 65358, 2428, 315, 279, 6122, 23218, 47516, 320, 9674, 20, 340, 22405, 389, 52475, 320, 9367, 18, 340, 64693, 11, 4499, 13, 220, 18, 510, 2252, 28400, 7162, 11, 555, 3365, 2053, 60, 320, 9378, 19, 340, 73637, 510, 4291, 3365, 2053, 26, 20276, 60, 320, 10750, 18, 1389, 220, 9378, 20, 340, 38783, 555, 35131, 28187, 13, 5907, 52686, 198, 76431, 89, 55512, 287, 11, 35131, 28187, 25, 578, 15457, 315, 5414, 9601, 198, 81428, 285, 33104, 268, 11, 578, 2418, 43474, 279, 20519, 198, 7229, 27383, 315, 35131, 28187, 198, 52059, 8350, 68198, 315, 46969, 4441, 198, 20027, 22129, 24789, 301, 11, 35131, 28187, 320, 3648, 11165, 77731, 4652, 340, 42, 49358, 28187, 3925, 198, 13730, 315, 330, 42, 49358, 28187, 702, 12289, 83712, 505, 3788, 1129, 2185, 4721, 14957, 2301, 66, 43473, 2726, 4420, 9199, 2348, 30, 2150, 28, 42, 49358, 1267, 277, 87, 5, 820, 307, 28, 4645, 19222, 24, 198, 97447, 9818, 323, 15180, 388, 128000, 47532, 279, 8483, 60545, 1701, 279, 6068, 1523, 5130, 3770, 627, 23562, 32947, 323, 42780, 18702, 264, 8205, 315, 3917, 5789, 2737, 6020, 11, 35410, 82, 11, 15266, 11, 323, 810, 627, 9619, 2680, 23778, 1059, 8270, 596, 68198, 315, 10170, 11, 5636, 3495, 9013, 304, 682, 5789, 315, 8198, 323, 5557, 627, 25310, 398, 1505, 701, 38618, 304, 927, 220, 3101, 1667, 315, 13970, 32594, 13, 7694, 927, 220, 16, 11, 931, 32594, 26, 279, 3778, 3314, 45231, 26, 2326, 39473, 11464, 2638, 323, 810, 13, 7531, 1536, 33462, 5548, 11, 7342, 612, 11103, 35871, 26, 28781, 7576, 5099, 627, 9619, 9529, 9908, 505, 220, 1544, 549, 815, 13, 3754, 32947, 627, 1905, 4977, 374, 459, 7718, 5507, 369, 12096, 11, 11486, 323, 38663, 6603, 11, 6275, 82, 11, 3154, 67132, 11, 79688, 11, 7353, 82, 3422, 11, 14370, 323, 9477, 11, 3196, 389, 5150, 21852, 7729, 304, 279, 549, 815, 13, 323, 22917, 627, 3915, 279, 48539, 388, 315, 279, 52248, 311, 3432, 596, 31186, 11, 19874, 279, 1274, 11, 4455, 11, 323, 22100, 315, 1057, 7140, 596, 15740, 627, 6014, 3313, 11941, 7969, 369, 502, 323, 1511, 9515, 369, 2225, 2254, 323, 5426, 14286, 323, 6807, 29590, 311, 1505, 279, 1888, 3568, 323, 1817, 704, 279, 11941, 31052, 323, 6873, 4219, 311, 4048, 810, 922, 279, 40508, 29642, 1920, 627, 50122, 15325, 11, 16195, 11, 323, 32100, 10401, 315, 27465, 4819, 323, 7016, 11, 323, 10396, 369, 23234, 11, 31434, 11, 323, 8420, 627, 7280, 8544, 323, 4519, 505, 279, 3778, 11896, 10229, 627, 6014, 279, 18539, 315, 1510, 6603, 11, 7855, 323, 2835, 304, 264, 4729, 315, 11990, 315, 15671, 13, 7429, 5727, 2539, 1495, 8544, 505, 5410, 32947, 627, 77921, 3495, 7626, 10209, 1579, 22867, 3495, 10105, 2737, 5064, 32313, 11, 5708, 6821, 11, 3887, 6821, 11, 328, 43945, 3495, 323, 578, 42158, 39693, 627, 10086, 18594, 389, 71820, 351, 97540, 3600, 323, 30282, 11, 2737, 18653, 1705, 11, 1841, 13023, 11, 4443, 3600, 11, 14286, 11, 323, 810, 627, 67412, 315, 279, 2539, 9529, 5684, 505, 220, 3753, 21, 311, 9303, 627, 35709, 31255, 39656, 315, 279, 10780, 41439, 11, 682, 47634, 505, 220, 1049, 23, 311, 220, 18, 4038, 4227, 13, 14434, 8162, 31255, 5764, 1475, 2199, 315, 1475, 14002, 315, 279, 17222, 11, 2737, 3113, 14058, 11, 5897, 35871, 323, 21771, 82, 627, 9619, 2199, 323, 4652, 5448, 449, 74743, 2539, 1495, 1203, 311, 279, 1176, 4360, 304, 220, 10336, 24, 311, 220, 2550, 19, 13, 1115, 4526, 5764, 7528, 14843, 5247, 8405, 2680, 311, 1475, 2199, 505, 1475, 2561, 4360, 627, 2028, 40508, 13023, 4729, 5764, 29302, 323, 19358, 47287, 11, 2532, 11470, 11, 69771, 323, 50518, 11, 323, 810, 627, 50083, 950, 17222, 5825, 15207, 32051, 1705, 11, 12074, 323, 31839, 449, 2930, 11, 6847, 19993, 481, 1176, 25417, 9815, 323, 71257, 10401, 315, 279, 11759, 11, 8396, 323, 4455, 315, 279, 892, 13, 56769, 505, 7028, 23, 311, 220, 1049, 19, 627, 63329, 9477, 4756, 304, 20023, 3778, 42780, 18702, 3674, 36788, 323, 94135, 439, 1664, 439, 8198, 323, 5557, 627, 19952, 311, 420, 2592, 369, 459, 1524, 37240, 15864, 315, 31322, 6325, 389, 67600, 5426, 4860, 11, 1322, 612, 1221, 627, 20171, 15493, 311, 279, 5526, 11761, 14756, 11, 5636, 14079, 2930, 2262, 11, 2737, 7252, 3341, 42282, 627, 359, 18736, 2680, 311, 810, 1109, 220, 16, 11, 931, 10292, 27875, 1989, 612, 11003, 2835, 6989, 15972, 555, 15324, 2955, 11909, 323, 13820, 627, 2127, 2930, 5452, 430, 33511, 15062, 11, 6681, 481, 5905, 2262, 449, 701, 6875, 596, 5070, 323, 8779, 499, 311, 656, 10819, 11, 810, 7524, 3495, 627, 9619, 9529, 10401, 505, 220, 2550, 20, 311, 9303, 627, 10086, 46139, 6108, 38462, 2038, 4832, 369, 2626, 323, 8661, 6787, 627, 7778, 13023, 11, 9578, 22658, 5496, 323, 15919, 14324, 2038, 505, 279, 40343, 22013, 10297, 54187, 323, 656, 38611, 53246, 726, 3229, 11, 7957, 63715, 3258, 627, 16328, 82, 323, 4183, 2539, 1495, 315, 63681, 42780, 505, 220, 2550, 20, 311, 3118, 11, 18702, 15223, 1778, 439, 2626, 11, 6873, 11, 54242, 323, 2383, 627, 32, 11191, 4526, 315, 220, 1041, 4, 2539, 9529, 64486, 3510, 44550, 4261, 950, 323, 7528, 3772, 2262, 11, 6319, 369, 6278, 323, 1579, 2978, 4236, 11, 86172, 52085, 520, 4029, 31252, 323, 23978, 11, 54918, 11, 323, 61459, 30627, 627, 24741, 63951, 15407, 311, 6873, 5552, 9908, 505, 220, 5162, 21, 311, 279, 3118, 627, 51102, 39750, 18734, 304, 19174, 13, 4557, 19309, 18594, 323, 8544, 11, 1684, 264, 13470, 11, 439, 1664, 439, 9364, 323, 6946, 13, 7531, 704, 1405, 701, 4885, 527, 2133, 11, 636, 58286, 55638, 59711, 2680, 311, 927, 220, 8652, 3610, 22486, 5448, 994, 499, 1515, 1139, 701, 1949, 12517, 6014, 2759, 4871, 279, 6875, 627, 3915, 2162, 499, 649, 2103, 1515, 304, 311, 2680, 12517, 6014, 596, 1949, 5070, 627, 15218, 389, 810, 1109, 220, 18, 11, 3443, 7032, 304, 220, 6281, 19647, 13, 27044, 6205, 66313, 323, 3504, 12197, 11, 323, 10631, 389, 65816, 13, 7429, 5764, 220, 2166, 11, 931, 55855, 323, 2655, 18143, 369, 7926, 4236, 627, 31224, 7569, 398, 323, 4689, 2262, 18702, 264, 7029, 8205, 315, 13650, 2737, 2890, 11, 6873, 11, 5557, 11, 2626, 11, 323, 279, 3674, 36788, 627, 96609, 264, 7029, 2134, 315, 7701, 21416, 11, 33315, 6197, 14307, 430, 499, 649, 1935, 11622, 2930, 13, 1666, 264, 6875, 3786, 12102, 304, 1695, 11509, 11, 499, 527, 20458, 311, 1521, 14307, 520, 912, 2853, 13, 48778, 1629, 369, 4848, 5672, 323, 502, 16079, 3240, 1475, 2305, 627, 57497, 2997, 25, 27738, 596, 8184, 18524, 11, 279, 68198, 315, 97189, 11, 279, 91150, 323, 47511, 67792, 18524, 11, 279, 68198, 315, 8184, 8245, 48132, 11, 323, 279, 79332, 18524, 315, 62770, 323, 33065, 7972, 627, 4054, 42311, 12185, 369, 32465, 32272, 323, 2038, 13, 31911, 19347, 11, 6156, 8336, 11, 32465, 323, 13042, 6492, 11, 323, 6160, 67245, 627, 42773, 3649, 11, 2883, 8544, 11, 323, 7274, 4860, 2001, 682, 8621, 73251, 555, 8420, 323, 2683, 50433, 13, 19545, 1555, 279, 6875, 596, 2723, 311, 10936, 6968, 701, 1866, 4443, 2759, 627, 2028, 1579, 4367, 11, 2539, 1933, 7528, 4526, 315, 18526, 14370, 374, 832, 315, 279, 1455, 16781, 2561, 13, 578, 6332, 315, 279, 4526, 17610, 315, 927, 220, 16, 13, 20, 3610, 14370, 315, 279, 3723, 4273, 323, 279, 1917, 627, 20171, 14002, 315, 279, 6051, 6177, 4330, 8286, 1194, 1391, 408, 2411, 315, 13970, 13443, 13, 31911, 927, 220, 1806, 11, 931, 828, 4101, 11, 389, 7029, 82105, 13650, 13, 14969, 1253, 1893, 32789, 12920, 323, 43653, 20924, 627, 16352, 323, 14580, 8336, 389, 3728, 3925, 505, 14154, 3115, 311, 279, 3118, 1938, 11, 4832, 369, 5575, 6821, 627, 31945, 398, 3967, 439, 31416, 16543, 11, 473, 9186, 3159, 5727, 389, 57364, 2835, 4967, 369, 927, 220, 2636, 3241, 8522, 11, 2737, 5210, 21705, 11, 29966, 45979, 11, 3674, 3772, 11, 323, 810, 4999, 52815, 17083, 25705, 24485, 5764, 9214, 315, 2626, 11, 4443, 11, 39725, 323, 6918, 7739, 627, 3692, 369, 586, 7576, 304, 279, 10780, 48013, 11, 2737, 1972, 12675, 31711, 11, 2291, 66, 42306, 11, 2626, 21746, 323, 14566, 811, 13, 1226, 7079, 872, 1949, 4092, 1817, 2532, 2663, 4343, 19174, 627, 3915, 279, 8410, 369, 77956, 25320, 315, 279, 3778, 11896, 10229, 11, 2567, 709, 311, 2457, 389, 279, 3754, 1022, 2363, 293, 1036, 826, 323, 52988, 11, 502, 10396, 323, 6821, 505, 279, 77956, 25320, 10554, 323, 279, 25320, 311, 4557, 5114, 11, 323, 1373, 14734, 79804, 9908, 389, 12625, 323, 20207, 11542, 627, 9619, 9529, 10401, 7314, 304, 5887, 220, 1049, 19, 311, 9303, 627, 50122, 21416, 6725, 7177, 11, 2737, 279, 43354, 11, 21800, 11, 480, 1507, 11, 8431, 2532, 11, 6411, 11, 1972, 12675, 11, 11326, 28706, 11, 323, 810, 13, 7429, 5764, 6500, 7512, 4967, 323, 3723, 4273, 33779, 627, 14710, 11, 11761, 11, 2626, 323, 5897, 2038, 627, 67412, 1203, 311, 279, 5209, 12, 5162, 15, 82, 3727, 420, 279, 24417, 31978, 9124, 4729, 18702, 279, 2115, 315, 2038, 8198, 627, 50122, 70022, 323, 19347, 315, 6603, 11, 439, 1664, 439, 32465, 18852, 11, 36744, 11, 323, 19567, 13, 27044, 3229, 6160, 67245, 627, 11180, 2930, 1520, 505, 84032, 369, 4236, 11, 439, 1664, 439, 16063, 11, 480, 1507, 11, 323, 33779, 13291, 369, 12884, 13, 30192, 25, 7357, 1938, 505, 220, 605, 25, 410, 264, 749, 13, 311, 33433, 627, 74209, 8213, 7272, 11, 665, 56262, 11, 409, 115177, 417, 3429, 98822, 11, 379, 29571, 3429, 594, 28999, 11, 480, 1507, 11, 379, 439, 89300, 409, 40457, 276, 7583, 3429, 89731, 13, 7923, 2850, 9157, 409, 220, 605, 25, 410, 264, 749, 13, 29626, 1208, 1812, 13389, 1557, 627, 6919, 832, 4791, 19101, 449, 6721, 7076, 84032, 11, 6068, 1022, 701, 3504, 6661, 477, 16063, 220, 1187, 14, 22, 369, 459, 25402, 3477, 11, 323, 2680, 11190, 5070, 369, 701, 2683, 2778, 11, 2737, 16063, 323, 3504, 6661, 20506, 13, 1472, 649, 1101, 2680, 1296, 18459, 7384, 311, 10772, 311, 733, 1203, 311, 2978, 477, 369, 264, 8205, 315, 7076, 14228, 7177, 627, 50122, 6913, 11, 29539, 11, 323, 11084, 7754, 304, 220, 1313, 15823, 11, 439, 1664, 439, 220, 21, 69422, 14307, 482, 6209, 279, 5410, 32528, 323, 36018, 8544, 439, 1664, 439, 21416, 3953, 311, 5376, 38231, 26, 1101, 5764, 28175, 14307, 369, 20769, 323, 2626, 40386, 13, 4324, 459, 2759, 449, 19048, 11688, 311, 3665, 701, 5208, 627, 791, 87839, 8167, 374, 264, 44010, 1963, 315, 9908, 4756, 304, 279, 46656, 6406, 42159, 323, 279, 800, 13, 15274, 9540, 32594, 505, 220, 3753, 21, 311, 279, 3118, 13, 578, 2539, 1495, 315, 1521, 9908, 374, 2561, 520, 279, 11896, 304, 1194, 11, 2930, 477, 8162, 31255, 627, 63329, 539, 1193, 1948, 3754, 7493, 719, 1101, 279, 2038, 13282, 389, 279, 5370, 14491, 315, 279, 5684, 11, 2737, 4686, 44615, 12968, 2038, 11, 5220, 11, 1274, 11, 3956, 11, 5099, 13, 56769, 505, 220, 3753, 20, 482, 1510, 627, 50083, 950, 17222, 5825, 15207, 32051, 1705, 11, 12074, 323, 31839, 449, 2930, 11, 6847, 19993, 481, 1176, 25417, 9815, 323, 71257, 10401, 315, 279, 11759, 11, 8396, 323, 4455, 315, 279, 892, 13, 56769, 505, 220, 9367, 16, 311, 220, 2550, 19, 627, 70850, 2930, 6975, 5452, 430, 8779, 5606, 4048, 2626, 11, 3241, 11, 5557, 323, 11782, 7512, 311, 11322, 4443, 323, 6721, 9021, 627, 10086, 704, 1148, 32947, 11, 42780, 11, 323, 32594, 279, 11896, 12680, 9620, 311, 2930, 11, 323, 1243, 2723, 311, 279, 4495, 4729, 311, 1373, 9908, 477, 4819, 627, 34, 9146, 682, 5789, 315, 16088, 11, 2737, 18653, 5050, 323, 28456, 13, 27044, 264, 6651, 315, 9908, 5439, 369, 4689, 2802, 323, 1884, 304, 279, 6593, 4913, 627, 53, 561, 11, 31681, 4526, 315, 1203, 4819, 315, 13166, 323, 5064, 5552, 9477, 2133, 1203, 311, 279, 7314, 315, 3892, 1401, 386, 2431, 306, 29085, 2737, 279, 34629, 43464, 18524, 11, 27512, 56294, 11, 323, 1401, 2626, 42338, 627, 56934, 13023, 11470, 323, 47287, 11, 11156, 2532, 17889, 1354, 11, 13709, 37869, 323, 2853, 42304, 369, 5370, 9515, 323, 27861, 505, 220, 4468, 19, 311, 3118, 627, 10086, 264, 5708, 477, 27848, 3887, 11, 3495, 1510, 477, 33547, 58348, 11, 1373, 31499, 6, 6821, 11, 323, 1518, 18594, 11, 6020, 6821, 11, 51262, 42338, 11, 323, 1401, 42338, 627, 24741, 5165, 66542, 14756, 220, 9367, 23, 12, 5520, 11, 5165, 66542, 18589, 261, 14756, 220, 679, 15, 12, 5520, 11, 439, 1664, 439, 11758, 315, 6946, 11, 14370, 11, 71554, 2315, 11, 323, 1023, 70752, 5448, 627, 77609, 4731, 430, 5764, 927, 220, 5313, 11, 931, 14242, 11, 2737, 68533, 4731, 11, 36967, 11, 4435, 11, 65337, 323, 8620, 4731, 627, 64445, 27862, 2680, 311, 279, 1561, 4356, 8691, 3997, 2737, 9908, 505, 220, 9741, 16, 49124, 1938, 11, 6625, 47634, 13, 12838, 539, 2997, 279, 2539, 92496, 25649, 13, 29524, 1879, 709, 369, 264, 1949, 12551, 19422, 2759, 320, 333, 499, 1541, 956, 2736, 617, 832, 8, 311, 2680, 15716, 499, 2351, 304, 279, 6875, 627, 12763, 279, 2723, 311, 49878, 264, 2082, 369, 220, 5332, 4207, 315, 1949, 2680, 311, 279, 1561, 4356, 8691, 389, 904, 315, 701, 7766, 13, 1472, 3358, 1243, 387, 33687, 311, 4254, 369, 264, 1949, 12551, 8691, 2759, 320, 333, 499, 1541, 956, 2736, 617, 832, 570, 3277, 701, 2082, 8640, 704, 11, 1120, 471, 311, 420, 2723, 311, 49878, 2500, 2082, 13, 27044, 2680, 311, 9908, 505, 220, 9741, 16, 49124, 1938, 11, 6625, 47634, 11, 323, 279, 5845, 311, 1005, 279, 12551, 19422, 6505, 10721, 13, 12838, 539, 2997, 279, 2539, 92496, 25649, 627, 9619, 2199, 323, 4652, 5448, 449, 74743, 2539, 1495, 1203, 311, 279, 1176, 4360, 13, 1115, 4526, 5764, 7528, 14843, 5247, 8405, 2680, 311, 1475, 2199, 505, 1475, 2561, 4360, 627, 6014, 279, 1455, 3293, 3728, 3754, 2262, 11, 439, 1664, 439, 39104, 902, 14841, 1203, 1139, 279, 220, 3753, 15, 82, 16850, 2262, 505, 32594, 11, 502, 2332, 3946, 11, 323, 3754, 6732, 304, 4642, 2539, 9529, 3645, 505, 279, 2326, 11, 7008, 11, 4606, 11, 10384, 11, 13936, 11, 20023, 5270, 11, 323, 8494, 627, 37, 2538, 323, 2536, 58162, 8641, 369, 682, 17051, 13, 7531, 1373, 19308, 3043, 6603, 323, 12283, 11, 2363, 8544, 11, 2363, 1912, 10430, 4860, 323, 3229, 13335, 627, 12608, 919, 315, 7528, 5070, 2737, 6603, 11, 7855, 3626, 11, 5448, 11, 9698, 323, 30525, 323, 22755, 627, 4438, 3629, 617, 499, 4460, 311, 1440, 279, 7438, 315, 264, 3492, 11, 31156, 922, 1202, 6371, 11, 477, 3463, 922, 1268, 499, 2643, 1005, 433, 1455, 13750, 30, 26275, 423, 45292, 617, 1120, 832, 3245, 304, 4059, 25, 18899, 10758, 1555, 459, 8830, 323, 11939, 369, 1057, 5496, 4221, 13, 27044, 5905, 4375, 389, 6498, 32528, 323, 10648, 439, 1664, 439, 14807, 58614, 369, 15823, 1778, 439, 15155, 11, 8620, 11, 323, 8690, 627, 2127, 86929, 3686, 65693, 7528, 4729, 389, 5526, 7829, 304, 5270, 323, 279, 1917, 11, 2225, 3347, 323, 3118, 13, 8681, 369, 11026, 477, 3925, 7224, 627, 276, 4228, 4791, 25700, 2930, 5507, 430, 6276, 499, 311, 1893, 6721, 4367, 11028, 315, 701, 2363, 304, 384, 47, 4594, 11, 11672, 8768, 11, 11612, 323, 810, 87247, 1555, 701, 6875, 627, 32, 15525, 3495, 323, 21913, 5507, 449, 810, 1109, 220, 508, 3610, 15393, 7729, 11, 810, 1109, 220, 605, 3610, 5448, 11, 323, 220, 6549, 74743, 11306, 627, 2028, 5016, 2592, 5039, 50270, 4791, 43085, 6072, 330, 2125, 425, 498, 706, 459, 304, 31410, 9266, 4729, 449, 19015, 11, 323, 709, 4791, 18920, 9266, 323, 87386, 2262, 11, 439, 1664, 439, 264, 1160, 315, 2561, 13172, 7032, 627, 24741, 2294, 13970, 5905, 6603, 2737, 25, 8681, 40495, 5659, 11346, 11, 578, 3799, 3536, 763, 5270, 11, 323, 39697, 11046, 45890, 13, 362, 2294, 2035, 311, 1212, 701, 3495, 627, 24661, 16381, 14370, 527, 3544, 13230, 6787, 315, 264, 3363, 477, 6424, 505, 220, 9714, 22, 12, 4468, 15, 13, 578, 14370, 1160, 8761, 10215, 323, 4857, 5219, 304, 1005, 520, 279, 892, 279, 2472, 574, 1903, 323, 3766, 5219, 627, 28660, 367, 11, 5274, 990, 11, 37419, 11, 17136, 38349, 323, 47210, 627, 32, 2294, 5211, 505, 24562, 3907, 8612, 369, 4236, 323, 42482, 33218, 13, 8876, 220, 6393, 23, 24507, 706, 4756, 279, 1888, 6625, 34225, 304, 6498, 11, 323, 1690, 315, 1202, 23691, 617, 3719, 53805, 315, 42482, 19347, 13, 9062, 8286, 374, 29329, 311, 264, 7057, 11, 477, 1514, 11, 477, 1912, 315, 11335, 13, 578, 6603, 527, 36762, 449, 264, 8205, 315, 42482, 276, 5448, 323, 5788, 25232, 627, 71616, 3495, 11, 2626, 6787, 11, 6020, 9293, 11, 8661, 323, 16953, 3876, 2038, 369, 2626, 7980, 13, 8681, 2592, 369, 2626, 9293, 627, 50122, 4062, 323, 4228, 2680, 311, 1510, 323, 13970, 44702, 828, 323, 38462, 2038, 11, 439, 1664, 439, 7526, 311, 1893, 14370, 323, 6821, 311, 41468, 11, 24564, 11, 323, 3619, 2486, 5814, 323, 3674, 2349, 627, 63329, 927, 220, 11387, 15671, 505, 279, 1455, 5526, 11326, 323, 29193, 6696, 42780, 11, 4261, 53703, 11, 323, 6603, 627, 16593, 17496, 323, 8649, 9214, 315, 7902, 311, 264, 220, 868, 4771, 1203, 14537, 11, 11450, 596, 10170, 40073, 279, 13225, 1990, 279, 8198, 430, 4236, 4048, 304, 279, 24978, 323, 279, 54098, 17919, 279, 23546, 315, 8198, 3432, 627, 15218, 323, 9650, 389, 927, 220, 21, 11, 931, 23301, 11, 220, 972, 11, 931, 27848, 10736, 11, 220, 1049, 11, 931, 2671, 323, 1023, 34919, 627, 791, 6020, 17222, 315, 3335, 10209, 304, 31410, 10401, 315, 5426, 323, 6625, 17452, 439, 1664, 439, 1176, 4478, 10401, 315, 2653, 3754, 13, 9742, 505, 220, 3753, 19, 482, 1510, 627, 50083, 950, 17222, 5825, 15207, 32051, 1705, 11, 12074, 323, 31839, 449, 2930, 11, 6847, 19993, 481, 1176, 25417, 9815, 323, 71257, 10401, 315, 279, 11759, 11, 8396, 323, 4455, 315, 279, 892, 505, 220, 9367, 24, 12, 1049, 15, 627, 63329, 539, 1193, 1948, 3754, 7493, 719, 1101, 279, 2038, 13282, 389, 279, 5370, 14491, 315, 279, 5684, 11, 2737, 4686, 44615, 12968, 2038, 11, 5220, 11, 1274, 11, 3956, 11, 5099, 13, 56769, 505, 220, 3753, 22, 482, 1510, 627, 20171, 15182, 315, 279, 22542, 42255, 28292, 311, 23301, 11, 27848, 10736, 323, 9473, 10398, 14589, 10736, 320, 43339, 82, 705, 14286, 11, 6807, 29590, 323, 8276, 5220, 13, 7429, 5727, 279, 15525, 3344, 343, 391, 5507, 45293, 31822, 69051, 8276, 2671, 627, 32, 220, 1041, 4, 2539, 9529, 4729, 13, 32662, 4686, 9908, 505, 9214, 315, 29085, 304, 8198, 11, 279, 94135, 11, 1989, 11, 2626, 11, 323, 2383, 627, 10343, 11346, 25, 18766, 48688, 320, 93013, 3925, 505, 279, 55383, 311, 3432, 8, 374, 279, 5652, 2713, 315, 14683, 3925, 5905, 7384, 369, 1579, 2978, 323, 1579, 11852, 6278, 2978, 75533, 13, 128000, 32, 12902, 3341, 17740, 477, 2876, 30, 3061, 1617, 3806, 304, 279, 16867, 198, 10493, 279, 2326, 28351, 53455, 311, 5734, 5380, 49852, 323, 53455, 596, 67502, 73169, 198, 17321, 287, 5734, 596, 9983, 16666, 744, 311, 10913, 13936, 198, 29184, 2100, 647, 25, 578, 4060, 315, 459, 320, 7279, 20631, 8, 48688, 304, 29389, 198, 48932, 304, 279, 13381, 315, 6295, 27445, 25, 6890, 198, 75341, 14409, 56171, 25, 362, 10423, 304, 4185, 1686, 198, 2078, 12, 30690, 65006, 350, 552, 25, 578, 1611, 63053, 423, 458, 16274, 198, 42069, 16910, 15037, 17236, 49038, 1232, 578, 5734, 38829, 304, 29389, 596, 30160, 35134, 198, 30690, 65006, 6, 364, 34917, 4409, 6, 53435, 729, 91212, 4185, 16491, 198, 22043, 765, 8398, 198, 32, 1396, 315, 5961, 527, 4857, 89022, 1245, 18198, 449, 279, 4754, 311, 14816, 8521, 29480, 14467, 13, 16910, 459, 11977, 7102, 4675, 361, 5380, 1383, 11519, 816, 25634, 369, 578, 46562, 81868, 198, 34593, 25, 52891, 63110, 815, 13, 19574, 14, 38675, 735, 13, 11355, 198, 791, 16867, 5654, 72318, 420, 4652, 11, 279, 1584, 315, 17089, 3973, 287, 279, 16867, 22302, 42949, 505, 8494, 311, 6457, 323, 279, 16526, 50714, 2345, 4752, 304, 279, 3347, 13515, 477, 779, 32126, 264, 22531, 304, 279, 1396, 315, 46398, 18198, 36027, 264, 330, 20322, 9722, 1, 2955, 311, 2187, 11213, 7677, 311, 387, 13375, 505, 872, 11213, 30881, 13, 34067, 21771, 439, 89022, 1245, 18198, 477, 36125, 7066, 388, 2971, 2739, 62380, 11, 814, 1047, 10213, 28883, 6129, 36752, 304, 279, 21391, 25917, 13, 30070, 279, 3347, 2478, 5672, 11, 430, 374, 11, 994, 264, 4101, 315, 4455, 30985, 1521, 31080, 1139, 3728, 3754, 31186, 627, 849, 11150, 279, 3723, 4273, 6, 1403, 4741, 6953, 2760, 291, 52139, 3806, 22416, 39608, 10058, 6652, 323, 279, 39608, 13789, 87713, 12131, 49525, 6457, 11, 1070, 527, 1457, 520, 3325, 45314, 1778, 18198, 13205, 11, 1694, 5918, 477, 304, 2532, 4315, 279, 13936, 64976, 596, 8235, 552, 439, 315, 3432, 13, 4314, 18198, 527, 19073, 7633, 439, 1694, 6319, 369, 89022, 1245, 7677, 11, 1418, 872, 5845, 311, 14816, 59432, 690, 1101, 387, 5505, 304, 7294, 18451, 85543, 39307, 323, 311, 3493, 12576, 304, 11344, 20631, 46865, 323, 73378, 53495, 320, 39, 97573, 8, 7677, 13, 16782, 11, 1455, 527, 264, 2098, 275, 3201, 505, 320, 269, 304, 5734, 596, 1162, 11, 2736, 13171, 315, 8, 10565, 8521, 29480, 14467, 11, 100082, 24087, 315, 459, 11977, 7102, 2403, 279, 39577, 315, 62915, 287, 52482, 42254, 304, 279, 5654, 627, 49137, 374, 5131, 4857, 1403, 220, 1544, 11, 4728, 75735, 69890, 15144, 47524, 16183, 88323, 423, 26246, 320, 43, 19694, 82, 8, 1234, 30833, 5907, 220, 7854, 23, 13, 578, 18198, 11, 473, 41192, 69890, 320, 43, 19694, 12, 2437, 8, 323, 473, 41192, 50301, 320, 43, 19694, 12, 1721, 8, 527, 3196, 389, 279, 15506, 19574, 596, 29604, 30397, 358, 5918, 555, 18157, 596, 12233, 519, 689, 13, 578, 2955, 574, 279, 13946, 315, 264, 10937, 449, 9822, 596, 19438, 951, 1221, 20232, 452, 2979, 645, 320, 5744, 45, 705, 902, 9076, 264, 8294, 2373, 315, 279, 35198, 3545, 538, 2955, 627, 791, 473, 41192, 69890, 374, 5131, 1694, 8308, 520, 426, 13983, 15264, 1389, 77331, 304, 11220, 22464, 68, 1306, 3515, 1027, 15453, 17551, 1523, 304, 18157, 323, 40460, 555, 9581, 311, 8494, 13, 3005, 690, 3810, 2532, 449, 279, 16591, 13673, 19574, 304, 220, 679, 19, 1418, 1077, 13219, 8448, 690, 5249, 1077, 1403, 1667, 3010, 13, 578, 445, 19694, 82, 690, 8454, 279, 473, 41192, 32856, 77767, 323, 279, 735, 16348, 65826, 15144, 18198, 304, 14918, 31474, 89022, 1245, 7677, 449, 264, 14580, 473, 97573, 10015, 627, 39804, 287, 420, 4652, 30, 9369, 1618, 311, 18447, 369, 2539, 2680, 13, 4702, 400, 20, 264, 2305, 627, 791, 69890, 538, 31080, 59227, 264, 3160, 315, 220, 9870, 13, 6086, 37356, 320, 23776, 13, 18, 10702, 705, 449, 264, 7340, 24310, 315, 220, 843, 37356, 320, 6550, 10702, 8, 323, 7340, 45196, 3948, 315, 220, 22, 13, 2318, 37356, 320, 1419, 13, 17, 10702, 570, 27697, 4732, 374, 220, 508, 61317, 11, 323, 279, 445, 19694, 82, 690, 10775, 3116, 55500, 14221, 78149, 220, 914, 9653, 8870, 10094, 6067, 11, 4848, 220, 717, 13, 22, 9653, 5780, 16766, 11, 459, 2147, 14, 8143, 48, 12, 914, 452, 953, 648, 16190, 291, 92983, 68652, 88, 11, 323, 264, 452, 360, 4657, 26290, 68652, 88, 627, 791, 445, 19694, 82, 690, 387, 3025, 311, 6920, 220, 16, 11, 24222, 15201, 323, 872, 7241, 13, 9220, 7458, 30881, 320, 606, 369, 3177, 11731, 11, 279, 1023, 369, 8987, 11731, 323, 26951, 8, 649, 29376, 709, 311, 220, 5120, 11731, 13, 9062, 8448, 706, 264, 1664, 9722, 369, 20948, 11003, 11, 1418, 279, 11213, 9722, 706, 20948, 19300, 369, 4848, 35931, 1954, 15144, 59432, 477, 3116, 6969, 12, 2618, 49335, 1982, 15144, 59432, 311, 14816, 25291, 13, 578, 18198, 527, 19167, 449, 264, 220, 1032, 11877, 29779, 7940, 35363, 505, 279, 29604, 30397, 358, 2955, 11, 8051, 8494, 706, 912, 6787, 311, 14816, 8521, 29480, 14467, 505, 1521, 18198, 13, 578, 5410, 3805, 1912, 690, 11383, 387, 264, 6651, 315, 29433, 39, 12, 1954, 7710, 59432, 323, 328, 12, 2031, 33, 43269, 24286, 7294, 18451, 85543, 59432, 13, 578, 15020, 277, 649, 29376, 709, 311, 220, 972, 59432, 11, 719, 8223, 690, 387, 279, 5410, 23606, 627, 23078, 374, 5016, 304, 279, 20197, 315, 11213, 30881, 304, 279, 5654, 304, 430, 433, 374, 279, 1193, 15481, 3224, 311, 5131, 14816, 8521, 29480, 14467, 505, 1202, 35991, 13, 578, 9029, 596, 72984, 13309, 1389, 19574, 320, 95179, 8, 374, 5131, 10565, 279, 84757, 20324, 11, 13517, 51687, 311, 387, 264, 59094, 735, 5308, 4816, 85393, 15144, 7447, 5898, 14467, 19115, 369, 279, 19953, 19574, 13, 4740, 459, 25706, 3925, 99563, 832, 1486, 11, 433, 574, 10171, 311, 3719, 264, 19596, 12109, 22416, 8448, 2231, 311, 9581, 389, 6287, 220, 605, 11, 220, 679, 16, 369, 279, 1176, 315, 3892, 9581, 19622, 13, 578, 84757, 20324, 374, 5131, 3196, 520, 63012, 42621, 11, 2162, 315, 279, 73666, 596, 4892, 15379, 26155, 11, 1405, 433, 27149, 439, 264, 4967, 8448, 627, 2181, 374, 2103, 25420, 1148, 84757, 20324, 596, 3805, 20611, 690, 1427, 1093, 11, 719, 264, 31089, 1253, 10457, 304, 279, 220, 966, 96857, 23606, 315, 279, 735, 5308, 4816, 85393, 5879, 12, 1058, 13, 578, 1443, 33495, 526, 622, 12, 868, 47152, 61536, 11, 264, 8620, 52714, 46398, 1534, 32905, 315, 279, 74874, 6292, 72, 17360, 12, 1544, 3061, 99348, 11, 706, 1027, 3970, 10565, 389, 4580, 2391, 279, 12387, 9581, 19622, 13, 1666, 279, 84757, 20324, 60880, 279, 4015, 21257, 946, 320, 12755, 12040, 4206, 72087, 35011, 8, 1749, 315, 10565, 14467, 11, 44922, 14467, 1093, 279, 622, 81601, 12, 1721, 19115, 1481, 17334, 362, 38879, 1234, 4500, 690, 539, 387, 3025, 311, 14816, 505, 279, 8448, 13, 622, 12, 868, 7677, 389, 4580, 279, 84757, 20324, 690, 1101, 387, 2917, 2629, 2230, 555, 10633, 323, 7885, 9669, 4245, 311, 279, 8448, 596, 4015, 21257, 946, 6683, 13, 75956, 29480, 12032, 2997, 279, 44472, 383, 1901, 12, 23, 11, 902, 1101, 706, 459, 362, 38879, 11678, 11, 323, 11000, 279, 29549, 869, 23109, 12, 1544, 16183, 953, 627, 2181, 574, 2736, 13882, 3685, 430, 5734, 690, 387, 4857, 810, 35991, 1306, 279, 84757, 20324, 13, 763, 3389, 5887, 220, 679, 18, 11, 7397, 58646, 315, 264, 4793, 315, 1148, 8111, 311, 387, 459, 14467, 19115, 1234, 8246, 13, 578, 14209, 315, 264, 54352, 3221, 459, 6964, 315, 279, 4793, 10633, 839, 33422, 430, 420, 19115, 690, 387, 19167, 449, 264, 45081, 21257, 946, 320, 27899, 73906, 2755, 13539, 12040, 12, 4699, 2030, 72417, 291, 35011, 8, 1887, 11, 902, 5734, 374, 1633, 27989, 389, 11469, 369, 1202, 3938, 19115, 26155, 13, 4452, 11, 2500, 2217, 315, 279, 84757, 20324, 389, 264, 4034, 311, 423, 10700, 389, 4726, 9581, 19622, 8111, 311, 1501, 264, 19115, 596, 15631, 3857, 1694, 5918, 304, 279, 4092, 13, 58603, 11, 420, 5992, 311, 387, 2500, 4015, 21257, 946, 2955, 11, 449, 279, 20779, 369, 264, 29779, 7940, 1694, 5115, 8196, 8994, 279, 4793, 1694, 304, 279, 35612, 627, 35, 10567, 81868, 37618, 198, 1991, 1176, 29906, 2680, 311, 3682, 9908, 3686, 311, 387, 6004, 11, 439, 1664, 439, 7902, 311, 3463, 10039, 85, 10979, 4068, 5548, 323, 304, 31410, 9908, 505, 1057, 13936, 64976, 8024, 812, 627, 644, 279, 19821, 315, 14509, 2038, 11, 33422, 374, 430, 279, 4793, 3970, 304, 38147, 374, 3060, 264, 8018, 5352, 477, 8246, 1646, 5918, 311, 1296, 323, 20461, 279, 4857, 17357, 315, 279, 8448, 17884, 311, 279, 73666, 13, 16782, 1023, 6821, 617, 11224, 430, 279, 4793, 374, 961, 315, 279, 5068, 4078, 220, 22534, 89022, 1245, 11965, 8448, 11, 4528, 311, 279, 549, 815, 19574, 596, 24912, 14406, 15144, 47524, 16183, 88323, 50071, 320, 43, 17455, 8, 8448, 13, 578, 502, 538, 690, 18307, 834, 2050, 1990, 220, 966, 12, 1272, 11, 931, 20181, 4184, 311, 2204, 8336, 11, 6920, 3116, 20118, 7868, 323, 709, 311, 220, 508, 59432, 13, 9849, 287, 2457, 374, 11846, 311, 387, 220, 679, 20, 627, 2409, 279, 84757, 20324, 4967, 709, 264, 6332, 315, 46398, 323, 3805, 13941, 11, 11469, 26411, 323, 31692, 264, 33235, 304, 19115, 7677, 1418, 4726, 35991, 527, 1694, 5918, 11, 1070, 374, 2697, 10712, 5734, 5992, 743, 311, 387, 279, 15481, 19115, 2410, 304, 279, 3221, 3938, 627, 2173, 682, 279, 17089, 61417, 52139, 3806, 304, 279, 13936, 64976, 11, 38048, 279, 1455, 20733, 706, 1027, 6457, 596, 13, 53306, 14222, 8640, 5655, 304, 279, 5654, 922, 6457, 596, 837, 34334, 8994, 1202, 23744, 333, 380, 1772, 11710, 16812, 11951, 49636, 279, 7140, 505, 61417, 15538, 10094, 11, 10633, 839, 555, 64610, 19788, 927, 1148, 374, 26617, 439, 6457, 596, 8060, 311, 7373, 520, 606, 369, 1202, 6299, 304, 4435, 5111, 8105, 13, 3161, 420, 304, 4059, 11, 279, 88963, 430, 24895, 1855, 7195, 315, 264, 11002, 52139, 454, 11, 21771, 439, 16183, 88323, 9607, 9666, 388, 320, 4195, 39, 8, 555, 279, 6457, 77331, 10323, 12, 61034, 11994, 320, 41, 4931, 5375, 705, 374, 2744, 45207, 13, 2030, 430, 12775, 956, 10717, 6457, 505, 1694, 279, 13936, 64976, 7140, 449, 279, 1455, 11213, 9722, 88202, 18198, 11, 449, 3116, 304, 2532, 477, 1694, 5918, 627, 791, 622, 4931, 5375, 44224, 279, 10320, 38060, 323, 1077, 13219, 358, 325, 304, 220, 1049, 24, 323, 220, 679, 16, 15947, 13, 4185, 49033, 220, 1032, 11, 15862, 20181, 5410, 323, 220, 777, 11, 931, 20181, 7373, 6799, 11, 279, 18198, 527, 19167, 449, 24872, 3290, 9976, 4565, 17357, 11, 10923, 1124, 311, 8854, 439, 5292, 18143, 369, 279, 622, 4931, 5375, 13, 578, 18198, 6, 6156, 9131, 374, 311, 734, 439, 459, 7294, 18451, 85543, 39307, 19115, 11, 323, 3116, 20948, 19300, 369, 59432, 527, 3984, 369, 389, 279, 11213, 9722, 11, 8051, 264, 7340, 315, 220, 806, 649, 387, 11953, 13, 578, 42408, 3197, 1376, 315, 279, 11213, 9722, 323, 279, 3813, 315, 279, 4741, 2405, 33383, 87, 13330, 32600, 28877, 744, 1053, 864, 866, 279, 10320, 38060, 15144, 505, 10565, 8521, 29480, 14467, 2085, 264, 12190, 11213, 9722, 56719, 13, 578, 4725, 36125, 23606, 374, 2380, 78449, 1105, 8050, 6570, 12, 1399, 42, 43269, 24286, 65617, 392, 85543, 59432, 323, 264, 3254, 4701, 82979, 61861, 1974, 386, 2198, 12, 4645, 77066, 70863, 10705, 5663, 2727, 24368, 36125, 26, 4869, 420, 649, 13592, 11911, 389, 279, 9131, 627, 791, 12438, 10320, 38060, 574, 17345, 6532, 304, 279, 473, 97573, 5149, 1306, 279, 33318, 38413, 323, 72155, 430, 17948, 6457, 304, 5587, 220, 679, 16, 13, 763, 5651, 220, 679, 18, 11, 1364, 6244, 279, 1176, 622, 4931, 5375, 8448, 311, 14816, 279, 42959, 43371, 12, 1313, 33, 15796, 1762, 88, 37300, 4744, 269, 14467, 2391, 279, 35607, 89228, 10368, 449, 279, 549, 815, 13, 23820, 31242, 1022, 279, 13962, 315, 7188, 627, 1966, 6287, 220, 21, 11, 220, 679, 18, 11, 6457, 8272, 709, 449, 279, 7195, 315, 279, 12438, 48923, 65725, 11, 279, 3063, 8448, 315, 459, 1524, 8294, 32004, 39, 2955, 13, 4185, 49033, 220, 777, 11, 2636, 8941, 4384, 323, 220, 1544, 11, 931, 20181, 7373, 6799, 11, 279, 48923, 65725, 323, 1077, 439, 12303, 295, 53873, 13219, 690, 387, 279, 7928, 18198, 304, 279, 622, 4931, 5375, 15808, 13, 9086, 279, 10320, 38060, 323, 358, 325, 1603, 1077, 11, 279, 48923, 65725, 690, 1101, 387, 51920, 15871, 449, 7294, 18451, 85543, 39307, 13, 578, 11213, 9722, 706, 4330, 36125, 20948, 19300, 430, 2187, 58632, 4363, 826, 477, 1935, 65039, 11, 449, 264, 7340, 23606, 315, 220, 975, 59432, 63234, 3284, 627, 19430, 311, 387, 44224, 304, 220, 679, 20, 11, 279, 48923, 65725, 596, 11213, 9722, 1587, 5101, 311, 387, 810, 6847, 44494, 311, 14816, 8521, 29480, 14467, 1109, 279, 10320, 38060, 538, 13, 1252, 20370, 49264, 11, 279, 48923, 65725, 596, 7195, 706, 41544, 26654, 11, 3515, 1027, 7633, 555, 279, 8620, 439, 459, 330, 1334, 7868, 24948, 7401, 304, 65081, 1210, 578, 2144, 430, 14188, 279, 48923, 65725, 6463, 10320, 38060, 15144, 18198, 527, 19167, 449, 1664, 97986, 369, 20948, 11003, 1053, 617, 7319, 38141, 430, 814, 527, 6319, 11951, 369, 14467, 7677, 627, 26070, 12126, 11887, 279, 432, 4012, 50, 67950, 3055, 304, 220, 1049, 20, 323, 44224, 433, 1403, 1667, 3010, 13, 763, 264, 3351, 430, 4461, 3287, 956, 733, 1523, 1664, 304, 27286, 11, 433, 3952, 279, 16526, 836, 315, 279, 30100, 520, 279, 4219, 315, 264, 52482, 26086, 449, 6457, 13, 362, 7447, 59338, 8448, 13171, 315, 11850, 264, 8205, 315, 25664, 11, 279, 67950, 3055, 13770, 2492, 220, 975, 11, 931, 20181, 4384, 323, 220, 972, 11, 931, 20181, 7373, 6799, 13, 14853, 18198, 315, 279, 538, 1051, 13205, 26, 4869, 279, 4948, 27274, 574, 26765, 555, 264, 3766, 3109, 13, 578, 2132, 11, 279, 432, 4012, 50, 2947, 2172, 11, 574, 311, 7831, 279, 1890, 25382, 11, 719, 11006, 574, 28101, 304, 220, 679, 17, 627, 791, 67950, 3055, 538, 374, 13171, 315, 15691, 709, 311, 220, 13104, 3678, 1572, 323, 5361, 11731, 11, 1418, 264, 1664, 28649, 6276, 369, 89022, 1245, 57919, 13, 2684, 527, 4330, 20948, 19300, 389, 1077, 11213, 9722, 3025, 311, 14816, 59432, 279, 1404, 315, 279, 78449, 1105, 8050, 328, 12, 2031, 5348, 82254, 14, 1542, 1494, 24286, 11, 1418, 279, 15020, 277, 649, 29376, 264, 7340, 315, 220, 868, 59432, 315, 5370, 4595, 13, 578, 67950, 3055, 574, 6319, 11951, 311, 6929, 330, 1959, 279, 56551, 1, 89022, 1245, 7677, 11, 49001, 89022, 1245, 20948, 7677, 449, 1579, 30699, 31971, 1741, 82, 323, 59432, 527, 11887, 3117, 505, 279, 20948, 35909, 311, 30437, 15635, 311, 279, 20948, 8448, 13, 6385, 60112, 706, 1027, 21091, 304, 220, 679, 15, 11, 994, 1364, 574, 961, 315, 264, 3465, 5457, 31474, 2778, 323, 25539, 7677, 369, 279, 1867, 58330, 432, 4012, 50, 8602, 263, 276, 11, 902, 1047, 1027, 68265, 304, 264, 4892, 16526, 45264, 3440, 627, 2181, 706, 1027, 26579, 430, 279, 67950, 3055, 596, 11213, 9722, 706, 1027, 49482, 449, 53560, 86185, 11, 902, 36050, 279, 5845, 315, 279, 11213, 9722, 311, 51571, 279, 1579, 20472, 315, 14467, 7677, 13, 4452, 11, 1093, 279, 622, 4931, 5375, 596, 10320, 38060, 15144, 11, 1077, 42408, 27367, 11213, 9722, 323, 39825, 315, 279, 4741, 21351, 7585, 1053, 1397, 16781, 17466, 1603, 8521, 29480, 14467, 1436, 14816, 1022, 1077, 627, 1016, 26240, 374, 279, 24417, 5793, 315, 264, 1510, 19115, 304, 279, 13936, 64976, 13, 578, 5373, 4931, 921, 587, 462, 29853, 361, 29651, 574, 20968, 555, 12233, 519, 689, 304, 18157, 323, 44224, 304, 5587, 220, 2550, 22, 13, 22196, 311, 279, 15506, 19115, 2394, 2910, 3527, 409, 20717, 324, 3557, 11, 433, 374, 29441, 449, 264, 220, 717, 11877, 29779, 7940, 311, 14816, 279, 16591, 27490, 19574, 596, 320, 5463, 45, 8, 26155, 315, 12431, 12, 23, 50, 7011, 5477, 320, 27588, 7401, 8, 44305, 13, 578, 921, 587, 462, 29853, 361, 29651, 574, 13517, 369, 49380, 23362, 22967, 320, 7244, 57, 8, 22156, 323, 9313, 323, 2778, 323, 17629, 11, 719, 433, 1436, 1101, 387, 1511, 369, 43772, 3290, 323, 2585, 11, 3805, 1862, 369, 279, 27490, 7479, 26155, 477, 21426, 16337, 627, 4944, 49033, 4661, 220, 806, 11, 2636, 20181, 2539, 2865, 11, 279, 921, 587, 462, 29853, 361, 29651, 374, 279, 25655, 14467, 19115, 5131, 304, 2532, 13, 3005, 574, 311, 14816, 264, 9709, 3805, 1912, 315, 7011, 67987, 323, 328, 12, 2031, 33, 43269, 24286, 59432, 11, 449, 279, 10860, 45, 23395, 5899, 4846, 15506, 14467, 369, 279, 7580, 13, 4452, 279, 14875, 6020, 11501, 315, 220, 2550, 22, 2231, 7318, 311, 1884, 51566, 11, 449, 264, 6996, 315, 11006, 2389, 5859, 279, 921, 587, 462, 29853, 361, 29651, 311, 2700, 1455, 315, 279, 892, 13, 578, 7011, 5477, 26155, 706, 1101, 16654, 28178, 11, 449, 279, 26155, 5616, 1694, 50682, 505, 10860, 45, 2532, 304, 220, 1049, 21, 627, 644, 3293, 1667, 279, 921, 587, 462, 29853, 361, 29651, 706, 7543, 810, 892, 520, 9581, 11, 10213, 311, 7945, 304, 473, 97573, 25664, 13, 3005, 3952, 961, 304, 16337, 7677, 304, 279, 40696, 315, 279, 220, 1049, 19, 7904, 22302, 38413, 323, 72155, 11, 323, 304, 2077, 311, 8821, 39262, 24455, 304, 3389, 220, 679, 15, 323, 4216, 220, 679, 16, 13, 763, 220, 679, 17, 16233, 370, 7376, 430, 433, 1047, 4036, 459, 2015, 505, 279, 16591, 27490, 19574, 369, 279, 47035, 315, 279, 921, 587, 462, 29853, 361, 29651, 596, 3290, 323, 2585, 1887, 627, 791, 435, 12, 1758, 33, 16225, 198, 4516, 527, 1521, 18198, 14467, 35991, 477, 539, 30, 1442, 499, 320, 1315, 398, 8, 2980, 264, 36125, 459, 14467, 11, 1243, 32654, 279, 4320, 374, 10035, 13, 2030, 311, 7664, 1521, 18198, 439, 14467, 35991, 304, 279, 8776, 5647, 315, 15691, 8521, 29480, 14467, 369, 15538, 10096, 11, 2574, 3719, 8309, 74, 1291, 13, 578, 84757, 20324, 323, 921, 587, 462, 527, 38048, 10825, 311, 6920, 8521, 29480, 14467, 505, 279, 68864, 11, 1524, 422, 279, 15629, 12775, 956, 2884, 779, 369, 264, 1317, 1418, 1457, 13, 4452, 11, 279, 69890, 323, 48923, 65725, 15144, 18198, 11, 1418, 3515, 264, 11213, 9722, 13171, 315, 10565, 10928, 12040, 4206, 36563, 47524, 320, 790, 46, 31798, 8, 44305, 1778, 439, 279, 85236, 5364, 35945, 435, 12, 1758, 33, 30833, 36478, 42667, 11, 1053, 2103, 1397, 5199, 17466, 1603, 814, 1436, 387, 25605, 304, 430, 5647, 627, 2520, 43806, 11, 279, 18198, 690, 1397, 264, 29487, 47056, 41394, 9435, 927, 279, 20948, 19300, 311, 6144, 279, 9722, 505, 279, 14560, 20472, 2391, 279, 435, 12, 1758, 33, 596, 20948, 11008, 13, 36233, 5043, 44305, 690, 1101, 3152, 264, 3544, 43257, 1862, 9986, 690, 1397, 311, 387, 3196, 389, 4580, 279, 8448, 11, 449, 810, 15020, 277, 323, 5942, 3130, 1694, 4529, 555, 37768, 11, 24804, 5596, 323, 1023, 1862, 7241, 323, 17274, 2631, 311, 1862, 279, 44305, 13, 2052, 420, 690, 1397, 6696, 33583, 304, 3634, 389, 4580, 279, 18198, 11, 902, 690, 4661, 7995, 30485, 872, 5845, 311, 2804, 872, 1023, 10825, 13073, 627, 14364, 3682, 88455, 2565, 1053, 387, 430, 1701, 14467, 35991, 304, 459, 15538, 8824, 7612, 279, 19115, 5196, 311, 387, 77656, 449, 1202, 1866, 8209, 1912, 13, 25122, 7000, 315, 1521, 16867, 8235, 552, 617, 279, 4208, 18143, 11, 814, 617, 3686, 311, 7373, 2274, 279, 46398, 33235, 477, 26411, 2631, 11, 323, 814, 1541, 956, 617, 3805, 323, 5015, 43160, 16572, 311, 14816, 304, 420, 1648, 13, 1115, 374, 682, 264, 6908, 49326, 11, 23537, 1667, 311, 6920, 1555, 11, 1524, 449, 1520, 505, 1510, 19115, 20197, 1778, 439, 279, 549, 815, 13, 19574, 13, 7089, 1109, 5734, 11, 7000, 315, 1521, 8235, 552, 5101, 311, 617, 6787, 369, 420, 304, 279, 3221, 3938, 627, 8142, 1063, 617, 29440, 279, 15919, 315, 220, 717, 12, 845, 435, 12, 1758, 75307, 389, 9722, 304, 264, 12324, 11, 433, 2011, 387, 6646, 430, 8994, 279, 3958, 3577, 11, 264, 7373, 25605, 435, 12, 1758, 690, 4097, 264, 1847, 11843, 4091, 304, 3805, 12896, 439, 584, 1440, 433, 13, 7570, 264, 21030, 315, 1521, 14467, 11, 45455, 37774, 10565, 505, 264, 13726, 24948, 7401, 77656, 555, 264, 8209, 1912, 304, 279, 13057, 11104, 16867, 11, 690, 3854, 6129, 12896, 23099, 323, 1391, 49895, 279, 83768, 369, 904, 82499, 304, 904, 12324, 13, 4452, 11, 279, 2144, 374, 430, 14188, 8494, 11, 6457, 477, 4987, 12126, 527, 11, 477, 617, 8199, 291, 369, 11, 42990, 279, 435, 12, 1758, 33, 11, 1524, 422, 279, 4846, 1403, 17089, 617, 8667, 709, 369, 279, 1221, 44322, 12040, 4206, 323, 47524, 435, 12, 1758, 32, 2373, 627, 2028, 12716, 603, 311, 279, 4325, 2362, 4360, 25, 18099, 13, 3161, 42484, 1234, 7410, 304, 8494, 477, 6457, 11, 14188, 3224, 374, 304, 264, 2361, 311, 3887, 1778, 18336, 4442, 304, 9232, 48378, 13, 35211, 17035, 380, 6821, 72665, 11, 279, 4623, 315, 14467, 35991, 505, 15481, 5961, 11380, 46303, 304, 279, 19001, 16867, 374, 11, 311, 1005, 264, 58412, 4751, 11, 5710, 304, 279, 3090, 627, 35541, 816, 25634, 374, 264, 23672, 520, 5464, 1978, 50047, 5513, 323, 41147, 627, 39563, 64976, 8235, 552, 198, 1517, 1617, 3806, 198, 39, 41192, 69890, 198, 2607, 4931, 921, 587, 462, 29853, 361, 29651, 198, 12830, 48923, 65725, 198, 1308, 41549, 67950, 3055, 198, 26070, 5734, 15379, 25, 24922, 596, 24772, 8733, 15379, 423, 458, 16274, 3161, 5734, 198, 4438, 13936, 4946, 7557, 47329, 315, 3420, 596, 36478, 389, 10471, 596, 65615, 318, 5676, 198, 5733, 309, 596, 11215, 520, 279, 15248, 1074, 315, 1322, 24781, 30241, 6890, 596, 1561, 94836, 7658, 198, 9315, 578, 46562, 81868, 596, 42248, 25, 6186, 220, 777, 11, 220, 2366, 15, 11, 14398, 198, 89335, 596, 622, 37, 12, 1114, 8527, 14767, 42667, 25365, 37970, 83942, 27675, 198, 9642, 11, 279, 59945, 51961, 2209, 16782, 650, 2205, 198, 1383, 8096, 22770, 14433, 300, 198, 52, 815, 13, 52139, 3806, 527, 539, 12207, 810, 20134, 3432, 13, 1102, 374, 1057, 4124, 315, 5905, 430, 706, 5614, 627, 32, 14013, 12, 679, 24, 13002, 311, 8620, 59945, 3341, 17740, 198, 1383, 23194, 13142, 198, 3923, 374, 279, 3938, 35782, 315, 279, 8620, 9029, 596, 72984, 13309, 19574, 19115, 2068, 5380, 23078, 596, 59945, 51961, 20423, 6055, 198, 1383, 34975, 37326, 68, 63206, 13201, 258, 198, 2170, 279, 3224, 22890, 1202, 1176, 39678, 19115, 11, 1148, 2643, 433, 617, 304, 4059, 5380, 9751, 29476, 2453, 329, 488, 64, 323, 279, 59945, 51961, 83888, 198, 1383, 3765, 71, 3251, 275, 27992, 198, 32, 502, 19115, 1093, 6890, 596, 1587, 810, 1109, 1120, 79164, 6437, 55051, 23099, 627, 1383, 24008, 2947, 7876, 198, 71730, 596, 4034, 48227, 291, 5734, 12, 5159, 46816, 20405, 11, 719, 279, 4410, 649, 2103, 20874, 627, 1383, 816, 5308, 22227, 30162, 587, 32945, 198, 49852, 596, 2708, 300, 1133, 4947, 9017, 53455, 11, 16625, 555, 74556, 48079, 323, 58817, 369, 3823, 3268, 11, 374, 12899, 279, 97851, 53624, 627, 1383, 816, 2933, 350, 14694, 25191, 198, 3957, 27647, 4857, 264, 5425, 28117, 3674, 15009, 1887, 11, 832, 3241, 6425, 520, 264, 892, 5380, 1383, 8279, 411, 969, 2394, 300, 12930, 198, 791, 41167, 596, 3293, 11031, 617, 282, 7443, 24087, 430, 433, 374, 665, 36022, 1317, 58606, 19226, 311, 1893, 264, 36142, 7140, 627, 3923, 596, 9479, 369, 62138, 596, 66659, 35979, 5380, 1383, 6941, 473, 21493, 198, 6153, 264, 2466, 2046, 369, 279, 3224, 596, 14076, 11, 264, 1427, 520, 1148, 1253, 10457, 8469, 369, 433, 439, 1664, 439, 34896, 64949, 11759, 810, 8965, 627, 71730, 94486, 68846, 82, 3011, 5734, 596, 70920, 4470, 9137, 15832, 2893, 57074, 57606, 198, 46023, 11527, 5068, 264, 17676, 10205, 304, 279, 1396, 315, 5157, 439, 814, 11007, 279, 8624, 649, 387, 9041, 1990, 29374, 1274, 627, 34648, 800, 2914, 3216, 1561, 17360, 12, 966, 45240, 40, 71172, 198, 1383, 66620, 40720, 830, 276, 480, 7759, 198, 791, 25902, 44305, 315, 279, 502, 98380, 527, 3685, 311, 387, 17903, 449, 279, 3805, 53926, 10880, 2373, 315, 279, 78084, 77406, 1043, 95657, 31551, 26290, 627, 49852, 596, 23896, 650, 4336, 311, 34507, 17671, 596, 15766, 304, 2326, 23590, 198, 49852, 596, 12801, 9675, 35549, 13028, 56239, 43347, 7418, 311, 48227, 813, 3224, 596, 3560, 1234, 1202, 4868, 60821, 449, 279, 549, 815, 13, 304, 330, 2743, 3634, 323, 9693, 1941, 1330, 10246, 34648, 3475, 83930, 61748, 12, 6174, 11, 3804, 85543, 95016, 10880, 13131, 4633, 68870, 198, 791, 26290, 7195, 505, 264, 85177, 5452, 1022, 279, 13962, 315, 1628, 73010, 43458, 3952, 2035, 389, 6186, 220, 777, 13, 128000, 10577, 220, 19, 91, 1399, 220, 17, 13, 777, 13, 1313, 12, 17, 13, 914, 13, 1313, 198, 55, 21538, 4381, 4756, 279, 2360, 13, 220, 16, 8792, 2246, 369, 220, 2366, 17, 11, 330, 7271, 84996, 315, 279, 10913, 10554, 323, 3314, 9251, 389, 44245, 5422, 21387, 315, 1219, 31882, 28014, 12605, 9151, 58320, 10315, 2223, 2065, 5664, 8489, 304, 220, 2366, 17, 1210, 320, 10031, 19903, 28986, 3857, 340, 71730, 94486, 1685, 4591, 927, 264, 16307, 65, 2868, 6574, 389, 220, 914, 7552, 311, 4358, 279, 3314, 9251, 596, 10165, 14050, 315, 279, 330, 62569, 5664, 8423, 1, 5946, 555, 279, 5165, 9029, 596, 8151, 320, 64299, 8, 323, 21835, 660, 389, 6821, 389, 279, 10913, 10554, 596, 26767, 990, 11, 8104, 449, 24886, 311, 279, 6020, 10706, 13, 320, 10031, 19903, 28986, 3857, 340, 16298, 596, 13690, 4756, 459, 66233, 320, 61337, 68931, 8, 389, 279, 15676, 315, 279, 220, 1187, 339, 20704, 25944, 11871, 304, 27647, 13, 320, 10031, 3998, 351, 10018, 5664, 3857, 340, 15777, 87638, 315, 279, 10913, 10554, 11, 3314, 9251, 11, 323, 10913, 28058, 9849, 17836, 330, 21119, 369, 72743, 323, 75096, 40432, 510, 16397, 60, 279, 364, 975, 339, 21594, 71998, 510, 21119, 31751, 702, 17, 13, 508, 578, 3331, 87638, 315, 279, 10913, 10554, 11, 3314, 9251, 11, 323, 10913, 28058, 9849, 320, 10190, 34, 8, 6051, 6004, 264, 330, 21119, 369, 72743, 323, 75096, 40432, 12220, 279, 364, 975, 339, 21594, 71998, 510, 21119, 60, 15260, 320, 6881, 10924, 14183, 311, 439, 330, 1820, 9878, 1865, 8718, 14782, 311, 26905, 439, 459, 330, 15693, 5457, 304, 279, 8246, 315, 41289, 6617, 2065, 1359, 279, 9878, 2663, 3815, 990, 5552, 311, 26905, 1664, 439, 330, 414, 8722, 596, 13263, 7060, 14135, 1210, 1102, 1101, 27463, 330, 985, 43526, 94486, 36287, 389, 9983, 2191, 449, 8620, 85084, 369, 264, 1561, 48688, 439, 19351, 1, 323, 330, 339, 14776, 398, 25976, 3331, 12667, 43526, 94486, 596, 3062, 91518, 5552, 311, 21487, 990, 1, 311, 22829, 9256, 1778, 439, 330, 25475, 354, 58, 287, 60, 279, 1579, 22867, 4500, 315, 21487, 990, 1210, 578, 9878, 706, 4848, 9021, 11, 32125, 25, 220, 16, 13, 330, 1141, 398, 3041, 1514, 311, 279, 3560, 315, 5054, 19351, 5233, 220, 17, 13, 330, 884, 31882, 28014, 4933, 279, 4367, 315, 77218, 14740, 5233, 220, 18, 13, 10768, 19553, 264, 60, 810, 22514, 1887, 369, 279, 17575, 315, 64863, 323, 10932, 2335, 6514, 510, 998, 43720, 26905, 6, 29658, 60, 5233, 220, 19, 13, 10768, 28389, 430, 60, 279, 23583, 3268, 510, 1073, 26905, 60, 5371, 5457, 1285, 9313, 5233, 220, 20, 13, 10768, 8110, 553, 279, 60, 2867, 47035, 315, 17357, 311, 8854, 323, 1862, 510, 85, 1430, 598, 60, 5233, 323, 220, 21, 13, 330, 22025, 66735, 270, 9890, 279, 16975, 315, 16044, 323, 5201, 1210, 763, 5369, 11, 433, 10212, 8223, 330, 15693, 30601, 794, 220, 16, 13, 330, 318, 35563, 279, 6373, 1887, 369, 21487, 22747, 5233, 220, 17, 13, 330, 67523, 18972, 279, 5054, 323, 42933, 19351, 315, 26905, 5233, 220, 18, 13, 330, 33980, 268, 279, 15180, 315, 279, 22165, 1887, 369, 26905, 5233, 220, 19, 13, 330, 884, 31882, 28014, 12192, 14740, 323, 75505, 10708, 369, 26905, 5233, 220, 20, 13, 330, 64119, 14234, 279, 6373, 2237, 315, 6411, 21624, 2532, 5233, 220, 21, 13, 10768, 19553, 264, 60, 22514, 15803, 1887, 369, 279, 17575, 315, 64863, 323, 10932, 2335, 6514, 510, 998, 43720, 26905, 6, 29658, 60, 5233, 220, 22, 13, 330, 33980, 268, 279, 20862, 315, 29488, 323, 42317, 7769, 369, 23757, 323, 60449, 5544, 5233, 323, 220, 23, 13, 330, 1141, 398, 3041, 1514, 311, 279, 5054, 66732, 315, 1403, 11815, 990, 320, 104836, 116557, 102301, 41418, 578, 9878, 1101, 2663, 389, 330, 543, 5990, 315, 4717, 42547, 11, 17047, 11, 323, 9959, 30028, 323, 6411, 26280, 1, 311, 6106, 279, 8292, 315, 279, 9878, 596, 9021, 323, 9256, 627, 4444, 1582, 22018, 17836, 8, 330, 7271, 84996, 315, 279, 10913, 10554, 323, 3314, 9251, 389, 44245, 5422, 21387, 315, 1219, 31882, 28014, 12605, 9151, 58320, 10315, 2223, 2065, 5664, 8489, 304, 220, 2366, 17, 702, 17, 13, 1313, 1952, 220, 1313, 7552, 11, 1630, 21538, 4381, 6004, 330, 7271, 84996, 315, 279, 10913, 10554, 323, 3314, 9251, 389, 44245, 5422, 21387, 315, 1219, 31882, 28014, 12605, 9151, 58320, 10315, 2223, 2065, 5664, 8489, 304, 220, 2366, 17, 1, 320, 6881, 10924, 14183, 311, 439, 279, 330, 7271, 84996, 4063, 11136, 389, 220, 19, 6186, 439, 279, 2360, 13, 220, 16, 8792, 2246, 369, 220, 2366, 17, 13, 578, 10901, 84996, 10555, 10742, 369, 30029, 5552, 311, 279, 28522, 11, 3728, 7100, 13654, 11, 323, 10182, 2349, 11, 323, 279, 10913, 10554, 596, 16801, 430, 19624, 79955, 2065, 323, 29149, 10396, 527, 3062, 369, 330, 29092, 323, 9498, 80431, 4500, 1210, 2435, 11224, 430, 990, 389, 279, 330, 28956, 19624, 4819, 1, 320, 46091, 107019, 65131, 2265, 10745, 11, 19624, 5789, 11, 323, 20957, 8, 304, 220, 2366, 17, 1288, 15499, 1833, 5370, 13878, 315, 42933, 323, 4947, 19351, 11, 2737, 2768, 43526, 94486, 36287, 389, 9983, 2191, 449, 8620, 85084, 369, 264, 1561, 48688, 11, 25976, 279, 9090, 315, 279, 8722, 596, 220, 777, 339, 8151, 323, 1856, 93672, 11, 4737, 330, 47079, 287, 5426, 3691, 4868, 323, 27252, 264, 3544, 13230, 471, 311, 19542, 439, 279, 1403, 5740, 5238, 1359, 323, 810, 13, 578, 10901, 84996, 11951, 10555, 8223, 3682, 9021, 315, 19624, 79955, 2065, 512, 1, 6600, 13671, 50056, 3691, 5788, 323, 279, 8312, 315, 3062, 8356, 449, 682, 510, 414, 60, 8333, 1, 555, 27276, 4954, 1060, 21691, 48114, 3158, 323, 2612, 315, 50056, 15657, 11, 32302, 47035, 279, 5788, 8824, 315, 29839, 28440, 323, 5707, 11, 23391, 264, 15528, 8312, 315, 15657, 11, 23391, 430, 7982, 41936, 374, 34235, 369, 20957, 555, 43468, 23395, 323, 43121, 11, 323, 24429, 38210, 58499, 3062, 29149, 3956, 1664, 627, 1, 626, 265, 18972, 1862, 369, 264, 6617, 29149, 2385, 1, 555, 23391, 279, 27331, 29149, 1005, 315, 802, 481, 4363, 11, 13390, 11218, 51157, 9021, 369, 18899, 3117, 86794, 11, 22923, 5557, 369, 1401, 29149, 4819, 11, 18899, 279, 4500, 323, 1005, 315, 29149, 7241, 11, 11469, 29149, 13077, 11, 323, 27252, 3682, 29149, 51751, 627, 4808, 688, 264, 3544, 13230, 471, 311, 19542, 555, 18899, 24717, 311, 8891, 12576, 11, 22923, 8738, 12992, 304, 8070, 369, 279, 19624, 7187, 11, 7859, 12576, 311, 1401, 5789, 12588, 7294, 75488, 17098, 12576, 477, 47397, 60995, 11, 323, 22923, 50401, 53881, 304, 7294, 75488, 17098, 12576, 627, 1, 14139, 389, 5064, 311, 12192, 19624, 4500, 1, 555, 14691, 311, 12192, 279, 18052, 315, 6156, 11, 14580, 11, 323, 80423, 5064, 304, 19624, 5789, 26, 11469, 19647, 311, 31518, 279, 1274, 323, 48513, 279, 8246, 315, 279, 36754, 1887, 389, 279, 14189, 2237, 26, 22923, 2254, 14740, 323, 75505, 26, 323, 22923, 279, 6307, 4500, 315, 30029, 323, 19624, 5789, 627, 1, 47041, 398, 323, 357, 2915, 12192, 279, 8246, 315, 19624, 5789, 1, 555, 3339, 22514, 24717, 369, 25976, 19624, 8246, 11, 14691, 7677, 369, 19624, 12434, 35093, 11, 50453, 6913, 14054, 304, 1401, 26593, 11, 22923, 264, 330, 58369, 47967, 1359, 323, 48513, 61876, 9293, 369, 586, 3600, 520, 279, 14189, 2237, 627, 7894, 3210, 7417, 19624, 35186, 555, 48513, 279, 8246, 315, 57193, 8722, 5315, 11, 9721, 1113, 330, 78995, 15771, 323, 3772, 369, 279, 8246, 315, 19624, 18330, 36017, 1359, 323, 709, 43591, 279, 9096, 323, 20334, 315, 19624, 8396, 627, 33703, 20542, 279, 8333, 315, 19297, 369, 4947, 36755, 323, 46417, 24717, 1, 12899, 19624, 79955, 2065, 555, 24050, 9341, 11, 48513, 6020, 3600, 11, 323, 48513, 279, 8246, 315, 330, 51977, 306, 7411, 1359, 439, 1664, 439, 15691, 704, 1401, 19624, 31343, 627, 1, 62367, 304, 323, 20259, 279, 8722, 596, 16195, 11692, 315, 364, 28956, 19624, 4819, 6, 990, 1, 555, 28230, 1113, 12014, 369, 19624, 79955, 2065, 11, 4857, 3831, 4717, 14726, 369, 19624, 990, 11, 323, 330, 911, 300, 10194, 3585, 510, 1527, 3217, 477, 1296, 7620, 60, 311, 3063, 8244, 990, 304, 12963, 28014, 28818, 19624, 79955, 2065, 10246, 54, 526, 25507, 25, 20915, 66735, 8000, 41593, 12, 7575, 9029, 596, 48189, 323, 4610, 535, 311, 18042, 1295, 279, 24987, 315, 279, 18592, 315, 7658, 304, 5734, 198, 17, 13, 1313, 16307, 65, 2868, 12308, 323, 5734, 7658, 13581, 16478, 29346, 25507, 320, 101538, 126915, 8, 18677, 279, 220, 868, 339, 5734, 39898, 1705, 17997, 304, 27647, 323, 12886, 264, 72005, 8982, 13, 763, 813, 8982, 11, 29346, 46728, 430, 433, 374, 5995, 311, 330, 329, 6881, 311, 279, 8722, 596, 11692, 11, 279, 1274, 1694, 279, 36467, 315, 872, 1866, 22747, 30309, 40265, 46729, 19967, 36668, 705, 323, 35186, 3196, 389, 279, 6037, 315, 2383, 26, 330, 1040, 18007, 2274, 4459, 51194, 1274, 596, 20095, 320, 37087, 112696, 104733, 121302, 1237, 6106, 430, 279, 1274, 527, 279, 36467, 315, 872, 1866, 22747, 555, 2383, 26, 323, 37106, 311, 12192, 4857, 264, 6037, 8838, 31412, 5734, 449, 1695, 7016, 323, 35186, 1210, 1283, 11922, 430, 330, 67733, 51194, 1274, 596, 20095, 1, 374, 264, 3682, 26501, 315, 279, 8722, 330, 21307, 279, 1274, 311, 12178, 26623, 32887, 19297, 11, 33232, 19297, 11, 323, 15325, 19297, 1359, 439, 1664, 439, 264, 330, 54121, 535, 4668, 430, 19512, 21168, 279, 20095, 315, 51618, 449, 8620, 17910, 449, 682, 13124, 315, 53416, 20095, 320, 114637, 113688, 53434, 121302, 8, 304, 279, 4410, 1210, 29346, 4726, 46728, 430, 279, 1690, 5897, 43195, 304, 5734, 1288, 617, 264, 28254, 8830, 315, 279, 3682, 19476, 315, 330, 67733, 51194, 1274, 596, 20095, 1359, 1288, 18885, 330, 44541, 950, 659, 91980, 323, 33232, 659, 91980, 1359, 323, 330, 359, 2332, 651, 11559, 1833, 279, 1853, 315, 41289, 26623, 5054, 4500, 449, 8620, 17910, 1210, 1283, 1243, 2663, 369, 330, 67523, 18972, 287, 3495, 323, 30617, 5552, 311, 5734, 596, 5426, 1887, 323, 5897, 1887, 11, 439, 1664, 439, 330, 64119, 24435, 304, 279, 6725, 315, 41289, 26623, 6037, 315, 2383, 8246, 10246, 97447, 65, 2868, 66379, 288, 10423, 5664, 8423, 11, 7462, 8799, 988, 389, 330, 777, 339, 10913, 10554, 596, 97588, 17535, 315, 9925, 49813, 69478, 22241, 8423, 1359, 330, 1622, 5664, 315, 279, 220, 2366, 16, 10913, 10554, 67046, 5664, 59143, 5856, 69478, 8423, 1359, 43526, 94486, 4203, 3422, 198, 17, 13, 914, 43526, 94486, 1685, 4591, 927, 264, 16307, 65, 2868, 6574, 389, 220, 914, 7552, 311, 4358, 279, 3314, 9251, 596, 10165, 14050, 315, 279, 330, 62569, 5664, 8423, 1, 5946, 555, 279, 5165, 9029, 596, 8151, 320, 64299, 8, 323, 21835, 660, 389, 264, 330, 777, 339, 10913, 10554, 596, 97588, 17535, 315, 9925, 49813, 69478, 22241, 8423, 1, 323, 330, 1622, 5664, 315, 279, 220, 2366, 16, 10913, 10554, 67046, 5664, 59143, 5856, 69478, 8423, 1210, 578, 16307, 65, 2868, 6574, 14407, 279, 33997, 323, 11774, 315, 220, 2366, 16, 11, 323, 9021, 304, 18459, 369, 279, 14827, 220, 508, 339, 8722, 8151, 13, 1102, 10555, 430, 420, 1060, 11, 20334, 690, 387, 279, 10844, 315, 990, 11, 23537, 7191, 8292, 315, 18563, 77249, 10396, 11, 5655, 6901, 15180, 323, 3157, 39535, 26, 25976, 19297, 32505, 4500, 4947, 11, 7859, 13018, 7631, 11, 323, 22923, 47672, 2254, 4500, 11, 330, 943, 10827, 16036, 2065, 1, 320, 17039, 25287, 60174, 104643, 33208, 705, 29149, 5788, 11, 323, 19624, 79955, 2065, 26, 22923, 279, 15528, 4500, 315, 7362, 9341, 323, 6696, 11, 18899, 279, 4676, 323, 3428, 24948, 6098, 4500, 26, 18189, 15635, 304, 279, 6020, 1887, 26, 323, 18899, 279, 1274, 596, 64751, 82, 323, 279, 4367, 315, 35186, 13, 578, 16307, 65, 2868, 37475, 279, 10913, 10554, 596, 37477, 4883, 315, 58074, 369, 29040, 279, 3062, 734, 315, 5054, 38217, 11, 11951, 279, 330, 38461, 10913, 10554, 449, 1219, 50176, 43526, 94486, 439, 279, 6332, 1, 48513, 58983, 11, 43790, 11692, 927, 6020, 990, 13, 2468, 279, 1890, 892, 11, 279, 16307, 65, 2868, 11224, 430, 279, 58074, 43522, 279, 6020, 10706, 596, 8738, 5435, 449, 330, 95574, 287, 279, 8722, 596, 16195, 11692, 11, 48513, 8722, 8246, 11, 510, 438, 60, 12963, 28014, 323, 26549, 510, 44018, 60, 4717, 35186, 320, 123201, 46281, 109759, 71005, 104478, 41418, 578, 16307, 65, 2868, 46728, 279, 1205, 369, 279, 8738, 48513, 315, 10913, 10554, 11692, 927, 279, 10706, 323, 38189, 311, 5471, 15635, 11, 10519, 20334, 11, 323, 5471, 21948, 13, 17830, 11, 433, 7373, 12054, 315, 279, 10913, 10554, 67046, 5664, 59143, 5856, 596, 220, 2366, 16, 990, 323, 220, 2366, 17, 6787, 627, 16298, 596, 13690, 66233, 25, 30833, 398, 7199, 279, 57357, 29098, 315, 279, 8691, 315, 26888, 11, 22462, 11, 323, 16418, 198, 17, 13, 1691, 9029, 596, 13690, 4756, 459, 66233, 320, 61337, 68931, 8, 389, 279, 15676, 315, 279, 220, 1187, 339, 20704, 25944, 11871, 304, 27647, 13, 10506, 287, 279, 20704, 33063, 11, 279, 66233, 61414, 430, 27647, 1047, 330, 33871, 12882, 279, 6928, 9090, 323, 2410, 315, 279, 8620, 1274, 311, 279, 1917, 323, 6267, 264, 502, 47403, 304, 279, 20704, 33063, 7351, 1210, 2876, 287, 430, 7946, 10168, 279, 20704, 33063, 330, 1285, 28611, 5734, 596, 64702, 11471, 311, 279, 1917, 1, 323, 330, 258, 29403, 10082, 323, 2410, 1139, 264, 1917, 510, 911, 391, 12127, 449, 60, 279, 36505, 315, 279, 28522, 1359, 433, 1903, 2380, 24654, 922, 279, 20704, 33063, 25, 5629, 11, 279, 20704, 33063, 1051, 330, 276, 53990, 50256, 320, 43292, 58318, 109522, 57106, 8, 70960, 58439, 18851, 4458, 1, 430, 5602, 5734, 596, 5178, 15253, 279, 7140, 1555, 11230, 12387, 60082, 13, 10657, 11, 279, 20704, 33063, 1051, 330, 276, 24674, 18101, 430, 574, 539, 4228, 311, 510, 13397, 72066, 578, 66233, 10555, 430, 5734, 10168, 279, 20704, 33063, 304, 279, 35446, 315, 279, 3728, 28522, 323, 23391, 279, 7296, 315, 13324, 330, 5610, 291, 279, 2294, 2410, 315, 22706, 38586, 287, 927, 27129, 323, 11774, 1210, 21530, 11, 433, 11224, 430, 279, 20704, 33063, 1051, 459, 330, 412, 10276, 30816, 315, 279, 33436, 315, 39143, 1210, 578, 66233, 10555, 430, 5540, 1778, 439, 22150, 2955, 323, 5557, 743, 264, 330, 943, 29531, 369, 279, 33063, 1210, 9479, 11, 433, 10555, 430, 279, 20704, 33063, 8710, 279, 12939, 315, 23915, 323, 31426, 304, 279, 3663, 315, 11774, 323, 32647, 2380, 58522, 369, 13016, 25, 220, 16, 13, 330, 10267, 603, 2567, 279, 4113, 98741, 315, 279, 25944, 7351, 32620, 304, 4059, 323, 53258, 10726, 1917, 9096, 5233, 220, 17, 13, 330, 10267, 603, 12192, 279, 9090, 315, 279, 25944, 7351, 323, 52696, 311, 6013, 311, 4279, 11774, 510, 69, 4628, 60, 279, 6625, 4029, 5233, 323, 220, 18, 13, 330, 10267, 603, 6725, 279, 16945, 315, 279, 25944, 7351, 323, 3136, 279, 49326, 315, 22923, 279, 5208, 315, 43384, 1210, 4740, 37810, 5734, 596, 7537, 311, 3136, 304, 79645, 1778, 439, 1694, 264, 330, 18331, 315, 1917, 9096, 11, 264, 26373, 311, 3728, 4500, 11, 323, 264, 29315, 315, 6625, 2015, 1359, 279, 66233, 20536, 25, 330, 644, 420, 3280, 315, 279, 13654, 315, 682, 5496, 2574, 11, 584, 527, 2539, 315, 22519, 505, 279, 58439, 18851, 4458, 315, 279, 27647, 20704, 33063, 323, 527, 2539, 315, 31293, 369, 279, 1828, 510, 67288, 25944, 11871, 948, 6914, 603, 4430, 279, 2294, 8063, 315, 279, 33063, 11, 53258, 1893, 279, 2294, 27025, 315, 279, 33063, 11, 323, 743, 1022, 3871, 9017, 279, 810, 6366, 3938, 315, 43384, 25765, 84778, 647, 1443, 833, 25, 510, 7456, 3296, 60, 2467, 1964, 287, 311, 22462, 323, 73808, 510, 6854, 1226, 60, 4610, 535, 41493, 569, 264, 27508, 12781, 198, 17, 13, 1313, 362, 34449, 647, 1443, 833, 320, 76161, 71174, 8, 31710, 10968, 389, 279, 220, 2970, 339, 47304, 8398, 15217, 5762, 505, 220, 972, 311, 220, 508, 7552, 13, 1102, 10555, 430, 279, 15217, 596, 7057, 315, 330, 359, 21656, 1520, 33028, 1, 27000, 279, 330, 1904, 3674, 19451, 315, 11104, 5961, 1, 323, 574, 330, 1820, 49497, 315, 11104, 5961, 539, 31474, 32100, 659, 60684, 479, 304, 2077, 311, 4442, 64233, 304, 264, 9478, 320, 102616, 102718, 8107, 39442, 19361, 55030, 27384, 75140, 91077, 8, 4245, 311, 264, 6996, 315, 10396, 311, 6013, 311, 3728, 11774, 1210, 578, 31710, 1243, 6688, 1403, 19075, 369, 330, 359, 21656, 1520, 33028, 1210, 5629, 433, 11349, 330, 34500, 287, 264, 4495, 4868, 1684, 430, 374, 330, 6228, 11, 28814, 11, 48566, 11, 323, 22556, 1, 304, 2077, 311, 2225, 2536, 10398, 329, 3079, 4868, 4819, 323, 87998, 24408, 430, 374, 15098, 3728, 304, 7138, 323, 7612, 29173, 369, 11175, 13, 10657, 11, 279, 31710, 32647, 279, 1205, 311, 330, 82, 2642, 82971, 2814, 44039, 2191, 323, 279, 3728, 2015, 1210, 1102, 10555, 430, 330, 55977, 5961, 1, 1047, 17045, 304, 6299, 430, 5343, 330, 7430, 344, 58, 287, 60, 24062, 5111, 7422, 320, 106142, 102778, 91763, 104083, 36493, 330, 3427, 58, 287, 60, 304, 2466, 369, 86978, 24679, 1359, 323, 330, 64717, 58, 287, 60, 90503, 19399, 323, 45647, 1210, 578, 31710, 50697, 430, 1778, 6299, 330, 6236, 5663, 311, 320, 105068, 45893, 69636, 77180, 108, 8, 279, 3682, 18845, 315, 3728, 7447, 2320, 7569, 2065, 323, 279, 97167, 2065, 315, 6625, 4398, 1, 323, 2663, 369, 5961, 311, 330, 33950, 398, 9429, 264, 502, 955, 315, 6625, 4398, 1, 32971, 555, 330, 7129, 940, 5201, 11, 51841, 323, 12437, 11, 323, 3243, 48789, 23915, 320, 112355, 55999, 120721, 10143, 304, 5369, 311, 24944, 1023, 506, 22780, 811, 13, 72633, 311, 279, 15217, 596, 3361, 3882, 389, 1268, 311, 1684, 5734, 596, 4500, 11, 433, 22628, 10507, 1778, 439, 5734, 596, 17575, 315, 20562, 12, 777, 40300, 311, 810, 1109, 220, 4364, 5961, 323, 6625, 11351, 323, 279, 33993, 323, 9728, 38756, 320, 33, 4403, 8, 311, 1501, 430, 330, 64, 5734, 430, 706, 810, 16757, 4500, 4367, 323, 16643, 23099, 369, 1957, 690, 40605, 3085, 810, 4907, 369, 3728, 1772, 2320, 438, 8274, 13654, 323, 1304, 7191, 19564, 311, 6625, 9096, 323, 20334, 1210, 578, 31710, 20536, 555, 28898, 430, 330, 2170, 264, 15690, 4562, 1614, 315, 279, 6781, 8398, 9251, 323, 279, 1917, 596, 2132, 68067, 8752, 11, 5734, 690, 1514, 279, 3560, 323, 734, 315, 264, 8647, 3682, 3224, 320, 106941, 111928, 27384, 29504, 1237, 3136, 311, 387, 264, 7514, 315, 1917, 9096, 11, 26373, 311, 3728, 4500, 11, 323, 264, 29315, 315, 279, 6625, 2015, 26, 323, 5249, 6206, 449, 682, 11314, 311, 53258, 1893, 264, 810, 6366, 1917, 304, 279, 1772, 2320, 438, 8274, 11639, 10246, 54, 526, 25482, 4203, 3422, 6193, 38771, 3791, 5165, 16478, 77751, 6, 30155, 198, 17, 13, 1419, 16307, 65, 2868, 46327, 10554, 12308, 323, 8620, 9029, 596, 31597, 20556, 1413, 15217, 320, 16234, 3791, 8, 5165, 10554, 16478, 29346, 25482, 320, 21980, 103, 106390, 8, 1685, 4591, 927, 323, 12886, 264, 8982, 520, 279, 220, 2287, 339, 16478, 9164, 596, 6574, 315, 279, 220, 1032, 339, 38771, 3791, 5165, 10554, 13, 578, 6574, 330, 444, 5735, 291, 279, 3293, 3062, 11470, 323, 9090, 315, 3331, 12667, 43526, 94486, 389, 3815, 38771, 3791, 990, 323, 10168, 279, 23690, 6574, 315, 279, 220, 1032, 339, 38771, 3791, 5165, 10554, 1664, 1, 323, 34793, 311, 264, 990, 6671, 1934, 389, 10073, 5382, 990, 369, 279, 23690, 6574, 315, 279, 220, 1032, 339, 38771, 3791, 5165, 10554, 13, 763, 813, 8982, 11, 29346, 27463, 279, 1205, 311, 330, 652, 351, 76, 7167, 323, 30820, 34477, 682, 7471, 323, 10073, 5382, 990, 1664, 510, 2000, 279, 23690, 6574, 315, 279, 220, 1032, 339, 38771, 3791, 5165, 10554, 19727, 323, 330, 3055, 28522, 27344, 323, 2585, 990, 1664, 1, 304, 2015, 311, 6106, 430, 279, 6574, 374, 264, 2450, 13, 72633, 311, 279, 10347, 287, 315, 279, 220, 508, 339, 8722, 8151, 3010, 420, 1060, 11, 568, 14407, 31474, 7640, 1778, 439, 330, 83, 6427, 279, 7493, 315, 279, 8722, 11125, 23871, 369, 279, 1274, 323, 5426, 73484, 367, 1664, 323, 11890, 7493, 315, 7447, 24993, 23915, 323, 5054, 29173, 1664, 11, 311, 656, 279, 990, 315, 76387, 2410, 369, 279, 220, 508, 339, 8722, 8151, 1664, 1210, 29346, 1101, 46728, 279, 12939, 315, 330, 631, 58, 1303, 60, 4741, 1579, 22867, 18463, 323, 18726, 1, 323, 330, 77752, 287, 510, 40575, 315, 3347, 990, 60, 430, 4219, 2212, 279, 9090, 315, 279, 10913, 38771, 3791, 5664, 15217, 1359, 304, 5369, 311, 25394, 1023, 6299, 13, 578, 6574, 1101, 12054, 279, 2768, 9477, 25, 220, 16, 13, 330, 791, 38771, 3791, 5165, 10554, 220, 2366, 16, 26623, 38217, 315, 279, 8292, 315, 220, 975, 339, 21594, 9941, 9878, 990, 6671, 1934, 1359, 220, 17, 13, 330, 1820, 28818, 6335, 29173, 990, 6671, 1934, 1359, 323, 220, 18, 13, 279, 38771, 3791, 5165, 10554, 4562, 9678, 8990, 990, 6671, 1934, 13, 578, 6574, 1101, 12054, 279, 5597, 311, 73138, 279, 10195, 488, 315, 29346, 30444, 320, 101538, 73597, 101, 705, 29346, 52150, 97337, 320, 101538, 106665, 237, 115333, 705, 21296, 48934, 320, 109863, 31106, 224, 705, 323, 53548, 816, 7141, 647, 320, 101523, 237, 108309, 105417, 8, 439, 3697, 315, 279, 38771, 3791, 5165, 10554, 627, 15777, 8410, 315, 279, 10913, 28058, 9849, 37543, 330, 7271, 84996, 389, 18042, 11780, 279, 87865, 315, 279, 5464, 12, 2461, 323, 12028, 2065, 315, 32817, 7977, 702, 17, 13, 1419, 578, 3331, 8410, 315, 279, 10913, 28058, 9849, 320, 10190, 34, 8, 6051, 11136, 264, 743, 315, 10901, 84996, 389, 279, 5410, 2065, 323, 330, 3231, 12, 2461, 1, 320, 124426, 33208, 8, 315, 95864, 13, 12362, 43526, 94486, 36287, 389, 9983, 2191, 449, 8620, 85084, 369, 264, 1561, 48688, 439, 330, 24343, 685, 1, 323, 330, 7430, 20222, 2212, 50453, 264, 6617, 6411, 43257, 1887, 323, 264, 6617, 6411, 3424, 6373, 1887, 1359, 279, 10901, 84996, 9395, 311, 1520, 17312, 10772, 369, 4208, 323, 9006, 4819, 304, 95864, 8246, 1778, 439, 264, 5357, 389, 19664, 2324, 927, 20646, 369, 323, 24435, 304, 12896, 13, 2140, 2101, 4848, 30732, 323, 220, 1313, 9908, 11, 279, 10901, 84996, 5357, 389, 2204, 4595, 315, 50154, 369, 23963, 323, 95864, 13, 763, 5369, 11, 279, 10901, 84996, 1101, 47032, 279, 1005, 315, 4519, 1778, 439, 330, 58369, 74477, 1, 323, 3428, 24948, 6098, 4500, 304, 95864, 2955, 11, 439, 1664, 439, 5627, 311, 7417, 279, 8246, 315, 95864, 1555, 5528, 1778, 439, 330, 24343, 287, 3157, 15086, 311, 27136, 16136, 304, 8246, 1210, 578, 10901, 84996, 330, 66, 2353, 989, 5891, 4035, 2212, 6411, 8446, 11, 4967, 11, 323, 9232, 1359, 330, 73140, 279, 18651, 315, 15180, 323, 4500, 369, 279, 6411, 1359, 323, 330, 630, 5528, 369, 5410, 4954, 279, 4553, 1920, 315, 95864, 8246, 323, 6373, 10246, 4444, 1582, 22018, 17836, 8, 12362, 279, 41143, 21460, 315, 279, 8722, 596, 88370, 71998, 4610, 50428, 311, 18042, 1295, 279, 5234, 29342, 10965, 11050, 315, 11997, 44550, 67046, 323, 62924, 1854, 5664, 323, 20776, 279, 12022, 22766, 1221, 1055, 287, 315, 279, 220, 508, 339, 8722, 8151, 8713, 6919, 8423, 520, 279, 77021, 68077, 1856, 9195, 315, 279, 220, 777, 339, 10913, 9849, 369, 98646, 67046, 198, 17, 13, 1187, 1630, 21538, 4381, 4756, 279, 1495, 315, 16307, 65, 2868, 46327, 10554, 12308, 323, 10913, 9849, 369, 98646, 67046, 320, 3791, 18091, 8, 11452, 70381, 2009, 7910, 596, 320, 122028, 102264, 104153, 8, 990, 1934, 12886, 389, 220, 972, 6186, 520, 279, 68077, 1856, 9195, 315, 279, 220, 777, 339, 93833, 40, 13, 35698, 287, 389, 279, 93833, 40, 596, 990, 304, 220, 2366, 16, 11, 70381, 27463, 3892, 13878, 315, 279, 93833, 40, 596, 990, 25, 220, 16, 13, 330, 33980, 398, 21630, 323, 8830, 43526, 94486, 36287, 389, 9983, 2191, 449, 8620, 85084, 369, 264, 1561, 48688, 11, 48513, 5054, 25917, 323, 279, 18526, 24151, 315, 12963, 28014, 323, 26549, 510, 44018, 60, 4717, 35186, 320, 123201, 46281, 109759, 71005, 104478, 8, 5233, 220, 17, 13, 330, 67523, 18972, 287, 5054, 38217, 40069, 87126, 2212, 279, 364, 20375, 82060, 6, 320, 110835, 104083, 104979, 8, 323, 44413, 264, 3831, 15803, 369, 7314, 279, 220, 975, 339, 21594, 9941, 9878, 1664, 5233, 220, 18, 13, 330, 25475, 11780, 364, 1962, 59772, 311, 387, 22681, 11, 1694, 12153, 311, 16988, 304, 21948, 11, 323, 539, 19762, 311, 387, 22681, 6, 320, 16937, 116773, 124884, 5486, 54253, 124884, 5486, 16937, 101067, 124884, 8, 6957, 510, 1820, 93833, 40, 1145, 19546, 810, 46417, 3135, 323, 810, 7524, 35186, 5233, 220, 19, 13, 330, 9254, 287, 279, 8292, 315, 279, 9090, 315, 279, 10913, 36944, 49357, 320, 109432, 102397, 48982, 111152, 8, 2085, 264, 4545, 596, 2800, 1, 323, 11039, 279, 330, 35124, 7739, 1, 320, 64803, 103125, 25, 16287, 2191, 11, 34846, 18071, 2191, 11, 61316, 263, 2191, 11, 323, 74164, 685, 1237, 220, 20, 13, 25228, 7922, 323, 3339, 2539, 1005, 315, 26767, 31261, 26, 220, 21, 13, 3318, 330, 74946, 311, 5718, 11, 26434, 11, 323, 2383, 1, 323, 18899, 5304, 38217, 11, 26434, 13627, 11, 323, 2383, 13627, 26, 220, 22, 13, 3339, 5208, 304, 330, 84146, 20695, 369, 279, 9346, 288, 1, 7640, 323, 52829, 1523, 389, 21948, 323, 53808, 61555, 2212, 279, 32738, 26, 323, 220, 23, 13, 48513, 330, 20885, 2065, 11, 57588, 320, 25333, 71005, 33208, 705, 323, 49823, 1, 323, 330, 97944, 287, 1579, 22867, 11, 28175, 1, 5687, 13, 9479, 11, 70381, 10666, 9021, 369, 279, 93833, 40, 369, 220, 2366, 17, 323, 279, 14827, 220, 508, 339, 8722, 8151, 25, 220, 16, 13, 330, 33980, 268, 4007, 323, 8292, 315, 279, 9090, 315, 279, 8722, 596, 68077, 1856, 9195, 11, 21760, 389, 279, 364, 16548, 6945, 323, 16188, 12034, 315, 279, 3224, 6, 320, 29504, 55030, 27384, 30046, 8, 311, 4585, 369, 279, 49823, 323, 390, 4523, 2065, 315, 5054, 38217, 5233, 220, 17, 13, 10519, 279, 8333, 323, 9006, 315, 17879, 7294, 46713, 14455, 9045, 26, 220, 18, 13, 3136, 311, 55414, 279, 10913, 36944, 49357, 323, 59233, 389, 21948, 323, 53808, 61555, 2212, 279, 32738, 26, 220, 19, 13, 7417, 279, 4367, 323, 7036, 315, 26767, 31261, 26, 220, 20, 13, 12192, 31343, 311, 7417, 279, 18052, 11, 38793, 11, 323, 27375, 315, 279, 26434, 26767, 1887, 26, 323, 220, 21, 13, 7417, 5054, 6677, 323, 7512, 11, 13788, 439, 330, 1820, 8722, 323, 279, 1274, 596, 29947, 72881, 10246, 17, 13, 1313, 77021, 7327, 6011, 320, 3791, 47, 14, 926, 8, 32724, 11452, 1229, 1122, 19730, 83227, 320, 107112, 119494, 58911, 8, 5762, 264, 4200, 21976, 6574, 449, 279, 7665, 20302, 596, 8722, 315, 279, 7665, 14043, 320, 1777, 43, 4390, 17, 13, 1419, 77021, 14, 926, 11452, 19508, 60608, 320, 74138, 96311, 249, 8, 18677, 279, 60810, 315, 279, 386, 27495, 79426, 70345, 452, 27253, 486, 37263, 6150, 11, 3196, 304, 69894, 323, 18538, 555, 4848, 18561, 11904, 5054, 9875, 11, 4669, 23895, 337, 771, 13, 19508, 1373, 264, 40588, 38220, 6661, 505, 43526, 94486, 13, 69894, 596, 4872, 8388, 689, 46962, 12825, 84, 60777, 323, 6164, 315, 279, 2978, 596, 4848, 36330, 9875, 12570, 520, 279, 1567, 13, 7409, 18071, 38220, 12197, 1051, 3288, 555, 4987, 10384, 596, 4872, 95805, 15504, 1366, 12252, 11, 52543, 90929, 596, 4872, 16807, 3527, 15385, 18614, 37832, 53913, 11, 98792, 596, 4872, 11186, 3496, 9928, 1466, 20822, 11, 31074, 67337, 596, 4872, 473, 425, 4323, 287, 677, 11, 323, 52320, 596, 4872, 66555, 1293, 57831, 526, 351, 10196, 11, 682, 6164, 315, 872, 20081, 9875, 627, 17, 13, 1419, 77021, 14, 926, 32724, 11452, 25507, 67927, 320, 112848, 102776, 8, 5762, 264, 2835, 1650, 449, 4846, 12801, 9675, 323, 1510, 21892, 315, 279, 37961, 8722, 315, 50064, 320, 86479, 57210, 8, 9671, 71, 402, 41240, 50064, 627, 17, 13, 1419, 77021, 14, 926, 32724, 11452, 58880, 2893, 4008, 320, 120299, 105623, 241, 106732, 8, 5762, 264, 2835, 1650, 449, 77424, 596, 17192, 12, 29543, 13015, 323, 8847, 258, 9265, 5165, 72984, 15248, 320, 37, 8143, 45, 8, 18740, 1676, 10010, 100214, 386, 9329, 1030, 2206, 4458, 13, 128000, 48, 25, 36476, 15391, 220, 17, 8018, 11480, 3250, 956, 990, 358, 1005, 36476, 15391, 220, 17, 11480, 311, 15411, 50507, 21438, 304, 832, 315, 856, 917, 13, 1115, 44165, 1501, 1268, 358, 18447, 311, 11480, 323, 9020, 311, 433, 596, 4455, 198, 9380, 2523, 1212, 368, 341, 262, 54240, 4893, 28177, 10849, 6407, 1271, 84306, 5172, 1535, 2865, 1502, 2455, 633, 2039, 2523, 18447, 1271, 84306, 5172, 4658, 52386, 341, 262, 471, 50507, 33544, 198, 286, 662, 9569, 1966, 60460, 39978, 340, 286, 662, 96159, 27664, 39978, 340, 286, 662, 9569, 1383, 1021, 394, 95712, 284, 314, 50507, 1492, 3665, 84306, 55730, 1889, 8, 1173, 394, 56346, 284, 314, 2905, 962, 16372, 11, 330, 84306, 40635, 4686, 909, 1173, 394, 33530, 284, 314, 384, 1492, 2905, 962, 16372, 11, 330, 84306, 40635, 1493, 498, 384, 8, 457, 286, 1763, 633, 65386, 33544, 374, 1665, 315, 11480, 27, 84306, 29, 955, 13, 1115, 682, 4375, 7060, 389, 1972, 3756, 449, 1972, 50507, 21438, 13, 4800, 358, 1390, 311, 5089, 1296, 279, 3665, 84306, 368, 1749, 323, 1456, 311, 8018, 279, 11480, 27, 84306, 29, 420, 1648, 198, 54665, 67536, 6491, 57348, 20051, 487, 1058, 340, 1058, 44088, 93879, 34949, 18700, 1504, 262, 571, 11832, 198, 262, 879, 27222, 767, 2683, 1898, 25, 36943, 12524, 1898, 198, 262, 879, 1062, 9128, 39978, 284, 3475, 39978, 746, 262, 879, 1062, 1925, 39978, 284, 3475, 39978, 746, 262, 879, 1062, 50507, 33544, 25, 11480, 27, 84306, 29, 284, 11480, 63310, 7, 84306, 1021, 310, 330, 5154, 6726, 7755, 18485, 20, 498, 48565, 10930, 1020, 6712, 12419, 262, 571, 11832, 198, 262, 879, 27222, 767, 1217, 6221, 25, 2724, 6221, 198, 262, 571, 11832, 198, 262, 879, 27222, 767, 37113, 25, 48970, 198, 262, 571, 11832, 198, 262, 879, 27222, 767, 50507, 1898, 25, 87832, 4518, 1898, 271, 262, 571, 2323, 198, 262, 2523, 1296, 84306, 8960, 368, 341, 286, 1062, 90803, 284, 220, 679, 20417, 12505, 4119, 198, 286, 1062, 54240, 4893, 284, 41739, 58712, 2892, 286, 15716, 4374, 6221, 16714, 1534, 1502, 6139, 27940, 3269, 50891, 63310, 13388, 51062, 286, 1062, 34756, 284, 44088, 93879, 34949, 29429, 769, 11, 2683, 1898, 11, 54240, 4893, 11, 9128, 39978, 345, 394, 1925, 39978, 11, 50507, 33544, 11, 1217, 6221, 11, 37113, 11, 50507, 1898, 340, 286, 34756, 5069, 746, 262, 457, 633, 40, 2846, 23132, 430, 994, 358, 1650, 34756, 5069, 368, 34756, 2011, 18447, 311, 50507, 33544, 323, 5371, 95712, 368, 1567, 449, 1665, 358, 3077, 3984, 13, 2030, 420, 4536, 956, 12765, 13, 3639, 1097, 358, 3815, 5076, 30, 4815, 32, 25, 578, 3475, 39978, 374, 5505, 422, 499, 1205, 311, 1296, 18912, 449, 701, 23914, 13, 8876, 701, 1193, 4747, 449, 701, 8292, 1288, 387, 311, 1629, 279, 4365, 14453, 7162, 11, 499, 1288, 2731, 1005, 264, 328, 37312, 5543, 60452, 368, 4619, 13, 1115, 690, 1243, 1650, 15493, 323, 22695, 2085, 264, 4617, 2349, 382, 32, 25, 2684, 596, 40107, 8863, 2133, 389, 1606, 315, 40885, 323, 46071, 389, 2728, 5692, 27898, 13, 95712, 368, 1587, 539, 636, 27979, 14453, 7162, 439, 3685, 555, 701, 1296, 2082, 627, 2409, 264, 3475, 39978, 11, 499, 649, 384, 1326, 13, 1650, 8346, 13245, 368, 477, 12178, 1489, 1383, 368, 311, 9203, 40107, 2082, 627, 128000, 53965, 6620, 12433, 4939, 220, 11483, 320, 35, 1366, 21557, 60017, 3402, 17158, 3475, 340, 791, 20278, 574, 9967, 1234, 35288, 4787, 627, 791, 1296, 20278, 11, 264, 6573, 11, 574, 11054, 439, 25, 435, 12, 12405, 19, 280, 21753, 1396, 220, 13754, 5894, 18634, 280, 88616, 1396, 220, 11286, 23309, 12, 2096, 12, 16, 627, 791, 1296, 20278, 1047, 459, 32792, 2457, 315, 5887, 11, 220, 679, 22, 198, 12, 96409, 1749, 25, 72171, 10688, 1051, 14890, 505, 1855, 6514, 323, 2585, 1912, 8223, 323, 11888, 2919, 4972, 311, 279, 1212, 315, 279, 1296, 1306, 35121, 279, 19371, 29051, 369, 2380, 323, 1403, 2919, 11, 15947, 13, 24086, 10688, 1051, 14890, 505, 279, 8389, 323, 69996, 2585, 5315, 4972, 311, 1296, 61568, 311, 7838, 1070, 1051, 539, 17303, 32466, 315, 1296, 20278, 304, 279, 2585, 10105, 13, 72171, 3090, 10688, 1101, 1051, 14890, 505, 73462, 46113, 1296, 53279, 304, 1855, 6514, 323, 2585, 1912, 520, 279, 7314, 315, 279, 1296, 11, 520, 13489, 17496, 28090, 2391, 279, 1296, 323, 520, 279, 842, 315, 279, 1296, 311, 6767, 32466, 315, 279, 1296, 20278, 13, 59450, 315, 279, 5708, 10105, 1694, 12886, 311, 279, 19371, 29051, 1051, 14890, 369, 6492, 389, 6187, 220, 806, 315, 279, 4007, 13, 24086, 23329, 10688, 315, 1296, 10105, 1051, 14890, 389, 6187, 220, 975, 4245, 311, 264, 1296, 6425, 9889, 72287, 902, 40028, 832, 46113, 1296, 25199, 198, 1073, 279, 220, 914, 11, 220, 1135, 323, 220, 1041, 33983, 70, 7586, 6514, 5315, 13, 2052, 10688, 1051, 14890, 505, 5209, 31410, 13, 59450, 311, 387, 30239, 2085, 74182, 773, 367, 1051, 14890, 1139, 9168, 8753, 9518, 27474, 1701, 9168, 63920, 16743, 24547, 47003, 11, 1418, 10688, 311, 387, 30239, 1306, 74182, 773, 367, 1051, 14890, 1139, 12466, 74182, 4838, 34083, 985, 9168, 33109, 75421, 627, 12, 19690, 5942, 4787, 1603, 6492, 25, 1688, 1855, 25936, 10074, 832, 743, 315, 10688, 1051, 15590, 7214, 369, 6492, 323, 832, 743, 315, 10688, 1051, 9967, 369, 3284, 3938, 6492, 627, 12, 6872, 25, 30440, 5708, 10105, 1051, 10235, 369, 1855, 315, 279, 4330, 32466, 12793, 11, 323, 1051, 10235, 4848, 3115, 2391, 279, 4007, 13, 3475, 6425, 32466, 1051, 539, 24257, 369, 279, 4642, 25795, 315, 279, 1296, 20278, 2391, 18459, 11, 323, 527, 3196, 389, 279, 1296, 20278, 439, 4036, 13, 578, 6156, 5708, 574, 4538, 10297, 2000, 13489, 220, 605, 477, 220, 868, 4520, 323, 9922, 2867, 323, 1933, 1752, 11, 449, 912, 9621, 36841, 82829, 13, 13625, 14580, 5708, 10105, 1051, 10235, 304, 20804, 37, 520, 47855, 32466, 315, 220, 5495, 11, 220, 5894, 11, 220, 5154, 323, 220, 2636, 33983, 70, 93422, 555, 55272, 19371, 1516, 315, 279, 6156, 5708, 13, 12937, 10105, 1051, 9967, 30477, 660, 304, 9168, 68705, 27474, 449, 350, 830, 12490, 12175, 12, 15472, 100078, 11, 323, 43391, 2469, 315, 1855, 5708, 1051, 9277, 304, 279, 6705, 85124, 1475, 832, 311, 3116, 2919, 2391, 279, 4007, 627, 791, 4330, 1296, 20278, 5708, 10105, 1051, 41772, 1139, 279, 19371, 29051, 27890, 53279, 520, 264, 4478, 315, 220, 605, 13, 410, 33983, 43, 14, 43657, 1405, 814, 1051, 9709, 449, 19371, 1516, 3090, 12886, 520, 264, 4478, 315, 220, 1041, 65170, 14, 43657, 311, 11322, 279, 12974, 1296, 32466, 627, 12, 33170, 25, 578, 8389, 2585, 4036, 19371, 1516, 3090, 1193, 13, 578, 69996, 2585, 574, 10235, 555, 24944, 473, 2989, 34, 41327, 20804, 37, 311, 279, 27890, 25199, 369, 279, 69996, 2585, 627, 12, 36424, 836, 315, 7458, 320, 61694, 69996, 11, 991, 14630, 3125, 477, 79835, 519, 1680, 13223, 42972, 630, 66796, 320, 8561, 37, 340, 12, 62261, 2214, 315, 7458, 304, 1296, 11298, 320, 13787, 6425, 323, 1620, 1296, 6425, 1161, 8, 477, 25288, 1161, 8, 2737, 2585, 1161, 37815, 32, 6156, 5708, 6425, 574, 10235, 555, 27890, 264, 16997, 3392, 315, 1296, 20278, 1139, 473, 2989, 34, 41327, 5213, 42972, 630, 66796, 320, 8561, 37, 8, 520, 264, 47855, 20545, 315, 220, 1041, 15, 33983, 70, 93422, 13, 578, 20545, 315, 20804, 37, 304, 279, 69996, 2585, 323, 682, 435, 12, 12405, 19, 6514, 5315, 574, 220, 15, 13, 16, 65170, 7586, 627, 12, 44796, 315, 2073, 1056, 8905, 3769, 320, 68, 1326, 13, 36841, 20227, 11, 7479, 4632, 11, 5099, 13, 1680, 791, 5708, 10105, 1051, 9709, 555, 47588, 11, 323, 9922, 2867, 323, 1933, 1752, 627, 12, 7874, 836, 25, 423, 1366, 21557, 60017, 198, 12, 4610, 467, 14, 20579, 25, 83858, 511, 261, 276, 198, 12, 4702, 2461, 369, 9606, 1023, 1109, 32031, 555, 1296, 73545, 25, 912, 198, 12, 8922, 25, 27833, 18908, 555, 469, 1929, 78717, 11, 6460, 263, 11, 23481, 198, 12, 13381, 315, 46679, 5708, 320, 14622, 323, 2134, 11, 8189, 1680, 423, 1366, 58444, 47752, 988, 1511, 304, 279, 1296, 1051, 2753, 1109, 220, 1187, 4207, 2362, 198, 12, 3926, 16490, 2391, 1296, 25, 10035, 198, 12, 12369, 955, 25, 21655, 315, 41580, 11, 62233, 16763, 3772, 11, 323, 80827, 523, 363, 320, 56, 1182, 705, 89804, 449, 264, 28170, 5708, 6425, 323, 264, 25288, 315, 279, 80744, 6307, 453, 6885, 11, 432, 1366, 307, 511, 301, 285, 1207, 11600, 275, 460, 627, 12, 26868, 25, 1688, 1855, 26040, 11, 1855, 1296, 25199, 574, 23114, 220, 15, 13, 2075, 65170, 315, 816, 1182, 11, 220, 16, 13, 20, 65170, 315, 68951, 323, 220, 15, 13, 1135, 65170, 315, 28170, 6425, 13, 1115, 3392, 315, 5510, 374, 6273, 311, 13489, 220, 15, 13, 6028, 14060, 356, 3529, 1366, 58444, 45839, 13, 6104, 420, 3392, 315, 5510, 36375, 279, 79517, 73545, 11349, 3392, 315, 220, 15, 13, 16, 311, 220, 15, 13, 17, 14060, 356, 3529, 1366, 58444, 45839, 11, 459, 13937, 3392, 574, 23114, 304, 2015, 311, 10519, 14343, 5510, 304, 279, 6530, 43847, 1887, 311, 1862, 22281, 39656, 7969, 627, 12, 43480, 25, 423, 1366, 77, 3447, 1051, 23114, 1403, 477, 2380, 3115, 824, 1938, 1555, 6187, 220, 21, 315, 279, 1296, 323, 1243, 1051, 23114, 3116, 3115, 824, 1938, 3156, 279, 1566, 1938, 315, 279, 1296, 627, 12, 6515, 566, 5582, 4261, 512, 12, 6515, 566, 5582, 4787, 320, 25030, 439, 1296, 477, 539, 1680, 53130, 294, 1366, 77, 3447, 1051, 89948, 304, 3090, 505, 279, 1890, 2592, 323, 520, 13489, 279, 1890, 9499, 439, 1511, 2391, 279, 1296, 627, 12, 4078, 323, 3392, 315, 3691, 25, 439, 304, 279, 1296, 198, 12, 3926, 16490, 11900, 25, 439, 304, 279, 1296, 198, 12, 6401, 2391, 1645, 566, 5582, 320, 3852, 29528, 13468, 1680, 53130, 294, 1366, 77, 3447, 304, 279, 7829, 1047, 9124, 459, 5578, 315, 520, 3325, 2380, 3995, 824, 6822, 824, 1938, 927, 279, 220, 22, 11477, 4261, 4972, 311, 279, 1296, 13, 578, 12884, 8710, 912, 12195, 315, 8624, 477, 8631, 323, 912, 384, 764, 2877, 689, 1051, 9124, 2391, 279, 10168, 4261, 627, 39174, 4716, 21626, 16976, 3579, 3651, 95176, 3083, 91396, 9109, 66444, 17485, 2794, 10271, 61094, 4015, 11488, 512, 791, 4330, 6822, 294, 1366, 77, 3447, 1511, 311, 8312, 47752, 988, 369, 279, 1296, 1051, 5762, 369, 220, 1187, 2919, 4972, 311, 4526, 315, 279, 99545, 3742, 369, 7649, 11, 323, 1047, 1855, 9124, 520, 3325, 832, 3766, 2967, 347, 13, 662, 2057, 39201, 279, 1296, 11, 279, 48770, 294, 1366, 77, 3447, 1051, 14890, 505, 279, 27833, 323, 94546, 258, 2718, 23217, 832, 477, 1403, 520, 264, 892, 311, 8481, 53279, 3156, 1855, 25199, 13282, 220, 20, 294, 1366, 77, 3447, 13, 9062, 1912, 315, 47752, 988, 1243, 574, 68824, 398, 12893, 311, 264, 2585, 477, 6514, 1912, 323, 279, 47752, 988, 1051, 23217, 311, 279, 1296, 87352, 311, 39201, 279, 1296, 13, 2052, 31711, 1051, 1903, 3770, 279, 3090, 7479, 1701, 7029, 1481, 461, 24547, 47003, 627, 5072, 43847, 198, 80427, 389, 14675, 8250, 512, 1691, 11477, 14675, 4261, 1234, 6530, 43847, 1296, 4787, 13, 578, 9889, 1887, 323, 279, 1296, 53279, 1051, 9277, 304, 264, 9499, 41370, 12434, 25199, 311, 10519, 279, 2218, 3090, 9499, 6957, 279, 1296, 4261, 627, 6860, 12, 10410, 320, 12591, 7586, 439, 14751, 8445, 18, 340, 508, 12, 1691, 297, 34, 198, 972, 13, 18, 14060, 7586, 439, 39695, 198, 1128, 1076, 1968, 512, 16884, 12, 18781, 320, 44223, 50, 70298, 340, 10238, 3501, 37438, 49, 22545, 512, 37412, 992, 16729, 2206, 40412, 198, 39589, 7935, 366, 5125, 48, 198, 49912, 688, 7935, 366, 5125, 48, 198, 21, 13, 18, 64012, 70, 7586, 220, 21, 13, 21, 64012, 70, 7586, 198, 1032, 64012, 70, 7586, 220, 24, 13, 24, 64012, 70, 7586, 198, 914, 64012, 70, 7586, 220, 1187, 64012, 70, 7586, 198, 1041, 64012, 70, 7586, 220, 4278, 64012, 70, 7586, 198, 12, 3475, 27274, 25, 3475, 87352, 1051, 220, 3101, 65170, 9168, 387, 8476, 627, 12, 4078, 320, 4644, 422, 539, 8581, 1680, 1825, 198, 12, 10441, 11, 1404, 11, 2010, 8920, 11, 5266, 8286, 25, 3475, 87352, 1051, 220, 3101, 65170, 9168, 387, 8476, 11, 13489, 220, 21, 13, 20, 10166, 304, 23899, 323, 220, 717, 10166, 304, 2673, 13, 91762, 11546, 15670, 9960, 1403, 20349, 389, 14329, 11314, 315, 1855, 1296, 44598, 311, 11810, 1296, 6425, 311, 6530, 304, 323, 704, 315, 279, 44598, 13, 578, 8149, 315, 279, 1296, 3090, 304, 264, 18740, 44598, 574, 13489, 220, 23, 10166, 11, 1418, 279, 8149, 315, 3090, 304, 264, 18740, 1296, 25199, 574, 13489, 220, 845, 10166, 627, 12, 362, 21597, 25, 52132, 8905, 24463, 32466, 1051, 69398, 111, 22, 13, 19, 14060, 7586, 320, 78086, 111, 6086, 4, 315, 50843, 1350, 12, 4078, 315, 6530, 43847, 320, 68, 1326, 13, 824, 380, 3223, 292, 477, 55272, 19371, 29051, 1680, 55272, 19371, 29051, 13, 3475, 53279, 1051, 220, 717, 445, 9168, 15715, 10649, 10409, 449, 13489, 220, 605, 445, 315, 1296, 3090, 13, 578, 8286, 304, 279, 1296, 53279, 574, 18908, 555, 459, 16891, 2700, 389, 279, 3185, 315, 279, 1296, 25199, 627, 12, 50086, 278, 4478, 315, 1296, 6425, 320, 47621, 14, 5072, 4478, 1680, 791, 21801, 315, 279, 1296, 6425, 430, 574, 62454, 1139, 1855, 46113, 1296, 25199, 574, 10273, 4972, 311, 279, 1296, 323, 13489, 17496, 2391, 279, 1296, 311, 6106, 430, 6530, 7969, 28830, 555, 912, 810, 1109, 20903, 220, 20, 4, 315, 279, 3152, 6530, 4478, 369, 279, 29641, 988, 13, 578, 4330, 1296, 20278, 5708, 10105, 1051, 41772, 1139, 279, 19371, 29051, 27890, 53279, 520, 264, 4478, 315, 220, 605, 13, 410, 33983, 43, 14, 43657, 1405, 814, 1051, 9709, 449, 19371, 1516, 3090, 12886, 520, 264, 4478, 315, 220, 1041, 65170, 14, 43657, 311, 11322, 279, 12974, 1296, 32466, 13, 578, 8389, 2585, 4036, 19371, 1516, 3090, 1193, 13, 578, 69996, 2585, 574, 10235, 555, 24944, 473, 2989, 34, 41327, 20804, 37, 311, 279, 27890, 25199, 369, 279, 69996, 2585, 13, 578, 20545, 315, 20804, 37, 304, 279, 69996, 2585, 323, 682, 435, 12, 12405, 19, 6514, 5315, 574, 220, 15, 13, 16, 65170, 7586, 627, 12, 2360, 13, 315, 44304, 824, 27274, 25, 9062, 46113, 13282, 1403, 87352, 449, 4330, 294, 1366, 77, 3447, 11, 13239, 304, 264, 2860, 315, 220, 508, 294, 1366, 77, 3447, 304, 1855, 6514, 323, 2585, 1912, 198, 12, 2360, 13, 315, 31080, 824, 7458, 2585, 320, 10200, 416, 988, 1680, 220, 17, 198, 12, 91608, 395, 8441, 4478, 512, 12, 8922, 37359, 36235, 315, 19371, 1516, 3090, 25, 37440, 263, 8489, 10164, 198, 12, 10884, 17808, 12782, 32352, 220, 16, 198, 12, 3744, 292, 6468, 5030, 512, 12, 93815, 25, 43252, 10666, 304, 330, 8780, 1023, 2038, 389, 7384, 323, 5528, 1, 3770, 198, 12, 393, 10027, 3422, 25, 22409, 10666, 304, 330, 8780, 1023, 2038, 389, 7384, 323, 5528, 1, 3770, 198, 12, 92479, 483, 25, 19, 13, 18, 12591, 7586, 198, 12, 1708, 36641, 13797, 25, 10967, 1389, 220, 11256, 14060, 7586, 439, 14751, 8445, 18, 198, 12, 14751, 3262, 70, 11595, 512, 12, 50935, 1968, 25, 14423, 1389, 220, 18775, 44223, 50, 70298, 198, 12, 21023, 11298, 2204, 505, 1296, 11298, 512, 12, 1357, 43298, 315, 3090, 4367, 19179, 25, 12220, 279, 220, 19, 12, 17490, 26572, 69352, 5075, 2041, 287, 279, 3475, 198, 47, 10027, 3422, 11, 10995, 1233, 323, 93815, 482, 20017, 73279, 10887, 555, 66223, 78717, 389, 10688, 14890, 389, 6790, 220, 22, 11, 220, 679, 20, 198, 12, 18235, 3376, 3205, 25, 845, 4207, 315, 3177, 323, 220, 23, 4207, 315, 27394, 13, 362, 220, 966, 24401, 9320, 4261, 315, 3428, 3177, 21261, 574, 3984, 994, 13001, 4024, 389, 323, 1022, 311, 5766, 11210, 4442, 304, 18186, 627, 12, 8828, 21261, 25, 8027, 15, 14379, 520, 279, 7479, 315, 279, 3090, 198, 12, 3165, 4628, 8331, 369, 1296, 32466, 512, 12, 4702, 2461, 369, 1701, 2753, 32466, 1109, 11472, 555, 73545, 512, 12, 16842, 9455, 4007, 25, 10035, 198, 12, 3475, 32466, 25, 220, 23, 13, 16, 11, 220, 1544, 11, 220, 1954, 220, 3101, 11, 220, 1041, 15, 14060, 7586, 198, 12, 18591, 1511, 311, 8417, 279, 4787, 369, 279, 45813, 4007, 25, 17101, 992, 1296, 32466, 1051, 220, 21, 13, 18, 11, 220, 1032, 11, 220, 914, 11, 220, 1135, 323, 220, 1041, 33983, 70, 435, 12, 12405, 19, 7586, 627, 9173, 7650, 198, 4278, 64012, 70, 7586, 198, 2727, 300, 13, 320, 9613, 340, 1985, 5634, 627, 1623, 7650, 198, 29, 220, 4278, 64012, 70, 7586, 198, 4174, 315, 47752, 988, 9124, 824, 42889, 1938, 323, 1396, 315, 47752, 988, 9124, 824, 3974, 6822, 520, 2466, 20353, 315, 279, 1296, 198, 12, 80354, 278, 75815, 25, 423, 1366, 77, 3447, 304, 279, 2585, 323, 6514, 5315, 430, 26968, 311, 1296, 35508, 8965, 9922, 4725, 6957, 279, 1296, 13, 2684, 1051, 264, 2478, 24654, 315, 294, 1366, 77, 3447, 304, 279, 6514, 5315, 430, 9922, 28639, 11, 98522, 867, 292, 477, 1051, 13468, 311, 387, 19596, 389, 279, 7479, 315, 279, 1296, 6425, 13, 4452, 11, 1521, 24654, 1051, 4225, 70791, 11, 30139, 311, 24654, 304, 279, 2585, 5315, 323, 1550, 539, 1833, 264, 19660, 59569, 5497, 13, 15636, 11, 1521, 24654, 6646, 311, 387, 2536, 2442, 35320, 5552, 627, 12, 31943, 811, 389, 2547, 3160, 323, 4785, 64943, 1366, 77, 3447, 304, 279, 8389, 2585, 1912, 37956, 220, 20, 13, 16, 9653, 304, 3160, 323, 220, 16, 13, 1682, 14060, 304, 9235, 4785, 11, 1418, 294, 1366, 77, 3447, 304, 279, 69996, 2585, 1912, 37956, 220, 20, 13, 16, 9653, 304, 3160, 323, 220, 16, 13, 1987, 14060, 304, 9235, 4785, 13, 2684, 1051, 912, 5199, 12062, 304, 279, 6650, 5137, 1990, 279, 8389, 323, 69996, 2585, 5315, 320, 79, 871, 220, 15, 13, 2304, 570, 15636, 11, 279, 2585, 828, 1051, 76476, 369, 12593, 449, 279, 6514, 5315, 13, 423, 1366, 77, 3447, 304, 279, 76476, 2585, 323, 279, 220, 21, 13, 21, 11, 220, 24, 13, 24, 11, 220, 1187, 11, 220, 1399, 323, 220, 4278, 33983, 70, 7586, 6514, 5315, 1047, 3152, 198, 4222, 82, 315, 220, 20, 13, 16, 11, 220, 20, 13, 16, 11, 220, 19, 13, 24, 11, 220, 20, 13, 15, 11, 220, 20, 13, 15, 323, 220, 20, 13, 15, 9653, 11, 15947, 11, 323, 3152, 9235, 14661, 315, 220, 16, 13, 1644, 11, 220, 16, 13, 777, 11, 220, 16, 13, 1958, 11, 220, 16, 13, 843, 11, 220, 16, 13, 972, 323, 220, 16, 13, 1644, 14060, 11, 15947, 13, 10771, 311, 29838, 83824, 596, 1296, 11, 1070, 1051, 47952, 5199, 43154, 304, 3152, 3160, 369, 279, 220, 24, 13, 24, 11, 220, 1187, 323, 220, 1399, 33983, 70, 7586, 6514, 5315, 304, 12593, 311, 279, 76476, 2585, 320, 79, 38394, 220, 15, 13, 2304, 570, 4452, 11, 279, 12062, 1051, 1633, 8275, 23246, 220, 19, 34971, 1550, 539, 1833, 264, 19660, 59569, 5497, 323, 1051, 4461, 4245, 311, 279, 15376, 5410, 86365, 2949, 1855, 743, 315, 828, 13, 15636, 11, 279, 47952, 5199, 43154, 16914, 304, 279, 6514, 5315, 1051, 539, 6646, 311, 387, 6160, 30450, 23222, 13, 2684, 1051, 912, 47952, 5199, 43154, 304, 3152, 9235, 4785, 369, 904, 435, 12, 12405, 19, 6514, 1912, 304, 12593, 311, 279, 76476, 2585, 4184, 311, 29838, 83824, 596, 1296, 320, 79, 871, 220, 15, 13, 2304, 570, 53123, 11, 279, 5782, 7650, 369, 6650, 320, 4222, 323, 9235, 4785, 8, 574, 220, 4278, 33983, 70, 7586, 11, 323, 279, 5125, 7650, 574, 871, 4278, 33983, 70, 7586, 11, 279, 8592, 20545, 12793, 627, 12, 7089, 24156, 24654, 25, 53130, 294, 1366, 77, 3447, 304, 279, 76476, 2585, 323, 279, 220, 21, 13, 21, 11, 220, 24, 13, 24, 11, 220, 1187, 11, 220, 1399, 323, 220, 4278, 33983, 70, 7586, 6514, 5315, 9124, 459, 5578, 315, 220, 14378, 11, 220, 11702, 11, 220, 8848, 11, 220, 11227, 11, 220, 12815, 323, 220, 6280, 3974, 3995, 824, 6822, 520, 279, 7314, 315, 279, 1296, 11, 15947, 13, 29838, 83824, 596, 832, 2442, 5805, 1296, 16717, 1070, 1051, 912, 47952, 5199, 43154, 304, 279, 3152, 1396, 315, 3974, 3995, 9124, 824, 6822, 520, 279, 7314, 315, 279, 1296, 304, 904, 435, 12, 12405, 19, 6514, 1912, 304, 12593, 311, 279, 76476, 2585, 320, 79, 871, 220, 15, 13, 2304, 570, 53123, 11, 3196, 389, 279, 1396, 315, 3974, 3995, 9124, 824, 6822, 520, 279, 7314, 315, 279, 1296, 11, 279, 5782, 7650, 574, 220, 4278, 33983, 70, 7586, 323, 279, 5125, 7650, 574, 871, 4278, 33983, 70, 7586, 11, 279, 8592, 20545, 12793, 13, 20817, 389, 279, 1396, 315, 3974, 3995, 9124, 824, 6822, 520, 279, 7314, 315, 279, 1296, 13468, 304, 279, 6514, 5315, 11, 279, 220, 1691, 11477, 21283, 605, 323, 21283, 1135, 2819, 1051, 2225, 11075, 311, 387, 871, 4278, 33983, 70, 7586, 11, 279, 8592, 20545, 12793, 627, 12, 22806, 2786, 315, 2585, 25, 6153, 220, 1691, 2919, 315, 14675, 11, 20237, 304, 279, 8389, 2585, 323, 69996, 2585, 5315, 574, 220, 1954, 13, 15, 323, 220, 2721, 13, 15, 13689, 15947, 13, 8876, 1070, 1051, 912, 47952, 5199, 12062, 304, 20237, 1990, 279, 8389, 323, 69996, 2585, 5315, 369, 904, 5852, 12793, 320, 79, 871, 220, 15, 13, 2304, 705, 279, 2585, 828, 1051, 76476, 369, 36595, 311, 279, 6514, 5315, 627, 12, 7089, 31959, 6372, 2585, 512, 12, 3765, 8416, 14847, 512, 12, 5884, 24654, 320, 68, 1326, 13, 61050, 8, 430, 2643, 5353, 264, 6811, 1990, 17303, 323, 47855, 2819, 512, 12, 13756, 32466, 49005, 2092, 392, 1429, 315, 20278, 304, 1296, 11298, 25, 763, 279, 4007, 10219, 472, 290, 12771, 279, 3090, 2092, 392, 1429, 315, 279, 20278, 23246, 16, 33983, 70, 7586, 8, 555, 520, 3325, 1403, 10373, 315, 26703, 1701, 20804, 37, 439, 264, 19115, 13, 330, 4599, 264, 27692, 1296, 2955, 706, 1027, 11951, 11041, 311, 29376, 279, 56399, 315, 1296, 3769, 477, 1023, 9547, 4461, 311, 5353, 54709, 304, 1296, 32466, 11, 323, 279, 2955, 374, 45487, 26613, 3196, 389, 14343, 33269, 2038, 11, 279, 4007, 690, 539, 387, 18010, 21742, 389, 279, 21319, 430, 17303, 32466, 28830, 555, 810, 1109, 220, 966, 3346, 315, 279, 47855, 20545, 1981, 791, 1455, 3062, 37057, 374, 430, 279, 1296, 5990, 2011, 539, 3217, 264, 6541, 304, 330, 1382, 3343, 3011, 374, 11, 279, 8592, 1296, 2237, 1288, 7293, 8592, 11, 279, 1828, 1288, 7293, 2132, 11, 5099, 1210, 320, 24, 570, 2684, 1051, 912, 1558, 36379, 315, 17303, 32466, 6957, 279, 4007, 13, 15636, 11, 279, 1579, 54709, 304, 17303, 32466, 1288, 539, 5536, 279, 23692, 315, 279, 4007, 3135, 627, 791, 83858, 511, 261, 276, 11, 423, 1366, 21557, 60017, 11, 574, 15246, 311, 435, 12, 12405, 19, 520, 3152, 17303, 32466, 315, 220, 21, 13, 21, 311, 220, 4278, 33983, 70, 7586, 1234, 6530, 43847, 4787, 369, 220, 1691, 2919, 13, 578, 20278, 10219, 472, 919, 12771, 279, 3090, 2092, 392, 1429, 907, 23246, 16, 33983, 70, 7586, 8, 555, 520, 3325, 1403, 10373, 315, 26703, 1701, 20804, 37, 439, 264, 19115, 13, 35053, 11, 1070, 1051, 912, 6160, 30450, 23222, 11, 47952, 5199, 6514, 14228, 6372, 389, 20237, 11, 39656, 477, 6650, 520, 32466, 38394, 4278, 33983, 70, 7586, 13, 53123, 11, 279, 5782, 7650, 11, 574, 11075, 311, 387, 220, 4278, 33983, 70, 7586, 13, 578, 5125, 7650, 323, 25832, 34, 1051, 2225, 11075, 311, 387, 871, 4278, 33983, 70, 7586, 11, 279, 8592, 20545, 12793, 627, 791, 220, 1691, 11477, 21283, 1135, 907, 369, 6822, 4998, 677, 1429, 574, 11075, 311, 387, 871, 4278, 33983, 70, 7586, 11, 279, 8592, 20545, 12793, 13, 20817, 389, 279, 1396, 315, 3974, 3995, 9124, 824, 42889, 1938, 11, 279, 220, 1691, 11477, 21283, 605, 323, 21283, 1135, 2819, 1051, 11075, 311, 387, 871, 4278, 33983, 70, 7586, 13, 20817, 389, 279, 1396, 315, 3974, 3995, 9124, 824, 6822, 520, 279, 7314, 315, 279, 1296, 11, 279, 220, 1691, 11477, 21283, 605, 323, 21283, 1135, 2819, 1051, 11075, 311, 387, 871, 4278, 33983, 70, 7586, 627, 791, 83858, 511, 261, 276, 11, 423, 1366, 21557, 60017, 11, 574, 15246, 311, 435, 12, 12405, 19, 520, 3152, 17303, 32466, 315, 220, 21, 13, 21, 311, 220, 4278, 33983, 70, 7586, 1234, 6530, 43847, 4787, 369, 220, 1691, 2919, 13, 578, 20278, 10219, 472, 919, 12771, 279, 3090, 2092, 392, 1429, 907, 23246, 16, 33983, 70, 7586, 8, 555, 520, 3325, 1403, 10373, 315, 26703, 1701, 20804, 37, 439, 264, 19115, 13, 35053, 11, 1070, 1051, 912, 6160, 30450, 23222, 11, 47952, 5199, 6514, 14228, 6372, 389, 20237, 11, 39656, 477, 6650, 520, 32466, 38394, 4278, 33983, 70, 7586, 13, 128000, 49, 32054, 65555, 311, 387, 66819, 291, 1389, 477, 12860, 5380, 4599, 279, 18526, 432, 32054, 65555, 574, 33484, 743, 453, 492, 323, 18340, 6702, 304, 220, 6393, 17, 555, 279, 24113, 17312, 63620, 1070, 11, 433, 574, 4461, 430, 433, 1053, 733, 279, 1648, 315, 1690, 1023, 15316, 323, 5042, 387, 76993, 13, 14968, 279, 6952, 4835, 315, 445, 718, 2630, 11, 889, 13234, 279, 220, 3101, 64434, 12675, 11, 5042, 2163, 433, 323, 10968, 389, 13353, 279, 4363, 1139, 264, 1176, 15144, 6230, 11, 10923, 279, 3838, 311, 14297, 18678, 11, 9564, 1120, 279, 17967, 88, 31717, 329, 14620, 9621, 3432, 627, 791, 4648, 315, 279, 220, 20, 339, 48510, 11, 279, 11495, 29867, 20199, 445, 718, 2630, 11, 304, 220, 1049, 20, 11, 29746, 279, 3070, 311, 1427, 1578, 520, 279, 12675, 13, 4452, 11, 4856, 1109, 5042, 4662, 433, 814, 6773, 311, 6994, 9293, 8041, 369, 279, 4857, 315, 264, 502, 3838, 323, 617, 1457, 2231, 2225, 369, 6412, 520, 7083, 18, 13, 20, 76, 13, 10541, 459, 8196, 3388, 315, 1957, 11, 279, 11709, 1903, 2873, 264, 2766, 10535, 13, 578, 502, 3838, 374, 16917, 72460, 10272, 304, 2955, 719, 279, 41579, 9124, 779, 3117, 617, 433, 274, 1639, 779, 3345, 311, 279, 2579, 31217, 875, 12811, 315, 279, 2362, 3838, 11, 323, 279, 20366, 9998, 315, 279, 8993, 11, 430, 433, 5084, 311, 617, 4661, 27212, 1070, 555, 11677, 13, 1102, 7995, 1587, 539, 2873, 311, 5101, 520, 2162, 304, 420, 3813, 323, 8111, 4661, 25142, 11, 13239, 304, 2380, 3544, 43563, 5540, 11039, 369, 71199, 304, 264, 2678, 3158, 627, 2170, 279, 31387, 43563, 7061, 36783, 30444, 3520, 2795, 304, 279, 364, 6971, 5908, 323, 22806, 277, 6, 22822, 315, 6740, 596, 8691, 17222, 11, 22225, 279, 2731, 3072, 1053, 387, 311, 15301, 279, 4113, 3838, 13, 1115, 1053, 4546, 1203, 279, 8335, 902, 25281, 1603, 323, 4148, 520, 3131, 279, 8196, 27129, 315, 9564, 279, 2362, 3838, 439, 264, 14880, 13863, 79760, 311, 20874, 449, 279, 502, 3838, 13, 91395, 50631, 279, 12675, 323, 9293, 8041, 690, 23127, 1781, 1578, 922, 420, 13155, 323, 1427, 14243, 520, 35093, 627, 2028, 4441, 574, 8621, 304, 369, 6412, 11, 5513, 323, 38213, 18112, 11, 3224, 3838, 11, 12675, 11, 4027, 11, 369, 6412, 11, 38031, 326, 718, 2630, 11, 3678, 57440, 9736, 3520, 11, 9293, 8041, 11, 436, 32054, 30195, 1216, 11, 35093, 11, 5687, 541, 15255, 13, 56518, 279, 80328, 627, 21, 81567, 311, 432, 32054, 65555, 311, 387, 66819, 291, 1389, 477, 12860, 5380, 40, 7655, 449, 3721, 894, 1626, 499, 617, 1071, 1618, 662, 4014, 5620, 279, 2362, 3838, 5196, 374, 22225, 810, 20406, 1109, 279, 502, 832, 11223, 2506, 617, 1027, 45243, 279, 30195, 1216, 369, 1667, 1457, 3721, 81, 2533, 2133, 1070, 439, 34361, 321, 994, 358, 12439, 82, 304, 279, 2254, 14458, 13, 1102, 374, 9257, 304, 3925, 323, 311, 15301, 279, 2362, 3838, 1053, 22225, 71211, 279, 3347, 304, 682, 1202, 27025, 627, 29132, 12263, 432, 32054, 1193, 264, 5743, 315, 5672, 4227, 11, 358, 574, 17948, 555, 1120, 1268, 2466, 279, 12811, 315, 279, 4113, 3838, 374, 13, 8595, 5606, 1053, 1390, 311, 7066, 1695, 3263, 2301, 85060, 323, 8454, 433, 449, 264, 11670, 364, 77, 1009, 2933, 12, 2265, 383, 6, 72460, 10272, 4857, 6724, 357, 12055, 757, 627, 40, 617, 20041, 279, 23844, 9454, 79903, 323, 682, 279, 9364, 358, 649, 636, 3412, 315, 11, 323, 1101, 11021, 264, 2478, 39339, 14741, 11, 304, 279, 46604, 3987, 315, 1694, 279, 18069, 1732, 430, 5334, 311, 15301, 264, 2294, 3838, 2949, 279, 1455, 11364, 6246, 1974, 13, 128000, 1271, 7431, 433, 25, 733, 311, 279, 35343, 4519, 5769, 315, 701, 48970, 323, 5268, 20796, 16039, 627, 1271, 5268, 701, 16039, 6376, 25, 733, 311, 279, 62153, 5769, 11, 1505, 62153, 3941, 25, 323, 3820, 701, 7075, 6376, 13, 1472, 649, 5268, 3508, 499, 1193, 1390, 311, 1518, 279, 9302, 6576, 5769, 11, 477, 422, 499, 10932, 311, 636, 2225, 279, 330, 4126, 2592, 1, 323, 279, 330, 4126, 1, 23204, 320, 1820, 4846, 690, 7195, 279, 289, 61503, 428, 6576, 26, 279, 15629, 690, 1825, 279, 9302, 832, 4390, 2675, 649, 4048, 810, 922, 279, 330, 15698, 4600, 5769, 1, 1887, 520, 25098, 675, 7723, 2726, 13, 3011, 2199, 3649, 1268, 311, 3480, 1990, 29846, 4669, 279, 12706, 389, 279, 5507, 25995, 627, 2460, 51944, 1701, 279, 9302, 6576, 690, 387, 38213, 449, 330, 9789, 4600, 1, 304, 3293, 4442, 11, 3821, 18035, 11, 323, 2199, 53210, 13, 2057, 2680, 279, 2724, 13002, 369, 279, 9302, 6576, 11, 4299, 389, 279, 12262, 30, 10143, 4706, 304, 1202, 27031, 13, 1442, 499, 6562, 311, 2349, 701, 16039, 6376, 477, 311, 11404, 279, 9302, 6576, 11, 420, 649, 387, 2884, 1234, 330, 20814, 1, 304, 701, 19882, 627, 3947, 374, 264, 2875, 8641, 520, 25098, 675, 7723, 2726, 430, 499, 649, 1833, 320, 300, 422, 433, 574, 264, 330, 2071, 1638, 909, 311, 4048, 922, 279, 4029, 990, 5995, 311, 10737, 279, 9302, 6576, 11, 323, 1202, 57616, 1887, 304, 4040, 11, 311, 701, 4029, 596, 3966, 627, 2746, 499, 649, 15025, 505, 6498, 1139, 1023, 15823, 11, 477, 1440, 5606, 889, 649, 11, 4587, 1833, 279, 7902, 3770, 13, 1472, 3358, 1520, 701, 4029, 636, 279, 1888, 3284, 3217, 994, 433, 4131, 311, 3834, 6743, 323, 9904, 5552, 311, 279, 9302, 6576, 13, 4740, 499, 4299, 389, 904, 7902, 11, 701, 4221, 1288, 387, 2561, 505, 279, 6068, 15220, 5130, 389, 279, 1314, 13, 9843, 499, 3077, 4183, 433, 11, 499, 3358, 1518, 279, 2246, 304, 6498, 3185, 555, 3185, 449, 904, 14807, 990, 2736, 2884, 304, 701, 4221, 13, 1472, 649, 923, 502, 37793, 477, 5719, 6484, 6305, 13, 578, 3834, 374, 21685, 520, 3788, 1129, 14372, 30807, 5181, 26, 499, 3358, 1205, 459, 2759, 422, 499, 2646, 25548, 1070, 1603, 13, 578, 1217, 8641, 6439, 520, 7972, 54996, 2726, 11, 369, 902, 499, 649, 1005, 701, 5912, 27685, 2759, 13, 1472, 2351, 10788, 311, 3729, 264, 4029, 83199, 15716, 499, 1205, 1520, 627, 5618, 1934, 4819, 11, 422, 904, 11, 304, 2405, 29997, 859, 11, 279, 502, 10077, 15194, 1887, 477, 389, 279, 8792, 11302, 2199, 320, 258, 904, 4221, 8, 389, 25098, 675, 7723, 2726, 13, 2684, 374, 1101, 264, 12514, 4617, 389, 279, 6498, 43205, 285, 930, 13, 763, 1162, 315, 13147, 320, 4908, 459, 16907, 10077, 14718, 24716, 5435, 705, 4587, 3729, 7957, 1789, 265, 3751, 11, 5761, 10790, 369, 279, 9302, 6576, 11, 520, 503, 2000, 265, 3751, 31, 49537, 28034, 2726, 477, 389, 60428, 304, 279, 674, 4503, 675, 7723, 82489, 4381, 839, 1960, 4667, 5613, 627, 70564, 287, 279, 9302, 6576, 520, 43205, 285, 930, 706, 1027, 3284, 9523, 311, 3293, 9045, 315, 26202, 13707, 350, 418, 323, 9708, 77, 11, 7396, 555, 17810, 299, 375, 11, 622, 8910, 23576, 942, 323, 622, 67, 2000, 265, 3751, 520, 279, 90940, 36082, 24893, 220, 679, 21, 13, 128000, 54, 483, 612, 423, 483, 17535, 455, 25, 16526, 92028, 4999, 42, 61148, 374, 264, 3224, 449, 459, 8056, 36105, 323, 3925, 1131, 323, 369, 420, 2305, 596, 32926, 612, 423, 483, 1567, 11, 856, 4885, 323, 358, 28284, 12126, 323, 872, 18406, 50777, 627, 42, 46295, 36105, 706, 28995, 1555, 279, 24552, 315, 3674, 323, 5054, 2349, 11, 1555, 433, 596, 4676, 323, 13042, 18845, 13, 1442, 499, 3077, 3596, 294, 1619, 520, 264, 16526, 10960, 11, 832, 3245, 430, 499, 3358, 3217, 374, 279, 5370, 293, 3581, 276, 11, 477, 2678, 3185, 26863, 11, 430, 527, 10434, 7214, 1418, 499, 3868, 369, 701, 15496, 311, 17782, 13, 1115, 36105, 374, 1101, 3967, 369, 279, 5526, 9955, 3904, 11, 56884, 26883, 627, 644, 1690, 5627, 11, 16526, 36105, 374, 264, 10824, 315, 11002, 323, 8620, 31547, 1572, 11, 4869, 20426, 11002, 36105, 11, 16526, 36105, 5829, 2753, 7795, 323, 53405, 323, 706, 810, 25309, 323, 36167, 8987, 26863, 1131, 323, 20426, 8620, 36105, 11, 16526, 36105, 5829, 2753, 5707, 13, 16526, 15657, 1101, 8541, 311, 387, 993, 292, 1291, 1109, 11002, 323, 8620, 26863, 13, 578, 8798, 315, 279, 3691, 6118, 4131, 505, 279, 59717, 430, 596, 3629, 1511, 627, 10156, 439, 304, 25491, 374, 304, 11002, 36105, 11, 779, 8783, 374, 304, 16526, 36105, 13, 1789, 1057, 32926, 612, 423, 483, 14177, 11, 358, 1101, 9076, 264, 779, 8783, 47500, 311, 6857, 449, 1057, 16526, 15496, 13, 2100, 8783, 374, 459, 56461, 7172, 902, 706, 264, 4528, 12945, 439, 76524, 13, 2100, 8783, 374, 5016, 304, 430, 433, 649, 387, 1903, 505, 3060, 20228, 11, 81817, 11, 10437, 39834, 477, 264, 10824, 315, 1521, 14293, 627, 8586, 527, 279, 26863, 430, 12637, 3691, 50343, 617, 14976, 311, 856, 4200, 32926, 612, 423, 483, 1567, 0, 2057, 1817, 704, 1148, 856, 4885, 323, 358, 1172, 15386, 389, 369, 1057, 14177, 11, 2733, 1949, 311, 1817, 704, 1057, 9041, 323, 19141, 19804, 13, 11361, 311, 682, 856, 12637, 3691, 50343, 369, 872, 37935, 323, 358, 3987, 499, 3041, 16526, 36105, 264, 1456, 5246, 4999, 1687, 2351, 6041, 420, 4883, 709, 449, 264, 2835, 555, 16431, 0, 1472, 1253, 617, 27569, 813, 3766, 6946, 369, 264, 3766, 350, 15329, 13782, 1567, 16850, 279, 3691, 18121, 1405, 568, 1903, 14432, 13, 1115, 892, 11, 568, 13551, 2500, 2835, 389, 13818, 34382, 0, 4343, 704, 813, 5117, 369, 279, 2539, 2835, 4999, 3923, 374, 264, 16526, 92028, 4883, 709, 2085, 264, 7173, 70, 64977, 11363, 311, 4430, 27074, 63554, 67527, 68, 374, 18667, 603, 311, 4430, 420, 11363, 369, 16526, 7173, 70, 64977, 13, 1102, 596, 264, 18406, 12269, 315, 3678, 15846, 25309, 430, 18065, 1701, 459, 14875, 38790, 320, 8370, 374, 264, 1401, 25795, 43492, 4343, 704, 67527, 68, 596, 5117, 369, 279, 11363, 4999, 40, 2216, 1781, 20228, 374, 264, 11204, 25795, 1606, 505, 433, 11, 499, 649, 636, 14403, 11, 20415, 11, 61260, 11, 323, 1521, 16526, 30616, 27211, 552, 13, 1115, 374, 264, 955, 315, 37433, 88, 20228, 19692, 430, 374, 5115, 18406, 0, 35336, 706, 6222, 420, 449, 603, 369, 279, 4883, 709, 323, 433, 596, 264, 2294, 12269, 311, 1456, 11, 5423, 994, 40901, 449, 264, 1629, 3919, 41951, 19151, 0, 4343, 704, 35336, 596, 5117, 369, 279, 11363, 4999, 40, 2846, 264, 2466, 8571, 315, 19151, 21494, 320, 36046, 11002, 19151, 21494, 705, 11000, 1606, 358, 14264, 709, 12459, 433, 7878, 505, 856, 3450, 596, 13863, 13, 2100, 433, 596, 912, 13051, 430, 358, 1053, 387, 264, 8571, 315, 46993, 596, 4441, 315, 480, 42888, 31074, 360, 13, 1115, 19151, 21494, 11363, 374, 1903, 555, 4179, 6605, 11, 902, 539, 1193, 18406, 719, 9498, 2288, 4999, 50, 5308, 20991, 574, 11075, 311, 636, 279, 4832, 281, 11305, 263, 555, 7649, 704, 264, 2478, 19141, 323, 1364, 5616, 2751, 279, 11363, 369, 279, 4832, 10651, 1364, 574, 3411, 369, 0, 2057, 1817, 704, 1148, 11363, 6575, 369, 1077, 323, 1101, 279, 17480, 315, 1063, 13548, 3754, 11, 4587, 1817, 1077, 5117, 4999, 45, 287, 29782, 603, 505, 26363, 311, 9502, 420, 18406, 13818, 34382, 31351, 30616, 13, 358, 4265, 3021, 311, 1440, 1077, 6367, 369, 279, 4832, 41951, 19151, 430, 779, 18406, 40901, 1077, 41951, 20228, 0, 358, 2846, 2744, 3411, 369, 5627, 311, 34997, 709, 856, 41951, 20228, 320, 300, 358, 2846, 8541, 311, 1005, 93267, 389, 1450, 8, 323, 56884, 26883, 10578, 1093, 264, 11364, 1648, 311, 42786, 709, 20228, 449, 264, 16526, 27744, 0, 4343, 704, 86183, 596, 5117, 369, 279, 11363, 4999, 19875, 483, 374, 8659, 279, 2324, 315, 420, 16526, 4717, 0, 3005, 596, 6222, 449, 603, 420, 11363, 369, 297, 22604, 612, 24964, 290, 54574, 731, 13, 1102, 596, 264, 2294, 12269, 369, 459, 30168, 3213, 439, 1664, 439, 3403, 369, 264, 82651, 15496, 13, 2893, 2771, 311, 1817, 704, 46993, 596, 5117, 369, 420, 11363, 3235, 449, 279, 2768, 18406, 16526, 26863, 439, 1664, 0, 128000, 36190, 2103, 15164, 6762, 4430, 315, 1948, 7032, 304, 8431, 2532, 15603, 198, 1591, 4448, 11215, 2103, 15164, 6762, 4430, 315, 1948, 7032, 304, 8431, 2532, 15603, 198, 10577, 5039, 3278, 596, 5219, 6288, 6068, 1022, 520, 10195, 5990, 1389, 1524, 4315, 10966, 6164, 7008, 323, 8494, 198, 2520, 279, 220, 12994, 11, 931, 477, 779, 3278, 20011, 304, 279, 6560, 8431, 2532, 11, 1070, 574, 1063, 1695, 3754, 1566, 2046, 13, 35390, 97666, 9045, 311, 5376, 279, 1396, 315, 10195, 3278, 304, 8792, 3109, 617, 7318, 1022, 13, 16803, 42832, 11, 315, 904, 10026, 11, 649, 387, 12691, 430, 814, 990, 369, 279, 22139, 449, 279, 8592, 1396, 315, 8954, 10195, 7510, 304, 4606, 323, 279, 11999, 2902, 7656, 315, 279, 480, 508, 5961, 627, 91483, 555, 50184, 11, 469, 56, 11, 279, 1455, 3293, 1963, 315, 8954, 7510, 304, 10195, 8792, 3109, 8158, 5039, 7008, 45769, 304, 279, 3063, 994, 433, 4131, 311, 22923, 3278, 311, 1202, 1455, 10195, 8158, 13, 2030, 279, 1963, 1101, 5039, 430, 1070, 374, 539, 264, 3254, 480, 508, 3224, 1405, 220, 1135, 4, 315, 1948, 3109, 8158, 527, 5762, 555, 3278, 627, 4518, 279, 2800, 315, 279, 4652, 555, 18965, 1618, 128000, 26538, 7532, 38987, 58984, 198, 791, 330, 55924, 12152, 22249, 6672, 48854, 38987, 58984, 1, 374, 22034, 311, 264, 22249, 6672, 2851, 889, 374, 264, 1510, 477, 4846, 19504, 315, 38975, 11, 374, 24096, 264, 12152, 1772, 30483, 44798, 389, 264, 2539, 7394, 8197, 11, 323, 889, 33511, 14584, 38656, 449, 264, 3831, 15507, 311, 279, 10775, 315, 22249, 6672, 627, 2213, 62932, 527, 2631, 311, 5266, 704, 279, 7473, 3459, 902, 5764, 3649, 315, 872, 22249, 6672, 7076, 323, 26202, 3217, 13, 38091, 315, 28116, 520, 264, 12152, 1772, 30483, 15244, 374, 2631, 627, 11874, 45370, 400, 1041, 15, 55855, 690, 387, 22034, 520, 279, 22249, 6672, 38975, 25992, 3331, 30155, 304, 3297, 315, 1855, 3280, 627, 791, 32368, 2011, 387, 37191, 2539, 7394, 323, 5131, 24096, 264, 15324, 12152, 1772, 30483, 43964, 13, 320, 648, 13, 23978, 11, 4029, 31252, 11, 11156, 14673, 340, 791, 32368, 2011, 387, 9879, 311, 1514, 22249, 6672, 304, 279, 1510, 5737, 3280, 627, 2213, 62932, 2011, 617, 594, 4591, 323, 9879, 2949, 22249, 6672, 38975, 10229, 320, 15723, 220, 18, 8, 439, 264, 2851, 369, 520, 3325, 220, 20, 15956, 13, 320, 60443, 11, 7683, 24823, 661, 11, 42174, 11, 3400, 37440, 11, 29334, 11, 27563, 32, 340, 2213, 62932, 690, 387, 16957, 3196, 389, 872, 15507, 311, 279, 10775, 315, 22249, 6672, 1555, 5737, 11, 24826, 11, 2856, 23747, 323, 1023, 26202, 7640, 439, 1664, 439, 2978, 323, 4029, 20852, 323, 2532, 627, 2675, 1253, 3881, 369, 279, 34225, 30171, 719, 527, 1193, 17446, 311, 3243, 279, 34225, 832, 892, 627, 51459, 527, 1457, 1694, 11928, 369, 279, 220, 2366, 15, 12, 1691, 2978, 1060, 627, 791, 22143, 369, 8522, 374, 5936, 220, 508, 11, 220, 2366, 16, 13, 128000, 791, 6020, 3600, 5064, 374, 264, 4106, 2788, 315, 44219, 719, 4619, 315, 20705, 279, 4441, 315, 502, 4311, 1139, 279, 3634, 439, 264, 1162, 315, 364, 355, 6, 19579, 364, 49818, 518, 279, 7941, 20197, 527, 36387, 323, 6975, 505, 279, 10937, 627, 65676, 653, 4150, 3966, 11, 323, 279, 16099, 8082, 315, 3600, 11, 527, 520, 279, 4851, 315, 44219, 304, 279, 10706, 13, 578, 4832, 3187, 315, 1521, 1403, 9547, 5108, 3871, 374, 4740, 14214, 13, 578, 2626, 11, 902, 11887, 304, 220, 679, 19, 11, 374, 279, 8271, 3124, 315, 220, 1544, 4771, 6418, 13673, 29349, 15341, 33518, 52757, 323, 16099, 5014, 279, 2362, 64369, 1887, 315, 11203, 1729, 902, 5602, 49835, 2343, 1022, 11822, 304, 4685, 1392, 627, 31437, 584, 2351, 2216, 3815, 374, 25935, 279, 6201, 315, 39959, 323, 18233, 11, 10695, 2678, 9873, 430, 1053, 617, 1047, 311, 733, 1234, 477, 8434, 956, 617, 1027, 3025, 311, 3139, 702, 32408, 3077, 15042, 872, 43972, 5115, 49139, 323, 6288, 13, 2435, 3077, 2216, 11054, 459, 653, 4150, 6130, 1205, 323, 433, 22020, 1268, 584, 1205, 311, 656, 264, 2731, 2683, 315, 22923, 1148, 584, 649, 4546, 311, 279, 2007, 304, 3878, 315, 1057, 1866, 2875, 9860, 40651, 17357, 1359, 2795, 1561, 22631, 627, 6153, 14214, 32216, 279, 6776, 369, 502, 3600, 304, 279, 40651, 3634, 13, 13596, 2626, 53728, 1139, 420, 374, 2678, 2626, 11941, 9287, 1322, 90298, 13, 578, 4330, 4771, 6418, 2883, 706, 6051, 8813, 279, 43291, 315, 43221, 220, 605, 11, 931, 17017, 311, 2678, 2626, 7980, 311, 279, 26306, 315, 400, 8652, 3610, 13, 330, 1687, 2351, 389, 264, 9131, 311, 2349, 279, 1648, 2678, 2626, 7980, 3217, 17452, 1359, 2795, 24101, 62314, 11, 10195, 8661, 6783, 520, 1322, 90298, 627, 8142, 433, 1253, 5101, 1322, 90298, 374, 5737, 304, 264, 3634, 8776, 14286, 617, 1317, 13234, 11, 439, 62314, 3585, 704, 11, 1070, 706, 1317, 1027, 459, 7120, 651, 7725, 6130, 2385, 627, 25938, 374, 2555, 1093, 220, 17, 13, 16, 3610, 2678, 2626, 304, 8494, 323, 36342, 11, 14286, 617, 539, 48907, 311, 430, 10706, 1606, 814, 3287, 956, 617, 279, 5326, 38575, 369, 433, 13, 3639, 584, 2351, 2216, 3815, 374, 25935, 279, 6201, 315, 39959, 323, 18233, 11, 10695, 2678, 9873, 430, 1053, 617, 1047, 311, 733, 1234, 477, 8434, 956, 617, 1027, 3025, 311, 3139, 1359, 2795, 62314, 627, 7189, 1541, 956, 1781, 279, 3392, 315, 892, 430, 499, 3077, 1027, 2212, 374, 14647, 2133, 311, 3041, 499, 459, 9610, 1389, 433, 596, 279, 7829, 499, 2274, 323, 279, 1648, 499, 92064, 439, 459, 22139, 10246, 1383, 53728, 1139, 264, 3016, 2385, 14286, 617, 1027, 12153, 311, 2532, 16264, 709, 279, 6776, 369, 264, 15664, 1990, 279, 21210, 323, 8776, 6020, 29533, 13, 63909, 11, 1322, 90298, 706, 54299, 264, 15664, 449, 4410, 46051, 627, 10944, 2351, 4401, 264, 18178, 2068, 779, 430, 994, 814, 2351, 12153, 311, 1520, 264, 2678, 2626, 6130, 1606, 814, 1541, 956, 617, 264, 2027, 430, 29076, 872, 8670, 11, 814, 8464, 1124, 311, 603, 1359, 15100, 62314, 627, 2170, 9558, 18042, 26464, 71094, 369, 8776, 23641, 29533, 3136, 311, 83400, 819, 304, 279, 8389, 19016, 11, 62314, 13919, 14286, 649, 8935, 505, 2128, 287, 709, 449, 44483, 1778, 439, 1322, 90298, 902, 374, 9298, 452, 5119, 24950, 505, 220, 966, 311, 220, 2031, 11, 1524, 304, 13422, 994, 279, 11941, 3851, 374, 539, 12054, 627, 10227, 1403, 1401, 2574, 584, 3085, 527, 4732, 323, 40075, 1359, 1364, 2795, 627, 58860, 810, 315, 279, 1917, 596, 72021, 20663, 520, 8121, 17997, 220, 679, 23, 13, 2175, 701, 4216, 12224, 14741, 1457, 323, 3665, 0, 128000, 33246, 220, 845, 11, 220, 679, 24, 611, 38218, 72695, 77, 18291, 611, 220, 15, 18149, 198, 79834, 650, 1394, 42221, 11, 54554, 364, 1691, 198, 79834, 650, 1394, 42221, 374, 264, 1176, 43927, 7926, 5575, 505, 4072, 67429, 11, 8421, 11, 477, 1148, 568, 13452, 311, 1650, 11, 330, 791, 4410, 8421, 77064, 1210, 5414, 11879, 311, 8421, 4584, 1110, 1302, 574, 832, 315, 3070, 1862, 323, 20343, 627, 16366, 6699, 14264, 709, 304, 7011, 309, 269, 437, 350, 3105, 360, 575, 300, 11, 264, 3973, 6424, 304, 17355, 12550, 13, 2435, 7882, 311, 279, 3723, 4273, 1306, 813, 18233, 574, 9076, 264, 2683, 439, 459, 20314, 24490, 304, 4072, 67429, 627, 79834, 574, 9405, 2380, 1667, 3010, 13, 5414, 6699, 4934, 1461, 311, 617, 279, 1888, 6873, 3284, 11, 779, 814, 3940, 45243, 8853, 323, 31252, 994, 24270, 574, 1193, 264, 8945, 13, 5414, 6691, 574, 5423, 12514, 311, 813, 3938, 323, 4024, 3485, 323, 7953, 369, 813, 6873, 627, 46240, 6699, 11, 304, 872, 5209, 220, 508, 596, 11, 7882, 311, 264, 502, 3224, 449, 4661, 4400, 311, 872, 836, 13, 358, 3629, 1781, 922, 1268, 13548, 323, 42351, 279, 3351, 2011, 617, 1027, 13, 2435, 1550, 4395, 2949, 872, 2410, 311, 3041, 757, 264, 6140, 520, 264, 2731, 2324, 13, 3092, 6691, 9687, 315, 264, 12239, 2978, 430, 574, 3967, 369, 1202, 3831, 14584, 17444, 719, 994, 1364, 304, 3004, 922, 665, 16608, 757, 11, 1070, 1051, 1193, 1403, 19300, 2163, 323, 814, 1053, 387, 2728, 389, 264, 1176, 1824, 638, 1176, 1355, 2841, 8197, 520, 220, 22, 264, 749, 13, 279, 1633, 1828, 1938, 13, 17314, 1430, 1171, 11, 856, 3450, 7543, 279, 3814, 304, 279, 13217, 2763, 315, 1148, 1053, 3719, 856, 12239, 2978, 13, 3277, 279, 14365, 9107, 520, 220, 22, 264, 749, 13, 279, 1828, 6693, 11, 1364, 574, 279, 2132, 2748, 304, 1584, 323, 358, 574, 279, 1566, 5575, 9879, 10246, 41672, 24270, 449, 813, 6691, 198, 4599, 433, 574, 892, 369, 24270, 311, 52880, 304, 1579, 2978, 11, 813, 6699, 15058, 956, 11537, 449, 279, 3778, 1579, 2978, 311, 7926, 15660, 13, 24270, 323, 813, 6699, 57098, 3871, 323, 11352, 430, 57829, 5234, 6150, 11, 264, 879, 11, 16879, 1579, 2978, 304, 4072, 67429, 11, 18908, 264, 220, 1041, 4, 7926, 26586, 4478, 11, 719, 39038, 574, 11646, 369, 279, 3070, 627, 33703, 4072, 67429, 323, 7011, 309, 269, 437, 11, 7926, 374, 810, 3629, 264, 8063, 1109, 264, 13336, 13, 3092, 3450, 11, 449, 279, 1890, 5899, 4107, 1364, 8710, 304, 665, 16608, 757, 369, 68223, 11, 1766, 1475, 3254, 34225, 358, 1436, 3881, 369, 323, 555, 279, 1176, 1938, 315, 2978, 11, 358, 574, 459, 37191, 5575, 520, 57829, 5234, 6150, 323, 389, 856, 1853, 311, 7926, 10246, 79834, 9778, 37191, 520, 31788, 3907, 11, 57017, 304, 220, 679, 18, 449, 264, 426, 885, 13, 304, 10170, 11, 12053, 11, 323, 13581, 13, 6104, 568, 574, 1070, 11, 568, 11096, 323, 6197, 459, 7471, 12514, 311, 8405, 1205, 6108, 55855, 311, 57017, 1579, 2978, 4236, 24096, 1403, 4771, 477, 3116, 4771, 14673, 627, 1, 34242, 264, 1176, 43927, 11, 3428, 32197, 5575, 315, 41985, 38052, 304, 5190, 6873, 574, 279, 4788, 11, 539, 279, 7617, 13, 358, 7111, 369, 264, 4029, 315, 7931, 449, 36576, 4528, 311, 856, 1866, 11, 902, 358, 1766, 304, 18667, 323, 6522, 459, 7471, 2663, 9853, 61338, 437, 409, 31788, 13, 1666, 264, 1912, 11, 584, 27415, 4147, 30171, 311, 3493, 1205, 6108, 55855, 311, 57017, 1579, 2978, 4236, 24096, 1403, 4771, 31252, 323, 23978, 13, 358, 6612, 430, 358, 574, 25455, 28787, 1113, 279, 9341, 779, 1690, 1274, 1047, 1903, 304, 757, 927, 279, 1667, 13, 2468, 430, 1486, 11, 358, 7020, 1268, 358, 4934, 311, 1005, 856, 2324, 4235, 10695, 4236, 505, 5107, 13463, 7380, 2680, 311, 2324, 49961, 10708, 627, 79834, 323, 813, 3070, 520, 813, 7926, 39554, 304, 220, 679, 18, 627, 6153, 7926, 11, 24270, 11928, 264, 2361, 449, 70377, 369, 5270, 439, 264, 220, 16, 267, 41327, 4221, 33315, 13, 1283, 10456, 3318, 449, 4236, 323, 14000, 1268, 814, 1051, 40028, 555, 3070, 13463, 477, 32116, 430, 568, 1436, 539, 1520, 449, 1555, 12917, 7636, 13, 1283, 15393, 430, 568, 4934, 311, 5569, 813, 5536, 7953, 279, 24978, 13, 1283, 6052, 2162, 311, 990, 520, 813, 82580, 53251, 11, 57829, 5234, 6150, 11, 439, 279, 10783, 315, 2467, 5287, 627, 57741, 1884, 2380, 1667, 520, 57829, 11, 358, 73897, 279, 8063, 315, 264, 2731, 2324, 311, 1475, 5575, 323, 2748, 889, 15203, 279, 52473, 315, 1057, 2978, 13, 46982, 856, 40061, 520, 57829, 5234, 6150, 11, 358, 26399, 304, 7859, 279, 1396, 315, 26445, 2841, 4236, 323, 279, 18160, 3392, 315, 55855, 430, 584, 1436, 3493, 1124, 13, 1952, 264, 7446, 8197, 358, 1047, 279, 6776, 311, 1520, 2349, 279, 3388, 315, 264, 3995, 1732, 596, 2324, 13, 22938, 520, 57829, 574, 459, 16044, 11, 279, 1455, 2523, 358, 617, 3596, 1047, 11, 323, 690, 16058, 387, 832, 315, 856, 550, 283, 5086, 53881, 497, 702, 79834, 596, 330, 10445, 4584, 1110, 1302, 48469, 79834, 2646, 35706, 568, 1053, 842, 709, 304, 2626, 2978, 13, 2030, 1418, 10043, 2212, 4072, 67429, 11, 568, 1053, 1518, 264, 8421, 4584, 1110, 1302, 54554, 86306, 11, 323, 433, 16075, 304, 813, 4059, 627, 1, 25025, 387, 3309, 11, 358, 1550, 539, 1781, 358, 4265, 636, 1139, 2626, 2978, 13, 358, 5828, 956, 2771, 422, 1948, 2626, 8853, 1053, 1518, 279, 907, 315, 856, 3217, 304, 6873, 13, 358, 574, 2653, 389, 7182, 11, 7422, 430, 8530, 358, 5828, 956, 1695, 3403, 13, 2030, 856, 4885, 323, 18105, 21190, 757, 311, 2231, 13544, 856, 1888, 5149, 323, 4510, 304, 7182, 4235, 323, 779, 358, 1550, 13, 358, 31256, 7182, 430, 358, 574, 28390, 323, 76554, 315, 12588, 5217, 6873, 13, 358, 2846, 33944, 311, 387, 23712, 555, 1695, 1274, 11, 323, 358, 2846, 779, 26259, 358, 3287, 956, 3041, 709, 10246, 79834, 2795, 1148, 19584, 813, 5597, 311, 2586, 311, 4584, 1110, 1302, 574, 813, 3217, 520, 34039, 4584, 1110, 1302, 25, 66071, 48534, 323, 279, 6776, 311, 3881, 311, 4584, 1110, 1302, 1555, 578, 73547, 369, 44825, 19723, 304, 9744, 11, 459, 30764, 315, 1948, 2626, 8853, 323, 5220, 11411, 311, 47594, 20057, 323, 28286, 304, 3728, 2626, 6873, 323, 11692, 627, 39469, 358, 3782, 311, 19816, 369, 66071, 48534, 11, 358, 1047, 539, 9435, 311, 578, 73547, 11, 459, 7471, 430, 5825, 2680, 311, 54554, 48911, 5070, 369, 1234, 53859, 4236, 13, 622, 21825, 57023, 11, 856, 4584, 1110, 1302, 48911, 9640, 11, 3952, 5296, 315, 430, 323, 92468, 398, 21190, 757, 311, 3881, 13, 2057, 757, 11, 4423, 889, 706, 2744, 7111, 369, 264, 4029, 11, 433, 574, 264, 1879, 430, 358, 1053, 387, 42777, 369, 1618, 520, 4584, 1110, 1302, 627, 79834, 1047, 3970, 1176, 25417, 430, 1524, 264, 1664, 50701, 11, 41385, 2978, 1093, 57829, 7846, 956, 10408, 688, 1475, 8815, 430, 4236, 3663, 477, 3493, 3403, 12576, 369, 1475, 5575, 311, 9604, 13, 1283, 16388, 430, 2626, 2978, 649, 1520, 1461, 11322, 813, 5915, 315, 28818, 323, 10565, 264, 2978, 430, 15316, 459, 26031, 315, 14584, 323, 2536, 38698, 70858, 1862, 369, 1202, 4236, 323, 872, 8689, 627, 57741, 1475, 5575, 358, 574, 3025, 311, 52880, 520, 57829, 477, 9966, 264, 34225, 369, 11, 1070, 1051, 520, 3325, 264, 23810, 810, 430, 358, 1436, 539, 1606, 315, 80431, 8125, 11, 6996, 315, 2978, 5070, 11, 5099, 13, 57829, 1587, 264, 2763, 315, 1695, 369, 779, 1690, 4236, 11, 7182, 5343, 11, 323, 682, 6980, 23528, 264, 1695, 2978, 449, 1274, 889, 36297, 2512, 922, 872, 2450, 13, 358, 6773, 311, 23564, 459, 54554, 1606, 358, 1390, 311, 74704, 856, 2324, 9017, 28041, 279, 5536, 315, 8853, 7559, 304, 1234, 53859, 323, 26445, 2841, 10977, 10246, 79834, 596, 55820, 311, 1472, 198, 10227, 2294, 3245, 922, 4584, 1110, 1302, 374, 430, 279, 1274, 1618, 11, 505, 279, 5687, 311, 4236, 323, 52121, 11, 617, 66847, 832, 4279, 17571, 25, 364, 8161, 956, 10894, 3249, 499, 3782, 1618, 3238, 2057, 757, 11, 420, 17571, 17482, 439, 264, 6926, 27626, 311, 6227, 1268, 358, 617, 56128, 505, 279, 45972, 323, 1520, 315, 3885, 11, 323, 856, 12014, 311, 656, 279, 1890, 10246, 92750, 956, 409, 970, 701, 11704, 323, 1541, 956, 11196, 922, 539, 3515, 279, 4832, 14584, 477, 6721, 5643, 13, 358, 1093, 311, 1781, 430, 8421, 4584, 1110, 1302, 11, 810, 779, 1109, 1023, 8853, 11, 16696, 311, 1505, 1274, 889, 617, 1903, 264, 1972, 5536, 304, 8996, 8824, 814, 10434, 323, 36297, 1390, 311, 656, 1695, 304, 279, 1917, 10246, 39202, 709, 311, 2457, 449, 682, 2574, 4584, 1110, 1302, 555, 40885, 311, 1057, 20846, 13, 11359, 603, 389, 14318, 311, 1518, 810, 922, 5575, 2324, 13, 1442, 499, 617, 904, 4860, 11, 4587, 5662, 704, 311, 54554, 2467, 5287, 13, 29271, 364, 336, 0, 128000, 18735, 3420, 1071, 304, 264, 7159, 1474, 80675, 7274, 430, 568, 6612, 1070, 574, 330, 34431, 2133, 389, 1, 449, 4900, 24448, 7250, 596, 2077, 311, 279, 3293, 993, 349, 315, 8951, 389, 2383, 13627, 627, 7189, 15746, 279, 4872, 11, 323, 7170, 279, 4339, 527, 10619, 11, 719, 499, 1120, 1427, 520, 279, 2547, 4221, 2001, 1070, 596, 2555, 2133, 389, 13, 2684, 596, 2555, 2133, 389, 13, 1628, 279, 4339, 527, 539, 3629, 10619, 11, 555, 279, 1648, 1359, 3420, 1071, 389, 330, 48414, 612, 23323, 10246, 4599, 17770, 311, 38263, 1148, 568, 8967, 11, 3420, 1071, 568, 1047, 330, 64, 2763, 315, 3958, 8430, 922, 510, 45437, 948, 702, 791, 1972, 12, 65215, 8622, 349, 6288, 26579, 11, 3582, 11, 430, 1690, 3776, 9053, 1455, 4461, 1047, 11704, 449, 2383, 21430, 11167, 9808, 430, 1690, 4251, 9053, 649, 956, 3619, 627, 12348, 596, 4762, 2555, 430, 584, 2216, 1541, 956, 1440, 11, 323, 7344, 584, 649, 956, 2733, 433, 7389, 584, 2351, 3776, 1359, 3420, 1071, 13, 330, 3112, 433, 374, 8659, 2555, 2133, 389, 1070, 11, 2288, 13, 1628, 430, 706, 311, 656, 449, 4967, 11, 323, 706, 311, 656, 449, 2555, 627, 42513, 1070, 596, 2555, 2133, 389, 11, 323, 7344, 584, 649, 956, 15641, 433, 7389, 499, 2351, 3776, 10246, 1966, 7418, 11, 2380, 4379, 9808, 1051, 7577, 304, 86269, 56747, 11, 29974, 11, 304, 1148, 279, 17352, 7633, 439, 459, 80065, 11549, 3440, 13, 47993, 420, 2305, 11, 4330, 9808, 1051, 7577, 555, 264, 63382, 304, 19051, 627, 16509, 596, 65506, 430, 330, 34431, 374, 2133, 389, 1, 706, 3719, 264, 7075, 58608, 994, 34685, 279, 52140, 315, 1023, 1579, 25171, 12678, 627, 28055, 459, 23474, 53161, 3440, 520, 459, 23983, 70832, 304, 28944, 6931, 420, 1060, 11, 3420, 50697, 430, 7250, 1253, 387, 53464, 311, 279, 20320, 7471, 11, 21039, 1070, 574, 330, 34431, 2133, 389, 1, 449, 279, 4872, 596, 2077, 311, 20320, 8951, 13, 128000, 3563, 264, 22556, 13863, 449, 1057, 50048, 596, 8641, 627, 26021, 264, 22556, 13863, 649, 387, 9193, 42093, 13, 1472, 649, 1520, 279, 4676, 11, 1418, 1101, 14324, 3300, 13, 4557, 1057, 50048, 596, 8641, 311, 22556, 60299, 323, 4048, 1268, 311, 636, 3940, 627, 4061, 704, 1057, 5117, 1772, 7054, 220, 19, 42419, 311, 1050, 817, 18343, 304, 4718, 19558, 13, 128000, 679, 18, 12, 605, 12, 1313, 482, 362, 10306, 617, 6004, 872, 502, 92197, 1041, 10106, 62038, 15534, 261, 320, 8253, 34, 8, 4101, 13, 578, 6992, 92197, 1041, 70418, 2134, 706, 1027, 33624, 449, 264, 502, 220, 3443, 650, 2134, 13, 1115, 374, 264, 7373, 22359, 2027, 520, 220, 3443, 650, 323, 649, 387, 9435, 311, 220, 13897, 11, 220, 3443, 323, 220, 18136, 650, 14488, 13, 59787, 220, 3443, 650, 1741, 22359, 92197, 1041, 70418, 82, 1051, 1523, 22359, 11028, 315, 220, 11738, 650, 1741, 22359, 8316, 13, 1115, 5825, 459, 5217, 220, 508, 3346, 597, 13114, 8824, 520, 912, 2853, 627, 2028, 33045, 2027, 690, 1505, 26586, 304, 220, 13897, 650, 5961, 1778, 439, 5734, 11, 220, 3443, 650, 13918, 1778, 439, 4606, 11, 279, 8857, 315, 13936, 11, 4987, 5270, 11, 323, 369, 264, 9333, 1396, 315, 5961, 1701, 220, 18136, 650, 1778, 439, 28796, 13, 578, 92197, 1041, 70418, 220, 3443, 650, 4101, 374, 18641, 449, 2225, 220, 1135, 323, 220, 1399, 37192, 17135, 779, 5961, 1778, 439, 6457, 477, 41862, 596, 14892, 449, 2225, 34873, 690, 1505, 3956, 5762, 304, 5708, 311, 387, 31368, 8581, 311, 3060, 4009, 627, 791, 7720, 369, 279, 842, 1217, 527, 264, 4827, 2853, 824, 597, 13114, 323, 264, 9333, 43972, 369, 264, 2728, 10959, 13, 578, 14247, 14324, 323, 11293, 1972, 12675, 2631, 369, 502, 45218, 477, 279, 7170, 17436, 25678, 8522, 527, 264, 330, 7678, 48789, 1, 6671, 369, 362, 10306, 596, 6444, 627, 2460, 220, 3443, 650, 2134, 3956, 6216, 527, 27809, 23759, 323, 14791, 369, 3728, 11987, 449, 264, 2134, 315, 15823, 2561, 389, 279, 54243, 3113, 13, 1666, 961, 315, 279, 44993, 92197, 1041, 2027, 20136, 11, 24804, 5596, 527, 25442, 1534, 323, 2561, 389, 2875, 5406, 449, 362, 10306, 596, 1203, 5352, 323, 1862, 627, 791, 92197, 1041, 70418, 220, 3443, 650, 4101, 374, 459, 10728, 6425, 369, 26192, 22465, 35121, 8522, 8405, 19815, 19812, 323, 3221, 96219, 27358, 315, 22465, 274, 2076, 323, 1765, 4282, 13, 578, 13241, 4519, 323, 5178, 315, 279, 220, 3443, 650, 92197, 1041, 70418, 690, 1518, 433, 1524, 810, 13882, 9435, 304, 8522, 439, 17226, 439, 11, 87836, 323, 13076, 6136, 9313, 1555, 311, 6593, 323, 828, 19169, 13, 46402, 11, 28578, 9200, 21577, 1397, 19815, 4335, 2410, 11, 279, 92197, 1041, 70418, 220, 3443, 650, 4101, 690, 3493, 19815, 7720, 311, 279, 842, 1217, 304, 279, 8518, 323, 13076, 26593, 13, 128000, 8284, 41160, 1534, 11509, 17301, 315, 279, 17508, 65, 7918, 41999, 75098, 5124, 81, 3029, 67, 5248, 24524, 198, 5744, 6061, 5492, 198, 1966, 279, 47788, 449, 800, 53470, 1122, 12970, 60796, 3808, 198, 32559, 220, 679, 20, 11, 220, 1758, 7, 23, 1680, 220, 8652, 18, 12, 17228, 16, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 82, 13, 679, 20, 13, 1758, 13, 8652, 18, 198, 33, 13382, 2136, 304, 934, 300, 72033, 66603, 6354, 797, 301, 39006, 449, 75098, 27541, 323, 72810, 2592, 198, 55, 648, 14851, 220, 16, 11, 323, 1901, 4317, 2303, 258, 1630, 28323, 220, 16, 345, 33849, 315, 92102, 23199, 11, 3907, 315, 35269, 10170, 323, 12053, 315, 5734, 11, 57807, 1072, 220, 20973, 24626, 198, 24141, 6841, 220, 679, 19, 67830, 6790, 220, 679, 19, 30114, 7552, 220, 679, 20, 198, 644, 420, 5684, 11, 584, 19874, 279, 934, 300, 72033, 66603, 6354, 797, 301, 39006, 320, 80, 16222, 6354, 1680, 1144, 58, 1144, 2414, 59, 90, 1144, 7413, 90, 7105, 92, 612, 77, 530, 35533, 77, 370, 4355, 59, 51953, 59, 16548, 5549, 1471, 10929, 77, 370, 4355, 308, 59, 16548, 7435, 59, 77, 370, 4355, 59, 51953, 59, 16548, 11781, 14946, 1471, 10929, 77, 370, 4355, 272, 59, 16548, 7405, 59, 10590, 5531, 90, 49, 26628, 77, 705, 1144, 80, 32710, 865, 59, 258, 59, 78435, 27362, 11, 83, 29, 15, 11, 3505, 612, 59, 959, 41422, 272, 530, 35533, 20892, 272, 1824, 39434, 11, 1144, 80, 32710, 865, 59, 258, 59, 78435, 27362, 11, 83, 29, 15, 11, 1144, 408, 90, 7105, 92, 1144, 1315, 13, 1144, 60, 1234, 87282, 4275, 64607, 19254, 4787, 304, 264, 62215, 8106, 59060, 78435, 59, 39353, 59, 10590, 6194, 90, 49, 92, 61, 45, 13244, 1789, 2225, 59060, 959, 41422, 28, 15, 3, 320, 1768, 57565, 12, 616, 11696, 292, 1162, 8, 323, 59060, 959, 41422, 29, 15, 3, 320, 1768, 57565, 58098, 57565, 1162, 705, 584, 690, 1501, 279, 3728, 3502, 7394, 14209, 323, 14113, 3502, 7394, 62215, 2136, 315, 10105, 311, 39006, 320, 80, 16222, 6354, 8, 449, 2225, 2536, 6953, 19927, 323, 5367, 13523, 3722, 36807, 389, 279, 2536, 12, 12296, 327, 8106, 59060, 78435, 55976, 902, 3493, 264, 22822, 311, 279, 29953, 85995, 62215, 2136, 6296, 13, 12523, 5352, 304, 1370, 57565, 12, 616, 11696, 292, 14, 1768, 57565, 58098, 57565, 8590, 354, 7332, 39006, 449, 5367, 13523, 58430, 11, 75098, 27541, 323, 72810, 2592, 13, 763, 4040, 11, 584, 7417, 279, 3293, 3135, 12457, 555, 29346, 8288, 72, 5364, 84, 320, 679, 19, 11, 11997, 13, 2140, 13, 45038, 13, 328, 599, 6266, 323, 29346, 5364, 84, 11419, 71, 833, 320, 679, 19, 11, 622, 13, 99836, 11964, 811, 4390, 44942, 25, 1370, 57565, 58098, 57565, 66603, 6354, 797, 301, 6067, 2637, 8121, 14209, 11, 1370, 57565, 12, 616, 11696, 292, 66603, 6354, 797, 301, 1887, 11, 62215, 2136, 627, 8991, 34805, 17908, 55982, 25, 26150, 25, 220, 1758, 42, 1758, 11, 220, 6083, 34, 1114, 26, 44634, 25, 220, 1758, 42, 20, 627, 34, 7709, 25, 1630, 648, 14851, 11, 1901, 4317, 2303, 258, 1630, 28323, 13, 426, 13382, 2136, 304, 934, 300, 72033, 66603, 6354, 797, 301, 39006, 449, 75098, 27541, 323, 72810, 2592, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 362, 11, 220, 679, 20, 11, 220, 1758, 320, 23, 8, 551, 220, 8652, 18, 12, 17228, 16, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 82, 13, 679, 20, 13, 1758, 13, 8652, 18, 198, 45, 13, 423, 13, 362, 7792, 587, 437, 11, 400, 43, 61, 79, 3, 14597, 315, 10105, 315, 13010, 1773, 3168, 7713, 39006, 10856, 6947, 13, 25570, 99836, 11964, 811, 11, 220, 19, 320, 4468, 24, 705, 220, 24920, 13, 36995, 25, 220, 605, 13, 6640, 15, 14, 23110, 25210, 27407, 25620, 679, 1032, 13, 5195, 25542, 198, 42, 13, 20287, 4317, 20568, 323, 386, 13, 473, 23174, 277, 14966, 11, 8121, 14209, 323, 62215, 2136, 315, 29924, 10105, 369, 264, 8590, 354, 7332, 1646, 449, 72810, 2592, 10856, 356, 13, 432, 13, 12644, 13, 41472, 13, 12366, 11, 220, 18113, 320, 679, 18, 705, 220, 21535, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 42664, 1764, 13, 679, 18, 13, 2589, 13, 21360, 13, 5195, 25542, 198, 41, 13, 12649, 14088, 587, 11, 350, 13, 356, 552, 102952, 323, 356, 13, 76602, 11151, 347, 81, 7992, 11, 8121, 14209, 6296, 13, 12523, 5352, 304, 264, 7373, 1370, 57565, 934, 300, 72033, 220, 16, 35, 66603, 6354, 797, 301, 1887, 10856, 11842, 23603, 20017, 2637, 220, 2075, 320, 679, 17, 705, 220, 20767, 20, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 1276, 64, 13, 679, 17, 13, 2371, 13, 24462, 13, 5195, 25542, 198, 55, 13, 117872, 323, 328, 13, 77547, 11, 426, 13382, 2136, 315, 10105, 311, 264, 934, 300, 72033, 1370, 57565, 12, 616, 11696, 292, 66603, 6354, 797, 301, 1887, 449, 72810, 2592, 10856, 4242, 13, 19331, 58945, 13, 41472, 2637, 220, 1806, 320, 679, 19, 705, 220, 12338, 21, 13, 36995, 25, 220, 605, 13, 1041, 17, 3262, 1764, 13, 15531, 17, 13, 5195, 25542, 198, 51, 13, 356, 552, 102952, 11, 3489, 300, 72033, 2536, 39451, 398, 1370, 57565, 1887, 61966, 8590, 354, 7332, 10856, 622, 13, 4242, 13, 20017, 13, 58945, 2637, 220, 17470, 320, 1049, 22, 705, 220, 9335, 15, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 1190, 1764, 64, 13, 1049, 21, 13, 2839, 13, 13837, 13, 5195, 25542, 198, 51, 13, 356, 552, 102952, 323, 393, 13, 33767, 1031, 354, 11, 94719, 892, 12523, 5352, 369, 264, 832, 33520, 934, 300, 72033, 1370, 57565, 58098, 57565, 8590, 354, 7332, 1887, 10856, 9489, 13, 358, 13, 473, 13, 393, 2003, 7063, 978, 2147, 11, 220, 1544, 320, 679, 15, 705, 220, 18318, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 13, 5676, 71, 4080, 13, 1049, 24, 13, 806, 13, 15794, 13, 5195, 25542, 198, 51, 13, 356, 552, 102952, 323, 356, 13, 800, 4481, 11, 94719, 7394, 12523, 709, 323, 3728, 3502, 7394, 653, 66786, 10105, 311, 264, 1370, 57565, 58098, 57565, 934, 300, 72033, 66603, 6354, 797, 301, 1887, 304, 5190, 15696, 10856, 622, 13, 99836, 11964, 811, 11, 220, 12326, 320, 679, 17, 705, 220, 23493, 17, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 1190, 451, 13, 679, 17, 13, 1721, 13, 23785, 13, 5195, 25542, 198, 51, 13, 356, 552, 102952, 323, 356, 13, 800, 4481, 11, 94719, 7394, 12523, 455, 304, 264, 2307, 42641, 934, 300, 72033, 1370, 57565, 58098, 57565, 66603, 6354, 797, 301, 1887, 304, 13167, 220, 17, 10856, 3298, 64, 58945, 13, 4242, 2637, 220, 9748, 320, 679, 19, 705, 220, 8878, 13, 36995, 25, 220, 605, 13, 1041, 22, 2754, 6849, 1272, 12, 16368, 12, 24742, 17, 12, 20, 13, 5195, 25542, 198, 51, 13, 356, 552, 102952, 323, 386, 13, 468, 771, 1565, 11, 94719, 7394, 12523, 5352, 304, 264, 934, 300, 72033, 1887, 315, 8590, 354, 7332, 10856, 11842, 1074, 10981, 11, 220, 1691, 320, 1049, 23, 705, 220, 6550, 22, 13, 36995, 25, 220, 605, 13, 6640, 23, 14, 26421, 16, 12, 24876, 20, 14, 1691, 14, 20, 14, 13858, 13, 5195, 25542, 198, 32, 13, 62458, 11, 25570, 99836, 11964, 811, 10856, 60006, 11, 320, 5162, 24, 570, 5195, 25542, 198, 39, 13, 473, 19580, 57647, 11, 445, 13, 33518, 30976, 11, 350, 13, 36704, 14406, 323, 426, 13, 29346, 11, 95633, 323, 14343, 4787, 369, 279, 69309, 480, 80156, 21106, 11500, 47435, 7881, 93334, 323, 8522, 311, 12233, 1291, 40720, 8099, 323, 67217, 43746, 263, 39006, 10856, 304, 40759, 292, 18825, 323, 11842, 23603, 25570, 99836, 11964, 811, 11, 220, 1627, 320, 679, 16, 705, 220, 11068, 13, 5195, 25542, 198, 35, 13, 423, 13, 5340, 437, 441, 323, 473, 13, 12639, 3141, 301, 11, 423, 18478, 11, 67537, 1286, 85, 69156, 11, 13852, 11696, 292, 11964, 811, 10856, 7665, 92102, 13581, 11, 320, 1049, 23, 570, 5195, 25542, 198, 44, 13, 362, 13, 43350, 2382, 323, 622, 13, 622, 13, 445, 13, 31298, 60921, 42221, 11, 362, 12523, 5352, 17383, 369, 264, 8590, 354, 7332, 1646, 10856, 9489, 13, 2522, 84, 8083, 20935, 13, 6433, 13, 393, 10994, 2493, 13, 41472, 2637, 220, 1187, 320, 2550, 22, 705, 220, 23736, 13, 5195, 25542, 198, 51, 13, 8270, 268, 323, 735, 13, 622, 13, 97864, 11, 8121, 14209, 369, 264, 1370, 57565, 8590, 354, 7332, 1646, 449, 27344, 315, 88204, 7113, 10856, 12605, 13, 58945, 13, 4242, 2637, 220, 1627, 320, 1049, 16, 705, 220, 11209, 13, 36995, 25, 220, 605, 13, 1041, 21, 14520, 3105, 13, 1049, 16, 13, 23439, 16, 13, 5195, 25542, 198, 51, 13, 8270, 268, 323, 735, 13, 97864, 11, 20880, 2269, 9585, 323, 934, 34106, 1355, 49205, 304, 4211, 369, 8590, 437, 19245, 7351, 10856, 3053, 13, 58945, 13, 4242, 13, 1229, 2637, 220, 605, 320, 1049, 17, 705, 220, 14408, 13, 5195, 25542, 198, 51, 13, 8270, 268, 323, 735, 13, 97864, 11, 362, 1217, 596, 8641, 311, 393, 1170, 4211, 369, 8590, 354, 7332, 10856, 622, 13, 4242, 13, 81894, 2637, 220, 2970, 320, 1049, 24, 705, 220, 10750, 13, 36995, 25, 220, 605, 13, 1041, 22, 2754, 6726, 5313, 12, 11436, 12, 11139, 16, 12, 18, 13, 5195, 25542, 198, 35, 13, 15083, 267, 18022, 323, 386, 13, 468, 771, 1565, 11, 426, 13382, 2136, 6296, 13, 12523, 5352, 304, 264, 8590, 354, 7332, 1887, 10856, 622, 13, 99836, 11964, 811, 11, 220, 12112, 320, 1049, 20, 705, 220, 4103, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 1190, 451, 13, 1049, 19, 13, 605, 13, 18642, 13, 5195, 25542, 198, 35, 13, 15083, 267, 18022, 323, 480, 13, 29346, 11, 46952, 5352, 304, 264, 8590, 354, 7332, 1646, 2085, 46220, 32946, 10856, 7665, 622, 13, 58945, 13, 4242, 2637, 220, 717, 320, 1049, 16, 705, 220, 11068, 13, 36995, 25, 220, 605, 13, 4645, 22, 11628, 26421, 25136, 5154, 1041, 21299, 18, 13, 5195, 25542, 198, 50, 13, 57704, 4849, 11, 350, 13, 1952, 78, 323, 350, 13, 94636, 6217, 11, 42145, 3225, 315, 279, 14209, 315, 12523, 5352, 10105, 311, 934, 300, 72033, 5367, 13523, 66603, 6354, 797, 301, 6067, 315, 1370, 57565, 58098, 57565, 955, 10856, 4242, 13, 19331, 58945, 13, 41472, 2637, 220, 1927, 320, 679, 18, 705, 220, 23901, 13, 36995, 25, 220, 605, 13, 1041, 17, 3262, 1764, 13, 14274, 17, 13, 5195, 25542, 198, 50, 13, 57704, 4849, 11, 735, 13, 50341, 72, 323, 350, 13, 94636, 6217, 11, 426, 13382, 2136, 304, 934, 300, 72033, 66603, 6354, 797, 301, 6067, 315, 1370, 57565, 58098, 57565, 955, 389, 2536, 12, 12296, 327, 62215, 31576, 10856, 622, 13, 99836, 11964, 811, 11, 220, 4146, 320, 679, 19, 705, 220, 15531, 18, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 1190, 451, 13, 679, 19, 13, 1721, 13, 22000, 13, 5195, 25542, 198, 54, 13, 622, 1435, 323, 328, 13, 29872, 32651, 11, 1952, 56506, 315, 10105, 311, 264, 1887, 315, 7276, 41264, 39006, 34579, 8590, 354, 7332, 10856, 4149, 13, 50873, 13, 4242, 13, 27670, 2637, 220, 18196, 320, 2550, 17, 705, 220, 18831, 13, 36995, 25, 220, 605, 13, 7743, 15, 11628, 931, 17, 12, 22897, 22, 12, 2550, 17, 12, 6849, 24887, 20, 12, 21, 13, 5195, 25542, 198, 36, 13, 435, 13, 66603, 323, 445, 13, 362, 13, 17652, 301, 11, 16065, 7246, 315, 78944, 29561, 52729, 19894, 439, 459, 56399, 10856, 622, 13, 578, 269, 13, 81894, 2637, 220, 1627, 320, 4468, 15, 705, 220, 18572, 13, 36995, 25, 220, 605, 13, 4645, 21, 14, 6726, 17, 12, 21851, 18, 7, 2031, 8, 7467, 6083, 12, 20, 13, 5195, 25542, 198, 45, 13, 72695, 540, 56017, 323, 393, 13, 9424, 11053, 11, 11842, 451, 7642, 2826, 315, 12523, 5352, 3585, 369, 279, 1370, 57565, 66603, 6354, 797, 301, 1887, 10856, 9489, 13, 358, 13, 473, 13, 393, 2003, 7063, 978, 2147, 11, 220, 2148, 320, 679, 19, 705, 220, 24866, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 13, 5676, 71, 4080, 13, 679, 18, 13, 2589, 13, 11194, 13, 5195, 25542, 198, 34, 13, 15130, 11, 445, 13, 29346, 11, 393, 13, 77547, 323, 1229, 13, 37120, 11, 8121, 14209, 323, 62215, 2136, 315, 29924, 10105, 311, 264, 1370, 57565, 58098, 57565, 8590, 354, 7332, 1887, 10856, 11842, 23603, 20017, 12898, 13058, 4435, 58945, 2637, 220, 975, 320, 679, 18, 705, 220, 9892, 19, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 50983, 81, 10196, 13, 679, 17, 13, 605, 13, 18642, 13, 5195, 25542, 198, 51, 13, 30162, 2192, 11, 46952, 5352, 315, 9038, 34575, 55443, 10105, 315, 264, 8590, 354, 7332, 1887, 10856, 12605, 13, 4242, 13, 41472, 13, 58945, 2637, 220, 20, 320, 2550, 20, 705, 220, 23864, 13, 5195, 25542, 198, 36, 13, 44329, 351, 56017, 323, 735, 13, 15796, 14966, 11, 8121, 14209, 315, 10105, 311, 264, 1370, 57565, 58098, 57565, 1887, 369, 8590, 354, 7332, 449, 7621, 53568, 10856, 11842, 23603, 20017, 2637, 220, 5728, 320, 679, 16, 705, 220, 17361, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 1276, 64, 13, 679, 15, 13, 2318, 13, 20078, 13, 5195, 25542, 198, 53, 13, 33242, 73, 1263, 19870, 11, 19531, 354, 7332, 11, 8450, 1375, 17718, 323, 52729, 79612, 10856, 622, 13, 578, 18673, 13, 81894, 2637, 220, 2983, 320, 4468, 18, 705, 220, 5495, 13, 36995, 25, 220, 605, 13, 4645, 21, 14, 6726, 17, 12, 21851, 18, 7, 5958, 8, 19319, 2491, 12, 20, 13, 5195, 25542, 198, 43, 13, 452, 47435, 7881, 11, 1556, 11838, 37587, 32305, 10856, 9489, 13, 2522, 13, 20935, 13, 7445, 13, 393, 10994, 2493, 13, 41472, 2637, 220, 508, 320, 5162, 21, 705, 220, 24865, 13, 5195, 25542, 198, 51, 13, 5476, 4749, 11, 46952, 455, 7865, 315, 57936, 10105, 311, 622, 1435, 8288, 1983, 32651, 1887, 304, 1579, 56987, 31576, 10856, 40710, 16158, 1662, 469, 44508, 36970, 73, 11, 220, 2166, 320, 1049, 20, 705, 220, 14125, 13, 36995, 25, 220, 605, 13, 10718, 24, 6801, 34183, 13, 2166, 13, 14125, 13, 5195, 25542, 198, 51, 13, 5476, 4749, 323, 350, 13, 56846, 11, 4366, 57565, 1887, 315, 8590, 354, 7332, 25, 46952, 455, 304, 264, 35326, 323, 279, 24746, 892, 10856, 19331, 58945, 13, 20017, 2637, 220, 23, 320, 1049, 16, 705, 220, 18634, 13, 5195, 25542, 198, 56, 13, 60608, 323, 386, 13, 468, 771, 1565, 11, 426, 13382, 2136, 304, 264, 934, 300, 72033, 1370, 57565, 58098, 57565, 66603, 6354, 797, 301, 1887, 449, 1207, 42641, 27541, 10856, 622, 13, 99836, 11964, 811, 11, 220, 12326, 320, 679, 17, 705, 220, 25073, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 1190, 451, 13, 679, 16, 13, 2318, 13, 18089, 13, 5195, 25542, 198, 56, 13, 60608, 323, 386, 13, 468, 771, 1565, 11, 3749, 940, 11113, 2136, 323, 83938, 315, 3544, 14271, 10105, 304, 264, 2380, 33520, 8590, 354, 7332, 1887, 449, 15652, 315, 523, 6868, 266, 2193, 519, 10856, 622, 13, 99836, 11964, 811, 11, 220, 12326, 320, 679, 17, 705, 220, 12326, 15, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 1190, 451, 13, 679, 16, 13, 2589, 13, 7755, 13, 5195, 25542, 198, 56, 13, 60608, 323, 1901, 885, 13, 29346, 11, 26517, 287, 6372, 315, 33464, 6296, 13, 2109, 34003, 304, 8590, 354, 7332, 10856, 4242, 13, 27972, 19331, 58945, 13, 41472, 2637, 220, 1419, 320, 679, 18, 705, 220, 16, 13, 36995, 25, 220, 605, 13, 8011, 17, 11628, 11592, 18248, 13860, 5154, 20078, 18, 13, 5195, 25542, 198, 41, 13, 358, 13, 350, 4896, 323, 386, 13, 468, 771, 1565, 11, 362, 8590, 354, 7332, 1887, 449, 72810, 2592, 10856, 6947, 13, 25570, 99836, 11964, 811, 11, 220, 843, 320, 1049, 22, 705, 220, 26537, 13, 36995, 25, 220, 605, 13, 6640, 15, 14, 23110, 25210, 11194, 16368, 7028, 2839, 13, 5195, 25542, 198, 49, 13, 8817, 309, 11, 55643, 9607, 29321, 33593, 950, 15264, 304, 77923, 323, 28415, 10856, 400, 17, 48922, 303, 32816, 14002, 11, 220, 2614, 320, 2550, 22, 570, 5195, 25542, 198, 43, 13, 29346, 11, 816, 13, 14851, 323, 356, 13, 15130, 11, 426, 13382, 2136, 304, 264, 1370, 57565, 58098, 57565, 934, 300, 72033, 8590, 354, 7332, 1887, 449, 72810, 2592, 10856, 4185, 9537, 323, 70067, 33593, 950, 15264, 11, 220, 1958, 320, 679, 19, 705, 220, 16474, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 82, 13, 679, 19, 13, 1958, 13, 16474, 13, 5195, 25542, 198, 43, 13, 29346, 11, 356, 13, 15130, 323, 393, 13, 77547, 11, 1952, 264, 934, 300, 72033, 1370, 57565, 12, 616, 11696, 292, 8590, 354, 7332, 1887, 449, 72810, 2592, 10856, 622, 13, 99836, 11964, 811, 11, 220, 4146, 320, 679, 19, 705, 220, 10336, 22, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 1190, 451, 13, 679, 18, 13, 717, 13, 11194, 13, 5195, 25542, 198, 57, 13, 362, 13, 29346, 323, 350, 13, 8270, 268, 11, 68533, 10105, 323, 5497, 18488, 369, 264, 8286, 21973, 8590, 354, 7332, 1646, 10856, 44205, 11, 220, 1114, 320, 1049, 22, 570, 36995, 25, 220, 605, 13, 7461, 18, 14, 16, 13, 16660, 22347, 19, 13, 5195, 25542, 198, 57, 13, 362, 13, 29346, 11, 1952, 8590, 354, 7332, 4211, 449, 2849, 7187, 22639, 10856, 4242, 13, 5008, 13, 24772, 13, 69883, 316, 2637, 220, 20, 320, 679, 15, 705, 220, 11908, 13, 36995, 25, 220, 605, 13, 6550, 16, 56280, 6331, 14, 679, 25210, 806, 13, 5195, 25542, 198, 57, 13, 362, 13, 29346, 11, 386, 13, 468, 771, 1565, 323, 423, 13, 32730, 89, 974, 74, 11, 11070, 30079, 18488, 304, 8590, 354, 7332, 6067, 449, 8286, 2269, 9585, 2515, 10856, 11842, 1074, 10981, 11, 220, 1187, 320, 679, 16, 705, 220, 13817, 24, 13, 36995, 25, 220, 605, 13, 6640, 23, 14, 26421, 16, 12, 24876, 20, 14, 1187, 14, 717, 14, 4119, 13, 5195, 25542, 198, 57, 13, 362, 13, 29346, 11, 386, 13, 468, 771, 1565, 323, 423, 13, 32730, 89, 974, 74, 11, 8121, 5912, 488, 6296, 13, 24746, 7394, 7936, 30079, 18488, 304, 264, 8590, 354, 7332, 1646, 449, 8286, 2269, 9585, 2515, 323, 5367, 13523, 58430, 10856, 31648, 1428, 622, 13, 4242, 13, 20017, 2637, 220, 2096, 320, 679, 17, 705, 220, 8652, 17, 13, 36995, 25, 220, 605, 13, 8190, 22, 14, 5120, 25724, 24425, 13, 5195, 25542, 198, 44, 13, 468, 771, 1565, 11, 426, 13382, 2136, 304, 279, 5190, 33520, 1370, 57565, 58098, 57565, 8590, 354, 7332, 1887, 449, 72810, 2592, 10856, 6947, 13, 25570, 99836, 11964, 811, 11, 220, 1758, 320, 679, 15, 705, 220, 9690, 21, 13, 36995, 25, 220, 605, 13, 6640, 15, 14, 23110, 25210, 13858, 22379, 24438, 1627, 13, 5195, 25542, 198, 44, 13, 468, 771, 1565, 11, 19531, 354, 7332, 449, 72810, 2592, 25, 15668, 7621, 3728, 10105, 323, 872, 62215, 2136, 6012, 10856, 622, 13, 4242, 13, 20017, 13, 58945, 2637, 220, 19746, 320, 1049, 23, 705, 220, 21295, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 1190, 1764, 64, 13, 1049, 23, 13, 2589, 13, 24508, 13, 5195, 25542, 198, 44, 13, 468, 771, 1565, 11, 94719, 7394, 12523, 5352, 304, 279, 5190, 33520, 1370, 57565, 58098, 57565, 66603, 6354, 797, 301, 1887, 10856, 622, 13, 4242, 13, 393, 1439, 58945, 2637, 220, 1041, 320, 679, 18, 705, 220, 20338, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 22417, 26047, 13, 679, 18, 13, 1721, 13, 11139, 13, 5195, 25542, 198, 44, 13, 468, 771, 1565, 11, 12838, 264, 364, 26116, 2269, 9585, 2515, 6, 2744, 5471, 8590, 354, 24045, 18678, 30, 10856, 4242, 13, 19331, 58945, 13, 41472, 2637, 220, 1644, 320, 679, 15, 705, 220, 717, 13, 36995, 25, 220, 605, 13, 1041, 17, 3262, 1764, 13, 8011, 21, 13, 5195, 25542, 198, 44, 13, 468, 771, 1565, 11, 4701, 35542, 6296, 13, 3728, 3722, 22784, 7865, 304, 279, 5190, 33520, 66603, 6354, 797, 301, 1646, 10856, 622, 13, 99836, 11964, 811, 11, 220, 14185, 320, 679, 15, 705, 220, 15287, 24, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 1190, 451, 13, 679, 15, 13, 2437, 13, 11436, 13, 5195, 25542, 198, 44, 13, 468, 771, 1565, 323, 735, 13, 356, 13, 52162, 648, 11, 426, 13382, 2136, 323, 35326, 7394, 18678, 304, 264, 8590, 354, 7332, 1887, 449, 8286, 2269, 9585, 2515, 10856, 11842, 23603, 20017, 2637, 220, 5332, 320, 679, 15, 705, 220, 6849, 19, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 1276, 64, 13, 1049, 24, 13, 2589, 13, 23785, 13, 5195, 25542, 198, 35, 13, 32730, 89, 974, 74, 11, 8121, 9504, 269, 369, 264, 8590, 354, 7332, 1646, 449, 27344, 315, 927, 1824, 654, 7113, 10856, 11842, 23603, 20017, 2637, 220, 2946, 320, 1049, 19, 705, 220, 9748, 18, 13, 36995, 25, 220, 605, 13, 4645, 21, 4537, 1276, 64, 13, 1049, 19, 13, 2318, 13, 16037, 13, 5195, 25542, 198, 42, 80780, 283, 63370, 648, 11, 34390, 10426, 5476, 4749, 13, 8121, 14209, 323, 62215, 2136, 304, 264, 1370, 57565, 12, 616, 11696, 292, 66603, 6354, 797, 301, 1887, 449, 4689, 27541, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 426, 11, 220, 679, 21, 11, 220, 1691, 320, 16, 8, 551, 220, 5932, 12, 4278, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 17319, 13, 679, 21, 13, 1691, 13, 5932, 198, 42, 80780, 283, 63370, 648, 11, 34382, 86238, 452, 819, 16618, 3105, 11, 8529, 22157, 94636, 6217, 13, 426, 13382, 2136, 304, 264, 934, 300, 72033, 1370, 57565, 58098, 57565, 66603, 6354, 797, 301, 1887, 449, 279, 27541, 400, 85, 88310, 16, 92, 50, 8317, 8, 13244, 15217, 62770, 11, 220, 679, 20, 11, 220, 679, 20, 320, 15495, 8, 551, 220, 21033, 12, 21757, 13, 36995, 25, 220, 605, 13, 18252, 19, 14, 16159, 13, 679, 20, 13, 24222, 19, 198, 51, 677, 3557, 5348, 13, 8121, 67217, 10105, 311, 264, 1370, 57565, 12, 616, 11696, 292, 66603, 6354, 797, 301, 1887, 449, 35044, 27541, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 328, 11, 220, 2366, 15, 11, 220, 1032, 320, 17, 8, 551, 220, 9079, 12, 10148, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 784, 13, 2366, 931, 22, 198, 47, 11345, 81, 426, 5888, 11, 34881, 36970, 4673, 14210, 11, 2895, 89, 797, 68423, 735, 1132, 13, 20902, 3728, 3502, 7394, 10105, 315, 279, 1370, 57565, 58098, 57565, 66603, 6354, 797, 301, 1887, 389, 279, 11277, 13, 26545, 389, 30688, 612, 43608, 18825, 11, 220, 679, 20, 11, 220, 975, 320, 21, 8, 551, 220, 11483, 22, 12, 11227, 21, 13, 36995, 25, 220, 605, 13, 18252, 19, 2971, 79, 5418, 13, 679, 20, 13, 975, 13, 11483, 22, 198, 44, 833, 88, 3524, 80473, 11, 328, 5859, 77547, 13, 400, 445, 61, 60474, 3, 12, 48899, 13186, 369, 62215, 2136, 304, 264, 934, 300, 72033, 1370, 57565, 12, 616, 11696, 292, 66603, 6354, 797, 301, 1887, 449, 2307, 42641, 27541, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 426, 11, 220, 679, 24, 11, 220, 1187, 320, 22, 8, 551, 220, 18163, 16, 12, 17690, 23, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 17319, 13, 679, 26218, 20, 198, 39, 3524, 28372, 11, 53548, 29346, 11, 328, 5859, 77547, 13, 426, 13382, 2136, 315, 10105, 311, 264, 7373, 1370, 57565, 66603, 6354, 797, 301, 1887, 449, 75098, 27541, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 426, 11, 220, 679, 22, 11, 220, 1313, 320, 19, 8, 551, 220, 9892, 20, 12, 10513, 19, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 17319, 13, 679, 18770, 23, 198, 54, 92299, 7409, 11, 88404, 12279, 24012, 38805, 13, 48989, 400, 43, 48922, 22447, 252, 32816, 62215, 2136, 369, 264, 5367, 13523, 1370, 57565, 58098, 57565, 66603, 6354, 797, 301, 1646, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 426, 11, 220, 679, 22, 11, 220, 1313, 320, 17, 8, 551, 220, 14777, 12, 18633, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 17319, 13, 679, 19597, 20, 198, 41, 2319, 42256, 35882, 27710, 13, 55643, 892, 12523, 5352, 315, 1690, 10105, 311, 264, 4689, 934, 300, 72033, 1370, 57565, 12, 616, 11696, 292, 66603, 6354, 797, 301, 1887, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 328, 11, 220, 2366, 15, 11, 220, 1032, 320, 17, 8, 551, 220, 12994, 12, 3192, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 784, 13, 2366, 4119, 18, 198, 50, 613, 24551, 57704, 4849, 13, 400, 43, 25928, 258, 38058, 3, 12, 85599, 3424, 369, 934, 300, 72033, 5367, 13523, 1370, 57565, 12, 616, 11696, 292, 66603, 6354, 797, 301, 6067, 13, 15217, 62770, 11, 220, 679, 18, 11, 220, 679, 18, 320, 15495, 8, 551, 220, 16596, 12, 17451, 13, 36995, 25, 220, 605, 13, 18252, 19, 14, 16159, 13, 679, 18, 13, 679, 18, 13, 16596, 198, 44, 833, 88, 3524, 80473, 11, 1630, 28323, 76311, 70381, 13, 400, 445, 25928, 25956, 400, 12, 48899, 13186, 369, 62215, 2136, 304, 264, 934, 300, 72033, 1370, 57565, 58098, 57565, 66603, 6354, 797, 301, 1887, 449, 2307, 42641, 27541, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 426, 11, 220, 679, 24, 11, 220, 1187, 320, 605, 8, 551, 220, 21618, 22, 12, 20823, 20, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 17319, 13, 679, 22393, 24, 198, 41, 21538, 10602, 29346, 11, 14851, 25507, 11, 14851, 526, 19730, 13, 4366, 57565, 78883, 292, 955, 66603, 6354, 797, 301, 1887, 389, 279, 4459, 3634, 1162, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 362, 11, 220, 679, 21, 11, 220, 1927, 320, 17, 8, 551, 220, 7461, 16, 12, 6640, 19, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 82, 13, 679, 21, 13, 1927, 13, 7461, 16, 198, 11342, 3074, 69698, 300, 11, 75698, 49845, 1291, 393, 8869, 11, 15754, 93103, 58201, 75, 532, 18812, 13, 28636, 14597, 369, 12523, 5352, 304, 264, 1370, 57565, 58098, 57565, 66603, 6354, 797, 301, 1887, 13, 15217, 62770, 11, 220, 679, 20, 11, 220, 679, 20, 320, 15495, 8, 551, 220, 21474, 12, 23713, 13, 36995, 25, 220, 605, 13, 18252, 19, 14, 16159, 13, 679, 20, 13, 13837, 24, 198, 50, 613, 24551, 57704, 4849, 11, 8529, 22157, 94636, 6217, 13, 46952, 5352, 304, 35326, 477, 24746, 892, 369, 934, 300, 72033, 5367, 13523, 66603, 6354, 797, 301, 6067, 315, 1370, 57565, 58098, 57565, 955, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 426, 11, 220, 679, 18, 11, 220, 972, 320, 605, 8, 551, 220, 4146, 24, 12, 15537, 21, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 17319, 13, 679, 18, 13, 972, 13, 4146, 24, 198, 2127, 2034, 277, 622, 2448, 983, 301, 11, 31346, 2009, 287, 526, 13, 46952, 5352, 315, 10105, 311, 18768, 10694, 9537, 1370, 57565, 12, 616, 11696, 292, 66603, 6354, 797, 301, 4211, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 426, 11, 220, 679, 24, 11, 220, 1187, 320, 24, 8, 551, 220, 19799, 20, 12, 22086, 17, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 17319, 13, 679, 21026, 24, 198, 50, 613, 24551, 57704, 4849, 11, 8529, 22157, 94636, 6217, 13, 426, 13382, 2136, 304, 264, 934, 300, 72033, 7373, 1370, 57565, 66603, 6354, 797, 301, 1887, 4669, 54229, 67537, 1286, 85, 5912, 488, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 328, 11, 220, 2366, 15, 11, 220, 1032, 320, 17, 8, 551, 220, 11483, 12, 12338, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 784, 13, 2366, 4119, 17, 198, 44, 23332, 90684, 48443, 11, 328, 5859, 77547, 13, 8121, 62215, 2136, 19579, 35326, 7394, 12523, 5352, 315, 10105, 311, 264, 934, 300, 72033, 7373, 1370, 57565, 66603, 6354, 797, 301, 1887, 315, 1403, 9606, 13, 26545, 389, 30688, 612, 43608, 18825, 11, 220, 679, 21, 11, 220, 868, 320, 16, 8, 551, 220, 14052, 12, 11387, 13, 36995, 25, 220, 605, 13, 18252, 19, 2971, 79, 5418, 13, 679, 21, 13, 868, 13, 14052, 198, 39, 3524, 28372, 11, 53548, 29346, 11, 328, 5859, 77547, 13, 8121, 62215, 2136, 315, 10105, 311, 264, 66603, 6354, 797, 301, 1887, 449, 75098, 27541, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 426, 11, 220, 679, 21, 11, 220, 1691, 320, 19, 8, 551, 220, 9263, 22, 12, 9413, 22, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 17319, 13, 679, 21, 13, 1691, 13, 9263, 22, 198, 50, 613, 24551, 57704, 4849, 13, 1556, 87975, 5603, 311, 400, 43, 25928, 258, 38058, 3, 12, 66786, 2136, 304, 934, 300, 72033, 66603, 6354, 797, 301, 6067, 13, 15217, 62770, 11, 220, 679, 20, 11, 220, 679, 20, 320, 15495, 8, 551, 220, 22276, 12, 22956, 13, 36995, 25, 220, 605, 13, 18252, 19, 14, 16159, 13, 679, 20, 13, 24254, 20, 198, 50302, 936, 33267, 351, 24235, 13, 362, 4689, 14209, 1121, 369, 53735, 10105, 311, 279, 66603, 6354, 797, 301, 1887, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 362, 11, 220, 679, 24, 11, 220, 2137, 320, 17, 8, 551, 220, 22393, 12, 26026, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 82, 13, 679, 23305, 23, 198, 39, 2192, 30237, 526, 39611, 11, 1901, 6151, 59016, 29346, 13, 8121, 83938, 315, 279, 2539, 33464, 5621, 79, 34003, 66603, 6354, 797, 301, 1887, 13, 4185, 9537, 612, 70067, 33593, 950, 15264, 482, 362, 11, 220, 679, 24, 11, 220, 15, 320, 15, 8, 551, 220, 15, 12, 15, 13, 36995, 25, 220, 605, 13, 18252, 19, 3529, 4484, 82, 13, 2366, 6726, 22, 198, 55, 648, 14851, 1901, 4317, 2303, 258, 1630, 28323, 128000, 20004, 40324, 198, 27264, 220, 24, 5697, 12393, 198, 7778, 28783, 15781, 38213, 449, 330, 677, 28222, 702, 35, 56407, 9711, 220, 16, 304, 220, 20, 31550, 520, 15748, 20562, 12, 777, 5326, 25, 4007, 198, 1729, 4074, 482, 12044, 220, 845, 11, 220, 2366, 15, 198, 2127, 13240, 220, 16, 13, 22, 7239, 1274, 2001, 810, 1109, 220, 508, 3346, 315, 279, 1917, 596, 7187, 2001, 5326, 10671, 35906, 29374, 449, 20562, 12, 777, 4245, 311, 16940, 2890, 5435, 1778, 439, 33048, 323, 4851, 8624, 11, 6492, 8710, 7742, 627, 791, 11775, 33333, 11, 902, 706, 7577, 810, 1109, 220, 12819, 11, 931, 1274, 31550, 2391, 279, 1176, 12330, 315, 279, 28522, 11, 69214, 6372, 6978, 16066, 505, 1080, 1474, 269, 21301, 1385, 627, 32, 2128, 315, 11909, 505, 279, 7295, 6150, 315, 10320, 43312, 323, 71343, 19152, 67458, 3728, 828, 7437, 315, 49909, 2737, 20335, 11, 21271, 8624, 323, 23495, 1511, 1521, 311, 16430, 1268, 1690, 1274, 527, 520, 60487, 5326, 315, 6129, 20562, 12, 777, 19405, 627, 7009, 1766, 430, 832, 304, 4330, 1274, 617, 520, 3325, 832, 16940, 2890, 3575, 10917, 1124, 304, 7191, 8137, 627, 8142, 539, 682, 315, 1884, 1053, 733, 389, 311, 2274, 15748, 13803, 422, 29374, 11, 279, 12074, 1071, 2212, 220, 19, 3346, 315, 279, 3728, 7187, 2001, 2212, 220, 8652, 3610, 8, 1053, 4461, 636, 14363, 3403, 311, 1397, 8952, 6514, 627, 48240, 5961, 3351, 704, 315, 51235, 11, 17047, 527, 3411, 369, 5627, 311, 6144, 279, 1455, 20134, 505, 264, 17188, 430, 374, 2103, 54828, 1359, 1071, 13929, 22010, 11, 889, 20162, 311, 279, 4007, 627, 22244, 2643, 21736, 63779, 1274, 449, 16940, 4787, 311, 11142, 3674, 73669, 11193, 8475, 311, 872, 2237, 315, 5326, 10246, 85917, 1071, 279, 14955, 1436, 1520, 17047, 1304, 11429, 389, 889, 21879, 264, 20562, 12, 777, 25474, 1176, 994, 832, 9221, 2561, 627, 15577, 18620, 449, 1023, 7978, 922, 20562, 5326, 11, 279, 12283, 1766, 430, 9191, 1274, 527, 304, 7191, 8137, 315, 3794, 14243, 653, 9336, 505, 279, 17188, 627, 28551, 1109, 220, 20, 3346, 315, 1274, 20330, 1234, 220, 508, 617, 459, 16940, 5326, 8331, 11, 7863, 449, 1403, 94237, 315, 927, 220, 2031, 82, 627, 72828, 449, 14992, 22673, 617, 17162, 1274, 449, 520, 3325, 832, 16940, 3044, 11, 719, 15635, 13592, 31550, 11, 4184, 311, 279, 6492, 627, 26375, 13218, 5415, 1778, 439, 86196, 323, 89313, 9334, 617, 4315, 279, 8592, 7969, 315, 20335, 2001, 264, 3967, 20562, 12, 777, 5326, 8331, 2001, 389, 9420, 11, 369, 3187, 627, 3112, 5961, 449, 279, 8592, 38009, 315, 23495, 93646, 11, 1778, 439, 384, 13521, 266, 6729, 323, 11876, 8942, 78, 11, 1101, 1205, 311, 387, 81334, 11, 1071, 12283, 315, 279, 3495, 4756, 304, 578, 39634, 295, 627, 644, 4606, 11, 810, 1109, 220, 966, 3346, 315, 1274, 617, 832, 477, 810, 2890, 4787, 11, 433, 8710, 627, 40413, 304, 264, 10815, 4068, 11, 64988, 5124, 27495, 1395, 505, 19326, 3907, 15219, 1543, 6150, 315, 3142, 6401, 11, 1071, 279, 4007, 8710, 330, 275, 374, 892, 311, 38680, 505, 264, 832, 7321, 2269, 1220, 23148, 5603, 311, 832, 430, 36282, 389, 1884, 1455, 520, 5326, 10246, 99729, 40085, 26587, 8624, 198, 1729, 482, 17907, 220, 914, 11, 220, 679, 22, 198, 7184, 35076, 11, 20992, 5493, 889, 3063, 11163, 306, 661, 79731, 323, 889, 617, 18306, 42408, 3691, 26870, 11, 5101, 311, 387, 810, 38097, 311, 26587, 19338, 1109, 3885, 13, 435, 23758, 26587, 8624, 374, 279, 1121, 315, 264, 1977, 5352, 315, 8834, 304, 279, 26587, 13, 1442, 279, 26587, 374, 9498, 11, 1070, 1288, 387, 2697, 477, 912, 8834, 304, 433, 13, 4452, 11, 7170, 11, 8834, 35715, 3240, 311, 6667, 304, 279, 26587, 7917, 13, 15344, 15055, 315, 8834, 304, 279, 26587, 6118, 5353, 912, 5435, 13, 4452, 11, 994, 2288, 1790, 8834, 22890, 304, 420, 2942, 11, 433, 649, 17477, 264, 2763, 315, 2890, 52642, 627, 2409, 279, 4788, 315, 279, 8271, 11, 279, 26587, 374, 279, 1455, 6485, 2942, 323, 2132, 7928, 2942, 304, 279, 2547, 13, 11699, 734, 374, 311, 1920, 4395, 584, 8343, 477, 7172, 323, 4141, 28856, 33155, 505, 279, 6680, 13, 1115, 1920, 374, 4869, 37883, 994, 279, 26587, 5727, 2288, 1790, 8834, 13, 3277, 8834, 9815, 369, 810, 1109, 4330, 3346, 315, 279, 26587, 596, 4785, 11, 279, 3044, 374, 7633, 439, 40085, 26587, 627, 2181, 374, 10671, 832, 315, 279, 1455, 4279, 4595, 315, 26587, 8624, 323, 433, 596, 1101, 832, 315, 279, 11384, 315, 26587, 9572, 323, 30570, 41196, 10934, 13, 578, 8624, 1253, 1101, 12446, 4245, 311, 41861, 5435, 1778, 439, 20335, 11, 33048, 477, 61245, 82801, 426, 323, 356, 19405, 627, 32, 23842, 315, 40085, 26587, 1436, 4933, 279, 17035, 369, 459, 63561, 4078, 220, 17, 20335, 13, 435, 23758, 26587, 8624, 649, 3063, 311, 459, 4704, 3690, 26587, 323, 1156, 20450, 13, 1115, 374, 2663, 56461, 73975, 422, 433, 596, 9057, 555, 16558, 2288, 1790, 13200, 323, 2536, 19308, 45494, 4179, 4428, 383, 4781, 20000, 422, 433, 596, 539, 5552, 311, 13200, 627, 3915, 1148, 358, 617, 11497, 779, 3117, 11, 433, 1288, 387, 8196, 430, 40085, 26587, 8624, 374, 264, 19433, 8624, 13, 7648, 1274, 5496, 449, 420, 8624, 527, 8834, 11, 50320, 323, 814, 1935, 13200, 627, 2181, 374, 810, 4279, 304, 3026, 323, 11434, 3485, 279, 4325, 315, 220, 1135, 13, 39515, 531, 4114, 323, 71975, 6978, 527, 1455, 4461, 311, 387, 29704, 449, 40085, 26587, 439, 814, 527, 2736, 47336, 449, 1579, 6680, 13465, 11, 34323, 323, 39086, 627, 11458, 11, 26333, 1093, 21747, 354, 38639, 349, 323, 26555, 5241, 56439, 649, 11, 719, 19029, 5353, 2536, 19308, 45494, 40085, 26587, 627, 8284, 19308, 45494, 40085, 26587, 8624, 6118, 11384, 912, 12195, 323, 13803, 13, 3277, 433, 1587, 11, 814, 1253, 2997, 36709, 11, 8009, 38575, 11, 6784, 304, 279, 8582, 1314, 64772, 323, 4785, 4814, 627, 37220, 36505, 2997, 264, 76193, 64772, 11, 433, 59064, 6930, 11, 63571, 315, 6680, 11, 22047, 477, 8009, 5044, 11, 23948, 323, 16124, 48897, 323, 12203, 1263, 560, 627, 37, 23758, 26587, 8624, 649, 7170, 387, 5107, 311, 58681, 1606, 832, 1253, 539, 617, 904, 13803, 13, 2684, 374, 912, 3254, 1296, 430, 649, 387, 1511, 311, 58681, 40085, 26587, 8624, 11, 719, 832, 1253, 6920, 704, 1063, 6680, 7177, 11, 26587, 99647, 11, 63859, 11, 19084, 477, 52460, 8737, 902, 1520, 311, 1893, 5448, 315, 279, 26587, 13, 4314, 5448, 690, 1501, 422, 1070, 527, 904, 7739, 315, 8834, 304, 279, 26587, 627, 2675, 1253, 387, 3025, 311, 5471, 2536, 19308, 45494, 40085, 26587, 8624, 555, 20958, 264, 9498, 4785, 369, 701, 2673, 13, 21347, 4642, 1456, 311, 656, 520, 3325, 220, 3965, 4520, 315, 24070, 10368, 1855, 2046, 477, 220, 966, 4520, 315, 10368, 369, 2919, 627, 23025, 889, 527, 50320, 477, 50254, 11, 264, 53722, 4785, 4814, 323, 5912, 10368, 374, 26160, 13, 1115, 539, 1193, 8779, 449, 40085, 26587, 719, 1101, 433, 690, 1520, 311, 8108, 1023, 15635, 315, 11469, 41713, 5435, 627, 16934, 477, 5766, 56461, 47497, 1606, 13200, 1524, 304, 27946, 15055, 1253, 1304, 40085, 26587, 11201, 627, 36, 1113, 9498, 15657, 430, 527, 3428, 304, 50585, 8834, 323, 8108, 701, 13465, 23730, 311, 2585, 701, 6680, 13465, 13, 43750, 701, 39086, 5990, 323, 1005, 26587, 33690, 627, 2149, 45494, 40085, 26587, 8624, 374, 81193, 13, 578, 26587, 1288, 471, 311, 4725, 422, 832, 18417, 16558, 13200, 13, 7570, 422, 832, 706, 1027, 264, 8987, 7172, 261, 369, 1690, 1667, 11, 18189, 477, 23351, 13200, 23730, 690, 617, 3062, 2875, 323, 1317, 9860, 7720, 389, 279, 26587, 323, 832, 596, 8244, 2890, 627, 1687, 3708, 39445, 20846, 311, 2567, 499, 1664, 16369, 389, 1510, 6401, 4819, 323, 3754, 304, 29258, 198, 51, 26488, 555, 571, 24, 5697, 46827, 198, 20644, 3028, 220, 679, 20, 482, 220, 24, 5697, 12393, 13, 362, 18221, 25188, 8184, 128000, 679, 19, 12, 806, 12, 777, 63724, 311, 17116, 40, 8288, 2599, 88634, 7391, 5482, 11, 18610, 13, 312, 31051, 17116, 40, 8288, 2599, 88634, 7391, 5482, 11, 18610, 13, 96671, 5441, 3083, 96671, 10022, 30442, 5288, 320, 49840, 58113, 4716, 78096, 570, 32739, 1105, 25, 8927, 29266, 11, 13398, 1111, 11, 432, 8253, 29661, 2864, 946, 11, 328, 13508, 7535, 11, 14644, 627, 679, 19, 12, 717, 12, 2318, 63724, 311, 90340, 37, 36345, 52699, 15942, 18610, 878, 53525, 9182, 312, 31051, 90340, 37, 36345, 52699, 15942, 18610, 878, 53525, 9182, 96671, 5441, 3083, 96671, 10022, 30442, 5288, 320, 49840, 58113, 4716, 78096, 570, 32739, 1105, 25, 17116, 40, 8288, 2599, 88634, 7391, 5482, 11, 18610, 627, 73741, 34933, 24198, 369, 24301, 277, 84667, 16346, 527, 3984, 369, 25689, 1113, 323, 73300, 287, 264, 42902, 2942, 1778, 439, 264, 19754, 2067, 21473, 13, 578, 34933, 24198, 2997, 264, 31409, 2547, 323, 459, 17543, 34356, 311, 279, 31409, 2547, 13, 578, 17543, 374, 30464, 323, 20336, 369, 23387, 323, 73300, 287, 279, 42902, 2942, 11, 323, 649, 387, 5762, 323, 27167, 505, 2949, 279, 31409, 2547, 477, 505, 459, 4994, 7479, 315, 279, 31409, 2547, 13, 578, 31409, 2547, 19170, 459, 58101, 369, 62174, 98741, 315, 8970, 315, 279, 42902, 2942, 627, 2028, 3851, 8349, 279, 8935, 315, 10844, 311, 549, 815, 13, 59090, 7473, 8409, 13, 2360, 13, 220, 5547, 14, 17335, 11, 25377, 11, 13019, 3799, 13, 220, 2148, 11, 220, 1049, 24, 323, 549, 815, 13, 59090, 7473, 8409, 13, 2360, 13, 220, 5547, 14, 15726, 11, 19192, 11, 13019, 5186, 13, 220, 1032, 11, 220, 679, 15, 11, 902, 527, 32762, 36881, 555, 5905, 11, 304, 872, 4553, 29646, 627, 791, 3118, 28229, 36716, 311, 34933, 16346, 13, 97485, 11, 279, 3118, 28229, 374, 15910, 311, 7766, 369, 24301, 277, 84667, 34933, 16346, 11, 323, 810, 8104, 311, 7766, 369, 1005, 304, 3254, 86719, 1854, 24301, 277, 84667, 34933, 320, 50, 1750, 50, 8, 16346, 13, 578, 3917, 34933, 7766, 527, 27167, 11, 304, 18859, 449, 832, 13189, 11, 505, 2949, 279, 326, 28999, 315, 264, 31409, 477, 505, 459, 16335, 7479, 315, 264, 31409, 13, 15483, 7766, 527, 7170, 61937, 330, 17483, 64631, 25847, 1210, 549, 815, 13, 59090, 62770, 35813, 2326, 220, 679, 15, 14, 4119, 23292, 19, 11, 2326, 220, 1049, 24, 14, 18070, 20275, 20, 11, 2326, 220, 1049, 23, 14, 11436, 21379, 21, 11, 2326, 220, 1049, 22, 14, 22000, 13460, 15, 11, 2326, 220, 1049, 22, 14, 18070, 10731, 17, 11, 2326, 220, 1049, 22, 14, 11592, 18322, 22, 11, 2326, 220, 1049, 22, 14, 11592, 18322, 21, 11, 323, 2326, 220, 1049, 22, 14, 11592, 19192, 20, 11, 1855, 315, 902, 374, 32762, 36881, 555, 5905, 11, 304, 1202, 49017, 11, 7664, 7766, 5552, 311, 279, 7766, 7633, 36881, 13, 578, 7766, 7633, 58179, 11, 323, 13878, 34366, 11, 2737, 6683, 315, 2585, 24717, 11, 3769, 6727, 11, 59251, 12823, 11, 439, 1664, 439, 1023, 13878, 11, 649, 387, 9435, 311, 279, 7766, 7633, 36881, 11, 449, 76824, 2515, 627, 38, 543, 2067, 21473, 15173, 706, 1027, 14110, 1534, 304, 3293, 1667, 11, 10223, 505, 459, 1825, 3709, 1854, 278, 15173, 311, 11, 5131, 11, 4661, 264, 32227, 24301, 277, 84667, 10537, 11, 1101, 3967, 439, 264, 21877, 750, 53354, 15173, 13, 1221, 44322, 21877, 750, 53354, 68823, 369, 523, 12747, 599, 72783, 21736, 279, 1005, 315, 3116, 8348, 51808, 320, 5323, 7766, 570, 763, 4689, 11, 832, 8348, 7063, 374, 22306, 304, 279, 37781, 321, 59344, 11, 1555, 902, 459, 842, 63753, 374, 22306, 11, 449, 1403, 8348, 51808, 1694, 22306, 389, 279, 1314, 3185, 315, 279, 64772, 369, 312, 27523, 323, 29905, 4954, 279, 19754, 2067, 21473, 11, 304, 2015, 311, 10765, 279, 3062, 14726, 13, 578, 11999, 8348, 7063, 374, 11383, 22306, 304, 279, 5209, 1074, 3485, 279, 37781, 321, 59344, 627, 791, 46752, 1749, 706, 3719, 279, 5410, 5603, 323, 706, 449, 52784, 17510, 1667, 315, 4442, 304, 34933, 10151, 7437, 11, 304, 5370, 5315, 315, 74272, 13, 6649, 8046, 6051, 11, 1524, 26627, 323, 76824, 12823, 369, 523, 12747, 599, 72783, 617, 1027, 8040, 430, 21736, 1193, 264, 3254, 8348, 7063, 477, 330, 403, 498, 2663, 60823, 50, 320, 15698, 3709, 1854, 24301, 277, 84667, 15173, 570, 578, 20212, 374, 430, 7154, 17510, 311, 36498, 3346, 315, 682, 19754, 2067, 21473, 68823, 690, 387, 10887, 304, 420, 11827, 304, 279, 1828, 4330, 311, 5899, 1667, 13, 1115, 5557, 18065, 39398, 264, 3254, 2700, 22306, 1555, 279, 37781, 321, 59344, 11, 449, 682, 279, 24198, 2133, 1139, 279, 57056, 56429, 1555, 279, 3254, 2700, 13, 70930, 4954, 323, 73300, 287, 279, 19754, 2067, 21473, 374, 17436, 449, 420, 5557, 11, 5423, 422, 279, 19754, 2067, 21473, 374, 1612, 2954, 4245, 311, 37140, 627, 3947, 527, 12823, 2561, 520, 3118, 369, 34330, 5620, 279, 3887, 355, 315, 279, 19754, 2067, 21473, 449, 35312, 1439, 2391, 60823, 50, 16346, 11, 8051, 1778, 12823, 527, 1633, 96190, 323, 5107, 11, 5423, 449, 459, 4704, 3690, 19754, 2067, 21473, 627, 2213, 62932, 15641, 430, 25689, 660, 11, 94972, 19754, 2067, 81308, 527, 70668, 422, 1701, 60823, 50, 5557, 369, 523, 12747, 599, 72783, 11, 8617, 10223, 1148, 574, 264, 43787, 11, 2539, 11347, 11, 1139, 264, 296, 5164, 481, 6070, 62174, 24198, 311, 34477, 279, 7147, 315, 279, 19754, 2067, 21473, 13, 98789, 4726, 15641, 430, 5042, 25689, 1113, 449, 264, 31409, 7636, 11, 323, 539, 66934, 279, 8736, 9057, 28592, 11, 690, 5353, 39897, 425, 315, 2163, 29352, 7384, 11, 902, 374, 539, 35946, 627, 11439, 398, 11, 1070, 8625, 264, 1205, 304, 279, 1989, 369, 7766, 430, 28696, 98741, 323, 312, 27523, 315, 19754, 2067, 21473, 304, 24301, 277, 84667, 16346, 430, 5471, 39897, 425, 315, 19754, 2067, 21473, 8970, 13, 578, 3118, 28229, 5825, 264, 6425, 369, 1521, 3966, 627, 644, 832, 13189, 11, 264, 34933, 14473, 369, 24301, 277, 84667, 16346, 374, 3984, 11, 902, 374, 30464, 323, 20336, 311, 25689, 349, 323, 73300, 264, 42902, 2942, 13, 578, 34933, 14473, 5764, 264, 31409, 2547, 11, 459, 17543, 11, 10739, 481, 449, 5201, 311, 279, 31409, 2547, 11, 30464, 323, 20336, 369, 23387, 323, 73300, 287, 279, 42902, 2942, 11, 323, 459, 58101, 3984, 304, 3717, 449, 279, 31409, 2547, 11, 30464, 323, 20336, 369, 62174, 98741, 315, 8970, 315, 279, 42902, 2942, 627, 791, 42902, 2942, 649, 387, 264, 19754, 2067, 21473, 13, 578, 17543, 649, 387, 5762, 2949, 11, 323, 10739, 481, 505, 11, 264, 326, 28999, 315, 279, 31409, 2547, 13, 578, 17543, 649, 387, 5762, 389, 11, 323, 10739, 481, 505, 11, 459, 4994, 7479, 315, 279, 31409, 2547, 627, 791, 17543, 649, 387, 264, 10739, 481, 36460, 6070, 13, 578, 36460, 6070, 649, 387, 10683, 1481, 72, 1503, 1778, 430, 279, 36460, 6070, 374, 27167, 555, 24408, 3984, 304, 264, 10683, 994, 279, 36460, 6070, 2289, 7953, 279, 31409, 2547, 555, 264, 87010, 6138, 13, 578, 36460, 6070, 649, 2997, 832, 477, 810, 3703, 1302, 20336, 311, 13334, 505, 279, 36460, 6070, 994, 279, 36460, 6070, 374, 304, 264, 27167, 6683, 13, 15483, 832, 477, 810, 3703, 1302, 649, 387, 1612, 750, 15910, 311, 28696, 312, 4302, 290, 315, 279, 36460, 6070, 1139, 279, 326, 28999, 315, 279, 31409, 2547, 13, 39578, 11, 1778, 832, 477, 810, 3703, 1302, 649, 387, 22267, 318, 750, 15910, 311, 28696, 20392, 315, 279, 3703, 1302, 449, 279, 9358, 7147, 315, 279, 42902, 2942, 13, 578, 36460, 649, 387, 20336, 779, 430, 279, 3703, 1302, 3351, 1139, 264, 2361, 6293, 10946, 277, 449, 14932, 19885, 315, 279, 36460, 11, 311, 28696, 312, 4302, 290, 315, 279, 36460, 1139, 279, 326, 28999, 315, 279, 31409, 2547, 627, 791, 36460, 6070, 649, 387, 3984, 449, 520, 3325, 832, 44585, 478, 2214, 311, 28696, 58218, 34786, 315, 279, 36460, 627, 791, 36460, 6070, 649, 387, 3984, 449, 264, 73405, 315, 14535, 11, 55443, 750, 28902, 922, 264, 68102, 8183, 315, 279, 34933, 14473, 13, 578, 1396, 315, 14535, 649, 387, 904, 477, 1403, 11, 2380, 11, 3116, 11, 4330, 11, 4848, 11, 8254, 11, 8223, 477, 11888, 11, 369, 3187, 13, 4452, 11, 7191, 477, 17162, 14535, 11, 1778, 439, 832, 477, 5899, 323, 779, 389, 11, 649, 387, 3984, 627, 791, 36460, 6070, 649, 2997, 264, 73405, 315, 24997, 81947, 311, 11810, 25152, 315, 279, 36460, 1418, 20958, 8333, 14343, 311, 57482, 73300, 279, 42902, 2942, 627, 644, 18859, 449, 2500, 13189, 315, 279, 28229, 11, 279, 17543, 649, 387, 264, 10739, 481, 9244, 6070, 627, 93114, 11, 279, 17543, 459, 97307, 6070, 13, 578, 17543, 649, 387, 30464, 323, 20336, 311, 387, 97307, 555, 832, 477, 810, 315, 264, 14812, 323, 264, 6962, 627, 791, 17543, 649, 2997, 264, 1612, 278, 17543, 13651, 323, 264, 22267, 2931, 17543, 13651, 11, 30464, 323, 20336, 311, 16988, 9358, 323, 16335, 27529, 315, 279, 42902, 2942, 11, 15947, 13, 578, 1612, 278, 17543, 13651, 323, 279, 22267, 2931, 17543, 13651, 649, 387, 49704, 38745, 64928, 10980, 555, 264, 6138, 14343, 311, 11810, 20392, 315, 264, 7147, 315, 279, 42902, 2942, 13, 1442, 12974, 11, 279, 1612, 278, 17543, 13651, 323, 279, 22267, 2931, 17543, 13651, 649, 387, 12984, 750, 4445, 505, 832, 2500, 555, 922, 220, 1954, 12628, 11, 449, 5201, 311, 264, 68102, 8183, 315, 279, 34933, 14473, 13, 39578, 11, 279, 1612, 278, 17543, 13651, 323, 279, 22267, 2931, 17543, 13651, 649, 387, 32302, 15638, 449, 832, 2500, 11, 449, 5201, 311, 264, 68102, 8183, 315, 279, 34933, 14473, 627, 791, 1612, 278, 17543, 13651, 323, 279, 22267, 2931, 17543, 13651, 649, 387, 315, 32302, 279, 1890, 6683, 13, 39578, 11, 279, 1612, 278, 17543, 13651, 323, 279, 22267, 2931, 17543, 13651, 649, 387, 315, 14091, 79962, 33483, 11, 1778, 439, 304, 6070, 11, 1396, 315, 5540, 11, 1404, 11, 3769, 11, 477, 304, 1023, 13878, 34366, 627, 644, 18859, 449, 279, 28229, 11, 279, 31409, 2547, 649, 2997, 264, 57463, 291, 1612, 278, 11813, 13, 362, 10739, 481, 11813, 63261, 649, 4726, 387, 3984, 311, 69033, 70576, 278, 11134, 555, 264, 57463, 291, 1612, 278, 11813, 315, 279, 31409, 2547, 13, 578, 10739, 481, 11813, 63261, 649, 387, 264, 1380, 92247, 1364, 589, 30464, 323, 20336, 311, 387, 27167, 927, 279, 57463, 291, 1612, 278, 11813, 315, 279, 31409, 2547, 13, 39578, 11, 279, 10739, 481, 11813, 63261, 649, 387, 264, 1380, 92247, 20206, 30464, 323, 20336, 311, 387, 27167, 505, 2949, 264, 326, 28999, 315, 279, 31409, 2547, 13, 578, 20206, 649, 387, 30464, 323, 20336, 311, 13334, 1612, 750, 7953, 279, 57463, 291, 1612, 278, 11813, 315, 279, 31409, 2547, 11, 311, 69033, 60220, 315, 264, 6070, 555, 279, 31409, 2547, 11, 994, 304, 264, 27167, 2361, 13, 578, 20206, 649, 387, 14454, 505, 264, 10062, 2165, 3769, 627, 644, 18859, 449, 279, 28229, 11, 459, 58101, 649, 387, 3984, 520, 279, 1612, 278, 842, 315, 279, 2547, 13, 39578, 11, 832, 477, 810, 1469, 531, 1439, 649, 387, 3984, 304, 264, 1612, 278, 842, 13651, 315, 264, 32617, 543, 315, 279, 2547, 627, 791, 17543, 649, 387, 14454, 520, 3325, 304, 961, 505, 832, 315, 264, 6211, 65196, 46964, 323, 264, 25468, 9699, 13, 39578, 11, 59780, 10062, 2165, 7384, 315, 14343, 8333, 11, 25152, 323, 39665, 649, 387, 1511, 13, 763, 18859, 449, 279, 28229, 11, 279, 17543, 649, 387, 14454, 520, 3325, 304, 961, 555, 21120, 14713, 627, 791, 31409, 2547, 649, 387, 904, 3160, 5995, 13, 763, 18859, 449, 832, 13189, 11, 279, 3160, 374, 922, 220, 508, 2960, 55336, 13, 1556, 16335, 23899, 315, 279, 31409, 2547, 649, 387, 904, 1404, 5995, 13, 763, 18859, 449, 832, 13189, 11, 279, 23899, 374, 922, 220, 17, 9653, 627, 791, 17543, 649, 387, 20336, 1778, 430, 11, 304, 264, 27167, 390, 1659, 11, 264, 2430, 11, 17303, 1380, 4550, 311, 264, 68102, 8183, 34366, 11, 374, 264, 7340, 315, 922, 8223, 3115, 430, 315, 264, 2430, 304, 264, 29368, 390, 1659, 11, 17303, 1380, 4550, 311, 279, 68102, 8183, 34366, 627, 791, 31409, 2547, 649, 387, 3984, 449, 264, 57463, 291, 842, 7479, 99410, 520, 922, 220, 1758, 12628, 449, 5201, 311, 279, 68102, 8183, 315, 279, 31409, 2547, 627, 32, 3790, 649, 387, 3984, 304, 3717, 449, 279, 3917, 24198, 11, 311, 28696, 34786, 34366, 627, 644, 18859, 449, 264, 4726, 13189, 315, 279, 28229, 11, 264, 1749, 315, 73300, 287, 264, 42902, 2942, 374, 3984, 11, 46338, 279, 7504, 315, 39398, 264, 2547, 1555, 459, 57056, 7147, 315, 264, 8893, 11, 39398, 279, 2547, 1555, 264, 7147, 315, 279, 42902, 2942, 11, 25689, 1113, 8970, 505, 279, 42902, 2942, 11, 61417, 264, 1176, 17543, 13651, 2949, 279, 42902, 2942, 11, 311, 16988, 459, 9358, 7479, 315, 279, 42902, 2942, 11, 323, 73300, 287, 279, 42902, 2942, 627, 644, 18859, 449, 279, 28229, 11, 279, 1749, 649, 4726, 2997, 279, 3094, 315, 61417, 264, 2132, 17543, 13651, 4994, 279, 42902, 2942, 311, 16988, 459, 16335, 7479, 315, 279, 42902, 2942, 627, 644, 18859, 449, 2103, 2500, 13189, 315, 279, 28229, 11, 264, 34933, 14473, 369, 24301, 277, 84667, 16346, 374, 3984, 11, 902, 374, 30464, 323, 20336, 311, 25689, 349, 323, 73300, 264, 19754, 2067, 21473, 11, 279, 14473, 3515, 3445, 369, 25689, 1113, 8970, 505, 264, 19754, 2067, 21473, 11, 323, 3445, 369, 23387, 323, 73300, 287, 279, 19754, 2067, 21473, 627, 644, 18859, 449, 2103, 264, 4726, 13189, 315, 279, 28229, 11, 264, 34933, 14473, 649, 387, 28648, 555, 264, 1920, 46338, 279, 7504, 315, 8405, 264, 15286, 1299, 31409, 449, 264, 326, 28999, 33459, 9139, 774, 1458, 11, 98423, 264, 10739, 481, 17543, 11, 323, 39398, 279, 10739, 481, 17543, 11, 304, 264, 9038, 34575, 29368, 390, 1659, 11, 1139, 279, 15286, 1299, 31409, 13, 578, 17543, 649, 387, 14454, 505, 264, 10269, 25468, 9699, 5708, 3769, 13, 578, 3094, 315, 98423, 649, 387, 10887, 555, 20314, 32643, 98423, 477, 21120, 98423, 11, 369, 3187, 627, 2181, 374, 311, 387, 16365, 430, 2225, 279, 88931, 4689, 4096, 323, 279, 2768, 11944, 4096, 527, 77381, 323, 527, 539, 10825, 311, 387, 33994, 627, 6507, 13, 220, 4370, 374, 264, 3185, 1684, 315, 264, 1612, 278, 842, 13651, 315, 279, 34933, 25689, 859, 5621, 55866, 315, 38699, 13, 220, 4331, 11, 3515, 1612, 278, 10739, 481, 45667, 35831, 20392, 5540, 323, 22267, 2931, 10739, 481, 550, 647, 35831, 20392, 5540, 11, 449, 682, 5540, 304, 264, 27167, 6683, 627, 9032, 690, 1457, 387, 1903, 304, 7872, 311, 279, 3118, 15236, 75653, 315, 279, 28229, 11, 10507, 315, 902, 527, 36762, 304, 279, 24442, 38940, 627, 644, 18859, 449, 832, 13189, 315, 279, 28229, 11, 264, 34933, 25689, 859, 5621, 55866, 374, 3984, 3515, 279, 8824, 311, 25689, 349, 323, 26418, 264, 14512, 14454, 28592, 11, 439, 1664, 439, 73300, 279, 19754, 2067, 21473, 13, 763, 18859, 449, 832, 13189, 11, 264, 31409, 315, 2753, 1109, 220, 17, 13, 20, 9653, 374, 11784, 1139, 279, 57056, 7147, 449, 264, 17676, 11813, 902, 649, 22710, 346, 279, 6930, 13, 578, 1890, 31409, 11813, 374, 3025, 311, 22710, 346, 279, 15962, 44518, 19754, 2067, 21473, 7147, 13, 578, 14329, 842, 311, 279, 31409, 11813, 649, 387, 3984, 449, 264, 19240, 311, 15866, 264, 6705, 85124, 477, 84878, 3756, 311, 1520, 311, 25689, 349, 279, 8970, 315, 279, 19754, 2067, 21473, 13, 9843, 279, 19754, 2067, 21473, 374, 94972, 315, 1202, 8970, 11, 279, 34933, 25689, 859, 5621, 55866, 596, 17543, 477, 84862, 17383, 649, 387, 27167, 627, 644, 18859, 449, 279, 28229, 11, 279, 1612, 278, 17543, 477, 84862, 17383, 649, 2997, 11, 369, 3187, 11, 5361, 50264, 36108, 5108, 704, 315, 279, 17676, 842, 315, 279, 31409, 11, 5361, 50264, 36108, 5108, 704, 315, 279, 31468, 3221, 279, 31409, 11813, 11, 459, 16335, 31468, 927, 279, 31409, 3515, 264, 6211, 65196, 46964, 9244, 12673, 311, 1403, 10548, 323, 994, 15753, 1523, 11, 279, 9244, 22204, 279, 6211, 315, 264, 938, 751, 668, 13, 40730, 389, 279, 24473, 8292, 11, 279, 31409, 11813, 649, 387, 6859, 520, 279, 842, 323, 994, 312, 55535, 29512, 649, 3719, 279, 6211, 315, 264, 6917, 13, 1442, 12974, 11, 264, 8821, 14473, 649, 387, 3984, 3515, 264, 31749, 9903, 11, 11784, 520, 279, 22267, 2931, 842, 315, 264, 31409, 2547, 13, 3277, 279, 8821, 14473, 374, 22306, 1555, 323, 7953, 264, 1612, 278, 842, 315, 279, 31409, 2547, 11, 433, 374, 27167, 11, 323, 279, 9903, 69589, 279, 4871, 315, 279, 19754, 2067, 21473, 7147, 627, 80245, 389, 279, 24473, 49497, 11, 3131, 420, 1612, 278, 17543, 13651, 374, 27167, 11, 279, 4459, 14473, 374, 50682, 3156, 279, 17676, 11813, 315, 279, 17543, 69589, 323, 27635, 311, 279, 4871, 315, 279, 19754, 2067, 21473, 7147, 32620, 13, 97295, 11, 264, 2132, 17543, 13651, 649, 387, 3984, 311, 16988, 279, 16335, 7479, 315, 279, 7147, 315, 279, 19754, 2067, 21473, 311, 28696, 264, 9966, 34477, 13, 578, 19754, 2067, 21473, 649, 1243, 387, 312, 55535, 477, 29905, 1534, 304, 904, 5216, 2085, 904, 39897, 425, 13, 9843, 279, 19754, 2067, 21473, 834, 2879, 505, 279, 26587, 374, 4686, 11, 279, 17543, 17383, 374, 3060, 312, 55535, 1139, 279, 14473, 477, 6062, 7833, 6901, 11, 8617, 28965, 1202, 20581, 505, 279, 19754, 2067, 21473, 7147, 13, 578, 14473, 690, 1243, 387, 50682, 505, 279, 19754, 2067, 21473, 7147, 627, 2181, 1288, 387, 10555, 430, 8051, 279, 7766, 315, 279, 3118, 28229, 527, 76824, 369, 523, 12747, 599, 72783, 16346, 11, 814, 649, 9610, 7162, 387, 9435, 311, 25689, 349, 11, 73300, 323, 5255, 70236, 1023, 42902, 36853, 11, 1778, 439, 279, 23152, 477, 72735, 62564, 11, 369, 3187, 13, 15903, 11, 7766, 304, 18859, 449, 279, 28229, 649, 387, 1511, 311, 37735, 1023, 39881, 2737, 36853, 11, 304, 5369, 311, 1884, 430, 527, 32302, 42902, 627, 41935, 304, 18859, 449, 279, 28229, 9610, 7162, 1520, 4384, 279, 8970, 505, 279, 2942, 449, 902, 433, 374, 1694, 1511, 11, 1778, 439, 279, 19754, 2067, 21473, 11, 2085, 39897, 425, 11, 323, 28696, 4228, 50087, 10194, 315, 279, 7147, 315, 279, 34366, 1606, 315, 4814, 315, 1612, 729, 2968, 315, 279, 2942, 7147, 374, 11293, 13, 578, 3917, 7766, 1101, 11810, 4228, 17065, 315, 279, 19754, 2067, 21473, 505, 279, 57056, 56429, 1555, 279, 37781, 321, 950, 2700, 4245, 311, 279, 29368, 1614, 315, 279, 2942, 13, 15903, 11, 9610, 7162, 11, 279, 2678, 1404, 315, 279, 3917, 24198, 30437, 477, 22472, 1156, 20450, 627, 2520, 279, 10096, 315, 16540, 323, 40134, 11, 323, 539, 20893, 11, 304, 18859, 449, 279, 28229, 11, 459, 77381, 49497, 315, 264, 34933, 25689, 859, 5621, 55866, 220, 1041, 374, 36762, 304, 38699, 50, 13, 220, 16, 12, 975, 13, 763, 18859, 449, 420, 3187, 11, 279, 34933, 25689, 859, 5621, 55866, 5764, 459, 9358, 31409, 3515, 264, 23899, 11, 369, 3187, 220, 16, 13, 20, 9653, 11, 323, 264, 31409, 2547, 220, 5894, 3515, 23899, 294, 16, 11, 369, 3187, 922, 220, 17, 9653, 11, 449, 264, 3160, 445, 16, 11, 369, 3187, 922, 220, 1049, 9653, 627, 2170, 36762, 304, 38699, 50, 13, 220, 806, 12, 975, 11, 902, 41468, 1005, 315, 279, 34933, 25689, 859, 5621, 55866, 315, 38699, 13, 220, 16, 11, 304, 60220, 11, 25689, 1113, 8970, 315, 323, 73300, 287, 264, 19754, 2067, 21473, 11, 15947, 11, 279, 25689, 859, 5621, 55866, 220, 1041, 649, 387, 35328, 6089, 927, 279, 19754, 2067, 21473, 220, 24606, 1243, 22306, 6089, 1555, 279, 6930, 315, 279, 57056, 7147, 220, 19146, 11, 1139, 279, 19754, 2067, 21473, 220, 24606, 11, 555, 35460, 315, 264, 57463, 291, 1612, 278, 11813, 220, 9263, 13, 362, 84878, 2592, 649, 387, 43770, 709, 311, 264, 27442, 220, 7322, 11, 1778, 439, 264, 445, 8977, 27442, 3984, 389, 279, 2547, 220, 5120, 11, 323, 279, 19754, 2067, 21473, 374, 25689, 660, 315, 1202, 8970, 220, 24242, 11, 1778, 439, 73394, 11, 505, 279, 326, 28999, 220, 22101, 34366, 11, 4669, 264, 1612, 278, 842, 98741, 58101, 220, 8878, 58179, 13, 578, 25015, 13587, 220, 4364, 649, 1243, 387, 11084, 311, 10739, 279, 17543, 220, 6860, 11, 902, 304, 279, 36762, 49497, 374, 304, 279, 1376, 315, 264, 36460, 449, 30777, 477, 3703, 1302, 220, 9335, 311, 16988, 477, 737, 2788, 1139, 279, 19754, 2067, 21473, 220, 24606, 11, 369, 38231, 34366, 13, 578, 34933, 25689, 859, 5621, 55866, 220, 1041, 374, 1243, 13541, 709, 6376, 279, 10631, 315, 279, 36460, 1139, 279, 19754, 2067, 21473, 34167, 13, 578, 34933, 25689, 859, 5621, 55866, 220, 1041, 649, 1243, 387, 13541, 709, 323, 279, 19754, 2067, 21473, 374, 9408, 311, 279, 12974, 2361, 13, 578, 2361, 38955, 17383, 220, 3965, 374, 9277, 2403, 279, 6930, 323, 16447, 11, 28592, 9482, 2518, 279, 19754, 2067, 21473, 304, 279, 2547, 56429, 10923, 990, 311, 387, 10887, 389, 433, 323, 2212, 433, 2085, 3515, 311, 312, 3571, 279, 19754, 2067, 21473, 35611, 627, 2170, 1888, 3970, 304, 279, 7872, 6325, 315, 38699, 50, 13, 220, 19, 323, 220, 20, 11, 459, 16335, 31468, 220, 9423, 374, 3984, 10219, 2265, 750, 4994, 315, 279, 31409, 2547, 220, 5894, 11, 323, 374, 12673, 311, 279, 22267, 2931, 842, 315, 279, 17543, 220, 6860, 11, 1418, 279, 1612, 278, 842, 315, 279, 17543, 220, 6860, 374, 12673, 311, 279, 31409, 2547, 13, 15483, 20581, 649, 387, 17427, 555, 26154, 30164, 1920, 11, 60022, 11, 1589, 6802, 287, 11, 22936, 5043, 18724, 11, 1008, 17082, 1924, 477, 2500, 14791, 15105, 11, 422, 12974, 627, 6507, 50, 13, 220, 21, 323, 220, 22, 527, 374, 459, 374, 24264, 7872, 6325, 315, 279, 1612, 278, 17543, 13651, 220, 6860, 315, 279, 34933, 25689, 859, 5621, 55866, 220, 1041, 11, 719, 449, 264, 6573, 11813, 220, 9413, 323, 1469, 531, 1439, 220, 10148, 369, 98741, 389, 264, 3185, 7479, 34366, 11, 6982, 304, 264, 29368, 3044, 323, 264, 27167, 3044, 11, 15947, 627, 644, 18859, 449, 264, 4726, 77381, 49497, 11, 439, 36762, 369, 3187, 11, 304, 38699, 50, 13, 220, 868, 12, 1313, 11, 264, 34933, 25689, 859, 5621, 55866, 220, 1049, 374, 3984, 449, 264, 31409, 2547, 220, 9870, 11, 264, 1612, 278, 17543, 220, 8273, 11, 264, 3790, 220, 8848, 11, 264, 22267, 2931, 27442, 220, 12112, 323, 264, 2361, 38955, 17383, 220, 3965, 13, 578, 31409, 2547, 220, 9870, 649, 617, 11, 304, 18859, 449, 832, 3187, 49497, 11, 264, 23899, 315, 922, 220, 16, 13, 20, 9653, 323, 264, 3160, 315, 1990, 922, 220, 3965, 9653, 323, 220, 1049, 9653, 627, 2170, 1888, 3970, 304, 38699, 50, 13, 220, 777, 12, 1313, 11, 902, 41468, 1005, 315, 279, 34933, 25689, 859, 5621, 55866, 315, 38699, 13, 220, 868, 11, 304, 60220, 11, 25689, 1113, 8970, 315, 323, 73300, 287, 264, 19754, 2067, 21473, 11, 15947, 11, 439, 449, 279, 3485, 51704, 49497, 11, 279, 25689, 859, 5621, 55866, 220, 1049, 649, 387, 35328, 927, 279, 19754, 2067, 21473, 220, 24606, 11, 323, 1243, 22306, 6089, 1555, 279, 57056, 7147, 220, 19146, 11, 1139, 279, 326, 28999, 220, 22101, 315, 279, 19754, 2067, 21473, 220, 24606, 13, 328, 2720, 649, 1243, 387, 43770, 709, 311, 279, 326, 8977, 27442, 220, 12112, 389, 279, 842, 34366, 11, 323, 279, 19754, 2067, 21473, 220, 24606, 374, 25689, 660, 315, 1202, 8970, 220, 24242, 11, 1778, 439, 73394, 13, 328, 2720, 649, 1243, 387, 6656, 1022, 323, 279, 17543, 220, 8273, 11084, 11, 439, 6982, 304, 38699, 13, 220, 1691, 11, 311, 29241, 264, 3254, 477, 5361, 31409, 10631, 320, 68, 1326, 2637, 4528, 311, 264, 90834, 9903, 570, 1666, 6982, 304, 38699, 13, 220, 1313, 11, 279, 34933, 25689, 859, 5621, 55866, 220, 1049, 374, 1243, 13541, 709, 6376, 279, 57267, 1139, 279, 9358, 7479, 315, 279, 7147, 315, 279, 19754, 2067, 21473, 220, 24606, 13, 5112, 11, 279, 34933, 25689, 859, 5621, 55866, 220, 1049, 374, 13541, 709, 323, 279, 19754, 2067, 21473, 374, 9408, 311, 279, 12974, 2361, 13, 578, 2361, 38955, 17383, 220, 3965, 374, 9277, 2403, 279, 6930, 323, 16447, 11, 28592, 9482, 2518, 279, 19754, 2067, 21473, 304, 279, 2547, 56429, 10923, 990, 311, 387, 864, 10365, 389, 433, 323, 2212, 433, 2085, 3515, 311, 35611, 312, 3571, 279, 19754, 2067, 21473, 220, 24606, 627, 6507, 50, 13, 220, 1419, 12, 2148, 1501, 5370, 6325, 459, 5217, 49497, 315, 264, 34933, 25689, 859, 5621, 55866, 304, 18859, 449, 279, 3118, 28229, 11, 3515, 264, 10739, 481, 36460, 35831, 17543, 220, 13679, 627, 1383, 1648, 315, 3187, 11, 279, 31409, 2547, 220, 5894, 374, 3984, 439, 264, 42902, 31409, 13, 763, 18859, 449, 832, 13189, 11, 279, 23899, 315, 279, 31409, 2547, 220, 5894, 649, 387, 922, 220, 17, 13, 16, 9653, 13, 763, 1005, 11, 279, 31409, 2547, 374, 22306, 1555, 279, 64772, 1234, 5419, 22695, 13, 578, 31409, 2547, 220, 5894, 374, 22306, 1139, 279, 19754, 2067, 21473, 220, 24606, 323, 56406, 527, 25689, 660, 1555, 279, 31409, 2547, 220, 5894, 13, 362, 31468, 220, 13679, 11, 902, 1253, 387, 14454, 505, 264, 15286, 1299, 3769, 11, 323, 1694, 5419, 311, 279, 31409, 2547, 220, 5894, 11, 374, 11084, 1612, 750, 311, 10739, 279, 9407, 481, 36460, 35831, 17543, 220, 13679, 11, 902, 374, 3611, 3366, 311, 279, 4156, 315, 279, 14019, 220, 18633, 13, 362, 31468, 220, 16522, 8640, 1555, 264, 326, 28999, 315, 279, 14019, 220, 18633, 11, 323, 374, 12673, 311, 279, 1612, 278, 13651, 315, 279, 17543, 36460, 220, 13679, 13, 1666, 1888, 3970, 304, 38699, 13, 220, 1544, 11, 264, 10683, 220, 12901, 374, 3984, 323, 374, 27528, 311, 279, 31468, 220, 16522, 11, 8617, 10683, 8441, 279, 17543, 36460, 220, 13679, 11, 1234, 24408, 9435, 9139, 11269, 13, 3277, 279, 17543, 36460, 220, 13679, 374, 11084, 7953, 279, 31409, 2547, 220, 5894, 11, 279, 24408, 315, 279, 10683, 220, 12901, 11384, 279, 36460, 311, 9407, 709, 311, 264, 3009, 13, 426, 2518, 315, 279, 17543, 36460, 220, 13679, 59381, 25703, 19779, 477, 3703, 1302, 220, 16546, 430, 9966, 279, 4871, 315, 279, 19754, 62564, 220, 24606, 627, 644, 1005, 11, 279, 5419, 6956, 527, 11383, 47862, 291, 4871, 279, 220, 17, 13, 16, 9653, 42902, 31409, 2547, 220, 5894, 13, 578, 31409, 2547, 220, 5894, 374, 1243, 22306, 1555, 279, 64772, 323, 1243, 1139, 279, 19754, 2067, 21473, 220, 24606, 13, 45406, 15462, 811, 220, 18634, 28696, 32145, 279, 12974, 24693, 6012, 315, 279, 17543, 36460, 220, 13679, 11, 323, 1101, 11810, 56406, 311, 387, 25689, 660, 3347, 279, 1612, 278, 11813, 315, 279, 17543, 36460, 220, 13679, 13, 9843, 279, 19754, 2067, 21473, 220, 24606, 374, 25689, 660, 11, 279, 17543, 36460, 220, 13679, 374, 11084, 1555, 279, 31409, 2547, 220, 5894, 11, 323, 1139, 279, 326, 28999, 220, 22101, 315, 279, 19754, 2067, 21473, 220, 24606, 13, 763, 18859, 449, 832, 13189, 11, 279, 17543, 36460, 220, 13679, 52956, 52046, 398, 11, 311, 264, 7340, 2430, 315, 922, 220, 845, 9653, 13, 763, 279, 36762, 49497, 11, 279, 3703, 1302, 220, 16546, 3663, 1612, 750, 11, 779, 430, 1070, 527, 912, 13116, 311, 2339, 389, 279, 31409, 2547, 220, 5894, 11, 994, 279, 36460, 220, 13679, 374, 15107, 1203, 1139, 279, 31409, 2547, 220, 5894, 627, 6153, 37027, 2949, 279, 326, 28999, 220, 22101, 315, 279, 19754, 2067, 21473, 220, 24606, 323, 24047, 315, 279, 17543, 220, 13679, 11, 279, 25689, 859, 5621, 55866, 649, 387, 55315, 1778, 439, 555, 12984, 477, 98280, 14807, 11, 311, 28696, 2680, 311, 279, 19754, 2067, 21473, 220, 24606, 13, 9843, 7108, 11, 279, 19754, 2067, 21473, 220, 24606, 374, 9277, 304, 264, 9145, 11, 369, 3187, 11, 323, 279, 17543, 36460, 220, 13679, 374, 312, 55535, 311, 4984, 279, 19754, 2067, 21473, 220, 24606, 505, 279, 25689, 859, 5621, 55866, 11, 902, 374, 1243, 7108, 505, 279, 8893, 627, 1271, 73300, 279, 17543, 36460, 220, 13679, 11, 279, 9358, 6678, 14019, 220, 18633, 374, 312, 55535, 13, 578, 19754, 2067, 21473, 374, 1243, 37779, 505, 279, 25689, 859, 5621, 55866, 13, 578, 17543, 36460, 220, 13679, 374, 1243, 6052, 311, 1202, 4113, 2361, 323, 279, 31409, 2547, 220, 5894, 374, 7108, 505, 279, 64772, 627, 644, 18859, 449, 279, 28229, 11, 279, 17543, 36460, 220, 13679, 374, 35105, 555, 904, 14791, 15105, 11, 311, 279, 9358, 14019, 220, 18633, 11, 1778, 439, 555, 60022, 11, 60877, 287, 477, 1589, 6802, 287, 13, 763, 18859, 449, 279, 28229, 11, 279, 31468, 220, 16522, 649, 387, 8599, 311, 279, 17543, 36460, 220, 13679, 555, 264, 67887, 3717, 11, 477, 1023, 14791, 15105, 627, 34160, 311, 279, 1579, 3392, 315, 5882, 323, 5938, 26800, 9277, 389, 279, 36460, 11, 3769, 2011, 387, 4183, 28178, 13, 23342, 5044, 95851, 477, 904, 14791, 7384, 649, 387, 1511, 13, 763, 18859, 449, 832, 13189, 11, 264, 1579, 8333, 25468, 9699, 46964, 374, 1511, 304, 272, 1503, 315, 15792, 5425, 22327, 82, 11, 311, 10519, 59623, 3770, 872, 22781, 458, 13693, 13, 763, 18859, 449, 279, 28229, 11, 220, 1114, 12, 22, 11079, 15534, 356, 25468, 9699, 449, 264, 1772, 30164, 8798, 2442, 35320, 311, 3044, 6969, 7467, 649, 387, 34716, 369, 420, 3851, 13, 763, 18859, 449, 279, 28229, 11, 1778, 264, 3769, 649, 617, 264, 22781, 458, 8333, 315, 13489, 220, 5154, 11, 931, 39126, 323, 74595, 367, 315, 220, 18, 4, 3685, 11, 449, 17832, 961, 50971, 2391, 8798, 2442, 35320, 13, 1442, 12974, 11, 264, 8381, 4135, 23143, 819, 323, 17876, 3428, 9499, 23360, 311, 5471, 40602, 4469, 8126, 1018, 45589, 649, 387, 1511, 311, 4148, 8798, 49104, 2391, 220, 7467, 8547, 435, 13, 1825, 3805, 61050, 4325, 2653, 6147, 627, 6507, 13, 220, 966, 374, 459, 374, 24264, 1684, 315, 264, 1612, 278, 17543, 220, 13679, 315, 264, 34933, 25689, 859, 5621, 55866, 3515, 264, 10739, 481, 36460, 6683, 11, 902, 374, 4528, 304, 1690, 43666, 311, 279, 49497, 36762, 304, 38699, 13, 220, 1419, 13, 578, 17543, 36460, 220, 14868, 44642, 1070, 1527, 304, 430, 433, 5764, 264, 73405, 315, 24997, 13931, 220, 14868, 264, 11, 220, 14868, 293, 11, 323, 5217, 44585, 15462, 811, 220, 21125, 11, 311, 12192, 8333, 1418, 28696, 264, 15062, 2349, 304, 390, 1659, 34366, 304, 1005, 13, 38699, 13, 220, 2148, 374, 264, 7872, 374, 24264, 1684, 315, 279, 1612, 278, 17543, 13651, 220, 14868, 315, 279, 34933, 25689, 859, 5621, 55866, 315, 38699, 13, 220, 966, 13, 763, 18859, 449, 832, 13189, 315, 279, 28229, 11, 279, 17543, 36460, 220, 13679, 323, 5255, 279, 17543, 36460, 19885, 220, 14868, 264, 11, 220, 14868, 293, 649, 387, 14454, 505, 264, 25468, 9699, 3769, 3515, 922, 264, 220, 15, 13, 6726, 17560, 5708, 26839, 627, 2409, 5905, 311, 38699, 50, 13, 220, 843, 12, 1958, 11, 2103, 2500, 49497, 315, 264, 34933, 25689, 859, 5621, 55866, 304, 18859, 449, 279, 3118, 28229, 374, 36762, 11, 3515, 264, 1612, 278, 17543, 220, 17048, 304, 264, 23851, 315, 279, 3485, 51704, 10739, 481, 36460, 14726, 13, 578, 1612, 278, 17543, 220, 17048, 5764, 52046, 398, 24050, 20735, 47620, 315, 3769, 220, 17048, 264, 11, 220, 17048, 293, 13, 362, 1925, 31409, 2547, 220, 17252, 374, 3984, 11, 3944, 34575, 9358, 311, 1023, 6956, 13, 362, 10739, 481, 11813, 63261, 220, 19038, 374, 1101, 3984, 13, 1666, 36762, 304, 38699, 13, 220, 843, 11, 279, 11813, 63261, 220, 19038, 374, 1618, 36762, 439, 264, 1364, 589, 902, 649, 387, 27167, 555, 63614, 20081, 10219, 2265, 14019, 1161, 705, 1778, 439, 832, 3984, 9038, 34575, 52046, 505, 279, 1925, 31409, 2547, 220, 17252, 13, 1666, 1888, 3970, 304, 38699, 13, 220, 1958, 11, 994, 264, 25633, 535, 5457, 374, 9435, 1612, 750, 389, 279, 20735, 47620, 220, 17048, 264, 11, 220, 17048, 293, 11, 814, 9407, 9038, 34575, 52046, 398, 11, 439, 449, 1023, 75653, 7633, 36881, 11, 4245, 311, 279, 6683, 34366, 323, 3769, 6727, 1070, 2000, 627, 6507, 50, 13, 220, 1758, 12, 1927, 41468, 264, 4726, 49497, 315, 264, 34933, 25689, 859, 5621, 55866, 304, 18859, 449, 279, 3118, 28229, 3515, 264, 1612, 278, 10739, 481, 17543, 220, 14033, 439, 264, 10739, 481, 36460, 11, 14454, 555, 3944, 34575, 4445, 13840, 315, 52046, 398, 24050, 17543, 19885, 220, 14033, 264, 11, 220, 14033, 293, 11, 902, 527, 8965, 45667, 35831, 304, 6683, 627, 644, 18859, 449, 279, 28229, 11, 279, 31409, 2547, 220, 18660, 649, 387, 20336, 439, 12974, 13, 763, 18859, 449, 832, 13189, 315, 279, 28229, 11, 279, 31409, 2547, 220, 18660, 706, 922, 264, 220, 17, 13, 16, 9653, 16335, 23899, 323, 220, 11057, 9653, 3160, 13, 362, 7296, 20206, 220, 23079, 649, 387, 3984, 369, 279, 1890, 2944, 439, 279, 1364, 589, 220, 19038, 315, 279, 3485, 51704, 49497, 11, 32125, 311, 69033, 70576, 278, 30988, 311, 279, 8893, 994, 279, 31409, 2547, 220, 5894, 374, 539, 37304, 323, 22815, 1694, 22306, 1555, 62690, 13, 763, 279, 6220, 2361, 36762, 304, 38699, 13, 220, 1758, 11, 264, 17676, 11813, 315, 279, 31409, 2547, 220, 18660, 374, 20858, 291, 555, 279, 20206, 220, 23079, 11, 902, 2289, 1612, 750, 3347, 279, 11813, 34366, 627, 1128, 3078, 989, 11, 311, 22710, 346, 264, 6070, 11, 279, 20206, 220, 23079, 374, 312, 55535, 555, 84060, 279, 36460, 220, 14033, 22267, 318, 750, 13, 328, 2720, 9435, 311, 264, 8792, 326, 28999, 6276, 369, 98741, 315, 8970, 1555, 279, 326, 28999, 11, 2212, 279, 20206, 220, 23079, 13, 39578, 477, 37938, 11, 15962, 649, 387, 25689, 660, 1555, 279, 320, 35124, 8, 44585, 15462, 811, 304, 279, 31409, 2547, 220, 18660, 3984, 369, 279, 24050, 17543, 19885, 220, 14033, 264, 11, 220, 14033, 293, 13, 1666, 5682, 660, 8970, 649, 387, 11953, 1555, 459, 9358, 14019, 323, 311, 279, 8599, 84878, 1887, 627, 31082, 11, 369, 24047, 315, 279, 17543, 19885, 220, 14033, 264, 11, 220, 14033, 293, 11, 279, 36460, 220, 14033, 374, 28932, 1612, 750, 11, 902, 1101, 3135, 304, 279, 20206, 220, 23079, 1694, 9277, 304, 279, 7296, 2361, 13, 763, 279, 36762, 49497, 11, 23204, 14454, 555, 389, 20081, 14535, 315, 279, 36460, 220, 14033, 16988, 20081, 16087, 304, 264, 17919, 2449, 11, 477, 1367, 8363, 220, 22266, 323, 264, 4585, 261, 11813, 220, 21975, 13, 578, 1367, 8363, 220, 22266, 323, 4585, 261, 11813, 220, 21975, 649, 387, 82161, 311, 20081, 9358, 323, 16335, 34083, 11, 1778, 439, 1180, 46262, 220, 22642, 11, 430, 649, 387, 3351, 3944, 34575, 8844, 311, 832, 2500, 11, 311, 7431, 2585, 315, 24047, 315, 279, 36460, 220, 14033, 627, 644, 1005, 11, 459, 9358, 14019, 320, 1962, 36762, 8, 8599, 311, 279, 1367, 8363, 220, 22266, 11, 649, 387, 11084, 1612, 750, 311, 10739, 279, 1612, 278, 1099, 33361, 19885, 220, 14033, 293, 11, 2949, 279, 19754, 2067, 21473, 13, 578, 4459, 25689, 859, 5621, 55866, 649, 1243, 387, 312, 55535, 22267, 318, 750, 3156, 279, 743, 315, 1612, 278, 17543, 19885, 220, 14033, 293, 527, 17045, 449, 459, 9358, 7479, 315, 279, 19754, 2067, 21473, 7147, 13, 578, 16335, 14019, 220, 22642, 11, 8599, 311, 279, 4585, 261, 220, 21975, 649, 1243, 387, 11084, 311, 1825, 279, 22267, 2931, 1099, 33361, 19885, 220, 14033, 264, 11, 311, 9407, 389, 279, 4994, 315, 279, 19754, 2067, 21473, 11, 28974, 287, 279, 7147, 315, 279, 19754, 2067, 21473, 1070, 42967, 627, 45600, 11, 279, 25689, 660, 19754, 2067, 21473, 374, 52123, 5762, 555, 279, 25689, 859, 5621, 55866, 323, 374, 3025, 311, 387, 55315, 555, 279, 46098, 1418, 433, 374, 75050, 291, 505, 21583, 31080, 323, 39881, 13, 763, 18859, 449, 832, 13189, 11, 279, 19754, 2067, 21473, 649, 1243, 387, 9277, 304, 459, 842, 84667, 4526, 9145, 323, 2225, 9358, 323, 16335, 34083, 649, 387, 312, 55535, 311, 6958, 279, 17543, 19885, 220, 14033, 264, 11, 220, 14033, 293, 4871, 315, 279, 31409, 2547, 220, 18660, 11, 311, 4984, 279, 19754, 2067, 21473, 13, 3804, 39742, 11, 279, 25689, 859, 5621, 55866, 649, 1243, 387, 7108, 505, 279, 64772, 323, 44310, 627, 2170, 449, 1023, 75653, 743, 13544, 36881, 11, 279, 36762, 6683, 315, 459, 25689, 859, 5621, 55866, 649, 387, 18751, 449, 13777, 7633, 36881, 627, 2170, 449, 1023, 75653, 7633, 36881, 11, 279, 17543, 19885, 220, 14033, 264, 11, 220, 14033, 293, 13334, 1555, 20081, 1469, 531, 1439, 11, 902, 527, 14454, 11, 304, 420, 1162, 11, 304, 279, 31409, 2547, 220, 18660, 555, 264, 14791, 15105, 11, 1778, 439, 555, 21120, 14713, 627, 644, 18859, 449, 832, 13189, 11, 279, 17543, 36460, 19885, 220, 14033, 264, 11, 220, 14033, 293, 649, 387, 14454, 315, 264, 220, 15, 13, 8504, 17560, 7716, 875, 11, 2539, 2653, 25468, 9699, 11, 477, 2500, 14791, 3769, 13, 578, 49872, 36460, 220, 14033, 649, 387, 14454, 505, 264, 3254, 477, 264, 73405, 315, 24997, 13931, 627, 73741, 5217, 10778, 75653, 315, 25689, 859, 5621, 2193, 1105, 304, 18859, 449, 279, 28229, 527, 3984, 11, 439, 11263, 627, 6507, 13, 220, 1806, 374, 459, 374, 24264, 1684, 315, 264, 1612, 278, 842, 13651, 315, 264, 4726, 49497, 315, 264, 34933, 25689, 859, 5621, 55866, 220, 7007, 304, 18859, 449, 279, 28229, 3515, 10739, 481, 45667, 5540, 220, 21112, 264, 11, 220, 21112, 293, 449, 3703, 1302, 14454, 1070, 263, 311, 28696, 20392, 449, 264, 42902, 6070, 13, 24987, 323, 5784, 315, 279, 25689, 859, 5621, 55866, 220, 7007, 374, 304, 10494, 449, 1023, 75653, 7633, 36881, 11, 1778, 439, 449, 279, 49497, 315, 38699, 50, 13, 220, 1758, 323, 220, 1927, 627, 6507, 13, 220, 1987, 374, 459, 374, 24264, 1684, 315, 264, 1612, 278, 842, 13651, 315, 2103, 264, 4726, 49497, 315, 264, 34933, 25689, 859, 5621, 55866, 304, 18859, 449, 279, 28229, 3515, 264, 1612, 278, 17543, 2449, 220, 19899, 14454, 555, 10739, 481, 45667, 5540, 220, 19899, 264, 369, 61417, 20081, 74595, 660, 3703, 1302, 220, 19899, 293, 627, 6507, 13, 220, 2137, 374, 459, 374, 24264, 1684, 315, 264, 1612, 278, 842, 13651, 315, 2103, 264, 4726, 49497, 315, 264, 34933, 25689, 859, 5621, 55866, 304, 18859, 449, 279, 28229, 11, 3515, 459, 98280, 11, 9038, 34575, 10739, 481, 9244, 17543, 220, 21251, 11, 10739, 481, 505, 279, 31409, 2547, 220, 19306, 34366, 13, 67392, 315, 279, 17543, 220, 21251, 649, 387, 89589, 555, 8405, 1612, 750, 86855, 5457, 311, 459, 1180, 54643, 21236, 11, 8599, 311, 264, 22267, 2931, 842, 315, 279, 9244, 17543, 220, 21251, 11, 323, 10219, 2265, 750, 26655, 2949, 279, 326, 28999, 315, 279, 31409, 2547, 220, 19306, 627, 6507, 13, 220, 1272, 374, 459, 374, 24264, 1684, 315, 264, 1612, 278, 842, 13651, 315, 2500, 49497, 315, 264, 34933, 25689, 859, 5621, 55866, 304, 18859, 449, 279, 28229, 11, 3515, 264, 11591, 950, 11, 9038, 34575, 10739, 481, 9244, 17543, 220, 6849, 15, 13, 362, 1612, 278, 13651, 315, 279, 11591, 950, 9244, 17543, 220, 6849, 15, 374, 27528, 311, 264, 1925, 31409, 2547, 220, 6889, 15, 11, 1418, 264, 22267, 2931, 842, 13651, 315, 279, 11591, 950, 9244, 17543, 220, 6849, 15, 374, 27528, 311, 264, 10219, 2265, 750, 16335, 1180, 54643, 14019, 220, 6889, 18, 13, 15636, 11, 8844, 7351, 1990, 279, 1925, 31409, 2547, 220, 6889, 15, 323, 279, 16335, 14019, 220, 6889, 18, 11, 2737, 12984, 323, 5255, 14807, 11, 649, 2515, 24047, 315, 279, 17543, 220, 6849, 15, 13, 578, 1612, 278, 842, 220, 6889, 17, 649, 387, 6573, 11, 477, 1825, 11, 477, 649, 2997, 1469, 531, 1439, 369, 98741, 389, 3185, 27529, 34366, 627, 6507, 13, 220, 3174, 374, 459, 374, 24264, 1684, 315, 264, 1612, 278, 842, 13651, 315, 2500, 49497, 315, 264, 34933, 25689, 859, 5621, 55866, 304, 18859, 449, 279, 28229, 11, 3515, 264, 3254, 97307, 1612, 278, 17543, 2449, 220, 8011, 15, 11953, 555, 264, 31409, 2547, 220, 8190, 15, 13, 578, 97307, 1612, 278, 17543, 2449, 220, 8011, 15, 649, 387, 70954, 4669, 832, 477, 810, 12006, 14454, 2949, 279, 31409, 2547, 220, 8190, 15, 11, 323, 20336, 323, 30464, 311, 387, 1672, 1386, 22851, 555, 264, 14812, 11, 1778, 439, 99107, 11, 477, 264, 6962, 11, 1778, 439, 31749, 3805, 477, 12782, 40589, 13, 1666, 449, 904, 315, 279, 75653, 7633, 36881, 11, 279, 1612, 278, 842, 220, 6889, 17, 649, 387, 6573, 11, 477, 1825, 11, 477, 649, 2997, 1469, 531, 1439, 369, 98741, 389, 3185, 27529, 34366, 627, 6507, 13, 220, 2983, 374, 459, 374, 24264, 1684, 315, 264, 1612, 278, 842, 13651, 315, 264, 4726, 49497, 315, 264, 34933, 25689, 859, 5621, 55866, 304, 18859, 449, 279, 28229, 11, 3515, 264, 73405, 315, 97307, 1612, 278, 17543, 5540, 220, 8874, 15, 264, 11, 220, 8874, 15, 293, 11, 3984, 389, 264, 31409, 2547, 220, 4513, 15, 11, 369, 15947, 23387, 9358, 323, 16335, 27529, 315, 264, 42902, 2942, 11, 1778, 439, 264, 279, 19754, 2067, 21473, 13, 578, 97307, 17543, 5540, 220, 8874, 15, 649, 387, 70954, 4669, 832, 477, 810, 12006, 14454, 2949, 279, 31409, 2547, 220, 4513, 15, 11, 323, 20336, 323, 30464, 311, 387, 1672, 1386, 22851, 555, 264, 14812, 11, 1778, 439, 99107, 11, 477, 264, 6962, 11, 1778, 439, 31749, 3805, 477, 12782, 40589, 13, 1666, 449, 904, 315, 279, 75653, 7633, 36881, 11, 279, 1612, 278, 842, 220, 6889, 17, 649, 387, 6573, 11, 477, 1825, 11, 477, 649, 2997, 1469, 531, 1439, 369, 98741, 389, 3185, 27529, 34366, 627, 6507, 50, 13, 220, 3391, 12, 2166, 41468, 5370, 6325, 315, 2103, 264, 4726, 49497, 315, 264, 34933, 25689, 859, 5621, 55866, 304, 18859, 449, 279, 3118, 28229, 3515, 264, 1612, 278, 17543, 220, 9565, 15, 449, 3944, 34575, 4445, 13840, 315, 52046, 398, 24050, 17543, 19885, 220, 9565, 15, 264, 11, 220, 9565, 15, 293, 11, 14454, 315, 20735, 47620, 315, 3769, 11, 369, 23387, 9358, 323, 16335, 7147, 27529, 315, 264, 42902, 2942, 11, 15947, 11, 439, 7633, 3485, 304, 3717, 449, 1023, 75653, 13, 763, 18859, 449, 420, 49497, 11, 264, 3351, 481, 9358, 31468, 220, 9423, 16, 374, 3984, 927, 279, 31409, 2547, 220, 9423, 15, 11, 927, 902, 264, 53735, 29539, 31468, 220, 9423, 18, 374, 3984, 11, 927, 902, 264, 3351, 481, 16335, 31468, 220, 9423, 22, 374, 3984, 13, 9062, 315, 279, 3351, 481, 31468, 82, 374, 687, 69855, 11, 449, 5201, 311, 279, 53735, 1925, 31409, 2547, 220, 9423, 15, 323, 29539, 31468, 220, 9423, 18, 13, 763, 18859, 449, 279, 28229, 11, 1612, 750, 86855, 25633, 535, 8603, 1121, 304, 57936, 52046, 14800, 315, 279, 20081, 17543, 19885, 220, 9565, 15, 264, 11, 220, 9565, 15, 293, 13, 1666, 449, 904, 315, 279, 75653, 7633, 36881, 11, 1469, 531, 1439, 220, 9423, 22, 369, 98741, 649, 387, 3984, 389, 3185, 27529, 315, 279, 31409, 2547, 220, 9423, 15, 627, 6507, 13, 220, 2491, 374, 264, 3185, 1684, 315, 264, 1612, 278, 842, 13651, 220, 8929, 15, 264, 315, 2103, 264, 4726, 49497, 315, 264, 34933, 25689, 859, 5621, 55866, 304, 18859, 449, 279, 28229, 11, 3515, 459, 9407, 481, 11546, 1612, 278, 17543, 5540, 627, 6507, 13, 220, 2491, 374, 264, 3185, 1684, 315, 264, 1612, 278, 842, 13651, 315, 2103, 264, 4726, 49497, 315, 264, 34933, 25689, 859, 5621, 55866, 304, 18859, 449, 279, 28229, 11, 3515, 1403, 9407, 481, 11546, 1612, 278, 17543, 5540, 220, 8929, 15, 264, 11, 220, 8929, 15, 293, 11, 449, 279, 1612, 60301, 17543, 220, 8929, 15, 264, 304, 264, 27167, 11, 17626, 390, 1659, 13, 38699, 13, 220, 1135, 374, 264, 3185, 1684, 315, 279, 34933, 25689, 859, 315, 38699, 13, 220, 2491, 11, 449, 2225, 17543, 5540, 27167, 11, 28974, 287, 264, 7147, 315, 279, 19754, 2067, 21473, 1070, 42967, 13, 1666, 449, 1023, 75653, 11, 279, 11546, 1612, 278, 17543, 5540, 220, 8929, 15, 264, 11, 220, 8929, 15, 293, 527, 8599, 311, 91966, 532, 5540, 311, 11810, 34786, 34366, 627, 6507, 13, 220, 3971, 374, 264, 3185, 1684, 315, 264, 1612, 278, 842, 13651, 315, 279, 34933, 25689, 859, 5621, 55866, 3515, 22267, 2931, 323, 1612, 278, 550, 647, 35831, 17543, 5540, 220, 10559, 15, 264, 11, 220, 10559, 15, 293, 11, 449, 1193, 1612, 278, 17543, 5540, 220, 10559, 15, 264, 27167, 13, 38699, 13, 220, 4103, 374, 264, 3185, 1684, 315, 279, 34933, 25689, 859, 5621, 55866, 315, 38699, 13, 220, 3971, 449, 2225, 9358, 320, 12489, 278, 8, 220, 10559, 15, 264, 323, 16335, 320, 42598, 2931, 8, 220, 10559, 15, 293, 17543, 5540, 27167, 13, 1556, 16335, 1364, 589, 220, 9800, 22, 374, 3984, 311, 28696, 357, 24060, 315, 279, 17543, 5540, 994, 312, 27523, 374, 8308, 627, 6507, 13, 220, 4331, 374, 264, 3185, 1684, 315, 264, 1612, 278, 842, 13651, 315, 459, 5217, 49497, 315, 264, 34933, 25689, 859, 5621, 55866, 304, 18859, 449, 279, 28229, 11, 3515, 1612, 278, 10739, 481, 45667, 35831, 20392, 5540, 220, 10513, 15, 264, 11, 323, 22267, 2931, 10739, 481, 550, 647, 35831, 20392, 5540, 220, 10513, 15, 293, 11, 30464, 323, 20336, 369, 10739, 481, 505, 4279, 16087, 3984, 304, 279, 31409, 2547, 220, 9892, 15, 13, 38699, 13, 220, 4370, 374, 264, 3185, 1684, 94012, 682, 17543, 5540, 304, 264, 27167, 6683, 11, 28592, 28974, 287, 279, 7147, 315, 279, 19754, 2067, 21473, 220, 24606, 1070, 42967, 627, 2181, 690, 387, 10186, 311, 1884, 26611, 304, 279, 1989, 430, 5370, 29882, 323, 27339, 649, 387, 1903, 304, 279, 3756, 323, 1749, 315, 279, 3118, 28229, 2085, 81573, 505, 279, 9090, 477, 7036, 315, 279, 28229, 13, 1102, 374, 8104, 50178, 430, 5540, 315, 832, 49497, 7633, 36881, 649, 9610, 7162, 387, 9435, 311, 904, 49497, 315, 7766, 304, 18859, 449, 279, 28229, 11, 1524, 422, 1778, 4519, 527, 539, 21650, 7633, 304, 3717, 9139, 98909, 11, 7389, 1778, 4668, 1288, 387, 53579, 14079, 477, 6062, 53924, 449, 1023, 4519, 315, 1778, 49497, 13, 14636, 11, 433, 374, 10825, 430, 279, 3118, 28229, 2997, 29882, 323, 27339, 430, 527, 2949, 279, 7036, 315, 279, 52287, 8349, 323, 872, 86106, 627, 2940, 258, 279, 1612, 278, 842, 315, 279, 17543, 374, 12673, 311, 459, 16335, 7479, 315, 279, 31409, 2547, 1778, 430, 279, 57463, 291, 1612, 278, 11813, 2289, 7953, 279, 1612, 278, 842, 315, 279, 17543, 304, 2225, 279, 29368, 323, 279, 17626, 27167, 33483, 627, 17, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 42418, 279, 58101, 304, 279, 31409, 2547, 374, 2040, 8046, 26655, 1990, 279, 22267, 2931, 323, 1612, 278, 10548, 315, 279, 17543, 304, 2225, 279, 29368, 323, 17626, 27167, 33483, 627, 18, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 42418, 279, 1612, 278, 842, 315, 279, 17543, 374, 49704, 38745, 8521, 8844, 311, 459, 4994, 7479, 315, 279, 31409, 2547, 627, 19, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 42418, 279, 17543, 374, 264, 10739, 481, 36460, 6070, 627, 20, 13, 578, 34933, 14473, 315, 3802, 220, 19, 11, 42418, 279, 36460, 6070, 374, 10683, 1481, 72, 1503, 1778, 430, 279, 36460, 6070, 374, 27167, 555, 24408, 3984, 304, 264, 10683, 994, 279, 36460, 6070, 2289, 7953, 279, 31409, 2547, 555, 264, 87010, 6138, 627, 21, 13, 578, 34933, 14473, 315, 3802, 220, 19, 11, 42418, 279, 36460, 6070, 5764, 520, 3325, 832, 3703, 65, 20336, 311, 13334, 505, 279, 36460, 6070, 994, 279, 36460, 6070, 374, 304, 279, 27167, 6683, 627, 22, 13, 578, 34933, 14473, 315, 3802, 220, 21, 11, 42418, 3703, 65, 374, 1612, 750, 15910, 311, 28696, 312, 4302, 290, 315, 279, 36460, 6070, 1139, 264, 326, 28999, 315, 279, 31409, 2547, 627, 23, 13, 578, 34933, 14473, 315, 3802, 220, 21, 11, 42418, 279, 520, 3325, 832, 3703, 65, 374, 22267, 318, 750, 15910, 311, 28696, 20392, 34366, 449, 459, 9358, 7147, 315, 279, 42902, 2942, 627, 24, 13, 578, 34933, 14473, 315, 3802, 220, 23, 11, 42418, 279, 36460, 374, 20336, 779, 430, 279, 520, 3325, 832, 3703, 65, 374, 32302, 15638, 311, 279, 31409, 2547, 323, 14932, 19885, 315, 279, 36460, 304, 279, 29368, 6683, 627, 605, 13, 578, 34933, 14473, 315, 3802, 220, 19, 11, 42418, 279, 36460, 6070, 374, 3984, 449, 520, 3325, 832, 44585, 478, 2214, 311, 28696, 58218, 34786, 315, 279, 36460, 627, 806, 13, 578, 34933, 14473, 315, 3802, 220, 19, 11, 42418, 279, 36460, 6070, 374, 3984, 449, 264, 73405, 315, 14535, 11, 55443, 750, 28902, 922, 264, 68102, 8183, 315, 279, 34933, 14473, 627, 717, 13, 578, 34933, 14473, 315, 3802, 220, 19, 11, 42418, 279, 36460, 6070, 5764, 264, 73405, 315, 24997, 81947, 311, 11810, 25152, 315, 279, 36460, 627, 1032, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 42418, 279, 17543, 374, 264, 10739, 481, 9244, 6070, 627, 975, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 42418, 279, 17543, 5764, 264, 1612, 278, 17543, 13651, 323, 264, 22267, 2931, 17543, 13651, 30464, 323, 20336, 311, 16988, 9358, 323, 16335, 27529, 315, 279, 42902, 2942, 11, 15947, 627, 868, 13, 578, 34933, 14473, 315, 3802, 220, 975, 11, 42418, 279, 1612, 278, 17543, 13651, 323, 279, 22267, 2931, 17543, 13651, 527, 49704, 38745, 64928, 10980, 555, 264, 6138, 14343, 311, 11810, 20392, 315, 264, 7147, 315, 279, 42902, 2942, 627, 845, 13, 578, 34933, 14473, 315, 3802, 220, 975, 11, 42418, 279, 1612, 278, 17543, 13651, 323, 264, 22267, 2931, 17543, 13651, 527, 12984, 750, 4445, 505, 832, 2500, 555, 922, 220, 1954, 12628, 11, 449, 5201, 311, 264, 68102, 8183, 315, 279, 34933, 14473, 627, 1114, 13, 578, 34933, 14473, 315, 3802, 220, 975, 11, 42418, 279, 1612, 278, 17543, 13651, 323, 279, 22267, 2931, 17543, 13651, 527, 315, 32302, 279, 1890, 6683, 627, 972, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 4726, 46338, 264, 10739, 481, 11813, 63261, 311, 69033, 70576, 278, 11134, 555, 279, 57463, 291, 1612, 278, 11813, 315, 279, 31409, 2547, 627, 777, 13, 578, 34933, 14473, 315, 3802, 220, 972, 11, 42418, 279, 10739, 481, 11813, 63261, 374, 264, 1380, 92247, 1364, 589, 30464, 323, 20336, 311, 387, 27167, 927, 279, 57463, 291, 1612, 278, 11813, 315, 279, 31409, 2547, 627, 508, 13, 578, 34933, 14473, 315, 3802, 220, 972, 11, 42418, 279, 10739, 481, 11813, 63261, 374, 264, 1380, 92247, 20206, 30464, 323, 20336, 311, 387, 27167, 505, 2949, 264, 326, 28999, 315, 279, 31409, 2547, 627, 1691, 13, 578, 34933, 14473, 315, 3802, 220, 508, 11, 42418, 279, 20206, 374, 30464, 323, 20336, 311, 13334, 1612, 750, 7953, 279, 57463, 291, 1612, 278, 11813, 315, 279, 31409, 2547, 11, 311, 69033, 60220, 315, 264, 6070, 555, 279, 31409, 2547, 11, 994, 304, 264, 27167, 2361, 627, 1313, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 42418, 279, 58101, 374, 3984, 520, 279, 1612, 278, 842, 315, 279, 2547, 627, 1419, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 42418, 279, 58101, 374, 3984, 304, 264, 1612, 278, 842, 13651, 315, 264, 32617, 543, 315, 279, 2547, 627, 1187, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 42418, 279, 17543, 374, 14454, 520, 3325, 304, 961, 505, 832, 315, 264, 6211, 65196, 46964, 323, 264, 25468, 9699, 627, 914, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 994, 304, 279, 17543, 374, 14454, 520, 3325, 304, 961, 555, 21120, 14713, 627, 1627, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 42418, 459, 16335, 23899, 315, 279, 31409, 2547, 374, 922, 220, 17, 9653, 627, 1544, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 42418, 279, 17543, 374, 20336, 1778, 430, 11, 304, 279, 27167, 6683, 11, 264, 2430, 11, 17303, 1380, 4550, 311, 264, 68102, 8183, 34366, 11, 374, 264, 7340, 315, 922, 8223, 3115, 430, 315, 264, 2430, 304, 279, 29368, 6683, 11, 17303, 1380, 4550, 311, 279, 68102, 8183, 34366, 627, 1591, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 42418, 279, 31409, 2547, 374, 3984, 449, 264, 57463, 291, 842, 7479, 99410, 520, 922, 220, 868, 12628, 449, 5201, 311, 264, 68102, 8183, 315, 279, 31409, 2547, 627, 1682, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 4726, 46338, 264, 3790, 304, 3717, 9139, 98909, 11, 311, 28696, 34786, 315, 279, 34933, 14473, 627, 966, 13, 578, 34933, 14473, 315, 3802, 220, 16, 11, 42418, 279, 31409, 2547, 5764, 264, 3185, 7479, 3515, 264, 73405, 315, 1469, 531, 1439, 369, 98741, 627, 843, 13, 578, 1749, 315, 3802, 220, 2148, 11, 4726, 46338, 279, 3094, 315, 25, 61417, 264, 2132, 17543, 13651, 315, 279, 34933, 14473, 4994, 279, 42902, 2942, 311, 16988, 459, 16335, 7479, 315, 279, 42902, 2942, 627, 2940, 258, 279, 1612, 278, 842, 315, 279, 17543, 374, 12673, 311, 459, 16335, 7479, 315, 279, 31409, 1778, 430, 279, 57463, 291, 1612, 278, 11813, 2289, 7953, 279, 1612, 278, 842, 315, 279, 17543, 304, 2225, 279, 29368, 323, 279, 17626, 27167, 33483, 627, 2940, 258, 279, 34739, 279, 10739, 481, 17543, 5764, 72908, 264, 1612, 278, 842, 315, 279, 17543, 311, 459, 16335, 7479, 315, 279, 31409, 1778, 430, 279, 57463, 291, 1612, 278, 11813, 2289, 7953, 279, 1612, 278, 842, 315, 279, 17543, 304, 2225, 279, 9038, 34575, 29368, 323, 279, 17626, 27167, 33483, 627, 34, 2784, 261, 2065, 11, 27685, 4441, 11, 5186, 13, 220, 20, 11, 220, 679, 16, 320, 18, 6959, 8, 1795, 1129, 268, 34466, 2726, 26583, 11547, 2784, 261, 2065, 627, 34746, 7694, 8423, 323, 34991, 60767, 369, 393, 1182, 14, 2078, 679, 15, 14, 25210, 18770, 11136, 3297, 220, 24, 11, 220, 679, 16, 627, 34746, 7694, 8423, 369, 393, 1182, 14, 2078, 2589, 14, 24495, 6069, 627, 34746, 7694, 8423, 369, 393, 1182, 14, 2078, 2589, 14, 21474, 1987, 627, 24581, 64631, 25847, 921, 12747, 599, 72783, 11, 45546, 12609, 11, 7188, 16867, 13235, 5955, 627, 1600, 14590, 10943, 15, 51, 18, 320, 268, 8, 220, 679, 17, 12, 2839, 12, 868, 842, 84667, 2942, 312, 27523, 1887, 323, 1749, 315, 1005, 34366, 13, 128000, 4897, 596, 1148, 584, 2351, 709, 2403, 11, 430, 433, 596, 26617, 439, 520, 38586, 430, 499, 649, 636, 76203, 304, 6186, 439, 16475, 311, 264, 65396, 13, 2876, 682, 5873, 374, 1695, 13, 7570, 422, 279, 6186, 73700, 36263, 10619, 11, 1524, 422, 499, 617, 264, 2216, 1695, 73700, 430, 596, 17808, 11, 358, 2103, 1440, 499, 6656, 1523, 1023, 2574, 369, 430, 311, 3621, 627, 4897, 596, 2555, 358, 649, 656, 374, 1456, 311, 1304, 279, 5130, 11, 439, 1790, 439, 358, 649, 11, 8881, 264, 2763, 315, 279, 5933, 81821, 315, 420, 961, 315, 279, 1917, 323, 8881, 1511, 311, 387, 279, 1648, 499, 1053, 8343, 1603, 499, 1436, 41868, 627, 3112, 8101, 1148, 30, 3011, 596, 1148, 58441, 14135, 374, 11, 3339, 279, 24322, 3280, 1566, 682, 1060, 1317, 13, 3092, 4359, 11, 279, 1455, 5016, 13560, 584, 617, 374, 37250, 11, 433, 1288, 387, 2555, 430, 422, 499, 2216, 48883, 1148, 37250, 374, 682, 922, 11, 499, 1053, 2216, 3619, 3691, 13, 2030, 1274, 1781, 433, 596, 922, 2840, 973, 88, 11, 439, 16475, 311, 9615, 36237, 287, 420, 701, 2294, 24322, 25960, 11, 323, 1457, 2231, 6392, 709, 779, 499, 1541, 956, 6917, 588, 927, 279, 12688, 13, 2030, 1274, 1541, 956, 1781, 922, 433, 430, 1648, 2345, 6881, 11, 433, 596, 279, 7314, 315, 279, 12459, 3280, 627, 26840, 7185, 55080, 656, 7655, 430, 3515, 682, 15657, 2561, 682, 279, 892, 649, 1304, 12459, 2753, 7245, 56912, 13, 1789, 3187, 11, 358, 2646, 8343, 7878, 41776, 704, 315, 1450, 1981, 11945, 369, 1475, 4498, 11, 994, 358, 281, 9933, 389, 279, 40715, 5192, 285, 1725, 505, 25166, 6406, 627, 24205, 11, 358, 5895, 922, 279, 15325, 488, 315, 12459, 3280, 750, 323, 10917, 3691, 709, 369, 12688, 13, 3161, 264, 2539, 892, 2361, 304, 67671, 11, 264, 3318, 32080, 11, 323, 264, 52335, 11, 358, 1781, 358, 2846, 3815, 1664, 311, 636, 4205, 36433, 389, 279, 2007, 1455, 2919, 13, 19418, 358, 3021, 311, 649, 323, 21813, 323, 2231, 709, 1884, 41613, 505, 856, 13863, 11, 779, 430, 358, 617, 36433, 91070, 323, 2254, 60399, 682, 12688, 30, 56647, 53676, 7344, 54108, 358, 3358, 636, 1070, 13, 2030, 304, 279, 33953, 11, 358, 649, 956, 11471, 430, 358, 3358, 4017, 7182, 311, 3789, 24822, 3156, 1828, 3297, 304, 279, 836, 315, 12459, 24392, 627, 40, 2846, 539, 5605, 420, 311, 18046, 50117, 596, 1486, 11, 1606, 358, 16917, 4510, 304, 12899, 279, 2254, 37500, 13, 358, 4265, 3021, 311, 11, 4869, 11, 15596, 279, 6677, 5070, 315, 5127, 1618, 4235, 5269, 9503, 584, 3974, 14201, 2915, 304, 264, 892, 1824, 6236, 2454, 1917, 5380, 40, 574, 1120, 7556, 922, 420, 3432, 389, 2500, 4580, 13, 358, 1781, 779, 1690, 1274, 1781, 315, 9498, 12459, 439, 459, 330, 543, 477, 4400, 1, 5603, 11, 323, 358, 1781, 433, 596, 539, 1694, 330, 63578, 1, 279, 1314, 1648, 311, 279, 586, 13, 2435, 6865, 330, 2028, 374, 3958, 369, 499, 11, 430, 374, 3958, 369, 499, 1359, 814, 1781, 330, 3947, 596, 4400, 2163, 311, 8343, 0, 2100, 814, 2571, 709, 872, 6206, 323, 11894, 8996, 814, 1518, 430, 5992, 323, 10578, 1695, 323, 374, 4062, 323, 4228, 320, 438, 12136, 8, 477, 814, 6678, 1555, 28578, 374, 18585, 627, 40, 1781, 584, 617, 17454, 779, 3117, 1022, 279, 1853, 315, 1148, 584, 527, 10171, 311, 387, 12459, 439, 3823, 23837, 430, 433, 596, 1120, 2133, 311, 1935, 53722, 89347, 323, 89347, 323, 3815, 701, 1888, 311, 1304, 279, 1314, 11709, 994, 323, 1405, 499, 649, 13, 1102, 596, 539, 922, 1694, 4832, 323, 6041, 311, 649, 701, 1866, 60399, 477, 1304, 701, 1866, 90398, 439, 430, 596, 539, 43303, 369, 1690, 315, 603, 320, 16564, 13455, 44935, 388, 1093, 757, 570, 4452, 11, 856, 30687, 7558, 304, 279, 28363, 1584, 3432, 374, 28211, 3221, 1148, 433, 574, 220, 20, 1667, 4227, 11, 323, 374, 389, 264, 6724, 2204, 11841, 505, 220, 605, 1667, 4227, 11, 719, 358, 1440, 358, 2846, 2103, 330, 1962, 1070, 1, 323, 358, 3136, 311, 52143, 994, 323, 1405, 358, 649, 13, 1628, 358, 353, 268, 4215, 9, 433, 13, 358, 1541, 956, 2733, 1093, 433, 596, 264, 50671, 13, 358, 1093, 9455, 704, 430, 420, 2027, 374, 2731, 1109, 430, 832, 477, 430, 358, 10932, 420, 832, 311, 430, 832, 1606, 872, 2883, 477, 8961, 1587, 2574, 358, 29251, 315, 323, 279, 43940, 2027, 1587, 539, 13, 1102, 706, 1903, 12185, 32180, 369, 757, 1578, 4619, 315, 264, 50671, 627, 3947, 596, 264, 2466, 98431, 922, 19307, 17677, 28, 18621, 323, 3582, 358, 1505, 1077, 85077, 11, 84485, 6015, 13558, 374, 3815, 264, 2294, 2683, 315, 83588, 430, 22881, 369, 279, 330, 17645, 3778, 1, 320, 69386, 430, 374, 570, 358, 1781, 520, 279, 1890, 892, 11, 8994, 279, 2653, 990, 315, 1690, 1093, 16450, 13, 50117, 11, 279, 4459, 330, 17217, 278, 1, 3245, 374, 539, 1694, 11497, 1664, 477, 15753, 704, 311, 279, 32738, 279, 1314, 1648, 13, 358, 2567, 7422, 422, 584, 1047, 4423, 1093, 84485, 6015, 13558, 889, 1436, 1501, 94112, 323, 92584, 323, 350, 6483, 56, 323, 2006, 33437, 20982, 6674, 439, 1664, 439, 5161, 36404, 984, 11, 36899, 49835, 1053, 1520, 6678, 43601, 555, 35460, 315, 7631, 11, 4619, 315, 10917, 704, 279, 2254, 8356, 320, 8370, 358, 1518, 1524, 304, 279, 2466, 8957, 66508, 1457, 11, 43169, 304, 7347, 12472, 14, 30265, 2676, 8, 323, 1124, 12096, 1148, 814, 2351, 1511, 311, 12096, 1606, 814, 2744, 3780, 433, 323, 814, 1541, 956, 1440, 1148, 311, 656, 449, 9038, 21168, 477, 1370, 9810, 3153, 477, 3249, 41613, 505, 2753, 1109, 220, 508, 8931, 3201, 527, 2731, 323, 49973, 1964, 1109, 1884, 11092, 291, 304, 505, 279, 1023, 3185, 315, 279, 3224, 627, 22105, 499, 649, 1193, 1304, 832, 3245, 323, 2231, 433, 3201, 369, 12688, 1314, 1457, 11, 323, 433, 596, 264, 2523, 11, 3070, 2447, 430, 499, 656, 369, 37250, 4619, 315, 5127, 342, 1813, 287, 439, 50117, 3585, 704, 11, 323, 1243, 499, 4774, 433, 994, 1884, 6453, 323, 9439, 2919, 2586, 304, 6186, 323, 7552, 323, 433, 11321, 1093, 279, 12688, 690, 2646, 842, 13, 1628, 433, 3727, 499, 15648, 13, 1628, 430, 596, 1148, 433, 596, 922, 627, 40, 617, 6051, 1047, 264, 2294, 3568, 315, 2802, 304, 6975, 311, 293, 19223, 3691, 13, 358, 1097, 88861, 430, 10151, 1457, 11, 323, 358, 1781, 358, 617, 2884, 433, 1664, 15913, 279, 1890, 892, 358, 1097, 6975, 1148, 311, 656, 449, 70121, 3789, 13, 1102, 374, 8056, 1268, 1690, 2204, 4595, 315, 3691, 584, 1518, 1555, 279, 15956, 430, 527, 7344, 704, 315, 1057, 4725, 28417, 547, 315, 1148, 584, 1253, 477, 1253, 539, 8343, 13, 1115, 7474, 358, 9687, 1268, 311, 3139, 323, 24322, 282, 2734, 301, 13, 5046, 3388, 358, 649, 2019, 430, 1790, 315, 856, 2802, 304, 1521, 2574, 4131, 505, 279, 13057, 3392, 315, 5403, 358, 656, 13, 13440, 433, 387, 389, 8866, 23180, 11, 12369, 323, 32926, 11, 480, 51802, 477, 264, 5117, 11, 264, 2294, 3568, 315, 2802, 304, 3691, 4131, 505, 1148, 374, 704, 1070, 304, 279, 3772, 627, 10086, 264, 2944, 311, 8343, 304, 3280, 627, 32, 2763, 315, 12459, 3280, 750, 8659, 79476, 2212, 12823, 369, 17677, 3691, 430, 596, 2561, 520, 279, 892, 627, 50872, 323, 20704, 15657, 527, 7995, 16127, 311, 4394, 11, 2533, 499, 11383, 617, 311, 656, 2555, 6532, 311, 279, 14293, 311, 1304, 872, 32523, 2586, 704, 13, 1115, 374, 264, 77120, 2204, 5603, 311, 17677, 1109, 1455, 12531, 323, 19367, 3691, 11, 1405, 499, 2351, 4461, 311, 636, 279, 1888, 3135, 555, 19994, 6206, 1022, 323, 20806, 279, 14293, 6604, 369, 5694, 627, 13699, 11, 358, 1781, 1070, 596, 7995, 264, 30296, 1990, 12459, 34100, 276, 6437, 36989, 304, 7552, 323, 12459, 54453, 34683, 6437, 36989, 320, 66463, 814, 2351, 2884, 304, 264, 1648, 430, 596, 29546, 9498, 323, 5933, 570, 37558, 2795, 499, 617, 311, 656, 682, 315, 279, 46643, 990, 6261, 13, 128000, 43, 287, 940, 2160, 1780, 198, 791, 28229, 36716, 311, 264, 38172, 940, 2160, 1780, 902, 649, 387, 8599, 520, 2225, 10548, 311, 279, 18311, 315, 264, 8893, 555, 3445, 315, 459, 65558, 3717, 304, 2015, 311, 10519, 279, 2361, 315, 279, 37065, 18311, 315, 279, 8893, 304, 1071, 37065, 2361, 13, 578, 2160, 1780, 55952, 3967, 5435, 23926, 449, 21349, 3769, 323, 1101, 50829, 1695, 25152, 439, 1664, 439, 1695, 6160, 12255, 54153, 323, 264, 1579, 8893, 6981, 13, 1102, 649, 1101, 387, 1511, 927, 264, 1317, 4261, 315, 892, 320, 258, 14560, 5157, 11, 369, 264, 19569, 8, 2085, 904, 65069, 6372, 389, 2890, 13, 578, 2160, 1780, 374, 1903, 315, 832, 3769, 902, 374, 3060, 71404, 477, 264, 71404, 46964, 627, 50, 14166, 89, 11, 80474, 320, 47, 2000, 89, 21215, 11, 3467, 340, 35, 306, 4202, 372, 622, 13, 393, 13, 468, 82276, 97041, 1430, 71187, 320, 3957, 2702, 268, 11, 3467, 340, 32, 5547, 34, 20, 14, 410, 26, 362, 5547, 34, 22, 14, 410, 26, 362, 5547, 34, 1032, 14, 11057, 26, 320, 63219, 16, 12, 22, 1680, 362, 5547, 34, 1032, 14, 11057, 198, 1049, 14408, 27134, 1419, 2755, 371, 479, 315, 18311, 323, 1749, 369, 20646, 18311, 6250, 11, 220, 1049, 20, 3206, 16400, 35472, 198, 1049, 13135, 19306, 845, 79581, 81121, 6654, 2989, 2891, 4874, 46373, 6841, 11, 220, 1049, 23, 445, 1892, 72, 1880, 453, 627, 1049, 10841, 18265, 2304, 6872, 369, 20646, 264, 2539, 18653, 554, 3756, 5887, 11, 220, 1049, 19, 59027, 198, 1049, 4728, 19597, 2721, 469, 1215, 456, 2740, 22756, 94612, 51593, 1820, 324, 88886, 54952, 29106, 323, 6593, 22972, 323, 16346, 5587, 11, 220, 1049, 23, 8940, 6491, 1880, 453, 627, 679, 931, 21144, 1958, 18335, 34391, 37949, 65231, 643, 350, 31832, 5441, 3651, 65231, 643, 10314, 37535, 12121, 7552, 11, 220, 679, 15, 21750, 1880, 453, 627, 1049, 19319, 23574, 2318, 1883, 277, 1015, 304, 48804, 11847, 323, 6872, 369, 2140, 16608, 264, 14227, 7984, 647, 287, 311, 279, 26823, 5651, 11, 220, 1049, 24, 37832, 34605, 198, 1049, 21026, 25388, 972, 54501, 46460, 22165, 1887, 6664, 11, 220, 1049, 24, 42409, 198, 1049, 19319, 23785, 6086, 19960, 67887, 46460, 31646, 5936, 11, 220, 1049, 24, 42409, 198, 1049, 20253, 25504, 3971, 49741, 3765, 332, 479, 323, 48804, 2417, 21494, 20636, 279, 26823, 6841, 11, 220, 1049, 22, 5657, 1880, 453, 627, 1049, 16496, 17763, 2589, 4953, 285, 278, 51346, 2007, 369, 29106, 28664, 42391, 477, 279, 1093, 6790, 11, 220, 1049, 19, 120859, 560, 74, 198, 1049, 17973, 10943, 2813, 8828, 46090, 323, 23201, 7922, 3756, 5887, 11, 220, 1049, 23, 26181, 198, 36, 12420, 11, 11947, 33372, 38599, 5484, 198, 54949, 88029, 44752, 964, 612, 386, 15108, 11, 51285, 320, 28487, 438, 4298, 11, 21571, 11, 2326, 340, 16, 13, 1556, 30299, 86815, 292, 56454, 304, 279, 1376, 315, 264, 38172, 940, 2160, 1780, 46338, 264, 15631, 3515, 1403, 10548, 11, 42418, 279, 2160, 1780, 374, 70554, 505, 1193, 832, 3769, 4183, 505, 279, 1912, 31706, 315, 71404, 323, 71404, 95851, 11, 279, 15631, 3515, 264, 64186, 5654, 3515, 264, 7479, 520, 1855, 315, 1202, 1403, 10548, 11, 323, 42418, 279, 64186, 13918, 527, 11413, 6901, 389, 279, 27529, 34366, 311, 387, 70241, 627, 17, 13, 578, 56454, 439, 4613, 304, 3802, 220, 16, 11, 42418, 279, 15631, 323, 279, 64186, 13918, 527, 70554, 439, 264, 5089, 661, 6070, 627, 18, 13, 578, 56454, 439, 4613, 304, 3802, 220, 16, 11, 42418, 279, 15631, 706, 32302, 279, 1890, 26839, 439, 279, 64186, 13918, 323, 279, 15631, 374, 8599, 311, 1855, 315, 279, 64186, 13918, 555, 264, 32302, 18698, 10496, 627, 19, 13, 578, 56454, 439, 4613, 304, 3802, 220, 17, 11, 42418, 279, 15631, 374, 70554, 505, 264, 11071, 9501, 3769, 627, 20, 13, 578, 56454, 439, 4613, 304, 3802, 220, 16, 11, 42418, 279, 15631, 374, 70554, 505, 264, 2814, 3843, 438, 9244, 627, 21, 13, 578, 56454, 439, 4613, 304, 3802, 220, 16, 11, 42418, 279, 11413, 6147, 315, 279, 64186, 7479, 315, 279, 64186, 13918, 374, 9124, 555, 9462, 2067, 15067, 11, 1880, 28075, 477, 21120, 2080, 1711, 627, 22, 13, 578, 56454, 439, 4613, 304, 3802, 220, 16, 11, 42418, 279, 15631, 374, 264, 5643, 67, 15631, 627, 23, 13, 578, 56454, 439, 4613, 304, 3802, 220, 16, 11, 42418, 279, 15631, 706, 7479, 13918, 520, 323, 5255, 1990, 1202, 10548, 389, 430, 3185, 315, 1202, 7479, 902, 690, 3663, 279, 18311, 315, 264, 8893, 11, 902, 7479, 13918, 527, 11413, 6901, 369, 279, 28377, 315, 264, 64186, 8479, 627, 24, 13, 578, 56454, 315, 3802, 220, 22, 11, 42418, 279, 15631, 50829, 264, 5643, 315, 4376, 21691, 5425, 3857, 627, 605, 13, 578, 56454, 315, 3802, 220, 22, 11, 42418, 279, 15631, 50829, 264, 5643, 315, 4376, 12, 13825, 5425, 3857, 627, 806, 13, 578, 56454, 439, 4613, 304, 3802, 220, 17, 11, 42418, 279, 15631, 706, 32302, 279, 1890, 26839, 439, 279, 64186, 13918, 323, 279, 15631, 374, 8599, 311, 1855, 315, 279, 64186, 13918, 555, 264, 32302, 18698, 10496, 627, 717, 13, 578, 56454, 439, 4613, 304, 3802, 220, 18, 11, 42418, 279, 15631, 374, 70554, 505, 264, 11071, 9501, 3769, 627, 1032, 13, 578, 56454, 439, 4613, 304, 3802, 220, 17, 11, 42418, 279, 15631, 706, 7479, 13918, 520, 323, 5255, 1990, 1202, 10548, 389, 430, 3185, 315, 1202, 7479, 902, 690, 3663, 279, 18311, 315, 264, 8893, 11, 902, 7479, 13918, 527, 11413, 6901, 369, 279, 28377, 315, 264, 64186, 8479, 627, 777, 13, 578, 56454, 439, 4613, 304, 3802, 220, 605, 11, 42418, 279, 15631, 706, 7479, 13918, 520, 323, 5255, 1990, 1202, 10548, 389, 430, 3185, 315, 1202, 7479, 902, 690, 3663, 279, 18311, 315, 264, 8893, 11, 902, 7479, 13918, 527, 11413, 6901, 369, 279, 28377, 315, 264, 64186, 8479, 627, 2028, 3851, 374, 264, 42271, 315, 7327, 7473, 2360, 13, 393, 1182, 14, 9377, 2839, 14, 6849, 2495, 11, 13019, 17907, 13, 220, 777, 11, 220, 1049, 18, 11, 902, 374, 32762, 36881, 555, 5905, 627, 791, 28229, 36716, 311, 459, 30299, 86815, 292, 56454, 304, 279, 1376, 315, 264, 38172, 940, 2160, 1780, 46338, 264, 15631, 430, 649, 387, 12673, 520, 2225, 10548, 311, 279, 18311, 315, 264, 8893, 555, 3445, 315, 264, 24532, 11049, 11, 304, 2015, 311, 2567, 279, 8893, 596, 18311, 304, 2361, 2768, 91852, 6514, 627, 791, 7580, 315, 38172, 940, 14389, 388, 374, 311, 2567, 18311, 304, 264, 502, 11, 37065, 2361, 2768, 30299, 86815, 292, 6514, 323, 311, 70236, 420, 2361, 13, 51958, 940, 14389, 388, 527, 6118, 70241, 311, 279, 18311, 389, 279, 2536, 92236, 320, 2785, 940, 8, 7479, 34366, 627, 50571, 1989, 38172, 940, 14389, 388, 6824, 11, 369, 3187, 11, 315, 264, 15631, 1903, 315, 11, 2019, 11, 264, 2536, 19415, 818, 5962, 3623, 11547, 81, 46964, 11, 439, 420, 46964, 26420, 430, 279, 33964, 374, 40044, 628, 2205, 311, 7431, 279, 64186, 13918, 311, 387, 35328, 311, 5052, 1664, 2403, 279, 7479, 315, 279, 18311, 13, 578, 64186, 13918, 527, 9124, 555, 60877, 287, 779, 19434, 9501, 11546, 37095, 315, 11, 384, 1326, 2637, 25468, 9699, 311, 279, 10548, 315, 279, 15631, 627, 791, 1925, 64725, 315, 420, 3169, 315, 38172, 940, 2160, 1780, 54350, 279, 1005, 315, 2204, 37182, 477, 95851, 323, 279, 2144, 430, 279, 9501, 11546, 11262, 374, 11096, 311, 279, 15631, 555, 60877, 287, 11, 439, 264, 1121, 315, 902, 279, 13957, 311, 56488, 477, 279, 6160, 12255, 54153, 315, 279, 2160, 1780, 374, 32302, 11293, 13, 24296, 11, 279, 64186, 13918, 5376, 279, 8244, 26839, 323, 8108, 8893, 6981, 627, 2181, 374, 459, 1665, 315, 279, 3118, 28229, 311, 3493, 264, 38172, 940, 2160, 1780, 9204, 1695, 628, 79443, 323, 6160, 12255, 54153, 1418, 31526, 279, 46752, 3769, 43918, 5435, 323, 3611, 2745, 24872, 8893, 6981, 11, 28592, 10923, 433, 311, 387, 24634, 369, 44387, 18852, 320, 258, 14560, 5157, 369, 264, 19569, 8, 2085, 14718, 2890, 14228, 3185, 6372, 627, 2028, 1665, 374, 17427, 11, 4184, 311, 279, 28229, 11, 555, 13354, 1113, 264, 38172, 940, 2160, 1780, 315, 279, 955, 4613, 3485, 505, 264, 3254, 3769, 4183, 505, 279, 1912, 31706, 315, 71404, 323, 71404, 95851, 627, 12289, 21211, 315, 279, 3118, 28229, 1903, 505, 71404, 477, 71404, 95851, 527, 7701, 6160, 12255, 38179, 323, 649, 8617, 387, 1511, 369, 1633, 1317, 18852, 315, 892, 2085, 14718, 904, 31959, 2890, 14228, 3185, 6372, 627, 57417, 11, 71404, 477, 71404, 95851, 527, 7384, 430, 527, 315, 3428, 13552, 19025, 320, 10516, 75124, 315, 95916, 705, 527, 628, 2205, 11, 3515, 264, 3428, 36573, 4017, 11, 323, 649, 387, 31368, 70241, 311, 18311, 627, 644, 264, 11678, 315, 279, 2160, 1780, 315, 279, 28229, 11, 279, 15631, 706, 264, 64186, 5654, 520, 1855, 842, 34366, 11, 555, 3445, 315, 902, 433, 649, 387, 70241, 304, 264, 4382, 323, 13687, 11827, 311, 279, 8893, 596, 18311, 627, 93114, 11, 4382, 14389, 388, 649, 387, 1511, 11, 1521, 1694, 24306, 315, 264, 15631, 1193, 323, 3629, 31706, 315, 264, 320, 69, 70941, 2814, 3843, 438, 8, 9244, 11, 279, 36573, 4017, 315, 902, 374, 779, 3428, 430, 433, 374, 628, 2205, 13, 4314, 4382, 82565, 539, 19167, 449, 64186, 13918, 527, 70241, 439, 1778, 311, 279, 38172, 940, 7479, 315, 279, 18311, 311, 387, 93163, 627, 43061, 279, 7036, 315, 279, 3118, 28229, 11, 64186, 374, 16365, 311, 3152, 904, 3169, 315, 3717, 430, 1008, 17082, 3210, 29782, 7384, 3871, 13, 45863, 11, 264, 11049, 649, 387, 3549, 1701, 904, 315, 279, 5410, 272, 3808, 20011, 304, 18653, 5050, 11, 4040, 10507, 315, 902, 369, 1005, 304, 279, 3118, 2317, 527, 2840, 18239, 26429, 272, 3808, 627, 9673, 14389, 388, 649, 1101, 387, 35426, 10235, 369, 64186, 555, 8405, 1124, 449, 35426, 10235, 7479, 13918, 520, 279, 6732, 1405, 814, 527, 311, 387, 70241, 311, 279, 8893, 596, 18311, 13, 763, 279, 45648, 1162, 11, 1521, 1053, 387, 7479, 13918, 7559, 520, 1855, 842, 315, 279, 15631, 13, 1115, 15631, 810, 52754, 706, 389, 1202, 3185, 6319, 311, 3663, 279, 7479, 315, 279, 18311, 832, 477, 810, 5217, 7479, 13918, 10235, 369, 64186, 311, 18311, 627, 791, 18459, 315, 279, 7479, 5654, 369, 64186, 10096, 1253, 6824, 315, 11413, 6147, 11, 369, 3187, 13, 58421, 6147, 649, 387, 27332, 555, 1880, 28075, 11, 9462, 2067, 15067, 11, 21120, 98423, 11, 477, 555, 22936, 98423, 11, 1778, 439, 8126, 3746, 287, 477, 9501, 14713, 627, 791, 2160, 1780, 374, 52754, 9124, 449, 1202, 15631, 323, 279, 1403, 64186, 13918, 30164, 264, 5089, 661, 6070, 13, 1442, 12974, 11, 279, 64186, 13918, 1253, 387, 30464, 311, 3493, 459, 74117, 7479, 3158, 369, 64186, 279, 2160, 1780, 311, 279, 18311, 627, 791, 15631, 810, 52754, 706, 32302, 279, 1890, 26839, 439, 279, 64186, 13918, 11, 323, 279, 9320, 1990, 279, 15631, 323, 279, 64186, 13918, 374, 1778, 430, 279, 15631, 32302, 82053, 449, 279, 64186, 5654, 477, 374, 12673, 9139, 11269, 304, 74820, 5133, 13, 763, 420, 1648, 279, 64186, 13918, 656, 539, 5376, 279, 8244, 26839, 11, 323, 8893, 6981, 374, 24872, 627, 2409, 5201, 311, 420, 16686, 439, 1664, 439, 311, 279, 1205, 369, 279, 45648, 3284, 15266, 1920, 11, 279, 2160, 1780, 374, 52754, 1903, 505, 11071, 9501, 11, 384, 1326, 2637, 555, 21899, 287, 627, 791, 4553, 2160, 1780, 11, 430, 374, 11, 279, 15631, 2737, 279, 64186, 13918, 520, 1202, 10548, 11, 374, 8617, 65139, 505, 279, 11071, 9501, 11, 477, 775, 70554, 1070, 1527, 304, 1063, 1023, 1648, 11, 779, 430, 279, 2160, 1780, 706, 13263, 26839, 13, 578, 5995, 33247, 13552, 19025, 374, 743, 555, 279, 18274, 4256, 278, 2427, 287, 4023, 13167, 315, 279, 15631, 627, 644, 2500, 15236, 49497, 11, 279, 15631, 315, 279, 2160, 1780, 374, 1903, 505, 7447, 42728, 438, 9244, 13, 763, 420, 1162, 11, 264, 73405, 315, 9244, 1488, 24469, 374, 63205, 311, 1376, 264, 9244, 13, 578, 3927, 1488, 24469, 1253, 387, 315, 279, 1890, 477, 2204, 4595, 13, 14636, 433, 690, 387, 264, 1633, 4382, 5030, 369, 279, 1732, 26611, 304, 279, 1989, 311, 8356, 14389, 388, 3515, 279, 12974, 22936, 6012, 9932, 3485, 11, 539, 1193, 555, 29865, 279, 1396, 315, 1488, 24469, 1511, 11, 719, 1101, 555, 27397, 1124, 4184, 311, 872, 22936, 8333, 2819, 13, 763, 420, 5363, 11, 539, 1193, 279, 23899, 315, 279, 3927, 1488, 24469, 11, 719, 1101, 872, 18528, 11, 649, 387, 28830, 779, 430, 11, 369, 3187, 11, 264, 1396, 315, 1488, 24469, 315, 5370, 4528, 71404, 95851, 649, 387, 1511, 13, 1115, 20628, 279, 7631, 369, 6160, 12255, 54153, 30164, 832, 315, 279, 26470, 315, 279, 28229, 627, 24350, 25843, 788, 14389, 388, 649, 387, 9124, 505, 4376, 21691, 477, 4376, 12, 13825, 5643, 67, 7384, 11, 323, 279, 7479, 13918, 2631, 369, 64186, 10096, 649, 387, 14454, 389, 279, 10269, 3185, 315, 279, 15631, 627, 2028, 55952, 279, 9546, 315, 41579, 323, 39300, 919, 389, 279, 2160, 1780, 11, 902, 527, 65069, 311, 21308, 53056, 11, 323, 1121, 11, 958, 453, 689, 11, 304, 13241, 8893, 6981, 11, 1606, 279, 25466, 11, 902, 649, 11388, 1633, 2678, 61437, 13918, 11, 690, 1193, 2586, 1139, 3729, 449, 264, 3769, 430, 374, 32302, 78909, 12314, 323, 8617, 11113, 627, 791, 64186, 13918, 527, 52754, 11413, 6901, 389, 279, 7479, 311, 387, 70241, 627, 73741, 5528, 527, 11349, 369, 11413, 6147, 279, 9959, 27529, 315, 279, 64186, 13918, 11, 1778, 439, 9462, 2067, 15067, 11, 11742, 1880, 28075, 477, 11, 304, 4040, 11, 21120, 2080, 1711, 11, 430, 374, 11, 98423, 449, 264, 21120, 18803, 11, 439, 36489, 304, 19613, 220, 15, 220, 25496, 220, 23873, 426, 16, 627, 791, 71404, 477, 71404, 46964, 38172, 940, 14389, 388, 315, 279, 28229, 649, 387, 70554, 304, 4040, 439, 264, 5089, 661, 6070, 2085, 16239, 60877, 287, 477, 279, 1005, 315, 5217, 9501, 11546, 37095, 477, 1023, 80506, 7384, 11, 779, 430, 279, 1579, 8547, 315, 6160, 12255, 54153, 315, 71404, 323, 71404, 95851, 649, 555, 7373, 51763, 627, 2127, 9610, 315, 71404, 323, 71404, 95851, 374, 430, 814, 617, 264, 3428, 75124, 315, 95916, 11, 779, 430, 279, 38172, 940, 2160, 1780, 5196, 690, 14085, 449, 1193, 264, 3428, 50203, 5457, 311, 904, 3284, 711, 1191, 34366, 555, 279, 26588, 311, 387, 5762, 304, 2035, 13, 1115, 374, 39061, 555, 279, 628, 79443, 11, 602, 1770, 2637, 279, 3428, 36573, 4017, 11, 315, 71404, 323, 71404, 95851, 11, 902, 3727, 279, 6211, 315, 279, 15631, 31368, 94848, 311, 279, 45982, 315, 264, 8893, 596, 11013, 627, 791, 10269, 1376, 11, 902, 374, 15236, 11, 374, 4228, 311, 8356, 555, 15266, 279, 38172, 940, 2160, 1780, 505, 264, 71404, 477, 71404, 46964, 11071, 9501, 11, 384, 1326, 2637, 555, 21899, 287, 477, 14713, 627, 644, 279, 15629, 1162, 5423, 11, 279, 64186, 5654, 374, 14454, 18698, 449, 279, 15631, 323, 374, 8617, 539, 1903, 59884, 555, 904, 60877, 291, 10539, 9501, 11546, 11262, 627, 791, 8767, 9932, 1749, 315, 21120, 2080, 1711, 320, 9377, 220, 15, 220, 25496, 220, 23873, 426, 16, 8, 11705, 459, 26613, 1396, 315, 38231, 6732, 11, 902, 374, 95561, 311, 264, 51263, 11, 27220, 65558, 11049, 627, 9673, 323, 1023, 22934, 315, 279, 28229, 527, 11497, 304, 7191, 7872, 3770, 449, 5905, 311, 279, 38940, 11, 304, 902, 512, 6507, 13, 220, 16, 25, 5039, 459, 15453, 42644, 306, 49497, 315, 264, 38172, 940, 2160, 1780, 315, 279, 28229, 280, 6507, 13, 220, 17, 25, 5039, 2500, 11678, 315, 279, 38172, 940, 2160, 1780, 315, 279, 28229, 280, 6507, 13, 220, 18, 25, 374, 264, 13861, 38344, 13340, 315, 264, 38172, 940, 2160, 1780, 315, 279, 28229, 12673, 311, 279, 4827, 16942, 315, 264, 8893, 26, 323, 198, 6507, 13, 220, 19, 25, 5039, 2500, 49497, 315, 279, 38172, 940, 2160, 1780, 315, 279, 28229, 627, 6507, 13, 220, 16, 46480, 264, 38172, 940, 2160, 1780, 1903, 315, 11, 384, 1326, 2637, 264, 71404, 46964, 11, 24073, 439, 264, 4459, 555, 279, 5905, 1396, 220, 605, 13, 51958, 940, 2160, 1780, 220, 605, 17610, 315, 264, 5643, 67, 15631, 220, 717, 323, 1403, 64186, 13918, 220, 975, 11, 220, 845, 14454, 832, 520, 1855, 842, 34366, 627, 43, 287, 940, 2160, 1780, 220, 605, 36762, 304, 38699, 13, 220, 16, 374, 65139, 505, 264, 71404, 46964, 11071, 439, 264, 5089, 661, 6070, 11, 602, 1770, 2637, 64186, 13918, 220, 975, 323, 220, 845, 527, 26154, 449, 15631, 220, 717, 13, 24296, 11, 38172, 940, 2160, 1780, 220, 605, 374, 315, 13263, 26839, 927, 1202, 4553, 3160, 11, 323, 420, 39990, 21308, 53056, 323, 11, 2533, 1070, 527, 912, 47862, 288, 477, 1760, 30970, 3095, 902, 1436, 38323, 279, 25466, 11, 57924, 279, 8893, 6981, 627, 90944, 287, 13918, 220, 975, 323, 220, 845, 527, 11413, 6901, 389, 872, 27529, 220, 972, 323, 220, 508, 15947, 304, 18459, 369, 64186, 279, 1890, 311, 264, 8893, 596, 26588, 11, 1071, 11413, 6147, 1694, 304, 279, 1376, 315, 264, 5950, 12970, 21120, 6070, 13, 1102, 374, 9093, 539, 5995, 311, 60877, 389, 264, 9501, 11546, 11262, 11, 439, 6062, 5995, 11, 902, 374, 539, 1193, 459, 9610, 449, 5363, 311, 279, 6160, 12255, 54153, 315, 279, 38172, 940, 2160, 1780, 315, 279, 28229, 11, 719, 1101, 26338, 279, 1396, 315, 5788, 7504, 11, 2533, 21120, 2080, 1711, 374, 1790, 8831, 311, 22829, 323, 374, 810, 60618, 13, 24296, 11, 56488, 5435, 527, 31890, 11, 2533, 279, 88465, 315, 5217, 7384, 1023, 1109, 71404, 477, 71404, 95851, 374, 912, 5129, 5995, 4245, 311, 279, 955, 315, 64186, 7479, 220, 972, 477, 220, 508, 1511, 627, 93114, 11, 64186, 27529, 220, 972, 11, 220, 508, 1253, 387, 9462, 2067, 15386, 477, 8590, 2740, 1880, 2454, 11, 304, 902, 1162, 433, 374, 1193, 5995, 311, 6106, 430, 279, 7479, 374, 49672, 11413, 6901, 449, 11, 304, 4040, 11, 96109, 1303, 34366, 11, 902, 690, 6106, 9966, 34330, 2747, 315, 279, 24532, 311, 279, 64186, 13918, 220, 972, 323, 220, 508, 627, 6507, 13, 220, 17, 46480, 2500, 11678, 315, 264, 38172, 940, 2160, 1780, 220, 966, 315, 279, 28229, 11, 902, 374, 24306, 315, 264, 15631, 220, 843, 323, 1403, 64186, 13918, 220, 1958, 11, 220, 1927, 13, 763, 420, 49497, 11, 279, 15631, 220, 843, 374, 82161, 311, 279, 26214, 28648, 64186, 13918, 11, 384, 1326, 2637, 555, 21120, 60022, 627, 87792, 220, 843, 374, 75893, 2740, 864, 95977, 779, 430, 279, 50351, 16632, 706, 311, 1304, 8275, 5217, 51479, 311, 279, 6211, 315, 279, 30280, 15631, 220, 843, 1603, 25012, 433, 304, 279, 11013, 315, 264, 8893, 323, 24532, 287, 433, 311, 279, 8893, 596, 18311, 627, 791, 64186, 13918, 220, 1958, 11, 220, 1927, 617, 264, 64186, 7479, 220, 1987, 323, 220, 1272, 15947, 11, 902, 374, 1578, 21120, 34030, 11, 439, 7633, 3485, 304, 3717, 449, 38699, 13, 220, 16, 627, 6507, 13, 220, 18, 374, 264, 13861, 38344, 40134, 315, 264, 14595, 20581, 6671, 16239, 264, 38172, 940, 2160, 1780, 11, 369, 3187, 264, 38172, 940, 2160, 1780, 220, 1135, 46338, 264, 15631, 220, 4370, 323, 64186, 13918, 220, 3487, 11, 220, 2970, 14454, 1070, 263, 627, 90944, 287, 13918, 220, 3487, 11, 220, 2970, 527, 70241, 311, 279, 38172, 940, 3185, 315, 11, 2019, 11, 279, 272, 30863, 3447, 315, 279, 4827, 16942, 220, 4103, 315, 264, 8893, 555, 264, 24532, 11049, 323, 814, 10519, 1071, 272, 30863, 3447, 11, 439, 1664, 439, 279, 3709, 42314, 7559, 1990, 1124, 11, 304, 279, 2361, 63260, 555, 3766, 91852, 6514, 1701, 1063, 1023, 30299, 86815, 292, 3756, 627, 6507, 13, 220, 19, 46480, 459, 10778, 49497, 315, 264, 2160, 1780, 220, 1399, 315, 279, 28229, 1903, 505, 264, 5643, 67, 71404, 3769, 3515, 264, 4376, 21691, 5425, 3857, 13, 27140, 279, 14389, 388, 36762, 304, 38699, 50, 13, 220, 16, 311, 220, 18, 11, 279, 38172, 940, 2160, 1780, 220, 1399, 706, 912, 74117, 5654, 389, 279, 10548, 220, 5538, 11, 220, 5495, 315, 1202, 33964, 220, 1227, 369, 64186, 311, 279, 27529, 315, 279, 18311, 11, 719, 4619, 279, 7479, 13918, 220, 2287, 11, 220, 3080, 527, 45408, 311, 279, 10269, 7479, 315, 279, 4376, 21691, 5643, 627, 6507, 13, 220, 19, 4726, 46480, 430, 279, 38172, 940, 14389, 388, 315, 279, 28229, 1253, 1101, 52754, 617, 7479, 13918, 220, 2614, 3235, 872, 15631, 520, 28090, 12435, 311, 279, 10093, 315, 279, 18311, 11, 902, 7479, 13918, 22822, 279, 7479, 13918, 220, 2287, 323, 220, 3080, 11, 779, 430, 420, 38172, 940, 2160, 1780, 220, 1399, 649, 11, 422, 2631, 11, 387, 1008, 17082, 3210, 12673, 311, 1855, 315, 279, 18311, 7396, 555, 15631, 220, 1227, 627, 21994, 59090, 25, 48804, 46460, 1887, 323, 1749, 369, 2515, 287, 264, 29106, 35093, 1701, 279, 1890, 198, 5971, 59090, 25, 744, 323, 1749, 369, 54626, 29106, 1841, 552, 128000, 100068, 323, 69224, 198, 20224, 24, 445, 10743, 21998, 5161, 220, 22741, 2437, 54370, 11, 14972, 198, 7778, 10180, 4073, 9359, 4073, 38747, 1796, 320, 15, 8, 3092, 8785, 57835, 198, 100068, 3112, 1163, 4825, 916, 765, 11208, 4718, 5492, 38571, 92408, 0, 765, 220, 16, 12, 4728, 12, 20775, 12, 22240, 22, 198, 3648, 14270, 38571, 69224, 198, 23580, 14270, 38571, 69224, 198, 60816, 24749, 7572, 14270, 38571, 1050, 566, 10670, 198, 2356, 1894, 1369, 1113, 320, 18, 340, 64431, 38571, 1369, 1113, 320, 18, 340, 4434, 481, 69224, 198, 56553, 612, 57817, 8471, 198, 4032, 9225, 11218, 8471, 198, 1687, 11544, 69224, 198, 7778, 38571, 16607, 198, 100068, 323, 69224, 20114, 198, 100068, 323, 69224, 3494, 11216, 198, 13129, 950, 24907, 64141, 198, 7778, 8345, 5513, 16675, 848, 11452, 8128, 8345, 31048, 315, 279, 7252, 14270, 578, 11796, 304, 279, 4435, 198, 60628, 315, 279, 7252, 14270, 578, 11796, 304, 279, 4435, 198, 2746, 499, 2351, 1093, 603, 11, 499, 4762, 4774, 1455, 315, 701, 9698, 520, 2162, 13, 2030, 7170, 26, 1070, 527, 9698, 430, 527, 779, 1695, 11, 779, 51517, 22610, 79863, 11, 323, 779, 25706, 430, 499, 1390, 311, 4774, 1124, 1405, 814, 2351, 10171, 311, 387, 15746, 25, 304, 279, 9439, 11, 6453, 91120, 315, 264, 5818, 27803, 449, 264, 14880, 15286, 315, 70805, 304, 1450, 11, 323, 264, 503, 49709, 28935, 7172, 304, 701, 10954, 596, 10747, 12102, 13, 4427, 9698, 527, 1120, 5922, 3794, 304, 279, 1841, 311, 6678, 311, 279, 27803, 11, 323, 2559, 304, 1584, 311, 3780, 264, 11989, 1120, 311, 1518, 433, 3131, 13, 2582, 11157, 13, 2582, 8254, 3115, 627, 1271, 387, 6762, 11, 433, 596, 539, 2744, 279, 5818, 13, 578, 5818, 44866, 5694, 649, 387, 779, 12738, 323, 779, 25706, 439, 311, 387, 5922, 279, 47947, 1120, 311, 636, 1070, 11, 912, 5030, 1148, 5818, 814, 2351, 5737, 13, 1628, 912, 11, 584, 2351, 539, 7556, 922, 220, 19, 35, 477, 1023, 502, 69, 40040, 4595, 315, 5222, 323, 6945, 8863, 5557, 13, 1226, 2351, 7556, 922, 459, 15400, 27803, 3217, 430, 690, 1304, 499, 2733, 1093, 5108, 1203, 369, 810, 13, 5810, 374, 1057, 1160, 315, 8254, 315, 279, 1888, 5818, 44866, 3596, 512, 791, 1708, 21781, 423, 15817, 56134, 304, 19816, 11, 8421, 1389, 5629, 9107, 304, 220, 2550, 22, 11, 279, 1708, 21781, 423, 15817, 56134, 649, 1457, 387, 1766, 304, 220, 1313, 2204, 10687, 304, 279, 2326, 13, 1102, 374, 11495, 369, 1694, 4315, 279, 1176, 44866, 311, 11142, 264, 810, 71358, 5818, 2695, 33024, 3217, 555, 10209, 10882, 38399, 11, 21662, 11, 323, 3691, 430, 499, 2643, 1505, 304, 459, 75023, 11, 7060, 18397, 10960, 627, 791, 356, 483, 6953, 37075, 304, 33995, 1969, 84, 11, 50064, 1389, 1115, 27803, 596, 3802, 311, 33651, 374, 1202, 2237, 315, 19913, 11, 449, 1202, 11646, 11989, 7729, 11, 72779, 18012, 26993, 11, 323, 73585, 3691, 10235, 555, 264, 30806, 13, 356, 483, 6953, 37075, 1101, 38119, 315, 3515, 2500, 9046, 304, 51289, 11, 4987, 12126, 627, 791, 452, 635, 82254, 49318, 304, 26832, 11, 1561, 4356, 1389, 13926, 10481, 304, 26832, 374, 1405, 499, 3358, 1205, 311, 733, 311, 1505, 420, 5016, 22150, 449, 2380, 15670, 1405, 26, 16038, 505, 264, 5818, 11, 499, 649, 961, 731, 315, 264, 3728, 5130, 323, 11003, 58076, 430, 527, 10434, 7833, 311, 701, 19913, 10954, 627, 791, 21246, 49318, 304, 7295, 11, 9635, 1389, 2057, 2019, 430, 420, 5818, 27803, 26, 1766, 304, 7295, 596, 2876, 1303, 8270, 12299, 11, 374, 5115, 1153, 71, 374, 459, 14653, 5722, 13, 10573, 264, 5818, 1418, 34948, 304, 3544, 11, 60421, 16712, 449, 4579, 267, 6309, 323, 8515, 61031, 65712, 26, 477, 389, 28036, 320, 9891, 11, 28036, 8, 7559, 520, 279, 4156, 315, 279, 4264, 13, 23485, 264, 16893, 315, 13378, 11, 477, 617, 1063, 83568, 19623, 1418, 99345, 287, 389, 3341, 4744, 33860, 11, 29375, 437, 11, 477, 264, 2466, 13651, 315, 34619, 426, 3695, 13, 1472, 649, 1101, 617, 21662, 520, 279, 2539, 3703, 26, 323, 617, 459, 1306, 1474, 6461, 15496, 520, 1202, 21246, 423, 10670, 13, 393, 9451, 11, 13118, 627, 791, 30011, 978, 10590, 4558, 593, 84939, 4105, 304, 12366, 1389, 3277, 374, 264, 5818, 27803, 810, 1109, 1120, 264, 2035, 311, 3821, 12631, 30, 3277, 433, 596, 1101, 264, 24925, 320, 4581, 34575, 11, 13971, 42395, 791, 24925, 961, 315, 279, 27803, 38119, 459, 16358, 4526, 315, 4632, 16420, 94450, 25, 505, 13970, 3673, 1778, 439, 6382, 7600, 54635, 11, 11204, 74265, 82, 11, 323, 81209, 15039, 505, 279, 3347, 26, 439, 1664, 439, 39568, 11, 45188, 11, 323, 7059, 1778, 439, 279, 11670, 8954, 12585, 1511, 304, 91083, 23272, 596, 4632, 6344, 55422, 13, 48525, 555, 11726, 31925, 377, 74680, 894, 11, 279, 27803, 5039, 12631, 505, 682, 927, 279, 1917, 11, 323, 7170, 15670, 11670, 12631, 315, 65765, 49428, 627, 791, 26291, 24789, 404, 49318, 304, 23720, 72977, 11, 6890, 1389, 1115, 5818, 27803, 5334, 3361, 6420, 369, 1202, 6800, 74564, 323, 11091, 23241, 2955, 25, 44952, 20705, 5789, 11, 16358, 1579, 22959, 9722, 291, 449, 523, 38221, 4918, 11, 89341, 11, 323, 37067, 1841, 85, 826, 1304, 420, 22150, 2733, 810, 1093, 264, 31070, 7858, 1109, 264, 27803, 13, 578, 26291, 24789, 404, 374, 832, 315, 279, 24417, 5818, 44866, 374, 6890, 11, 3515, 1027, 5918, 304, 220, 4468, 21, 11, 323, 374, 264, 5526, 2816, 369, 5818, 21134, 288, 315, 45080, 12631, 13, 10573, 279, 5818, 389, 459, 5066, 40248, 4264, 1418, 22128, 8388, 87909, 11, 323, 293, 1091, 304, 279, 27803, 596, 15400, 3925, 627, 791, 66331, 8620, 27315, 304, 9853, 12167, 11, 7188, 1389, 2360, 10430, 315, 5818, 44866, 1053, 387, 4686, 2085, 2737, 279, 66331, 8620, 27315, 13, 49386, 311, 1274, 555, 1202, 810, 5526, 5144, 26, 439, 279, 40113, 7282, 596, 8620, 27315, 11, 323, 1243, 439, 279, 30960, 596, 8620, 27315, 11, 279, 66331, 8620, 27315, 374, 459, 3062, 961, 315, 5818, 3925, 13, 67888, 369, 1202, 17681, 12839, 315, 39627, 1405, 499, 649, 1505, 279, 4579, 323, 1450, 24370, 315, 701, 7075, 9958, 26, 279, 91582, 8620, 27315, 1101, 4519, 264, 33687, 7364, 11, 477, 499, 649, 1120, 1935, 304, 264, 5818, 9204, 389, 279, 27803, 596, 11191, 4264, 627, 4110, 701, 1866, 61098, 5818, 3217, 555, 10307, 12631, 304, 701, 1633, 1866, 5492, 38571, 13, 75535, 323, 69224, 916, 649, 3493, 1511, 323, 502, 5818, 27803, 16712, 311, 3041, 701, 5818, 3130, 430, 13513, 27803, 2733, 13, 1226, 8312, 10632, 323, 8518, 63337, 449, 1511, 323, 502, 27803, 16712, 26, 439, 1664, 439, 14619, 481, 69224, 323, 5492, 38571, 40819, 13, 1226, 1101, 4685, 11, 4148, 11, 8175, 704, 11, 323, 56756, 819, 5818, 16712, 369, 499, 13, 662, 21335, 603, 264, 1650, 520, 320, 4728, 8, 220, 20775, 12, 22240, 22, 11, 477, 3729, 603, 2930, 369, 682, 315, 701, 5818, 27803, 10954, 44983, 323, 369, 810, 2038, 627, 3648, 20680, 2303, 14270, 38571, 9305, 261, 482, 5492, 38571, 1369, 1113, 198, 791, 5492, 38571, 96069, 198, 56553, 32323, 198, 3648, 38571, 69224, 198, 23580, 38571, 1369, 1113, 198, 6182, 2490, 1628, 12632, 198, 100068, 1628, 69224, 662, 470, 198, 13058, 27803, 16712, 3085, 1972, 6981, 323, 39665, 13, 8876, 220, 1049, 17, 11, 2162, 7980, 11, 44866, 11, 323, 9873, 617, 6656, 311, 603, 311, 3493, 1124, 449, 1579, 22867, 27803, 16712, 323, 26993, 11, 23090, 11, 323, 7855, 520, 17049, 7729, 627, 4599, 279, 13001, 5213, 323, 279, 1501, 12302, 11, 279, 10877, 7930, 1441, 323, 93018, 1139, 13513, 27803, 16712, 11, 6319, 311, 387, 10882, 323, 1317, 65265, 627, 679, 22, 7388, 75535, 438, 1163, 4825, 916, 128000, 49, 4748, 348, 13, 43982, 611, 45624, 507, 20987, 11525, 1507, 13, 3639, 596, 279, 13756, 389, 21445, 388, 323, 6401, 35695, 5380, 73849, 27562, 5651, 220, 1187, 11, 220, 2366, 17, 11, 220, 23, 25, 914, 1097, 6287, 220, 16, 11, 220, 2366, 17, 18149, 4206, 389, 79552, 348, 13, 43982, 611, 45624, 507, 20987, 11525, 1507, 13, 3639, 596, 279, 13756, 389, 21445, 388, 323, 6401, 35695, 5380, 4387, 5651, 220, 1187, 11, 220, 2366, 17, 198, 2028, 6693, 11, 279, 13814, 7301, 315, 279, 3723, 4273, 320, 3624, 1831, 2078, 8, 1766, 304, 4799, 315, 279, 1614, 315, 29538, 304, 279, 65351, 1302, 1162, 320, 66, 1639, 304, 7872, 3770, 570, 763, 3815, 779, 11, 7683, 1831, 2078, 1101, 69098, 4972, 7683, 1831, 2078, 11429, 304, 79552, 320, 4468, 18, 8, 323, 45624, 320, 2550, 17, 705, 13750, 49636, 11578, 535, 2512, 304, 5415, 1405, 1070, 6866, 864, 11151, 4748, 323, 330, 18975, 1, 48609, 315, 20710, 13, 31391, 48609, 527, 1405, 1614, 2383, 2736, 48609, 2680, 11, 304, 1063, 8547, 11, 311, 11578, 535, 2512, 1288, 79552, 387, 69098, 13, 8876, 79552, 574, 69098, 304, 279, 65351, 1302, 5597, 11, 433, 374, 709, 311, 1855, 1614, 311, 8417, 2680, 311, 11578, 535, 2512, 304, 872, 1614, 13, 2057, 18920, 11, 5415, 449, 1778, 48609, 13893, 7524, 5304, 279, 67687, 287, 315, 79552, 3196, 389, 864, 11151, 4748, 7016, 477, 864, 6953, 55804, 1614, 1957, 2997, 25, 8927, 11, 31976, 11, 31672, 11, 27438, 11, 3110, 11, 44190, 11, 50579, 11, 13256, 11, 18983, 11, 10504, 11, 11672, 11, 39544, 11, 29822, 11, 10619, 11, 7683, 11, 8189, 11, 32023, 11, 17467, 11, 26639, 11, 75525, 11, 43023, 323, 468, 56, 13, 5046, 902, 10619, 11, 8014, 11, 8189, 11, 17467, 323, 13256, 527, 14247, 323, 3885, 2949, 220, 966, 2919, 477, 5304, 1614, 5597, 389, 1268, 311, 3790, 864, 11151, 4748, 7016, 2103, 389, 279, 6603, 430, 9120, 11578, 535, 2512, 13, 13625, 1023, 5415, 617, 16717, 814, 2288, 690, 33330, 17294, 311, 11578, 535, 2512, 2680, 304, 1063, 1376, 11, 2737, 25, 13062, 11, 2006, 11, 19629, 323, 8014, 13, 82671, 11, 279, 2768, 5415, 617, 477, 3197, 311, 1935, 1957, 311, 6106, 8738, 2680, 311, 11578, 535, 2512, 25, 9362, 11, 7432, 11, 19084, 11, 3467, 13, 42416, 11, 11598, 11, 16691, 11, 14306, 11, 9917, 11, 25464, 11, 27816, 11, 12551, 11, 2794, 11, 48597, 11, 34051, 11, 29666, 323, 279, 11182, 315, 19326, 627, 791, 3230, 4860, 37260, 311, 7683, 1831, 2078, 304, 279, 65351, 1302, 1162, 1051, 512, 16, 13, 13440, 682, 864, 8437, 79443, 14541, 6055, 389, 98590, 54373, 527, 53925, 627, 17, 13, 13440, 279, 32939, 315, 264, 864, 8437, 79443, 2383, 430, 36236, 3278, 596, 2890, 11, 279, 38929, 315, 86333, 2911, 11, 323, 279, 17025, 315, 279, 6593, 4913, 323, 8396, 1288, 387, 30239, 1234, 45624, 596, 330, 1263, 361, 23104, 1, 5410, 477, 93893, 24836, 83, 596, 44463, 315, 7720, 323, 64074, 627, 18, 13, 13440, 20710, 12850, 617, 4948, 24993, 11509, 311, 41043, 264, 2383, 430, 36236, 3278, 596, 2890, 505, 279, 37064, 315, 3389, 9860, 54373, 627, 70786, 1708, 6491, 39056, 279, 220, 21, 12, 18, 9647, 320, 8370, 574, 21907, 20086, 311, 279, 34947, 10165, 9647, 304, 3297, 705, 449, 14681, 12007, 39427, 449, 279, 5597, 304, 4799, 315, 29538, 719, 539, 430, 279, 5597, 4460, 311, 67687, 79552, 611, 45624, 13, 426, 8233, 261, 11, 328, 354, 316, 1155, 323, 735, 18851, 14091, 16243, 13, 12007, 11355, 11224, 430, 420, 5597, 1436, 387, 27927, 1109, 279, 20710, 4360, 11, 20444, 1708, 6491, 11224, 420, 5597, 1288, 1193, 3881, 311, 279, 4360, 315, 20710, 13, 55106, 11, 279, 7301, 1766, 430, 20710, 374, 539, 2682, 439, 264, 330, 2808, 1368, 1, 1234, 279, 13625, 46487, 22454, 6273, 9313, 22381, 2533, 433, 374, 539, 32366, 291, 304, 279, 32006, 323, 3925, 315, 420, 7140, 13, 1472, 1253, 1684, 279, 5597, 555, 279, 7301, 1389, 220, 777, 12, 10125, 17, 65351, 1302, 348, 13, 13972, 11215, 596, 6401, 21021, 320, 2705, 14, 1187, 14, 2366, 17, 8, 320, 13066, 1864, 762, 29686, 14489, 340, 39, 789, 25, 578, 18039, 1587, 539, 49843, 264, 1314, 311, 20710, 26, 79552, 323, 45624, 527, 927, 2739, 839, 26, 323, 279, 11447, 311, 37377, 20710, 374, 6052, 311, 279, 1274, 323, 872, 16689, 24005, 13, 393, 79, 13, 220, 23, 4235, 4643, 627, 37132, 388, 323, 2890, 3197, 39701, 46227, 311, 1935, 1957, 2768, 420, 5597, 527, 21190, 311, 6604, 449, 872, 5897, 477, 8907, 6721, 1603, 4737, 904, 1957, 311, 6106, 8907, 449, 8581, 2383, 13, 1102, 374, 1101, 3062, 311, 5766, 13893, 28856, 17320, 449, 8420, 889, 10519, 18463, 53108, 2204, 1109, 279, 7471, 596, 627, 2356, 402, 1468, 5856, 706, 1027, 389, 1948, 315, 420, 4360, 369, 1057, 8403, 323, 649, 3085, 1862, 15851, 315, 279, 2361, 814, 1253, 617, 389, 279, 4360, 11, 2737, 42118, 279, 8907, 11774, 430, 1253, 2586, 449, 48810, 3738, 10396, 477, 3197, 14769, 304, 2077, 311, 279, 65351, 1302, 5597, 13, 2893, 2771, 311, 3729, 701, 2009, 402, 1468, 5856, 18740, 13, 3580, 3770, 369, 2539, 3649, 389, 279, 5157, 22628, 36881, 323, 279, 5536, 315, 279, 5597, 389, 23234, 323, 2890, 6787, 11, 2737, 3062, 4860, 311, 2610, 323, 38864, 311, 1781, 922, 627, 18902, 4652, 4756, 3297, 220, 24, 11, 220, 2366, 17, 11, 1306, 279, 24237, 315, 279, 10165, 9647, 369, 279, 65351, 1302, 13814, 7301, 315, 279, 3723, 4273, 320, 3624, 1831, 2078, 8, 1162, 13, 3580, 3770, 369, 2539, 3649, 389, 420, 1162, 323, 433, 596, 5536, 389, 23234, 323, 2890, 6787, 627, 1, 11356, 6187, 1, 7263, 810, 1109, 279, 1212, 315, 264, 502, 2305, 13, 5513, 2592, 71833, 4756, 264, 13054, 22098, 1934, 430, 279, 13814, 7301, 315, 279, 3723, 4273, 320, 3624, 1831, 2078, 8, 10165, 5597, 320, 83, 15621, 330, 16, 267, 29664, 1, 315, 279, 330, 7271, 37400, 315, 279, 7301, 909, 304, 279, 29538, 320, 4931, 8, 1162, 320, 35, 677, 1302, 348, 13, 13972, 11215, 596, 6401, 21021, 8, 17436, 279, 89846, 315, 264, 9120, 389, 54373, 1306, 220, 868, 5672, 315, 20209, 13, 510, 3624, 1831, 2078, 54501, 28802, 220, 717, 14, 16, 14, 1691, 12632, 14, 3246, 1250, 25750, 763, 65351, 1302, 11, 10504, 4691, 7683, 1831, 2078, 311, 67687, 2225, 79552, 348, 13, 43982, 320, 4468, 18, 8, 323, 47240, 50265, 348, 13, 45624, 320, 2550, 17, 705, 311, 22472, 279, 6918, 1314, 311, 20710, 11, 323, 304, 45624, 11, 279, 1314, 311, 387, 1949, 505, 91642, 23104, 304, 51582, 279, 1314, 311, 20710, 1603, 63746, 68507, 13, 510, 10031, 369, 1023, 46305, 7016, 69098, 304, 3293, 1667, 11, 19392, 430, 420, 7683, 1831, 2078, 13731, 706, 264, 7363, 1815, 369, 3815, 779, 13, 933, 1, 5451, 11, 21816, 709, 510, 2940, 60, 1981, 499, 1120, 2163, 1022, 11, 12007, 56859, 11, 389, 6220, 9167, 7016, 11, 279, 40633, 812, 304, 420, 1162, 11, 510, 40, 60, 1981, 4510, 11, 439, 4718, 43044, 14618, 704, 11, 617, 46728, 49058, 64074, 1694, 264, 3063, 477, 279, 3063, 2944, 430, 3278, 6056, 54373, 13, 358, 1053, 47032, 6220, 9167, 7016, 11, 439, 1888, 358, 3077, 1027, 3025, 311, 1505, 11, 1176, 3782, 1139, 14209, 304, 220, 2550, 24, 304, 8421, 13, 2435, 2351, 1457, 64564, 11, 323, 499, 2351, 4495, 11, 12007, 56859, 11, 430, 814, 48839, 430, 6908, 23104, 13, 358, 1053, 1101, 923, 430, 439, 311, 2001, 439, 311, 64074, 2391, 20209, 11, 358, 1053, 47032, 430, 72354, 374, 810, 15987, 323, 17049, 323, 2561, 1109, 433, 574, 520, 279, 892, 315, 79552, 477, 45624, 13, 1102, 17482, 279, 1890, 5915, 315, 10923, 3278, 311, 10491, 422, 11, 994, 11, 323, 1268, 1690, 2911, 311, 617, 1210, 1389, 54501, 28802, 304, 4799, 315, 10504, 369, 67687, 287, 79552, 323, 45624, 627, 76874, 27857, 287, 198, 70786, 1708, 6491, 320, 71216, 555, 468, 13, 14409, 8, 14238, 279, 9647, 315, 279, 5590, 11, 902, 15151, 433, 1253, 387, 264, 5597, 49448, 304, 4799, 315, 10504, 13, 3161, 279, 8857, 315, 279, 13731, 21489, 555, 9540, 79739, 11, 323, 2225, 19655, 323, 32126, 304, 4972, 11429, 11, 8965, 11, 311, 16025, 15692, 323, 463, 26928, 11, 279, 220, 21, 12, 18, 10165, 5597, 5039, 682, 315, 1884, 9540, 99463, 4702, 1238, 30230, 311, 67687, 79552, 323, 45624, 11, 449, 426, 8233, 261, 11, 328, 354, 316, 352, 269, 11, 323, 735, 16133, 279, 14091, 812, 320, 1962, 2915, 11, 24846, 99463, 4702, 1238, 570, 578, 6541, 505, 810, 18250, 311, 330, 6387, 54268, 1, 320, 64, 4068, 8965, 1511, 719, 539, 13687, 11, 34375, 649, 1101, 387, 463, 63726, 11, 5099, 6266, 374, 43426, 323, 61414, 5304, 555, 12007, 328, 354, 316, 352, 269, 1389, 330, 791, 24519, 9120, 430, 29538, 706, 2231, 304, 2035, 11, 279, 4848, 30609, 9120, 11, 279, 10092, 39701, 1071, 584, 2351, 3815, 433, 510, 331, 34869, 287, 79552, 612, 45624, 1457, 60, 1606, 584, 617, 502, 71712, 389, 279, 13814, 7301, 10246, 1, 49, 4748, 574, 83164, 13610, 5076, 505, 279, 1212, 1359, 279, 10165, 9647, 5415, 627, 2173, 3388, 11, 264, 2246, 30929, 264, 330, 16, 267, 29664, 1, 3445, 420, 9647, 323, 11, 16472, 11, 279, 5597, 5196, 11, 1436, 2349, 1990, 1457, 323, 279, 30199, 4984, 2457, 315, 279, 5150, 5597, 13, 32121, 304, 5651, 13, 94737, 5651, 220, 1544, 339, 11, 279, 1566, 1938, 315, 279, 4751, 6118, 4694, 369, 279, 1455, 20733, 1162, 11429, 627, 2149, 6491, 596, 10165, 5597, 315, 279, 5590, 29633, 430, 3268, 2682, 555, 279, 18039, 11, 719, 539, 21650, 9932, 304, 433, 320, 359, 40601, 660, 3268, 8, 2011, 387, 16917, 41976, 304, 549, 815, 13, 3925, 323, 14135, 627, 7189, 1781, 430, 430, 374, 961, 315, 433, 11, 10035, 13, 1628, 358, 1781, 11, 369, 1690, 3278, 11, 430, 374, 459, 17235, 5107, 5873, 11, 719, 433, 596, 832, 430, 420, 7301, 369, 220, 1135, 1667, 706, 15324, 2011, 387, 2163, 709, 311, 1124, 3196, 389, 872, 21463, 323, 872, 42563, 323, 872, 26314, 922, 1148, 374, 1888, 369, 279, 3388, 315, 872, 6439, 1210, 1389, 54501, 28802, 369, 304, 4799, 315, 279, 78382, 11125, 311, 67687, 58096, 29538, 20710, 2383, 627, 72603, 315, 6193, 413, 287, 315, 79552, 612, 45624, 389, 22413, 63641, 198, 15841, 3149, 2890, 6787, 1053, 387, 3917, 311, 1614, 76053, 11, 1418, 659, 50701, 6787, 527, 39028, 505, 1455, 1614, 8276, 76053, 824, 27590, 35301, 13, 320, 10031, 52683, 14046, 11252, 10181, 3495, 389, 1614, 7016, 5552, 311, 42889, 2890, 570, 578, 8276, 18921, 374, 2736, 40240, 11, 323, 430, 374, 449, 79552, 612, 45624, 35539, 13, 22413, 10401, 315, 11578, 535, 2512, 374, 65509, 304, 1193, 4848, 5415, 320, 5158, 11, 12551, 11, 11598, 11, 16691, 11, 2794, 11, 29666, 570, 578, 1396, 315, 1023, 5415, 449, 1063, 2237, 315, 11578, 535, 2512, 17294, 21986, 505, 220, 1313, 311, 220, 1627, 323, 7982, 13, 320, 10031, 52683, 14046, 11252, 10181, 3314, 11216, 8483, 570, 1442, 279, 7683, 1831, 2078, 5597, 13118, 67687, 82, 79552, 323, 45624, 11, 1884, 5415, 690, 617, 17294, 477, 48609, 304, 5457, 7214, 627, 7894, 389, 6401, 35695, 198, 15841, 3149, 6787, 690, 387, 3917, 311, 264, 1614, 2383, 49636, 10401, 11, 16785, 323, 1694, 264, 8893, 311, 459, 20710, 13, 763, 5415, 449, 48609, 477, 20020, 389, 11578, 535, 2512, 11, 1063, 23234, 527, 13126, 10396, 323, 7620, 311, 7945, 304, 17028, 367, 323, 12798, 369, 11578, 535, 2512, 304, 264, 1614, 1405, 54373, 527, 5897, 627, 12363, 50701, 6787, 527, 539, 11754, 555, 1614, 7016, 320, 20670, 527, 35319, 555, 27590, 35301, 11, 264, 6918, 2383, 279, 82847, 1614, 2383, 323, 29790, 11, 10213, 11, 3544, 23234, 311, 743, 872, 1866, 10396, 8, 49636, 11578, 535, 10401, 11, 449, 279, 4788, 315, 5415, 430, 9337, 553, 68365, 11578, 535, 2512, 13, 7570, 1243, 11, 1063, 5415, 527, 4560, 311, 636, 8469, 315, 430, 6023, 555, 665, 36022, 872, 1866, 7016, 22973, 1884, 505, 20710, 17028, 367, 58165, 13, 578, 15632, 315, 47336, 279, 1614, 7016, 690, 912, 10712, 842, 709, 304, 5590, 627, 16067, 47, 17718, 369, 78055, 535, 10852, 198, 37132, 261, 21829, 811, 369, 64815, 78055, 535, 10852, 17331, 6401, 35695, 477, 18715, 198, 20981, 21395, 23234, 690, 617, 311, 24564, 872, 6787, 6, 3268, 323, 30255, 555, 13126, 279, 2768, 512, 3957, 279, 3197, 659, 50701, 320, 269, 2237, 8, 477, 7373, 53142, 5380, 12363, 14, 3374, 50701, 6787, 690, 8965, 539, 387, 3917, 311, 279, 9120, 323, 649, 3085, 2890, 3197, 10401, 477, 71111, 369, 5944, 311, 264, 1614, 430, 5825, 11578, 535, 2512, 627, 2028, 374, 23073, 418, 9373, 13, 578, 34483, 1253, 4148, 279, 3827, 3350, 1022, 369, 5944, 369, 11578, 535, 10096, 13, 362, 3827, 3350, 12744, 1253, 2103, 387, 2561, 369, 2890, 10401, 627, 29089, 704, 8838, 21395, 20710, 369, 264, 659, 50701, 3197, 304, 264, 2204, 1614, 387, 704, 8838, 57832, 30, 2650, 690, 433, 387, 50546, 30, 4946, 1614, 51727, 3881, 304, 279, 1614, 49636, 54373, 30, 2052, 1521, 4860, 690, 1205, 36864, 323, 4250, 387, 1440, 520, 420, 6566, 627, 23956, 1614, 374, 701, 2626, 2503, 355, 5380, 845, 5415, 323, 279, 423, 732, 2637, 617, 7016, 430, 6144, 2680, 311, 11578, 535, 2512, 11, 449, 7432, 11, 27816, 323, 29666, 18667, 279, 1160, 1120, 420, 1060, 627, 32, 2077, 311, 67687, 287, 79552, 1436, 18813, 7958, 2579, 5415, 430, 527, 11, 8965, 11, 12579, 13543, 311, 9120, 477, 9067, 20710, 11, 323, 6437, 5415, 12579, 4528, 7016, 439, 279, 220, 845, 3485, 320, 300, 315, 3297, 220, 18, 11, 220, 2366, 17, 8, 311, 6144, 279, 1314, 311, 20710, 323, 11542, 505, 91642, 23104, 304, 51582, 279, 79552, 1314, 864, 8437, 79443, 627, 22186, 701, 1614, 48486, 17028, 367, 315, 11578, 535, 2512, 11, 1093, 8421, 5380, 5519, 499, 617, 8420, 389, 5091, 1341, 4577, 477, 34129, 5380, 31916, 451, 22454, 1053, 1121, 304, 1521, 8420, 539, 3515, 2680, 311, 11578, 535, 2512, 11, 1093, 659, 50701, 3197, 3697, 477, 53142, 3197, 3697, 304, 5415, 22973, 279, 1314, 311, 11578, 535, 2512, 627, 38275, 3508, 311, 3085, 459, 3072, 369, 1884, 8420, 4669, 832, 315, 279, 5528, 14407, 3770, 627, 8538, 5415, 690, 1005, 1614, 24853, 34129, 311, 17452, 11578, 535, 2512, 369, 1884, 2085, 2680, 320, 5158, 11, 42416, 11, 11598, 11, 16691, 11, 14306, 11, 12551, 11, 2794, 11, 612, 29666, 4390, 5519, 499, 617, 8420, 389, 279, 43606, 10852, 3298, 596, 1614, 19224, 58358, 320, 68, 1326, 2637, 73295, 7188, 87527, 914, 5415, 9067, 8276, 10401, 1524, 304, 879, 8276, 6787, 11, 2737, 1884, 1555, 279, 19224, 627, 38275, 422, 499, 1053, 1390, 264, 4947, 311, 2686, 279, 1205, 369, 1521, 8420, 627, 11787, 499, 264, 586, 19683, 5380, 1313, 5415, 9067, 10401, 369, 586, 8420, 627, 32664, 58358, 11, 5091, 1341, 4577, 11, 31822, 612, 34129, 64815, 315, 78055, 535, 10852, 374, 1322, 93617, 198, 791, 65439, 22454, 59538, 1005, 315, 6918, 10736, 369, 20710, 15851, 315, 279, 2704, 315, 79552, 11, 45624, 612, 1614, 2383, 320, 62852, 369, 17199, 11, 43980, 11, 323, 38037, 479, 315, 6691, 596, 2890, 570, 578, 4360, 315, 889, 690, 2343, 369, 54373, 690, 3719, 810, 6485, 1288, 7683, 1831, 2078, 67687, 79552, 11, 11889, 279, 5597, 439, 311, 89846, 315, 20710, 1855, 1614, 13, 320, 49, 4748, 6244, 2383, 304, 220, 4468, 17, 85439, 311, 4148, 279, 5415, 6, 11140, 1816, 315, 3268, 311, 11578, 535, 2512, 323, 12625, 304, 42889, 2890, 323, 7342, 2585, 29275, 47, 17718, 369, 18589, 369, 78055, 535, 10852, 198, 8607, 3544, 23234, 617, 13605, 872, 14944, 320, 269, 2736, 617, 10487, 1778, 4947, 304, 2077, 311, 279, 8421, 2383, 44977, 304, 220, 2366, 16, 8, 311, 96260, 549, 815, 13, 8420, 320, 438, 17446, 6904, 812, 304, 1063, 5157, 8, 709, 311, 400, 19, 11, 931, 304, 5944, 18512, 320, 68, 1326, 2637, 14484, 11, 82035, 11, 28712, 7586, 88, 728, 11, 8339, 11, 5195, 11, 56141, 94511, 11, 426, 23568, 11, 18002, 75758, 11, 323, 86414, 311, 836, 264, 2478, 570, 3700, 279, 15774, 38493, 6247, 3857, 220, 11702, 11, 5944, 323, 77747, 527, 98678, 1759, 481, 6593, 18512, 13, 578, 60428, 374, 21989, 555, 279, 6918, 3109, 13, 13440, 279, 282, 6910, 690, 2187, 71111, 315, 1778, 5944, 18512, 311, 5371, 1148, 264, 1614, 1253, 82577, 12079, 1436, 617, 73443, 16296, 369, 902, 433, 374, 2288, 5246, 311, 10765, 323, 64601, 627, 2520, 3187, 1389, 578, 34483, 1587, 539, 11810, 3827, 12862, 10401, 315, 1614, 12, 36009, 13018, 8717, 65509, 311, 387, 9076, 19683, 64650, 2890, 10401, 279, 1890, 439, 264, 32080, 13, 6104, 279, 1614, 690, 539, 3827, 430, 10401, 11, 279, 34483, 1587, 0, 4946, 279, 34483, 656, 279, 1890, 449, 60428, 220, 11702, 30, 1322, 66917, 3827, 12862, 5944, 369, 1148, 374, 25660, 12079, 304, 279, 19504, 1614, 30, 2582, 11, 690, 1193, 1614, 51727, 387, 40028, 30, 12411, 2383, 690, 539, 7124, 330, 69216, 18512, 1, 311, 2980, 1614, 2383, 5897, 6593, 16346, 30, 8442, 892, 690, 3371, 13, 2893, 2771, 499, 527, 8667, 709, 369, 279, 2009, 402, 1468, 5856, 3754, 30350, 779, 430, 499, 690, 387, 16369, 315, 4442, 304, 279, 2383, 28987, 701, 2890, 6787, 323, 41734, 369, 3827, 1949, 5944, 18512, 369, 10096, 315, 11578, 535, 2512, 627, 37132, 261, 14908, 369, 10323, 50701, 9878, 56769, 315, 4470, 8838, 87615, 78055, 535, 10852, 18589, 198, 1858, 2336, 323, 38864, 430, 1391, 49895, 264, 4947, 315, 10209, 6020, 323, 5255, 17028, 367, 7194, 369, 11578, 535, 2512, 2997, 512, 38, 2177, 5352, 16498, 311, 5766, 682, 2890, 3197, 477, 6593, 20900, 5718, 627, 2028, 3072, 1053, 3827, 279, 9548, 323, 374, 17395, 555, 4819, 5552, 311, 83832, 287, 1023, 7720, 5552, 311, 8070, 323, 40240, 3851, 315, 10396, 430, 1436, 5101, 68763, 627, 61524, 264, 71111, 1555, 264, 6401, 1050, 318, 52173, 18925, 57733, 477, 1023, 659, 50701, 3197, 627, 45, 2159, 87013, 7649, 1053, 2103, 3881, 627, 2746, 279, 34483, 312, 58143, 6593, 20900, 369, 10096, 315, 3827, 12862, 60428, 220, 11702, 96260, 1392, 311, 2980, 89846, 315, 279, 10537, 11, 420, 1253, 1391, 49895, 420, 3072, 627, 4054, 7394, 12306, 369, 279, 5944, 323, 2853, 315, 10537, 304, 264, 1614, 62174, 11578, 535, 2512, 627, 2028, 3072, 690, 1121, 304, 264, 5190, 51727, 430, 264, 20547, 709, 323, 1436, 3118, 279, 1890, 11341, 315, 97249, 477, 21934, 627, 2746, 279, 659, 50701, 3197, 28727, 311, 1629, 682, 10537, 323, 5944, 7194, 1555, 279, 3197, 11, 439, 904, 1023, 6593, 18512, 11, 814, 690, 2103, 1205, 311, 7124, 279, 8935, 627, 36349, 311, 4320, 994, 27409, 459, 11578, 535, 2512, 8935, 2997, 512, 3923, 527, 279, 13693, 11, 3878, 11, 5099, 13, 5380, 2746, 1701, 459, 473, 5726, 1646, 11, 1148, 1053, 71111, 1427, 1093, 5380, 11787, 499, 6376, 709, 459, 4553, 502, 473, 5726, 1120, 369, 1521, 10096, 5380, 10149, 433, 387, 18751, 449, 459, 66038, 11733, 60952, 2890, 3197, 5380, 11787, 3197, 9477, 323, 1023, 2890, 3197, 8907, 11193, 6646, 5380, 10149, 7432, 33, 5726, 1205, 311, 387, 9076, 5380, 26198, 3314, 27820, 25368, 311, 78055, 535, 10852, 198, 46237, 11, 279, 25378, 39856, 323, 279, 220, 2366, 16, 8421, 2383, 1903, 433, 264, 8431, 9977, 369, 904, 1732, 46927, 279, 20895, 5333, 449, 5944, 311, 5371, 459, 20710, 13, 1115, 3445, 11, 23234, 1436, 13893, 3663, 24305, 369, 68365, 5944, 311, 2500, 1614, 4669, 8405, 279, 5944, 10736, 477, 2890, 3197, 10401, 311, 3493, 11578, 535, 2512, 13, 2030, 5415, 527, 304, 264, 8209, 311, 3060, 6144, 701, 3268, 832, 1648, 477, 2500, 11, 11911, 389, 902, 3185, 499, 16025, 627, 644, 2077, 311, 58096, 1614, 7016, 304, 8421, 11, 25378, 11, 323, 29538, 323, 304, 2077, 311, 279, 65351, 1302, 11, 1063, 5415, 527, 4737, 1957, 311, 1304, 872, 5224, 439, 311, 279, 89846, 315, 20710, 304, 430, 1614, 422, 79552, 323, 45624, 1051, 311, 387, 69098, 13, 763, 7188, 11, 26313, 220, 8011, 17, 320, 8370, 690, 387, 20669, 304, 279, 93666, 13093, 389, 3297, 220, 24, 8, 374, 264, 6767, 430, 1053, 3493, 11006, 369, 704, 8838, 21395, 11062, 889, 1253, 5944, 1070, 369, 11578, 535, 2512, 13, 23212, 11, 7188, 39856, 374, 3318, 389, 264, 4121, 430, 1053, 6144, 1884, 889, 28696, 5944, 311, 279, 1614, 369, 1778, 2512, 13, 2650, 279, 19359, 690, 3790, 279, 51551, 5897, 11774, 374, 12266, 311, 1440, 1418, 682, 1521, 11193, 527, 2103, 1694, 6646, 13, 320, 14953, 28406, 706, 264, 4528, 2383, 311, 7188, 1101, 3318, 1202, 1648, 1555, 39856, 29275, 26054, 11, 304, 9784, 11, 279, 2360, 15545, 15996, 82, 369, 88981, 36565, 15050, 2191, 3298, 690, 48486, 23234, 505, 98678, 1759, 287, 477, 12798, 6089, 369, 5944, 18512, 311, 733, 704, 8838, 21395, 311, 5371, 11578, 535, 2512, 627, 1, 10149, 420, 15244, 18167, 279, 357, 20345, 430, 420, 11705, 304, 279, 586, 21063, 430, 279, 18039, 323, 1202, 5403, 527, 1120, 5054, 14385, 7673, 1389, 12007, 328, 354, 316, 352, 269, 198, 36064, 374, 66836, 3156, 279, 5597, 374, 37402, 6004, 13, 5884, 79482, 315, 7016, 311, 2586, 11, 6372, 315, 1510, 11, 3629, 45548, 61386, 660, 7016, 11, 323, 1524, 279, 15632, 315, 279, 7683, 1831, 2078, 5597, 304, 29538, 11, 374, 66836, 13, 6193, 413, 287, 79552, 323, 45624, 690, 38048, 617, 38413, 6372, 4028, 1690, 6956, 315, 1057, 6439, 11, 2737, 19683, 4947, 11, 51727, 11, 2890, 2512, 11, 6691, 323, 31383, 29528, 11, 28989, 315, 1690, 3278, 323, 3674, 21976, 627, 63717, 11, 8907, 389, 13, 44840, 315, 902, 2361, 459, 19683, 690, 1935, 11, 433, 374, 3062, 311, 2980, 279, 1690, 8907, 7016, 430, 690, 2586, 1139, 1514, 994, 10917, 304, 2035, 904, 7720, 477, 3827, 1481, 51565, 1639, 7620, 13, 31966, 449, 701, 8420, 323, 3815, 779, 449, 27541, 4250, 387, 927, 10655, 13, 1102, 649, 3665, 264, 2763, 315, 55403, 13, 9176, 7016, 690, 2997, 264, 5406, 17575, 4999, 38275, 42247, 449, 27541, 13, 3277, 25394, 264, 16614, 8712, 1093, 20710, 11, 1070, 374, 13118, 279, 29736, 4423, 1436, 636, 54221, 477, 617, 3831, 18463, 13, 9934, 311, 387, 5030, 315, 2144, 4856, 1109, 3515, 459, 9647, 477, 3339, 264, 20212, 439, 422, 433, 374, 264, 3967, 3245, 13, 1789, 3187, 11, 4619, 315, 5605, 330, 791, 51215, 315, 79552, 690, 387, 69098, 1210, 21829, 330, 3624, 1831, 2078, 10165, 9647, 53100, 37400, 69098, 79552, 1210, 2582, 11, 330, 1271, 10150, 8420, 8738, 2680, 311, 11578, 535, 2512, 11, 72189, 374, 2561, 1210, 2876, 11, 330, 1271, 2187, 8420, 311, 10368, 872, 1314, 311, 54373, 1981, 1210, 1102, 1253, 387, 5922, 3794, 8469, 315, 279, 10652, 449, 701, 9548, 7187, 422, 499, 617, 264, 38462, 1405, 420, 1253, 5353, 1063, 14322, 98563, 304, 279, 32027, 13, 1115, 374, 4216, 3686, 13, 2684, 374, 264, 2763, 311, 387, 3967, 323, 11429, 3686, 311, 387, 1903, 13, 7281, 1873, 1418, 20646, 374, 2744, 264, 5222, 5603, 13, 6914, 603, 1440, 1268, 584, 649, 1520, 4999, 24581, 1520, 30, 21445, 388, 1288, 8666, 264, 3827, 323, 14740, 14065, 311, 24564, 872, 30255, 323, 3268, 13, 1789, 682, 701, 8276, 4860, 11, 2009, 402, 1468, 5856, 374, 701, 22542, 37713, 323, 1618, 311, 1520, 499, 5388, 553, 1268, 311, 1888, 29166, 2561, 5070, 323, 7720, 13, 14998, 264, 3827, 477, 14740, 14065, 30, 6914, 603, 1440, 0, 1226, 617, 15236, 40705, 449, 1948, 78611, 29054, 31434, 627, 370, 26973, 3268, 47799, 535, 2512, 12393, 3197, 20710, 3504, 1435, 4748, 348, 289, 1037, 3624, 1831, 2078, 128000, 4451, 9277, 389, 25820, 304, 279, 10948, 11896, 4319, 6468, 369, 220, 17, 4207, 323, 1253, 539, 5387, 279, 6875, 13, 4204, 25, 42904, 1253, 1817, 704, 872, 1866, 21137, 7384, 477, 2500, 596, 555, 3361, 8041, 13, 5321, 8464, 311, 279, 25820, 6274, 3459, 369, 62781, 2038, 627, 791, 25820, 11348, 54068, 4920, 279, 2532, 18496, 304, 1650, 1396, 2015, 13, 7281, 26692, 527, 4691, 311, 1715, 21137, 3673, 369, 1817, 704, 555, 1650, 1396, 320, 8370, 1253, 387, 1766, 555, 18965, 389, 279, 330, 6014, 3388, 30600, 1, 2723, 304, 480, 1750, 11, 279, 10211, 52, 55612, 16808, 570, 128000, 42, 9729, 44, 2871, 11, 84320, 19645, 198, 52337, 315, 622, 88139, 612, 50280, 25, 41169, 477, 47847, 367, 5380, 1956, 25, 6287, 220, 22, 11, 220, 679, 24, 7279, 25, 2468, 360, 4241, 587, 220, 1806, 18149, 198, 1945, 25, 26475, 8612, 198, 15327, 47, 6197, 3109, 315, 6890, 389, 7159, 84347, 279, 3361, 2704, 315, 1202, 1193, 10451, 8857, 17271, 622, 88139, 323, 50280, 1555, 4101, 315, 13621, 10373, 323, 92640, 324, 66, 660, 279, 1614, 1139, 1403, 11552, 39543, 1306, 23391, 4686, 51235, 304, 279, 34681, 555, 11889, 9214, 315, 17312, 11, 49941, 2917, 69, 28844, 11, 84866, 8431, 323, 5054, 6164, 11, 9482, 2518, 682, 20362, 315, 17320, 323, 555, 6968, 459, 16975, 315, 31069, 8850, 11, 28013, 323, 22047, 32620, 19392, 430, 279, 14771, 315, 279, 27800, 374, 7554, 304, 420, 20716, 5797, 10368, 13, 6104, 1690, 21391, 7904, 6164, 64895, 279, 5597, 439, 18526, 369, 279, 52482, 17025, 315, 6890, 719, 1690, 50280, 72, 20071, 2733, 65397, 323, 78778, 323, 527, 20910, 422, 814, 1903, 264, 18526, 1529, 8154, 555, 63686, 279, 1403, 5392, 367, 10334, 13, 1102, 374, 34707, 430, 264, 7140, 430, 3131, 21095, 779, 77849, 2403, 8013, 4879, 311, 22497, 1202, 41021, 1778, 439, 50120, 389, 10597, 5238, 374, 5737, 279, 1890, 14289, 1847, 449, 1202, 1866, 1274, 889, 617, 19755, 5675, 10082, 304, 433, 4245, 311, 92947, 519, 34568, 1147, 24950, 505, 46072, 13552, 3252, 315, 16374, 311, 1948, 12127, 315, 12345, 7167, 16689, 17047, 13, 763, 279, 4339, 315, 459, 84629, 14584, 1122, 32034, 2206, 76909, 4235, 330, 13461, 422, 13659, 220, 14648, 1051, 311, 387, 84347, 11, 279, 14050, 311, 11857, 622, 88139, 323, 50280, 596, 2704, 311, 9323, 49187, 11, 1524, 422, 28191, 11, 374, 6319, 311, 2854, 35950, 459, 2736, 1207, 48802, 660, 7187, 13, 2650, 33304, 264, 10451, 30801, 1614, 6866, 304, 6890, 30, 50280, 649, 1457, 539, 1524, 387, 22542, 311, 387, 264, 1614, 13, 578, 70985, 315, 420, 6767, 374, 539, 18052, 11, 433, 374, 72818, 11, 315, 264, 6710, 449, 27545, 323, 80304, 11489, 66697, 311, 40804, 315, 872, 2035, 304, 6890, 10246, 12834, 279, 11527, 520, 6832, 387, 6536, 682, 420, 574, 2884, 35256, 279, 3109, 315, 6890, 11, 814, 617, 2884, 539, 1193, 459, 25912, 50256, 5674, 311, 279, 16044, 315, 420, 35544, 719, 617, 1101, 45877, 433, 439, 264, 7140, 430, 1375, 21168, 304, 15061, 21300, 1903, 311, 1202, 1866, 1274, 13, 2052, 420, 1288, 539, 2586, 439, 264, 13051, 2728, 430, 279, 1274, 889, 3952, 420, 60883, 5597, 2586, 505, 264, 538, 315, 36142, 31714, 11514, 288, 889, 617, 1027, 35901, 76588, 520, 4737, 11429, 5986, 20653, 3012, 291, 520, 1888, 323, 304, 62421, 20631, 520, 12047, 13, 18056, 1521, 6680, 1074, 3196, 272, 20603, 6445, 288, 35256, 1193, 220, 605, 12, 868, 4, 315, 279, 7904, 7187, 719, 617, 1027, 68366, 323, 71701, 279, 70934, 315, 279, 1207, 35172, 14168, 2533, 1317, 555, 63614, 586, 9647, 1701, 43510, 26411, 315, 57937, 35242, 11, 15256, 55608, 11, 503, 29008, 2191, 11, 5099, 323, 1555, 872, 66275, 398, 12491, 44440, 4546, 21648, 323, 834, 265, 8660, 311, 279, 4459, 7140, 13, 1442, 832, 1051, 311, 49586, 279, 8603, 4920, 682, 20733, 11, 71580, 323, 57937, 11429, 4529, 304, 6890, 927, 279, 1566, 1403, 24552, 11, 4661, 682, 1053, 74614, 2586, 704, 311, 617, 1027, 4529, 477, 46036, 555, 4423, 505, 420, 33956, 398, 927, 2320, 309, 43868, 323, 44081, 13987, 538, 13, 320, 998, 617, 264, 2731, 8830, 315, 872, 18526, 98753, 1238, 11, 832, 374, 26160, 311, 1373, 279, 43422, 315, 2999, 13, 31930, 318, 969, 78, 3383, 2788, 29234, 570, 1628, 1457, 814, 617, 83675, 291, 66592, 389, 50280, 13, 2435, 2873, 311, 10894, 430, 1418, 17047, 2586, 323, 733, 719, 3738, 98753, 1238, 617, 61555, 311, 21830, 10980, 17089, 627, 791, 60466, 315, 279, 50280, 4185, 8660, 7058, 34648, 2751, 24589, 505, 8013, 6037, 304, 220, 6393, 22, 719, 26907, 574, 17071, 291, 1139, 1403, 17089, 32125, 6890, 323, 17076, 13, 9636, 279, 17071, 3197, 11, 36142, 8857, 5789, 315, 8013, 6890, 1051, 311, 35256, 6890, 323, 279, 10451, 8857, 5789, 1051, 311, 35256, 17076, 13, 73436, 315, 82660, 989, 5415, 315, 279, 1207, 75695, 1051, 2728, 279, 5873, 315, 3060, 1046, 16490, 311, 904, 315, 1521, 1403, 11358, 919, 477, 7293, 9678, 719, 1051, 26160, 311, 2567, 304, 4059, 872, 1274, 596, 25223, 323, 54001, 13463, 13, 50280, 574, 264, 10451, 8857, 1614, 11, 320, 300, 824, 220, 6393, 16, 44702, 8, 719, 433, 1047, 264, 36142, 31714, 356, 5642, 53690, 19580, 889, 15453, 4934, 311, 7293, 9678, 13, 2030, 60199, 264, 463, 12, 34648, 37300, 304, 279, 49080, 596, 19451, 11, 17076, 19755, 51157, 459, 30215, 555, 40489, 80592, 889, 5246, 17439, 13057, 39543, 902, 527, 1457, 61937, 439, 17076, 25366, 50280, 13, 578, 22743, 42728, 9890, 6342, 4691, 369, 6890, 596, 1520, 902, 28478, 1461, 315, 6411, 1520, 719, 389, 279, 3044, 430, 568, 1046, 15686, 311, 279, 7904, 11358, 290, 13, 4740, 568, 7378, 11, 7904, 17312, 1051, 73973, 398, 3805, 2922, 2130, 291, 311, 279, 17271, 323, 279, 4498, 315, 279, 6864, 328, 26355, 38812, 574, 32098, 719, 96380, 21168, 1990, 7904, 8603, 323, 17076, 22126, 80592, 8738, 369, 2478, 4038, 3156, 6890, 16495, 279, 21623, 315, 3723, 19687, 627, 32, 11175, 320, 2618, 8, 30105, 220, 1691, 5936, 220, 6393, 23, 5946, 555, 6781, 9849, 369, 6890, 323, 17076, 2663, 369, 14247, 82873, 323, 2486, 3748, 277, 2065, 315, 279, 17271, 779, 430, 264, 7245, 65, 3510, 635, 2643, 1935, 2035, 311, 8417, 279, 690, 315, 50280, 72, 1274, 13, 578, 30836, 315, 279, 8603, 555, 2225, 11314, 4869, 2646, 7077, 323, 6463, 279, 7245, 65, 3510, 635, 1606, 6890, 4934, 459, 97929, 30836, 315, 8603, 1234, 902, 17076, 1047, 311, 15142, 1176, 389, 279, 2944, 430, 433, 574, 459, 13632, 269, 13, 17076, 1550, 539, 7655, 311, 420, 323, 30526, 264, 50715, 304, 6514, 902, 315, 3388, 574, 18010, 555, 6890, 627, 12834, 1243, 5370, 25243, 555, 17876, 6781, 74051, 2737, 1884, 555, 4584, 16589, 3948, 263, 323, 64795, 617, 1027, 18010, 555, 6890, 323, 17076, 1234, 5370, 55586, 13, 58795, 80865, 6890, 1101, 671, 71, 1105, 25243, 315, 54708, 323, 77673, 304, 420, 26086, 1524, 3582, 433, 842, 23242, 54708, 439, 264, 1749, 369, 17516, 315, 682, 6625, 42254, 304, 1202, 16812, 320, 17064, 220, 3971, 570, 4740, 29319, 287, 72629, 64532, 320, 1820, 12801, 9675, 315, 50280, 8, 304, 220, 6280, 18, 11, 7904, 3109, 95536, 279, 50280, 13345, 311, 459, 13112, 430, 3432, 433, 706, 3719, 279, 1455, 62533, 1534, 10353, 304, 279, 1917, 449, 1202, 14708, 1694, 1234, 279, 6926, 38494, 315, 279, 17903, 8603, 13, 6890, 10423, 1101, 19167, 1202, 17903, 8603, 449, 1778, 13057, 323, 93803, 1122, 13736, 320, 8154, 2204, 15312, 811, 1093, 20479, 88292, 5099, 8, 539, 62113, 1524, 555, 279, 8013, 13309, 63620, 304, 6890, 2391, 279, 37683, 6037, 13, 2684, 617, 1101, 1027, 18873, 555, 50280, 72, 48011, 82, 430, 6890, 706, 36192, 81173, 16374, 304, 50280, 323, 555, 3815, 779, 706, 15164, 50280, 285, 872, 26623, 3268, 627, 34996, 5292, 315, 279, 35468, 3556, 3314, 315, 622, 88139, 612, 50280, 1234, 6890, 198, 27831, 50280, 574, 5535, 3156, 1457, 311, 617, 1202, 1866, 16812, 323, 5292, 719, 279, 6926, 21623, 555, 279, 10913, 3109, 304, 279, 27743, 22747, 315, 622, 88139, 323, 50280, 374, 912, 8340, 2144, 13, 4212, 323, 1578, 3314, 17047, 304, 50280, 617, 1027, 27292, 520, 70205, 323, 282, 32737, 315, 279, 8792, 3109, 1234, 28830, 55586, 13, 1050, 43733, 82, 369, 279, 56767, 62407, 617, 1101, 1027, 23540, 369, 264, 44387, 892, 13, 1628, 1457, 433, 706, 1027, 1903, 264, 9323, 49187, 323, 690, 387, 27800, 6089, 555, 279, 8792, 3109, 304, 902, 50280, 285, 690, 617, 2697, 2019, 422, 912, 2019, 13, 3861, 1288, 5895, 422, 1778, 264, 1887, 374, 12153, 311, 990, 304, 452, 1182, 315, 22767, 320, 2940, 1070, 374, 264, 3663, 12744, 1990, 279, 39856, 323, 10913, 10423, 4661, 389, 264, 7446, 8197, 8, 1243, 1268, 433, 690, 990, 304, 50280, 1405, 586, 9647, 374, 2736, 9234, 295, 449, 834, 2715, 12181, 627, 25729, 1070, 6866, 7631, 315, 659, 1773, 82137, 304, 50280, 5380, 3947, 374, 912, 10712, 430, 2533, 220, 6393, 22, 11, 50280, 706, 1027, 8126, 299, 2230, 304, 264, 2294, 59322, 449, 11758, 315, 29536, 323, 88438, 3794, 7577, 30171, 2391, 3663, 12744, 449, 279, 17903, 8603, 63620, 1070, 13, 34199, 266, 380, 19567, 617, 1101, 1027, 4642, 304, 279, 50280, 13345, 2533, 1317, 323, 439, 824, 4033, 17989, 11, 9349, 69239, 1113, 505, 1521, 19567, 706, 7577, 9214, 315, 7931, 13, 578, 3293, 18639, 3440, 304, 35962, 86, 3105, 902, 7577, 927, 220, 1135, 6411, 48830, 574, 832, 24059, 4101, 315, 1023, 1778, 4455, 9204, 430, 682, 374, 539, 1664, 304, 50280, 439, 706, 1027, 11922, 555, 50024, 17047, 13, 9176, 5526, 7904, 6164, 1093, 23720, 575, 81, 95095, 29853, 44957, 617, 30447, 26579, 279, 13345, 596, 834, 2715, 12181, 7119, 6890, 13, 763, 279, 4339, 315, 23720, 575, 81, 95095, 29853, 44957, 4235, 198, 1, 3915, 682, 279, 2038, 358, 617, 11, 220, 2721, 3346, 315, 50280, 20071, 656, 539, 6562, 311, 387, 477, 7293, 7904, 10495, 13, 358, 10712, 9093, 279, 24278, 315, 4560, 311, 2567, 1274, 555, 5457, 1405, 814, 656, 539, 6562, 311, 4822, 13, 1115, 4250, 719, 617, 6129, 1317, 9860, 5054, 16296, 11, 3582, 7214, 433, 1253, 7937, 4947, 323, 4587, 586, 9647, 10246, 97846, 6051, 1524, 279, 7904, 24245, 315, 50280, 13479, 88, 391, 278, 73320, 26579, 430, 50280, 285, 617, 5675, 10082, 304, 279, 26623, 1920, 439, 16374, 304, 50280, 617, 1027, 81173, 13, 35802, 505, 420, 11, 5370, 6821, 315, 279, 6781, 323, 11344, 10734, 1219, 5287, 389, 9770, 32153, 3095, 11, 3148, 69246, 11, 96330, 323, 50162, 304, 50280, 11203, 12743, 279, 8349, 315, 4725, 11377, 13, 2052, 1521, 13363, 20259, 279, 5811, 430, 1070, 374, 264, 7631, 369, 659, 1773, 82137, 304, 50280, 1555, 1202, 21261, 323, 7036, 4250, 387, 439, 12525, 2692, 304, 19821, 315, 22622, 23925, 311, 430, 2515, 13, 23674, 11, 50280, 706, 1027, 19487, 7245, 65, 3510, 635, 555, 7000, 1023, 1109, 279, 3723, 19687, 627, 25729, 50280, 69001, 279, 5137, 315, 659, 1773, 82137, 1234, 7327, 7658, 5380, 12363, 1773, 82137, 1234, 7327, 2383, 706, 3719, 264, 67600, 4360, 1521, 2919, 449, 2294, 6811, 1990, 279, 5439, 2383, 323, 279, 12659, 315, 279, 5415, 13, 61695, 5370, 6625, 20038, 323, 45593, 2737, 6781, 49705, 11, 59332, 6616, 323, 19845, 1600, 9150, 44917, 279, 1314, 311, 659, 26314, 439, 459, 56193, 1314, 719, 304, 6725, 5415, 617, 19029, 90833, 420, 15507, 389, 872, 10437, 690, 323, 8965, 282, 4935, 5304, 904, 4879, 315, 659, 1773, 82137, 5423, 9434, 659, 1773, 82137, 320, 19171, 3967, 439, 14560, 5574, 25947, 306, 659, 1773, 82137, 8, 555, 904, 5502, 1234, 872, 7524, 2585, 323, 44592, 13, 40741, 6625, 9676, 388, 323, 45593, 3137, 922, 279, 1314, 315, 659, 1773, 82137, 323, 15324, 433, 439, 264, 73348, 7617, 1093, 1314, 36376, 64, 8019, 4978, 320, 1315, 49009, 311, 682, 570, 13659, 220, 16, 315, 279, 6781, 49705, 85775, 1154, 10323, 9607, 82137, 439, 459, 16945, 315, 279, 3723, 19687, 369, 279, 48513, 4435, 26888, 13, 26778, 43595, 315, 6781, 2737, 38216, 220, 9690, 19, 315, 220, 5162, 15, 323, 49517, 32467, 89375, 315, 220, 4468, 15, 64523, 279, 1314, 315, 659, 1773, 82137, 315, 1274, 13, 49517, 32467, 42021, 706, 555, 3117, 1027, 279, 1455, 16195, 28664, 2987, 315, 279, 7434, 315, 10323, 9607, 82137, 323, 57133, 264, 6928, 29672, 389, 1475, 1614, 311, 12192, 279, 17966, 315, 659, 1773, 82137, 315, 1274, 13, 1102, 1101, 57133, 264, 8389, 29672, 389, 1475, 1614, 311, 58608, 505, 1884, 6299, 902, 36980, 535, 279, 1274, 315, 872, 1314, 311, 10323, 9607, 82137, 323, 11542, 13, 35339, 11, 1403, 1023, 3062, 6625, 45593, 32125, 59332, 6616, 323, 19845, 1600, 9150, 1101, 3137, 922, 420, 1314, 323, 3493, 430, 682, 1274, 617, 279, 1314, 311, 659, 1773, 82137, 323, 5415, 902, 527, 9875, 311, 279, 65004, 617, 264, 14523, 311, 12192, 433, 13, 18056, 6890, 374, 264, 4717, 311, 1521, 272, 16651, 1821, 11, 433, 1903, 3738, 41162, 323, 62411, 659, 1773, 82137, 1193, 304, 279, 1654, 73369, 2065, 49340, 323, 1101, 14610, 430, 433, 11815, 279, 659, 1773, 82137, 315, 1193, 1884, 1274, 889, 527, 1234, 7362, 55949, 323, 539, 315, 264, 3857, 315, 1274, 5496, 1234, 46384, 9678, 5415, 13, 1102, 374, 11846, 430, 6890, 1903, 1521, 41162, 10494, 304, 4059, 279, 5370, 513, 26540, 380, 19567, 389, 1202, 1866, 17614, 323, 5423, 449, 24886, 311, 279, 50280, 4360, 627, 13317, 535, 323, 55389, 6492, 12, 1115, 5825, 430, 264, 1912, 311, 35256, 1274, 2011, 3917, 3210, 2733, 430, 433, 374, 2204, 505, 279, 2800, 315, 279, 40771, 315, 279, 6691, 1614, 323, 433, 1288, 1101, 27651, 279, 16945, 13186, 315, 60157, 304, 3878, 315, 1202, 18455, 11, 57978, 11, 4221, 11, 7829, 11, 4221, 11, 13901, 11, 5099, 13, 1666, 374, 30576, 505, 5370, 6821, 323, 7978, 11, 8857, 315, 50280, 285, 656, 2733, 3917, 3210, 2204, 505, 279, 2800, 315, 6890, 323, 60157, 315, 50280, 706, 1027, 15324, 19073, 555, 279, 7904, 3109, 779, 1790, 779, 430, 50280, 574, 5535, 3156, 1457, 311, 617, 264, 8821, 16812, 323, 5292, 323, 2728, 7191, 51360, 1109, 1023, 7904, 5415, 13, 3075, 3210, 1101, 279, 60157, 315, 50280, 304, 3878, 315, 1202, 18455, 320, 16966, 467, 788, 25911, 705, 57978, 320, 42, 1003, 20531, 72, 705, 4221, 320, 42, 1003, 20531, 72, 705, 7829, 320, 42, 1003, 20531, 72, 705, 13901, 320, 1762, 1773, 8129, 18007, 10451, 8, 374, 539, 264, 55026, 2144, 13, 15636, 50280, 285, 649, 387, 1071, 311, 387, 50698, 279, 44122, 323, 16945, 37057, 315, 1274, 889, 649, 10368, 279, 1314, 311, 659, 1773, 82137, 627, 5005, 73369, 2065, 70288, 4235, 9636, 7327, 2383, 7631, 315, 659, 1773, 82137, 374, 35516, 1193, 304, 279, 1162, 315, 1654, 73369, 2065, 49340, 323, 304, 1063, 5157, 23540, 1654, 73369, 2065, 49340, 13, 2057, 12391, 430, 6890, 374, 264, 15235, 4954, 2410, 304, 50280, 374, 264, 5107, 3465, 323, 810, 779, 994, 50280, 285, 4774, 1890, 3268, 323, 58165, 439, 2800, 315, 279, 30507, 1234, 279, 2383, 315, 279, 4363, 72665, 5015, 50446, 13, 18056, 433, 374, 13882, 11846, 430, 50280, 285, 1541, 956, 1390, 311, 7293, 304, 6890, 477, 430, 814, 1390, 311, 5249, 17076, 719, 304, 19821, 315, 904, 31744, 11, 7245, 65, 3510, 635, 477, 30798, 311, 430, 2515, 433, 374, 5107, 311, 77277, 279, 9647, 315, 279, 8857, 13, 4452, 11, 1070, 374, 912, 41566, 430, 1690, 50280, 285, 5363, 6890, 439, 459, 72280, 5457, 323, 1890, 649, 387, 28823, 304, 279, 7446, 23170, 11, 75028, 1147, 11, 10581, 5104, 11, 7294, 12, 34648, 36049, 2194, 4776, 323, 9998, 2320, 301, 1303, 389, 7904, 8603, 63620, 304, 50280, 682, 315, 902, 706, 3719, 264, 14348, 31017, 1457, 13, 13596, 3062, 2144, 430, 25930, 61225, 374, 279, 24047, 315, 927, 220, 5067, 931, 7904, 28058, 48830, 304, 50280, 449, 13057, 93803, 1122, 13736, 13, 24805, 586, 9647, 304, 50280, 1027, 37805, 349, 7119, 6890, 11, 433, 1053, 539, 617, 594, 13909, 311, 1521, 14560, 7504, 323, 27639, 11193, 627, 52502, 1960, 532, 65907, 12, 549, 10462, 42145, 307, 295, 285, 374, 264, 622, 355, 3623, 19059, 7617, 304, 7327, 2383, 323, 5961, 907, 872, 52482, 17025, 810, 1109, 4205, 775, 719, 279, 98883, 3488, 1618, 374, 649, 264, 3224, 1304, 279, 5811, 315, 52482, 17025, 9002, 264, 37545, 55026, 18455, 13, 3053, 682, 4860, 9002, 279, 1023, 1455, 3062, 622, 355, 3623, 19059, 40851, 1093, 11344, 3268, 11, 8431, 323, 5054, 31220, 387, 559, 28736, 1022, 555, 279, 17983, 3802, 315, 549, 10462, 9483, 3746, 307, 295, 285, 30, 1115, 7995, 374, 539, 304, 26306, 449, 279, 9090, 315, 3723, 19687, 323, 5370, 7327, 272, 16651, 1821, 2737, 59332, 6616, 323, 19845, 1600, 9150, 430, 24906, 478, 2740, 64523, 279, 81171, 16565, 315, 26581, 8431, 323, 5054, 3268, 304, 18859, 449, 279, 16565, 315, 11344, 10734, 323, 279, 690, 315, 279, 1274, 13, 50280, 374, 38048, 264, 55026, 18455, 1234, 279, 3008, 14630, 315, 7327, 2383, 323, 14188, 6890, 6463, 17076, 649, 26741, 1022, 279, 3488, 315, 1202, 659, 1773, 82137, 555, 279, 6105, 315, 549, 10462, 9483, 3746, 307, 295, 285, 477, 52482, 17025, 13, 7429, 11, 433, 5084, 2288, 3117, 66, 950, 311, 3802, 304, 420, 6617, 18250, 323, 1772, 17515, 944, 1917, 430, 549, 10462, 9483, 3746, 307, 295, 285, 374, 3485, 11344, 10734, 627, 25729, 1070, 6866, 904, 13336, 315, 279, 10368, 315, 279, 1314, 315, 659, 1773, 82137, 304, 50280, 5380, 7184, 449, 279, 671, 12184, 367, 315, 279, 3361, 2704, 323, 5419, 51360, 315, 6890, 5762, 50280, 11, 1070, 374, 2697, 3987, 315, 4205, 315, 430, 3460, 12765, 304, 279, 1510, 15398, 2728, 430, 6890, 706, 892, 323, 1578, 16436, 311, 293, 20132, 389, 1202, 2559, 430, 50280, 374, 1202, 26154, 961, 13, 1628, 1202, 264, 43643, 11218, 8206, 315, 279, 1917, 3925, 430, 9333, 323, 43383, 5054, 15086, 1234, 264, 810, 8147, 323, 97937, 1499, 488, 617, 1027, 19029, 5535, 311, 513, 95974, 477, 14760, 3201, 505, 279, 15629, 653, 91895, 750, 1524, 422, 279, 15629, 706, 1027, 9749, 311, 387, 459, 72280, 5457, 13, 1102, 706, 1101, 1027, 13468, 430, 304, 1690, 1778, 26350, 11, 7327, 2383, 14865, 323, 27702, 69871, 5097, 927, 279, 71532, 315, 279, 7327, 7365, 439, 706, 1027, 3970, 304, 279, 513, 26540, 380, 19567, 304, 8147, 17089, 1093, 8524, 323, 5734, 1405, 814, 617, 1027, 70287, 56089, 323, 279, 1917, 4029, 1436, 656, 2697, 3734, 19054, 61225, 13, 6890, 374, 1101, 264, 7982, 7100, 323, 6411, 2410, 449, 264, 3682, 20631, 3109, 6832, 1972, 380, 323, 503, 29008, 380, 61555, 527, 389, 14943, 30819, 323, 304, 1778, 15398, 1070, 374, 2697, 3987, 430, 433, 690, 3568, 20331, 12821, 4501, 449, 1884, 50280, 285, 889, 527, 834, 2715, 12181, 349, 7119, 433, 13, 15636, 904, 4879, 555, 50280, 285, 902, 374, 26617, 33615, 555, 279, 17864, 36693, 367, 1053, 14647, 387, 23188, 85627, 7389, 1070, 374, 264, 60883, 2349, 304, 279, 15983, 28765, 32360, 6070, 315, 279, 1207, 35172, 14168, 477, 315, 50280, 627, 20552, 35210, 11, 433, 374, 832, 315, 279, 8706, 11245, 552, 323, 9950, 4309, 285, 552, 315, 279, 220, 508, 339, 9478, 430, 1063, 1274, 889, 1047, 21095, 369, 872, 11542, 449, 779, 1790, 8571, 23920, 323, 1377, 373, 4749, 18291, 74688, 912, 892, 304, 5737, 449, 50280, 596, 11542, 11, 31426, 323, 38929, 3131, 814, 1047, 15075, 872, 1866, 505, 872, 37683, 36467, 13, 50280, 30675, 2731, 323, 539, 1120, 50280, 11, 279, 4459, 1207, 75695, 3966, 11542, 505, 63677, 41589, 77249, 51215, 11, 1207, 99344, 11, 21934, 11, 40761, 11, 323, 21948, 323, 33792, 315, 264, 2478, 21342, 6445, 288, 323, 6989, 889, 617, 2533, 1317, 5762, 59468, 1202, 5070, 323, 617, 100252, 398, 490, 66107, 5304, 279, 3268, 323, 38929, 315, 3885, 13, 2030, 2728, 430, 9434, 659, 1773, 82137, 374, 19029, 6992, 304, 6625, 25946, 323, 4661, 12266, 2085, 279, 14771, 315, 279, 6691, 5502, 430, 374, 8147, 323, 28860, 11, 50280, 285, 1288, 4856, 1456, 311, 9966, 459, 7524, 5419, 659, 1773, 82137, 2949, 279, 1510, 25543, 12914, 430, 7720, 682, 1023, 39210, 315, 420, 26086, 4856, 1109, 3339, 433, 264, 7315, 76911, 1847, 13, 19572, 367, 477, 60969, 276, 8082, 315, 420, 81389, 1207, 35172, 14168, 690, 1193, 3063, 311, 32317, 505, 1023, 7362, 13736, 889, 649, 12391, 810, 824, 77, 9824, 323, 33615, 439, 649, 387, 32126, 304, 21139, 323, 279, 12877, 6460, 13, 2435, 1288, 2567, 304, 4059, 430, 35901, 279, 7904, 1207, 35172, 14168, 706, 2744, 60610, 21020, 369, 60732, 1234, 832, 8147, 5502, 369, 20334, 11, 2410, 11, 33651, 11, 323, 44202, 13, 43633, 1070, 706, 1027, 13096, 11, 834, 2498, 11, 323, 32141, 11, 433, 706, 75803, 1139, 5655, 11501, 323, 264, 4948, 2410, 706, 4529, 279, 9610, 323, 2728, 75362, 311, 5127, 439, 574, 279, 1162, 2391, 279, 8013, 30747, 13, 32140, 50280, 477, 904, 1023, 5502, 315, 279, 1207, 75695, 449, 513, 26540, 380, 51566, 1288, 8881, 17693, 389, 279, 2458, 2786, 315, 13463, 323, 872, 68507, 439, 459, 9678, 7140, 1603, 4737, 904, 14560, 3094, 13, 2435, 1288, 4856, 1456, 311, 9966, 872, 3268, 323, 38929, 2949, 279, 1510, 25543, 30295, 315, 279, 1207, 35172, 14168, 555, 73301, 323, 82589, 449, 1023, 11754, 5315, 323, 555, 45925, 43525, 2585, 927, 279, 8792, 11447, 304, 1162, 814, 48969, 279, 17864, 36693, 367, 13, 1628, 304, 264, 13057, 1207, 75695, 1093, 420, 902, 374, 2539, 315, 2294, 20057, 11, 814, 1053, 8659, 1505, 264, 2763, 315, 33818, 62380, 323, 11640, 2402, 315, 1274, 389, 872, 11314, 422, 814, 27136, 1456, 323, 55250, 19846, 311, 15572, 3871, 369, 22498, 12437, 323, 539, 369, 57383, 315, 15376, 659, 65873, 82, 13, 1628, 420, 1053, 387, 1790, 8831, 369, 1124, 1109, 11125, 93657, 483, 5627, 311, 513, 95974, 323, 1629, 3201, 505, 10093, 315, 2410, 323, 12014, 323, 1243, 67678, 1139, 28013, 323, 66693, 12324, 13, 3296, 19301, 279, 91529, 5603, 11, 814, 1053, 387, 32145, 912, 24589, 719, 389, 279, 26102, 42292, 1023, 824, 77, 9824, 13736, 311, 40978, 323, 1812, 91485, 1139, 279, 1207, 12, 83951, 22747, 323, 37663, 1202, 70934, 11, 16044, 11, 323, 38929, 13, 1628, 420, 264, 892, 12793, 2362, 5605, 430, 330, 23175, 584, 2559, 323, 18255, 584, 4498, 10246, 2170, 369, 1884, 889, 527, 13088, 1234, 279, 304, 3141, 462, 1113, 10383, 315, 357, 2718, 87958, 278, 2410, 11, 814, 1288, 1440, 430, 420, 1917, 374, 719, 459, 41919, 323, 374, 83234, 3333, 439, 374, 30576, 304, 279, 58964, 315, 832, 315, 872, 1866, 4846, 13015, 889, 574, 779, 28495, 311, 1518, 420, 50280, 4545, 13, 1628, 430, 814, 4985, 387, 5762, 36977, 369, 8996, 814, 656, 3060, 304, 420, 1917, 477, 304, 279, 1618, 10924, 477, 304, 2225, 12, 4359, 8964, 279, 1888, 13, 1628, 430, 1070, 374, 264, 6811, 1990, 279, 12437, 315, 4498, 1260, 893, 323, 430, 315, 279, 4225, 543, 1260, 92414, 889, 374, 682, 14392, 11, 3596, 3821, 1285, 323, 30462, 304, 29299, 20324, 627, 5028, 309, 57238, 527, 1884, 889, 90838, 1274, 323, 43049, 1036, 553, 5304, 279, 4363, 2085, 1314, 13, 2435, 690, 617, 264, 26175, 25060, 627, 2149, 29342, 27105, 220, 2983, 25, 2983, 198, 85743, 0, 9468, 234, 117, 198, 28892, 11184, 43922, 682, 11, 1603, 41365, 389, 420, 4360, 323, 1023, 8158, 11, 4587, 1373, 1057, 67929, 11, 12332, 60463, 20163, 612, 12535, 48528, 311, 5766, 904, 22047, 477, 70847, 627, 62648, 10245, 30, 54770, 8871, 198, 5358, 46, 12, 8201, 42, 12244, 6353, 1600, 49102, 5604, 42, 9729, 44, 2871, 66873, 12, 1170, 4292, 16818, 3579, 612, 54741, 715, 1937, 56, 198, 29986, 555, 2468, 360, 4241, 587, 198, 1688, 360, 4241, 587, 374, 264, 2383, 5575, 505, 1561, 22767, 11, 6890, 13, 70803, 682, 8158, 555, 2468, 360, 4241, 587, 198, 21994, 30013, 1772, 25, 578, 7434, 315, 68553, 266, 10826, 71882, 67031, 198, 5971, 9479, 1772, 25, 2209, 15256, 55608, 264, 39475, 47409, 98252, 5380, 1806, 11555, 389, 330, 52337, 315, 622, 88139, 612, 50280, 25, 41169, 477, 47847, 367, 48469, 50, 12273, 22812, 28073, 50, 1810, 2428, 2795, 512, 39, 1900, 1022, 311, 499, 116785, 4999, 45605, 304, 1778, 8396, 1405, 11542, 5196, 264, 22380, 499, 617, 2884, 459, 15400, 2683, 62904, 235, 198, 40, 1541, 956, 617, 4339, 719, 499, 3077, 3309, 430, 499, 527, 14188, 264, 18507, 6463, 30355, 627, 5159, 56650, 527, 2744, 449, 499, 627, 1688, 360, 4241, 587, 2795, 512, 13359, 499, 328, 12273, 369, 701, 20616, 323, 29488, 1708, 5721, 67, 360, 484, 1494, 13, 8489, 422, 499, 1212, 26060, 11, 499, 690, 7142, 430, 9096, 7962, 1247, 388, 323, 3268, 709, 17075, 304, 6890, 527, 7191, 1109, 4208, 1474, 647, 388, 719, 26907, 279, 15629, 42945, 7191, 2410, 323, 11447, 1521, 2919, 323, 527, 1101, 810, 9621, 323, 26480, 1109, 279, 4846, 13, 1628, 422, 499, 23846, 6576, 10522, 315, 1063, 21102, 32594, 11, 499, 690, 1505, 1690, 4751, 287, 279, 3109, 596, 3351, 439, 25142, 11, 59525, 323, 53925, 13, 40484, 26907, 25320, 706, 1027, 11293, 311, 22380, 369, 1063, 6989, 323, 14491, 304, 1690, 17089, 315, 279, 1917, 13, 622, 1394, 587, 77578, 369, 279, 56650, 0, 3297, 279, 453, 68405, 16458, 323, 8641, 499, 4999, 7927, 8158, 527, 2744, 779, 1664, 57098, 323, 24770, 4241, 587, 13, 358, 574, 1633, 23268, 323, 56507, 1306, 279, 3754, 323, 311, 1505, 1524, 33142, 1274, 3794, 10791, 304, 420, 62236, 3674, 3772, 45990, 627, 4071, 1120, 994, 358, 574, 8430, 1633, 3428, 358, 2751, 264, 73001, 1772, 389, 264, 5605, 315, 7136, 1494, 94702, 816, 30636, 10018, 11, 1405, 568, 374, 11890, 813, 49260, 430, 420, 1917, 374, 264, 622, 4845, 323, 459, 12799, 7713, 13, 3011, 6688, 757, 9096, 13, 1628, 75980, 374, 44222, 13, 1226, 649, 956, 1629, 3201, 505, 1057, 3927, 477, 22498, 71542, 4999, 40, 2288, 1047, 5439, 264, 2478, 8158, 389, 420, 2324, 1694, 264, 8063, 323, 264, 8903, 1501, 13, 358, 656, 4510, 304, 430, 0, 6914, 603, 3987, 323, 24739, 430, 1695, 5647, 8031, 6341, 323, 430, 584, 617, 810, 19226, 315, 9096, 323, 3021, 1109, 35242, 4999, 16939, 6151, 706, 1027, 264, 1614, 369, 1063, 1667, 719, 10035, 11, 1070, 8625, 264, 2466, 12324, 1990, 3314, 323, 4219, 13, 6104, 67736, 52384, 71, 706, 1027, 264, 26639, 369, 17051, 323, 430, 574, 279, 1888, 3245, 430, 7077, 311, 433, 13, 1442, 433, 1047, 8208, 311, 904, 1614, 433, 1053, 617, 1027, 264, 21426, 369, 279, 11062, 627, 85743, 30449, 682, 11410, 247, 237, 198, 13359, 499, 28146, 369, 5403, 420, 3350, 5352, 323, 8405, 1778, 264, 11944, 6492, 323, 5803, 20616, 315, 18821, 389, 420, 4360, 13, 578, 1984, 430, 420, 1917, 374, 459, 41919, 374, 1070, 4661, 304, 1475, 36017, 2737, 11604, 3686, 1690, 2873, 311, 10894, 420, 323, 1935, 420, 41919, 439, 8903, 323, 1101, 369, 11938, 13, 40484, 584, 1288, 24739, 430, 1695, 5647, 8031, 6341, 439, 1664, 439, 9096, 304, 279, 1207, 35172, 14168, 13, 358, 617, 37065, 279, 961, 1405, 358, 77634, 14183, 22767, 439, 26639, 13, 11361, 369, 39686, 430, 4360, 13, 26888, 387, 5304, 499, 2288, 13, 29614, 453, 352, 74, 372, 4999, 5159, 17069, 4241, 587, 13, 24708, 1664, 627, 11787, 499, 264, 44068, 5380, 2822, 13, 358, 1097, 264, 2383, 5575, 5131, 304, 856, 11999, 1060, 13, 27623, 232, 198, 10596, 291, 1093, 430, 311, 757, 25, 11346, 477, 7658, 27623, 232, 198, 2675, 527, 1633, 10107, 4241, 587, 13, 2052, 279, 1888, 198, 2149, 5721, 67, 360, 484, 1494, 13, 3297, 279, 453, 68405, 1888, 363, 5127, 449, 433, 422, 1202, 264, 35460, 13, 1472, 527, 1633, 3169, 13, 46863, 24886, 4999, 75120, 8115, 1994, 69396, 331, 355, 2795, 512, 1305, 13070, 311, 1518, 430, 701, 961, 315, 279, 1917, 1101, 9731, 311, 58003, 279, 75235, 19595, 315, 96553, 627, 63993, 13, 1202, 34707, 719, 837, 430, 814, 28088, 1063, 315, 279, 5076, 2531, 27121, 13, 9930, 499, 369, 701, 24208, 323, 20616, 13, 28584, 198, 2028, 574, 264, 1633, 7185, 323, 39319, 1772, 13, 9930, 499, 369, 11821, 420, 627, 13359, 499, 369, 701, 11302, 0, 11410, 234, 115, 9468, 234, 115, 9468, 234, 115, 198, 26840, 1664, 45877, 323, 75748, 3094, 311, 16805, 279, 8206, 304, 1510, 15398, 315, 6890, 13, 1102, 596, 1633, 39319, 1772, 13, 11361, 13, 7252, 468, 21168, 198, 13359, 499, 779, 1790, 369, 279, 3169, 24208, 13, 27623, 232, 198, 42, 1003, 20531, 690, 1457, 7293, 459, 26154, 961, 315, 6890, 13, 13659, 220, 14648, 612, 220, 1758, 362, 374, 304, 279, 16174, 7006, 13, 1102, 596, 539, 5108, 1203, 1457, 4999, 37, 92120, 13759, 2689, 80, 2795, 512, 42, 1003, 20531, 39285, 6910, 323, 549, 3906, 1494, 24708, 82, 198, 70983, 1445, 25, 9984, 88775, 17768, 1389, 328, 12273, 452, 28073, 274, 1810, 2428, 198, 85415, 11, 439, 2744, 0, 1115, 1917, 374, 2771, 264, 17395, 2035, 2001, 912, 5030, 1405, 832, 6439, 4999, 12947, 369, 701, 4034, 323, 20616, 73645, 13, 11410, 234, 117, 9468, 234, 117, 9468, 234, 117, 198, 19749, 2473, 2795, 512, 4438, 8271, 86, 13883, 6890, 374, 13, 76460, 239, 198, 97967, 309, 452, 525, 291, 2795, 512, 25025, 7633, 779, 69704, 13, 18231, 1057, 4339, 990, 369, 279, 11542, 315, 597, 1003, 20531, 285, 627, 644, 19549, 1494, 18107, 251, 31643, 46593, 369, 279, 4034, 323, 20616, 13, 622, 1394, 587, 77578, 20774, 1334, 4999, 82, 2255, 2259, 2795, 512, 31765, 2468, 360, 4241, 587, 11, 9901, 499, 369, 701, 13356, 627, 41, 5, 42, 1436, 387, 264, 1633, 11944, 11249, 323, 264, 2478, 5238, 477, 4339, 1053, 539, 77256, 13, 5629, 323, 43780, 6890, 3782, 1139, 279, 3118, 1376, 477, 4856, 304, 279, 8294, 1376, 1690, 3115, 304, 1202, 1633, 1317, 3925, 13, 622, 5, 42, 574, 961, 315, 430, 14154, 6890, 1690, 3115, 13, 4740, 24589, 11, 1690, 315, 279, 5415, 315, 3118, 11477, 6890, 1047, 311, 387, 7263, 304, 279, 11552, 2403, 279, 690, 315, 26291, 300, 20906, 675, 3518, 13, 622, 5, 42, 11, 389, 279, 1023, 1450, 11, 3782, 73652, 323, 67879, 11, 12222, 659, 10039, 21974, 7808, 315, 20071, 11, 17076, 10805, 38477, 323, 7263, 65396, 311, 279, 5654, 13, 58951, 622, 5, 42, 264, 10597, 1933, 374, 32677, 13, 5659, 430, 12496, 11, 50280, 285, 617, 1027, 29070, 344, 3695, 682, 872, 2324, 87799, 1566, 16579, 1667, 477, 779, 13, 763, 2144, 11, 430, 374, 832, 2944, 872, 94115, 706, 2744, 1027, 1633, 2204, 505, 279, 2800, 315, 279, 10451, 1917, 13, 7904, 8792, 11692, 706, 2884, 1690, 21294, 304, 279, 3347, 719, 622, 5, 42, 11692, 374, 18813, 8647, 369, 279, 3118, 11477, 2704, 13, 2360, 832, 706, 12222, 311, 2457, 4691, 816, 51410, 73320, 430, 1268, 1587, 813, 7555, 3974, 1778, 264, 80234, 2324, 994, 568, 706, 912, 14610, 2592, 315, 8070, 627, 40, 1781, 420, 374, 279, 1888, 6140, 94920, 315, 622, 5, 42, 2751, 304, 279, 1566, 220, 5332, 1667, 311, 4546, 279, 1614, 311, 4725, 11377, 4856, 1109, 3794, 28314, 86, 771, 291, 555, 13662, 13309, 11, 889, 1053, 387, 20558, 311, 10519, 872, 64751, 422, 50280, 5353, 8898, 1523, 13, 4212, 706, 2586, 369, 45552, 94920, 311, 2559, 709, 2403, 13662, 72, 13309, 11, 902, 706, 7263, 279, 3224, 520, 279, 68215, 315, 36707, 323, 6625, 31398, 627, 2028, 856, 1486, 315, 1684, 323, 358, 4510, 304, 29408, 11759, 4856, 1109, 64262, 2191, 627, 1354, 492, 1285, 6973, 1896, 198, 5451, 315, 682, 9523, 369, 7231, 1778, 264, 11944, 20616, 315, 18821, 389, 420, 67600, 4360, 13, 10868, 602, 5201, 701, 6325, 719, 584, 649, 1782, 13, 38254, 499, 3287, 956, 1373, 279, 17102, 961, 315, 420, 1772, 13, 617, 27463, 433, 369, 701, 19679, 13, 7252, 25223, 4999, 40, 1047, 539, 1193, 1373, 701, 17102, 719, 1023, 6742, 596, 6170, 2288, 13, 578, 10052, 574, 539, 11622, 311, 499, 719, 311, 1690, 13016, 2288, 11, 889, 4034, 701, 5526, 5117, 627, 3617, 352, 369, 9096, 13, 121643, 31643, 198, 9468, 234, 117, 9468, 234, 117, 9468, 234, 117, 198, 32, 1664, 57098, 323, 24770, 5603, 311, 3350, 389, 264, 7701, 16614, 323, 75235, 4360, 13, 8595, 649, 956, 279, 21391, 3772, 304, 6890, 1935, 264, 75336, 3560, 304, 82382, 279, 837, 7138, 315, 264, 3575, 430, 706, 3940, 2781, 3785, 279, 1633, 13354, 315, 279, 4459, 8396, 13, 6890, 649, 956, 10150, 311, 387, 87552, 311, 264, 2704, 1023, 1109, 264, 37019, 11, 26623, 323, 23053, 1614, 627, 12947, 369, 279, 4034, 323, 20616, 13, 1102, 596, 34707, 719, 837, 430, 52451, 8637, 2191, 374, 13490, 311, 69871, 323, 34731, 1521, 2919, 13, 2360, 3224, 649, 10150, 311, 1935, 264, 1239, 49053, 2559, 369, 1317, 13, 7252, 25223, 4999, 53, 819, 278, 480, 4202, 2795, 512, 49, 686, 323, 1862, 198, 2485, 1129, 485, 28323, 5328, 40750, 916, 14, 679, 24, 14, 2545, 14, 1419, 14, 21656, 74, 1003, 20531, 6018, 49833, 2674, 2795, 512, 14262, 311, 856, 5117, 1795, 1129, 2185, 1258, 438, 2837, 68, 40750, 916, 18798, 72, 402, 616, 1122, 2191, 323, 50280, 198, 56902, 1003, 9599, 2795, 512, 27312, 1795, 1129, 2185, 6521, 61943, 438, 2837, 68, 40750, 916, 18798, 72, 402, 616, 1122, 2191, 323, 50280, 198, 40, 1373, 701, 2199, 13, 3297, 10087, 3041, 499, 19351, 323, 9096, 13, 1472, 617, 2751, 1695, 4477, 7512, 11, 69152, 433, 369, 279, 1314, 5353, 13, 1541, 956, 29115, 51215, 555, 98859, 18798, 72, 402, 21148, 13, 5414, 5627, 617, 1027, 6818, 323, 12793, 1603, 13, 2435, 19168, 53057, 369, 279, 1917, 13, 2435, 2643, 12391, 53057, 369, 499, 2288, 11, 1618, 439, 1664, 439, 304, 279, 1618, 10924, 13, 1472, 690, 387, 45487, 389, 279, 8197, 315, 701, 54811, 323, 539, 389, 279, 8197, 315, 1268, 1690, 17089, 499, 69912, 477, 93519, 627, 4518, 66760, 11, 499, 690, 2586, 311, 2731, 31342, 902, 690, 387, 24629, 311, 1124, 323, 311, 499, 627, 2149, 29342, 27105, 220, 20, 13, 23, 12, 330, 46, 20043, 889, 4510, 0, 2559, 704, 32620, 369, 28471, 11, 439, 28823, 311, 6762, 14892, 11, 323, 1095, 539, 279, 35242, 315, 3885, 311, 499, 1304, 499, 2064, 5976, 311, 5076, 323, 11776, 505, 12437, 13, 2893, 1120, 25, 430, 374, 1828, 311, 9115, 2676, 25, 323, 8850, 28471, 13, 1789, 28471, 374, 1664, 38698, 447, 31329, 449, 682, 430, 20043, 656, 10246, 1305, 3988, 11, 98753, 1238, 18036, 10980, 8689, 11, 34775, 323, 17089, 627, 14809, 25223, 0, 11410, 234, 117, 9468, 234, 117, 9468, 234, 117, 198, 50, 5418, 581, 41769, 2795, 512, 32845, 1245, 24271, 86148, 3962, 10315, 2328, 315, 13659, 220, 14648, 3788, 1129, 784, 5418, 581, 40750, 916, 14, 679, 24, 14, 605, 14, 914, 14, 94427, 12, 17800, 37612, 96396, 25414, 5621, 85, 2328, 8838, 78505, 12, 14648, 6018, 46593, 369, 11821, 13, 617, 1373, 323, 2728, 856, 26793, 13, 7252, 25223, 4999, 31765, 682, 11, 1603, 41365, 389, 420, 4360, 323, 1023, 8158, 11, 4587, 1373, 279, 67929, 323, 1057, 4029, 20392, 323, 4068, 17959, 320, 2485, 1129, 266, 360, 15237, 587, 916, 43616, 42610, 13954, 51907, 311, 5766, 904, 22047, 477, 70847, 13, 128000, 93963, 31748, 409, 2563, 300, 304, 37501, 15844, 11, 34411, 60, 77654, 8375, 402, 10994, 374, 35821, 369, 279, 1176, 1060, 33160, 944, 437, 409, 11655, 15003, 409, 37501, 15844, 320, 90528, 15844, 18589, 39501, 12383, 7609, 358, 617, 1027, 18719, 11, 304, 420, 14002, 11, 311, 4128, 279, 3363, 369, 264, 2046, 627, 14364, 3245, 358, 4048, 505, 856, 330, 444, 74095, 520, 279, 10960, 1, 449, 46991, 8976, 374, 430, 1772, 50889, 2191, 374, 32971, 555, 3515, 810, 315, 7434, 4856, 1109, 3813, 11, 4737, 11626, 11, 1690, 3115, 11, 315, 2362, 14016, 311, 10737, 349, 311, 19225, 13463, 13, 358, 4128, 279, 27512, 6875, 23245, 23869, 998, 11, 902, 574, 32593, 291, 505, 459, 2362, 13041, 288, 593, 17120, 13, 358, 1097, 1101, 29123, 555, 279, 1690, 5277, 3799, 78, 14016, 315, 279, 3363, 11, 6319, 555, 6522, 7665, 56035, 13, 578, 832, 358, 4128, 374, 539, 279, 1455, 7185, 11, 719, 433, 374, 264, 1695, 3187, 315, 279, 21976, 430, 279, 1772, 50889, 380, 4857, 1828, 11, 374, 24038, 449, 433, 627, 24901, 358, 23846, 279, 27512, 3157, 11, 902, 374, 2294, 369, 279, 53500, 315, 1202, 5238, 323, 27378, 323, 358, 733, 311, 6604, 311, 832, 315, 279, 7795, 72255, 388, 11, 889, 10975, 757, 1268, 568, 35292, 1475, 2046, 311, 279, 15757, 4692, 369, 17135, 13, 128000, 4450, 31042, 4506, 198, 220, 4793, 12369, 198, 262, 13334, 14026, 4303, 198, 262, 13334, 659, 271, 262, 711, 25795, 198, 415, 659, 5331, 7, 1034, 86, 7, 83571, 481, 14098, 13339, 39999, 8908, 10331, 560, 6758, 11588, 220, 19, 60, 1763, 262, 842, 271, 262, 711, 36581, 198, 415, 61988, 3891, 3578, 24825, 198, 262, 842, 271, 262, 711, 14098, 198, 415, 17067, 22572, 24825, 198, 262, 842, 271, 262, 711, 13339, 198, 415, 16691, 835, 24825, 198, 262, 842, 271, 262, 711, 39999, 8908, 10331, 560, 198, 415, 16019, 33, 18220, 5604, 24825, 198, 262, 842, 271, 220, 842, 198, 408, 198, 128000, 2028, 7474, 16008, 279, 7195, 315, 264, 6883, 502, 25706, 4731, 19309, 24882, 98520, 689, 11, 32689, 682, 2574, 5567, 8539, 520, 735, 818, 65, 20069, 5657, 11, 279, 357, 2718, 2162, 315, 7091, 627, 6251, 40328, 1063, 315, 279, 8987, 13630, 315, 279, 220, 1954, 82, 11, 279, 2380, 11477, 19309, 320, 35720, 220, 2148, 267, 482, 7418, 220, 17, 303, 6250, 8, 690, 1514, 3552, 311, 279, 13452, 315, 279, 24241, 91271, 11, 22302, 41962, 17952, 11, 3926, 7442, 11, 578, 34944, 74089, 11, 11291, 29271, 612, 578, 8828, 11, 47363, 15344, 11, 11514, 323, 5867, 32337, 627, 791, 19309, 11, 4737, 2035, 520, 279, 27373, 473, 531, 8350, 15255, 22150, 11, 690, 1101, 1518, 279, 17755, 315, 364, 36328, 8539, 68533, 518, 264, 2539, 69155, 3871, 449, 7091, 7200, 323, 8810, 13839, 1705, 16785, 5016, 11028, 315, 5567, 8539, 53805, 627, 57850, 98520, 689, 617, 1101, 61310, 709, 449, 28812, 15612, 15244, 20214, 315, 14936, 13, 473, 37588, 304, 279, 6295, 7054, 11, 814, 690, 4668, 1063, 315, 279, 1888, 6469, 93627, 315, 279, 11639, 11, 2737, 25, 30534, 32618, 11, 32866, 8527, 11, 36967, 648, 426, 323, 42592, 78, 627, 39814, 311, 58966, 19922, 2391, 58966, 17772, 10563, 220, 806, 482, 220, 868, 5651, 369, 701, 6140, 311, 387, 520, 24882, 98520, 689, 19309, 420, 7474, 0, 128000, 29815, 389, 459, 8990, 555, 44365, 7793, 2448, 37907, 315, 279, 38696, 315, 279, 5016, 3297, 276, 51070, 12381, 1887, 11, 578, 7658, 315, 4212, 64664, 430, 892, 374, 279, 20789, 8331, 315, 59012, 13, 1115, 61127, 502, 21063, 315, 892, 9815, 369, 279, 26348, 38088, 304, 279, 5933, 2015, 627, 32, 1867, 980, 661, 311, 420, 21063, 315, 892, 374, 430, 279, 15798, 315, 892, 374, 9888, 20933, 24746, 13, 18589, 287, 10819, 1109, 279, 4732, 315, 3177, 11, 8122, 2398, 88, 374, 8617, 54682, 50256, 505, 892, 16365, 439, 279, 3217, 315, 14453, 62791, 627, 644, 3177, 315, 279, 1510, 62938, 11501, 323, 279, 1205, 369, 22706, 311, 471, 311, 279, 5933, 18912, 11900, 11, 279, 220, 1032, 17781, 13470, 706, 1027, 10666, 555, 279, 5114, 369, 279, 7658, 315, 4212, 439, 264, 1176, 3094, 9017, 312, 34500, 287, 1917, 26348, 323, 20789, 9096, 13, 17331, 279, 5114, 596, 90196, 1238, 11, 279, 29935, 5277, 8304, 11, 264, 3728, 9096, 7351, 311, 2349, 311, 279, 666, 46004, 17781, 14, 1591, 11477, 13470, 706, 1457, 9041, 311, 810, 1109, 220, 1954, 5961, 627, 791, 5114, 16008, 279, 13470, 2349, 439, 264, 5995, 3445, 315, 15180, 15853, 1268, 12966, 1781, 520, 279, 1455, 6913, 2237, 1389, 872, 7446, 18912, 2068, 13, 1115, 16188, 2349, 304, 7422, 1389, 2291, 29412, 555, 55152, 439, 279, 1455, 5995, 3094, 369, 12966, 311, 1935, 422, 814, 527, 311, 5766, 264, 1917, 65396, 1389, 374, 1101, 304, 12178, 315, 264, 502, 6566, 315, 3728, 15740, 11, 279, 912, 66222, 13, 128000, 40, 6051, 15075, 420, 6710, 323, 1097, 22128, 433, 63689, 13, 1102, 596, 6366, 323, 77754, 13, 578, 18659, 10216, 3857, 374, 264, 1695, 8815, 369, 757, 13, 358, 7664, 7182, 439, 459, 11084, 29539, 2851, 11, 520, 264, 1486, 1405, 358, 1505, 7182, 24450, 311, 990, 389, 12823, 430, 1520, 757, 3351, 311, 264, 5190, 2237, 13, 1115, 6710, 5084, 1695, 369, 430, 13, 128000, 2028, 4652, 374, 922, 279, 3752, 304, 7445, 48394, 34321, 13, 426, 34783, 13, 1789, 1023, 5829, 315, 330, 1305, 1780, 498, 1518, 47155, 627, 791, 27719, 47155, 19786, 264, 4288, 27719, 505, 264, 23166, 978, 13131, 627, 791, 27719, 47155, 374, 264, 52135, 3752, 304, 279, 1847, 7445, 48394, 34321, 13, 426, 34783, 13, 1283, 374, 15609, 555, 3816, 11, 279, 1925, 8762, 3752, 315, 27719, 3816, 6207, 323, 27719, 7997, 6207, 11, 27719, 8868, 6207, 11, 27719, 26541, 6207, 11, 323, 872, 1323, 2094, 11, 1701, 279, 2955, 315, 279, 3752, 1176, 3970, 304, 27719, 6785, 6161, 323, 27967, 20147, 86274, 627, 93276, 25121, 47155, 29409, 505, 7445, 48394, 34321, 13, 426, 34783, 627, 791, 27719, 47155, 374, 279, 1176, 52135, 27719, 18740, 304, 279, 7445, 48394, 34321, 13, 4101, 889, 374, 539, 459, 5150, 27719, 13, 18056, 264, 82151, 3752, 11, 568, 374, 539, 459, 5150, 25902, 11, 4619, 65440, 904, 315, 813, 2380, 27719, 304, 279, 4092, 315, 279, 6566, 11, 813, 2128, 31706, 315, 20685, 2154, 273, 11, 34583, 1065, 4202, 11, 323, 4969, 14038, 13, 578, 1193, 3351, 279, 29994, 27772, 374, 27719, 10604, 11, 902, 6276, 279, 2851, 311, 3480, 704, 813, 2380, 27719, 520, 690, 6957, 279, 8209, 13, 1283, 1101, 9651, 32267, 27719, 15716, 832, 374, 38612, 4265, 13, 578, 27719, 1101, 1629, 389, 264, 61784, 1887, 430, 7621, 729, 1124, 11, 439, 872, 61784, 43154, 279, 5129, 814, 527, 704, 389, 279, 2115, 13, 11205, 13321, 48394, 374, 37749, 36633, 11, 902, 706, 279, 29994, 3708, 704, 682, 2380, 27719, 520, 3131, 311, 3440, 13, 578, 27719, 47155, 374, 52468, 555, 74406, 93244, 89, 627, 791, 27719, 47155, 304, 279, 3804, 8920, 469, 1869, 661, 627, 644, 279, 3804, 8920, 469, 1869, 661, 11, 568, 20724, 449, 32103, 889, 8779, 1461, 1505, 813, 4969, 14038, 323, 34583, 1065, 4202, 13, 578, 1403, 1101, 13123, 468, 3370, 323, 264, 3544, 3804, 8920, 13309, 12585, 11, 480, 5164, 316, 13, 2435, 527, 6924, 505, 279, 12585, 596, 55774, 367, 555, 16197, 23844, 11, 323, 814, 2128, 449, 1461, 11, 2947, 339, 323, 99734, 27905, 13, 3277, 92372, 264, 6908, 3804, 8920, 13309, 1912, 389, 279, 79463, 3385, 315, 264, 16700, 320, 12452, 23844, 706, 2163, 311, 2160, 731, 279, 20442, 655, 67, 705, 814, 527, 6924, 555, 24270, 323, 813, 2128, 320, 4026, 11, 90742, 11, 40079, 11, 323, 58811, 4390, 644, 7445, 48394, 34321, 13, 369, 23643, 220, 18, 6061, 323, 7445, 48394, 34321, 13, 369, 40292, 549, 11, 46890, 2391, 8209, 374, 40542, 11, 779, 4969, 14038, 574, 1903, 1139, 264, 8821, 3752, 11, 1418, 279, 27719, 47155, 11, 20685, 2154, 273, 11, 323, 34583, 1065, 4202, 527, 912, 5129, 52135, 13, 1283, 11, 20685, 2154, 273, 11, 323, 34583, 1065, 4202, 5101, 439, 6667, 481, 54544, 11, 4869, 627, 791, 8762, 27719, 47155, 304, 7445, 48394, 34321, 13, 29950, 627, 791, 8954, 27719, 47155, 304, 7445, 48394, 34321, 13, 29950, 627, 93276, 25121, 47155, 4780, 439, 264, 52135, 3752, 304, 7445, 48394, 34321, 13, 29950, 13, 3161, 279, 17065, 315, 279, 61784, 1887, 11, 832, 649, 1514, 439, 20685, 2154, 273, 11, 34583, 1065, 4202, 11, 477, 4969, 14038, 369, 459, 11838, 4261, 315, 892, 449, 912, 16750, 13, 362, 8954, 27719, 47155, 11678, 649, 1101, 387, 1511, 11, 323, 374, 47952, 20086, 311, 279, 8762, 832, 13, 3005, 374, 15609, 555, 27967, 11, 279, 1925, 8954, 3752, 315, 27719, 6785, 6161, 6207, 323, 27719, 27967, 20147, 6207, 13, 30301, 45039, 24196, 279, 8954, 27719, 47155, 11, 1418, 33919, 14596, 26224, 24196, 279, 8762, 13, 362, 8857, 315, 279, 8762, 27719, 47155, 596, 17637, 527, 1101, 2204, 505, 7445, 48394, 34321, 13, 426, 34783, 439, 1664, 627, 93276, 25121, 47155, 320, 454, 13921, 10026, 8, 578, 16506, 520, 279, 35769, 4999, 93276, 25121, 10604, 374, 279, 27719, 47155, 596, 1523, 3361, 3351, 11, 323, 555, 9070, 279, 1523, 3361, 3351, 315, 4969, 14038, 11, 20685, 2154, 273, 11, 323, 34583, 1065, 4202, 13, 578, 3351, 374, 3196, 389, 279, 5845, 369, 4311, 311, 3480, 704, 872, 27719, 5209, 1481, 4730, 304, 279, 27719, 4101, 11, 10923, 4311, 311, 3480, 1990, 1701, 20685, 2154, 273, 11, 34583, 1065, 4202, 11, 323, 4969, 14038, 304, 430, 2015, 13, 27719, 10604, 374, 1101, 9651, 1511, 15716, 832, 315, 279, 27719, 596, 61784, 374, 79266, 477, 15716, 832, 374, 38612, 4265, 13, 1115, 3351, 4250, 387, 1511, 7214, 1306, 9216, 51946, 11, 477, 520, 682, 304, 5209, 1334, 13, 8266, 6372, 527, 1101, 539, 11953, 927, 1990, 27719, 11, 3582, 5674, 54208, 527, 11, 323, 264, 27719, 596, 61784, 312, 63399, 1418, 433, 374, 539, 304, 1005, 627, 644, 7445, 48394, 34321, 13, 29950, 11, 279, 3351, 374, 1790, 10819, 11, 323, 279, 61784, 45239, 374, 7108, 13, 1102, 649, 1101, 387, 2884, 304, 5209, 1334, 627, 83926, 36633, 374, 279, 27719, 47155, 596, 13321, 48394, 13, 578, 29994, 22014, 704, 682, 2380, 315, 813, 27719, 311, 3440, 520, 279, 1890, 892, 13, 34583, 1065, 4202, 13280, 449, 25450, 87353, 11, 264, 15376, 24310, 315, 3177, 430, 27176, 4028, 279, 4264, 26, 4969, 14038, 449, 6785, 58436, 11, 264, 35678, 39057, 430, 35292, 4028, 279, 4264, 26, 323, 20685, 2154, 273, 449, 40602, 34826, 11, 264, 3090, 3440, 430, 8314, 954, 304, 5361, 18445, 520, 3345, 2134, 11, 682, 315, 902, 3568, 19815, 5674, 1603, 19949, 527, 33085, 1203, 555, 279, 1620, 6785, 58436, 13, 1442, 264, 2851, 374, 2288, 3345, 311, 279, 2128, 1418, 814, 527, 23664, 11, 814, 527, 33085, 1139, 279, 3805, 4856, 1109, 1139, 279, 3440, 627, 60105, 279, 4553, 3440, 11, 264, 1495, 3830, 6319, 1306, 279, 6305, 304, 27719, 25328, 323, 37343, 8111, 389, 279, 5740, 315, 279, 4264, 11, 5605, 11, 330, 18293, 430, 11, 37749, 36633, 9135, 1442, 279, 3440, 13280, 11, 279, 21976, 4442, 311, 2019, 11, 330, 2181, 596, 2307, 7524, 19318, 57616, 279, 955, 27375, 45239, 315, 279, 27719, 4101, 627, 12834, 4969, 14038, 374, 279, 1193, 27719, 315, 279, 2380, 311, 471, 304, 7445, 48394, 34321, 13, 369, 23643, 220, 18, 6061, 323, 7445, 48394, 34321, 13, 369, 40292, 549, 11, 1202, 13321, 48394, 706, 1027, 5614, 311, 1202, 35356, 38321, 627, 93276, 25121, 47155, 362, 1732, 889, 25930, 27719, 323, 28788, 1124, 439, 8717, 304, 8209, 13, 763, 8209, 11, 264, 47155, 6835, 10373, 311, 279, 27719, 323, 5829, 3673, 13, 1102, 596, 539, 459, 39030, 367, 311, 2019, 25572, 649, 387, 2834, 477, 5675, 389, 264, 47155, 596, 3254, 19092, 3351, 13, 1183, 21211, 5019, 872, 23492, 1139, 872, 27719, 323, 4430, 19788, 11, 51978, 11, 323, 16267, 439, 814, 18427, 304, 16388, 315, 10671, 27719, 34722, 627, 84520, 25, 27719, 47155, 1131, 3011, 596, 279, 7564, 7231, 10373, 4920, 264, 27719, 11, 1314, 5380, 89765, 301, 25, 10291, 11, 323, 420, 27719, 47155, 374, 26991, 20685, 2154, 273, 11, 34583, 1065, 4202, 11, 323, 4969, 14038, 13, 2435, 4097, 3090, 11, 16763, 11, 323, 4027, 11, 323, 814, 2351, 682, 8147, 627, 84520, 25, 2100, 568, 3727, 813, 27719, 4465, 1418, 568, 23874, 1203, 323, 32860, 13, 45241, 1093, 264, 1695, 3568, 422, 499, 2610, 757, 627, 89765, 301, 25, 1102, 596, 539, 1093, 430, 11, 40756, 13, 13266, 27719, 8434, 956, 1440, 1148, 311, 656, 422, 279, 27719, 47155, 5828, 956, 1070, 7231, 10373, 13, 763, 1475, 8209, 11, 1070, 596, 264, 27202, 3815, 279, 11039, 11, 323, 264, 29094, 11890, 1461, 1148, 311, 656, 13, 3296, 3318, 3871, 439, 264, 2128, 11, 814, 22829, 1790, 810, 1109, 3060, 1436, 389, 872, 1866, 13, 2100, 1095, 596, 656, 420, 3871, 11, 8427, 627, 84520, 25, 2564, 24220, 1131, 33739, 499, 2019, 11, 52798, 627, 5494, 32, 27719, 6785, 6161, 612, 27719, 27967, 20147, 320, 2545, 14, 1049, 19, 8, 21317, 25, 10466, 28223, 0, 3639, 656, 35198, 88, 11, 48677, 11, 75671, 11, 66821, 11, 323, 14937, 682, 617, 304, 4279, 30, 3011, 596, 1314, 482, 814, 2351, 682, 27719, 1183, 21211, 0, 1115, 27719, 11060, 304, 279, 3339, 374, 279, 1890, 13, 6984, 304, 7445, 48394, 34321, 13, 426, 34783, 11, 568, 21095, 311, 387, 279, 1633, 1888, 26, 1093, 912, 832, 3596, 574, 13, 2057, 53006, 1124, 574, 813, 1972, 1296, 26, 311, 7195, 1124, 574, 813, 5353, 4999, 74442, 25, 42248, 892, 0, 3639, 656, 35198, 88, 11, 48677, 11, 75671, 11, 66821, 323, 14937, 682, 617, 304, 4279, 30, 3011, 596, 1314, 482, 814, 2351, 682, 27719, 1183, 21211, 0, 1115, 27719, 11060, 304, 279, 3339, 374, 1120, 279, 1890, 13, 1283, 21095, 311, 387, 279, 1633, 1888, 26, 1093, 912, 832, 3596, 574, 482, 1203, 304, 7445, 48394, 34321, 13, 426, 34783, 13, 2057, 53006, 1124, 574, 813, 1972, 1296, 26, 311, 7195, 1124, 574, 813, 5353, 627, 93276, 25121, 47155, 374, 832, 315, 279, 2478, 24080, 311, 1193, 636, 4330, 25631, 45188, 304, 7445, 48394, 34321, 13, 426, 34783, 11, 4619, 315, 279, 13783, 4848, 13, 1115, 374, 1101, 6222, 449, 14103, 3370, 11, 622, 20831, 398, 79, 1386, 11, 323, 44317, 627, 4054, 315, 27719, 47155, 596, 10778, 45188, 706, 279, 1890, 8146, 439, 2500, 27719, 47155, 26, 56943, 596, 28403, 505, 27719, 64196, 627, 2028, 2199, 574, 1566, 19685, 389, 5936, 220, 1313, 11, 220, 679, 24, 11, 520, 220, 777, 25, 2946, 13, 128000, 2675, 527, 1618, 25, 5492, 611, 82028, 611, 49918, 320, 5920, 220, 18, 30653, 17881, 220, 20, 12, 22, 340, 93324, 320, 5920, 220, 18, 30653, 17881, 220, 20, 12, 22, 340, 29146, 220, 24, 11, 220, 679, 20, 3296, 293, 1030, 2953, 26257, 264, 12535, 198, 1729, 24765, 350, 13, 11233, 616, 198, 7, 16, 12, 806, 8, 1115, 2759, 315, 1556, 276, 3557, 323, 328, 680, 71, 9008, 374, 264, 12703, 832, 369, 2771, 13, 1226, 6562, 1521, 2574, 1053, 539, 3621, 304, 279, 9441, 11, 719, 814, 656, 13, 578, 1633, 2144, 430, 22125, 2103, 617, 264, 1949, 690, 11, 1524, 1306, 814, 527, 6924, 11, 3727, 433, 3284, 369, 7589, 311, 387, 304, 279, 9441, 13, 1666, 2653, 439, 420, 8903, 374, 311, 4287, 11, 433, 374, 837, 13, 330, 59447, 1587, 539, 1456, 311, 36451, 927, 279, 6671, 719, 36716, 279, 1567, 449, 3776, 8146, 627, 1, 16, 11, 220, 17, 13, 328, 680, 71, 9008, 304, 279, 1676, 3105, 292, 25466, 3445, 6366, 13, 9086, 23229, 370, 300, 11, 1364, 323, 1077, 10177, 6216, 264, 6710, 315, 3424, 13, 1556, 276, 3557, 11, 449, 813, 7555, 596, 6677, 11, 11075, 5304, 279, 3197, 315, 12967, 1193, 961, 315, 279, 3300, 311, 279, 39571, 645, 11, 719, 55906, 430, 814, 1051, 7231, 682, 13, 220, 18, 23210, 527, 539, 3309, 1268, 11291, 15324, 420, 64575, 26, 433, 574, 4762, 555, 30467, 77052, 13, 11291, 11684, 1556, 276, 3557, 539, 449, 31952, 2299, 1461, 719, 449, 19969, 311, 93928, 279, 19229, 17326, 13, 578, 19229, 17326, 374, 14224, 264, 1732, 11, 323, 33487, 220, 19, 5039, 430, 279, 19229, 17326, 374, 1101, 4359, 627, 1204, 644, 49918, 220, 20, 25, 18, 11, 11291, 1071, 430, 1556, 276, 3557, 1047, 47253, 311, 279, 19229, 26099, 25, 304, 49918, 220, 20, 25, 19, 11, 568, 1071, 430, 1556, 276, 3557, 1047, 47253, 311, 4359, 13, 14636, 11, 4359, 323, 279, 19229, 26099, 527, 1511, 74450, 7162, 11, 9204, 9539, 430, 279, 19229, 17326, 374, 4359, 1210, 320, 791, 66114, 596, 17377, 5680, 1, 19, 13, 578, 2068, 315, 11821, 12205, 304, 279, 4216, 8993, 574, 264, 32227, 37079, 832, 323, 539, 65868, 13, 6104, 279, 4363, 14958, 304, 1556, 276, 3557, 6, 19243, 11, 433, 574, 813, 7636, 311, 28490, 315, 439, 568, 14896, 26, 323, 1524, 1306, 568, 1047, 6216, 433, 11, 279, 3300, 574, 813, 311, 656, 449, 439, 568, 18949, 13, 1556, 276, 3557, 6, 7589, 1550, 539, 6824, 304, 813, 10494, 1203, 279, 3300, 11, 719, 304, 813, 55906, 264, 4686, 20503, 2214, 311, 4359, 1418, 36192, 10494, 1203, 961, 315, 279, 3300, 627, 3343, 791, 1890, 25382, 430, 17948, 1556, 276, 3557, 927, 91453, 328, 680, 71, 9008, 11, 323, 1364, 11299, 1523, 323, 27489, 13, 2684, 374, 912, 2944, 311, 4510, 430, 1556, 276, 3557, 323, 328, 680, 71, 9008, 1051, 539, 6924, 11434, 13, 11205, 7106, 4648, 574, 264, 30467, 19971, 5304, 1124, 902, 1550, 539, 21736, 279, 3488, 315, 872, 46035, 13, 578, 1633, 2144, 430, 814, 1051, 52013, 11075, 279, 17748, 488, 315, 872, 7589, 13, 2435, 1051, 55906, 311, 330, 82, 852, 910, 682, 1, 719, 1051, 36192, 10168, 1203, 505, 4359, 13, 1115, 374, 264, 7589, 430, 649, 387, 11411, 1193, 555, 264, 9052, 1210, 320, 791, 468, 6310, 44514, 17377, 73544, 340, 2181, 374, 3284, 369, 22125, 311, 7589, 11, 1524, 264, 7589, 30449, 4648, 25, 330, 2746, 5606, 16008, 813, 10868, 7589, 1251, 264, 7589, 902, 1587, 539, 27152, 311, 4648, 11, 568, 690, 2610, 11, 323, 1283, 690, 3041, 1461, 2324, 369, 1884, 889, 5379, 7589, 539, 6522, 311, 4648, 13, 2684, 374, 7589, 6522, 311, 4648, 13, 358, 656, 539, 2019, 430, 568, 1288, 24739, 922, 430, 13, 2052, 653, 1315, 34172, 2136, 374, 7589, 11, 323, 1070, 374, 7589, 539, 6522, 311, 4648, 1210, 320, 16, 3842, 220, 20, 25, 845, 12, 1114, 8, 1226, 1288, 539, 1935, 34504, 1521, 19530, 369, 22125, 13, 358, 1440, 315, 22125, 11, 358, 4510, 11, 889, 4024, 311, 23070, 1603, 814, 1288, 617, 11, 439, 264, 1121, 315, 872, 690, 1285, 7589, 13, 4800, 279, 21765, 5900, 389, 311, 2019, 11, 330, 1687, 1440, 430, 39371, 374, 9405, 315, 4359, 1587, 539, 7589, 510, 60621, 7589, 5378, 719, 568, 889, 706, 1027, 9405, 315, 4359, 13912, 5678, 11, 323, 279, 45077, 832, 1587, 539, 5916, 1461, 1210, 320, 16, 3842, 220, 20, 25, 972, 340, 1687, 4510, 430, 22125, 527, 311, 3974, 264, 74810, 9052, 2324, 26, 430, 1587, 539, 3152, 430, 814, 2646, 7589, 11, 719, 430, 814, 1541, 956, 1390, 311, 7589, 320, 10596, 520, 1057, 49817, 220, 22, 12, 23, 4007, 570, 4452, 11, 814, 656, 7589, 323, 430, 374, 3249, 584, 1205, 1521, 50399, 25, 330, 2746, 584, 2019, 430, 584, 617, 912, 7589, 11, 584, 93928, 13520, 11, 323, 279, 8206, 374, 539, 304, 603, 13, 1442, 584, 48466, 1057, 40444, 11, 1283, 374, 37513, 323, 1120, 311, 44491, 603, 1057, 40444, 323, 311, 81155, 603, 505, 682, 653, 1315, 34172, 2136, 13, 1442, 584, 2019, 430, 584, 617, 539, 274, 21203, 11, 584, 1304, 21058, 264, 73724, 11, 323, 5414, 3492, 374, 539, 304, 603, 1210, 320, 16, 3842, 220, 16, 25, 23, 12, 605, 340, 40, 617, 2322, 1274, 389, 2225, 11314, 315, 279, 20326, 18815, 279, 7589, 4360, 13, 4427, 22125, 3802, 430, 814, 2646, 7589, 11, 323, 3885, 527, 16984, 430, 814, 617, 11411, 279, 22355, 46396, 481, 7589, 13, 5629, 11, 422, 499, 2019, 430, 499, 617, 912, 7589, 323, 527, 4832, 11, 499, 527, 21078, 1606, 4359, 2795, 912, 832, 374, 4832, 11, 539, 1524, 22125, 13, 34067, 1521, 1274, 84375, 7589, 439, 279, 330, 16548, 6305, 1, 814, 1781, 11, 1093, 10102, 11, 96696, 11, 323, 779, 389, 11, 719, 4359, 1587, 539, 1304, 1521, 87259, 304, 5414, 3492, 627, 791, 3575, 449, 420, 10334, 11, 430, 584, 649, 387, 4832, 1603, 584, 636, 311, 23070, 11, 374, 430, 433, 1120, 374, 539, 837, 11, 1524, 3582, 584, 527, 311, 387, 4832, 439, 1283, 374, 4832, 26, 420, 374, 264, 5915, 430, 584, 690, 539, 12756, 5662, 3156, 584, 636, 311, 23070, 13, 3011, 374, 3249, 584, 1205, 220, 16, 3842, 220, 16, 25, 24, 11, 1606, 584, 656, 617, 264, 1205, 11, 439, 22125, 11, 311, 48466, 1057, 40444, 13, 11291, 6688, 1556, 276, 3557, 323, 813, 7555, 328, 680, 71, 9008, 459, 6776, 311, 63278, 11, 719, 814, 3287, 956, 1935, 433, 11, 779, 814, 8636, 369, 872, 653, 6263, 22456, 7589, 627, 791, 1023, 1162, 11, 1405, 264, 9052, 15849, 568, 477, 1364, 706, 11411, 279, 22355, 46396, 481, 7589, 11, 814, 617, 539, 11, 1606, 814, 527, 1234, 29191, 315, 7589, 13, 1442, 814, 1047, 11411, 279, 22355, 46396, 481, 7589, 11, 814, 1053, 539, 1524, 387, 11920, 922, 433, 11, 814, 1053, 387, 779, 71836, 13, 578, 17983, 2144, 430, 814, 527, 1694, 23959, 555, 279, 19229, 17326, 5039, 430, 814, 649, 2103, 387, 73695, 13, 578, 22355, 46396, 481, 7589, 374, 3604, 63686, 279, 19229, 17326, 596, 91134, 287, 315, 264, 1732, 315, 872, 1205, 315, 46035, 13, 9843, 264, 1732, 706, 8636, 433, 374, 2288, 3389, 311, 63278, 323, 5371, 3771, 596, 65268, 369, 46035, 627, 40, 4510, 11, 3582, 11, 430, 584, 690, 1518, 1556, 276, 3557, 323, 328, 680, 71, 9008, 304, 23070, 13, 1472, 1518, 11, 4359, 706, 73695, 603, 304, 3771, 11, 719, 584, 690, 617, 311, 3041, 459, 2759, 315, 1057, 6439, 994, 584, 2559, 1603, 21058, 13, 9176, 22125, 304, 279, 9441, 617, 274, 21203, 1093, 1521, 1403, 1550, 11, 323, 1690, 315, 1521, 22125, 617, 539, 8636, 7214, 13, 8595, 374, 420, 30, 1102, 374, 1606, 1521, 1403, 1051, 1511, 439, 10507, 315, 1148, 4359, 11321, 922, 603, 7422, 430, 584, 649, 93928, 21058, 13, 1283, 8964, 4395, 584, 656, 11, 2019, 11, 323, 1781, 11, 779, 584, 1205, 311, 387, 16994, 315, 1057, 52140, 4999, 10438, 584, 1935, 279, 19229, 6947, 16588, 584, 1205, 311, 21635, 13520, 11, 800, 13, 7043, 2795, 13, 330, 55915, 39371, 50777, 420, 16385, 477, 21662, 420, 10747, 315, 279, 10425, 304, 459, 15375, 34594, 11827, 690, 387, 16390, 315, 279, 2547, 323, 6680, 315, 279, 10425, 13, 2030, 1095, 264, 893, 21635, 5678, 11, 323, 779, 1095, 1461, 8343, 315, 279, 16385, 323, 7172, 315, 279, 10747, 13, 1789, 568, 889, 50777, 323, 21662, 304, 459, 15375, 34594, 11827, 50777, 323, 21662, 19971, 311, 5678, 11, 539, 42645, 287, 279, 10425, 596, 2547, 13, 1789, 420, 2944, 1690, 527, 7621, 323, 14363, 4315, 499, 11, 323, 1690, 6212, 510, 19553, 8636, 948, 1789, 422, 584, 1053, 11913, 13520, 510, 16, 3842, 220, 16, 25, 24, 1145, 584, 1053, 539, 387, 45487, 13, 2030, 994, 584, 527, 45487, 11, 584, 527, 75207, 6901, 555, 279, 10425, 11, 430, 584, 1253, 539, 387, 39025, 449, 279, 1917, 1210, 320, 16, 74074, 220, 806, 25, 1544, 12, 843, 340, 7, 806, 8, 4359, 374, 264, 27823, 4359, 11, 4423, 706, 10555, 430, 279, 46968, 304, 64530, 220, 21, 527, 539, 5605, 330, 31153, 1359, 330, 31153, 1359, 330, 31153, 1359, 994, 814, 527, 4191, 27606, 1603, 4359, 11, 719, 527, 5605, 11, 330, 72291, 1359, 330, 72291, 1359, 330, 72291, 9135, 4359, 6944, 603, 311, 3974, 27823, 6439, 369, 1057, 1866, 1664, 1694, 323, 369, 5414, 836, 596, 25491, 11, 1606, 430, 374, 6832, 584, 527, 26, 584, 527, 5414, 836, 596, 25491, 13, 330, 1548, 11767, 757, 304, 279, 13006, 315, 71329, 369, 5414, 836, 596, 25491, 1210, 320, 21051, 7828, 220, 1419, 25, 18, 65, 340, 22244, 1567, 7263, 2294, 51517, 323, 8850, 315, 4359, 1139, 279, 8993, 323, 62113, 264, 4087, 7922, 10383, 13, 5810, 369, 279, 1176, 892, 304, 49918, 279, 3492, 369, 8993, 11, 27955, 10784, 79083, 82, 689, 11, 8111, 13, 1102, 3445, 11, 2663, 704, 11, 323, 19813, 311, 279, 8260, 704, 315, 18341, 10495, 505, 872, 10632, 311, 279, 586, 14956, 369, 44973, 10096, 13, 578, 3492, 374, 4529, 927, 555, 279, 18341, 8775, 323, 1511, 315, 6921, 439, 279, 1274, 315, 4359, 13, 11699, 1005, 304, 279, 18125, 9093, 15151, 430, 279, 9441, 374, 279, 502, 1274, 315, 4359, 13, 1115, 3492, 374, 2646, 1511, 315, 264, 4857, 13, 1102, 2955, 988, 2225, 279, 8993, 520, 3544, 320, 20, 25, 806, 26, 220, 24, 25, 2148, 26, 220, 508, 25, 1591, 8, 323, 2254, 77415, 811, 315, 52013, 320, 806, 25, 1627, 26, 220, 1032, 25, 16, 4390, 7, 717, 8, 330, 791, 4216, 22125, 1550, 539, 617, 872, 1866, 4857, 369, 24863, 719, 2322, 304, 50899, 596, 20388, 331, 11, 902, 77317, 279, 11226, 3185, 315, 279, 13057, 27850, 3158, 1210, 320, 791, 468, 6310, 44514, 17377, 73544, 8, 34067, 814, 2322, 304, 10632, 477, 49959, 14016, 439, 584, 690, 1518, 304, 1023, 5596, 315, 49918, 627, 67410, 826, 323, 40164, 32971, 279, 25887, 315, 279, 4216, 9441, 323, 527, 18813, 10825, 311, 387, 3685, 304, 323, 1555, 279, 9441, 3432, 13, 510, 16, 74074, 220, 717, 25, 220, 16, 12, 2148, 11, 584, 617, 264, 4007, 389, 420, 304, 1057, 74074, 31710, 13, 933, 74737, 18449, 323, 3861, 30242, 11, 43737, 3083, 57184, 13, 578, 4216, 8993, 14264, 19019, 439, 364, 1820, 10425, 3779, 311, 279, 8993, 7446, 1884, 889, 1051, 1694, 6924, 6, 320, 93324, 220, 17, 25, 1544, 570, 763, 220, 19, 25, 843, 11, 220, 1644, 11, 433, 374, 5068, 430, 279, 7982, 49068, 315, 52013, 1051, 25051, 264, 28254, 13167, 315, 18330, 31426, 13, 5629, 11, 814, 1051, 364, 1073, 832, 4851, 2965, 902, 374, 264, 4096, 304, 279, 4113, 18341, 11, 7438, 364, 258, 26306, 6, 477, 364, 258, 13105, 6, 449, 832, 2500, 13, 2057, 2231, 433, 2500, 1648, 11, 814, 1051, 682, 2133, 279, 1890, 1648, 11, 88853, 3871, 13, 10657, 11, 814, 1051, 315, 364, 606, 13836, 6, 320, 57753, 25548, 439, 364, 606, 4059, 1861, 1115, 706, 264, 61085, 5655, 7438, 304, 279, 4113, 18341, 13, 1102, 16280, 3445, 364, 998, 37397, 6, 477, 364, 998, 37397, 88853, 3871, 3238, 578, 3135, 315, 420, 4367, 315, 18330, 31426, 1051, 2225, 8147, 323, 15325, 1210, 320, 3648, 17326, 435, 4473, 9601, 17377, 340, 10227, 35279, 323, 17936, 23948, 315, 279, 19225, 8993, 374, 430, 1202, 1274, 527, 539, 7091, 6573, 304, 872, 10082, 304, 279, 5496, 10425, 10811, 3771, 13, 11205, 6164, 527, 779, 24450, 311, 3854, 872, 35589, 84, 5548, 449, 6380, 1274, 11, 779, 27989, 311, 2586, 311, 459, 4228, 28377, 449, 279, 1917, 11, 779, 10032, 311, 387, 8579, 389, 7589, 323, 74582, 315, 4661, 904, 19433, 11, 430, 279, 8993, 706, 4661, 912, 5536, 389, 1057, 7829, 627, 27806, 584, 527, 2133, 311, 6211, 1057, 8396, 311, 8854, 4359, 323, 16044, 21058, 11, 433, 690, 539, 387, 520, 279, 26938, 3830, 477, 1555, 279, 5054, 13736, 824, 513, 13, 1102, 690, 387, 555, 279, 60135, 2410, 315, 4359, 596, 1866, 82426, 17326, 10671, 35225, 989, 304, 2585, 315, 3927, 52013, 889, 527, 7626, 304, 872, 56357, 311, 3771, 13, 9029, 11, 14733, 1274, 889, 2559, 389, 872, 10082, 304, 1057, 20941, 11, 690, 6211, 8396, 323, 2349, 1057, 36017, 369, 1695, 810, 1109, 690, 5899, 16579, 11, 2466, 7394, 6007, 21343, 449, 682, 872, 2840, 11289, 323, 80049, 627, 1, 28622, 374, 539, 3411, 369, 11113, 11, 50738, 6057, 3046, 13, 1283, 374, 3411, 369, 264, 2478, 35482, 35826, 889, 690, 2559, 7626, 369, 21058, 11, 889, 690, 539, 1344, 37850, 1603, 872, 54844, 11, 889, 690, 539, 8850, 912, 5030, 1268, 1790, 3885, 1253, 57943, 323, 91503, 304, 34049, 13, 6914, 757, 836, 719, 264, 2478, 315, 1521, 3067, 3935, 1752, 6305, 512, 61760, 304, 15212, 345, 41686, 304, 64678, 345, 26368, 304, 25431, 323, 15704, 345, 32559, 483, 304, 10384, 345, 93387, 16271, 13120, 287, 1604, 304, 279, 61811, 345, 53477, 655, 9009, 304, 13527, 345, 5953, 17012, 25379, 304, 4892, 5270, 627, 2181, 5097, 25775, 311, 387, 7626, 323, 93111, 627, 2181, 3445, 264, 893, 477, 5333, 2011, 387, 14265, 369, 4359, 323, 5414, 9506, 627, 2181, 18651, 430, 584, 387, 2204, 505, 279, 13734, 627, 4071, 1057, 20941, 49593, 1884, 889, 16044, 21058, 25765, 7, 3923, 37970, 61094, 37246, 19048, 1729, 279, 3229, 315, 362, 59646, 42906, 520, 82976, 220, 1419, 11, 468, 13, 59809, 66603, 340, 7, 1032, 8, 578, 7120, 4234, 527, 10307, 603, 682, 279, 892, 311, 1518, 422, 1057, 46035, 374, 1972, 13, 18156, 814, 1253, 2019, 2574, 1093, 11, 330, 12174, 11, 433, 374, 1120, 264, 10474, 814, 527, 2133, 1555, 11, 814, 690, 636, 927, 433, 1210, 7429, 11, 1524, 3582, 814, 1253, 5201, 603, 814, 527, 16984, 315, 1148, 3885, 690, 1781, 315, 1124, 422, 814, 636, 6924, 11, 477, 814, 527, 16984, 315, 279, 56529, 433, 690, 4546, 13, 4418, 956, 3041, 709, 11, 433, 1253, 1935, 1667, 11, 719, 422, 584, 2567, 52232, 369, 1124, 323, 2567, 5496, 369, 279, 10425, 814, 11, 304, 1690, 5157, 11, 690, 2586, 311, 1440, 3771, 439, 872, 4443, 10425, 323, 77046, 627, 8586, 374, 264, 837, 2759, 315, 420, 1633, 1890, 3245, 12765, 6051, 304, 6890, 25, 330, 791, 220, 6550, 4771, 6418, 893, 14980, 1603, 813, 12637, 61921, 13, 578, 1274, 31387, 279, 29920, 893, 323, 14980, 520, 436, 2756, 6666, 11, 8748, 311, 6865, 1148, 568, 1047, 311, 2019, 13, 1666, 279, 4339, 6137, 311, 88050, 704, 315, 813, 11013, 11, 279, 1274, 7020, 2555, 574, 48863, 2204, 627, 21230, 5159, 25237, 4885, 323, 61921, 11, 779, 1690, 1667, 358, 73956, 32186, 323, 358, 93698, 279, 22125, 264, 2763, 2965, 568, 6137, 13, 364, 4071, 682, 1521, 1667, 358, 1047, 912, 9096, 304, 856, 4851, 13, 5112, 358, 15393, 856, 40444, 323, 358, 3782, 311, 1440, 430, 1193, 10811, 3771, 1436, 44491, 856, 40444, 11, 323, 3041, 757, 9096, 315, 4059, 13, 2100, 3508, 499, 5622, 757, 477, 539, 11, 358, 1097, 2133, 311, 1935, 74927, 24314, 10227, 1274, 1051, 48026, 520, 813, 14265, 58473, 315, 10082, 13, 2435, 2103, 1436, 20781, 4510, 872, 6548, 994, 279, 2960, 268, 8997, 323, 813, 3070, 14896, 311, 387, 90225, 323, 6244, 4642, 3697, 315, 279, 2254, 44468, 369, 13936, 7984, 648, 3078, 9441, 627, 90299, 3711, 6164, 304, 27852, 5808, 11, 1405, 420, 893, 6439, 11, 1051, 539, 14792, 520, 279, 2543, 315, 4455, 13, 2435, 1047, 1027, 54560, 323, 52232, 430, 4359, 1053, 4148, 279, 59355, 315, 14076, 505, 279, 893, 596, 6548, 18951, 2791, 2362, 477, 3995, 11, 4846, 38568, 9663, 315, 22125, 527, 3432, 56501, 279, 10082, 814, 3131, 67414, 7716, 4129, 311, 279, 34296, 315, 4359, 596, 1274, 1210, 320, 38, 27248, 369, 13936, 5513, 5666, 6790, 220, 1049, 21, 340, 7, 975, 8, 4800, 520, 420, 1486, 304, 3925, 779, 1690, 1051, 3794, 6924, 430, 279, 47859, 645, 5675, 3839, 315, 1268, 1690, 1070, 1051, 13, 330, 14101, 48571, 315, 279, 1404, 315, 279, 9441, 555, 220, 5154, 510, 1846, 60, 13592, 1990, 4330, 323, 30335, 3346, 315, 279, 7187, 315, 279, 510, 62080, 60, 21080, 1210, 320, 42042, 488, 17331, 578, 5838, 10612, 340, 7, 868, 12, 845, 8, 6058, 708, 430, 814, 7263, 279, 14363, 704, 1139, 279, 14708, 323, 17551, 1124, 389, 28036, 323, 27240, 288, 11, 430, 520, 3325, 279, 12737, 315, 11291, 12579, 555, 2643, 4498, 389, 1063, 315, 1124, 13, 7429, 264, 49068, 20802, 505, 279, 14932, 9919, 311, 26523, 11, 12967, 14363, 1274, 323, 1884, 889, 1051, 5801, 28078, 555, 653, 18883, 31739, 11, 323, 814, 1051, 682, 62320, 1210, 320, 35293, 11291, 3287, 956, 1935, 709, 459, 10209, 1618, 11, 477, 1524, 2019, 4205, 922, 3300, 28684, 28622, 1511, 3361, 71912, 311, 7838, 5414, 1984, 311, 279, 1274, 315, 430, 892, 520, 279, 7314, 315, 279, 9441, 13381, 11, 719, 430, 374, 539, 311, 2019, 430, 4359, 4250, 477, 690, 539, 656, 420, 955, 315, 3245, 1578, 13, 578, 2363, 315, 49918, 374, 279, 6437, 43245, 369, 279, 9441, 11, 719, 584, 1101, 1205, 311, 3619, 430, 279, 16665, 574, 17551, 555, 10811, 323, 279, 70332, 47859, 645, 3235, 449, 800, 13, 7043, 13, 2100, 499, 1541, 956, 11203, 1523, 2500, 16665, 1306, 279, 4857, 374, 2133, 627, 57741, 584, 527, 4359, 596, 12637, 7487, 26, 499, 527, 4359, 596, 2115, 11, 499, 527, 4359, 596, 4857, 13, 10771, 311, 279, 21507, 315, 4359, 902, 574, 2728, 311, 757, 11, 439, 264, 24219, 7491, 7514, 358, 617, 17551, 279, 16665, 11, 323, 2500, 22890, 389, 433, 13, 2030, 1095, 1855, 832, 1935, 75499, 1268, 568, 22890, 389, 433, 13, 1789, 912, 1023, 16665, 649, 5606, 11203, 1109, 430, 902, 374, 17551, 11, 902, 374, 10811, 3771, 1210, 320, 16, 74074, 220, 18, 25, 24, 12, 806, 340, 21230, 55915, 11, 315, 1521, 3026, 889, 617, 24895, 603, 682, 279, 892, 430, 279, 10425, 10811, 4024, 304, 323, 704, 4315, 603, 11, 7314, 505, 279, 74927, 315, 3842, 311, 430, 1938, 994, 1283, 574, 4529, 709, 505, 603, 11, 832, 315, 1521, 2011, 3719, 264, 11550, 449, 603, 315, 5414, 62532, 37049, 1628, 814, 67797, 323, 1071, 11, 364, 2675, 11, 507, 10425, 11, 889, 1440, 279, 23492, 315, 682, 11, 1501, 902, 315, 1521, 1403, 1472, 617, 12146, 311, 1935, 961, 304, 420, 25887, 323, 39571, 645, 2200, 505, 902, 11462, 300, 555, 1380, 30840, 11299, 11, 430, 568, 2643, 733, 311, 813, 1866, 2035, 3238, 1628, 814, 6445, 872, 10283, 11, 323, 279, 2763, 11299, 389, 90587, 13, 1628, 568, 574, 49926, 449, 279, 45314, 39571, 645, 1210, 320, 93324, 220, 16, 25, 220, 1691, 12, 1627, 8, 2100, 3432, 584, 656, 539, 617, 459, 39571, 645, 2200, 439, 433, 574, 304, 279, 4216, 9441, 11, 719, 1070, 527, 39571, 645, 304, 279, 5647, 315, 86316, 11, 1427, 520, 1057, 69472, 288, 5493, 220, 19, 4007, 627, 10227, 12737, 315, 11291, 574, 539, 11204, 6463, 574, 433, 10825, 311, 3493, 264, 15150, 13, 18156, 4359, 5829, 7106, 6302, 439, 264, 1486, 520, 902, 1057, 10082, 1253, 1304, 264, 3169, 315, 2723, 1990, 279, 3970, 323, 279, 64233, 320, 4151, 220, 777, 25, 717, 570, 578, 16385, 323, 10747, 315, 6947, 16588, 11, 279, 3090, 315, 74927, 11, 323, 279, 459, 787, 287, 5707, 320, 29184, 220, 20, 25, 975, 8, 527, 1063, 10507, 1210, 320, 3648, 17326, 435, 4473, 9601, 17377, 340, 4897, 1694, 1071, 11, 1063, 3432, 527, 3339, 3300, 704, 315, 11889, 9863, 315, 28392, 430, 617, 1027, 67797, 927, 11, 323, 814, 923, 11, 21730, 690, 1833, 422, 499, 3708, 603, 3300, 11, 719, 320, 20670, 34608, 8, 330, 2201, 3300, 11, 912, 21730, 1210, 2650, 3117, 505, 279, 8206, 11, 323, 1268, 824, 22361, 527, 1778, 1274, 889, 1053, 4639, 323, 71721, 1778, 2574, 0, 2052, 358, 649, 2019, 374, 430, 814, 690, 387, 45487, 369, 1778, 264, 47274, 1349, 315, 279, 27498, 11, 44308, 44468, 315, 1057, 10425, 10811, 3771, 0, 86785, 374, 264, 1949, 8352, 11, 323, 21730, 374, 1101, 264, 1949, 8352, 4999, 644, 279, 10846, 40214, 1070, 374, 459, 3187, 315, 4423, 3339, 11626, 704, 315, 21730, 323, 1148, 7077, 311, 1461, 512, 7184, 13106, 13005, 11, 29094, 315, 279, 13695, 315, 279, 11734, 315, 12911, 11, 574, 264, 2294, 323, 74590, 893, 304, 279, 6548, 315, 813, 7491, 11, 1606, 555, 1461, 279, 58477, 1047, 2728, 12845, 311, 12911, 13, 1283, 574, 1101, 264, 42727, 893, 315, 14448, 11, 719, 264, 514, 716, 99065, 13106, 13005, 4024, 449, 813, 27928, 323, 1181, 11345, 11, 323, 568, 14980, 520, 279, 6134, 315, 469, 1706, 64, 596, 3838, 13, 1628, 469, 1706, 64, 3288, 264, 50596, 311, 1461, 47487, 568, 510, 16589, 13005, 948, 42700, 1523, 323, 73307, 8254, 3115, 304, 279, 17527, 11, 4184, 311, 279, 5605, 315, 279, 893, 315, 4359, 26, 323, 813, 26000, 574, 28101, 1093, 279, 26000, 315, 264, 2697, 1716, 11, 323, 568, 574, 4335, 627, 3112, 568, 6052, 311, 279, 893, 315, 4359, 11, 568, 323, 682, 813, 53989, 11, 323, 3782, 323, 14980, 1603, 1461, 26, 323, 568, 1071, 11, 364, 44623, 11, 1457, 358, 1440, 430, 1070, 374, 912, 4359, 304, 682, 279, 9578, 11, 3734, 304, 6921, 26, 1457, 9093, 11, 4587, 1935, 264, 8352, 505, 701, 41564, 3238, 2030, 568, 1071, 11, 364, 2170, 279, 58477, 6439, 11, 1603, 8884, 358, 2559, 11, 358, 690, 5371, 4400, 3238, 1628, 568, 28932, 1461, 311, 1935, 433, 11, 719, 568, 16436, 99065, 568, 1071, 311, 1461, 11, 364, 11087, 304, 9096, 3238, 2100, 568, 56696, 505, 1461, 264, 2875, 6138, 627, 4071, 74680, 18291, 11, 279, 41564, 315, 469, 1706, 64, 279, 893, 315, 4359, 11, 1071, 11, 364, 10596, 11, 856, 7491, 706, 74688, 13106, 13005, 420, 18636, 11, 1418, 539, 12588, 505, 813, 6206, 1148, 568, 7263, 26, 719, 439, 279, 58477, 6439, 11, 358, 690, 1629, 1306, 1461, 323, 1935, 2555, 505, 1461, 627, 4516, 13106, 13005, 1071, 11, 364, 5618, 11, 1935, 1403, 35032, 3238, 1628, 568, 28932, 1461, 11, 323, 6965, 1403, 4442, 315, 67556, 11, 323, 23415, 1124, 311, 1403, 315, 813, 42832, 26, 323, 814, 11953, 1124, 389, 8469, 315, 1461, 13, 3277, 568, 3782, 311, 279, 6681, 15503, 11, 568, 3952, 1124, 505, 872, 1450, 11, 323, 9967, 1124, 3201, 304, 279, 3838, 26, 1243, 568, 1095, 279, 3026, 733, 11, 323, 814, 56696, 627, 7184, 568, 4024, 304, 323, 14980, 1603, 813, 7491, 13, 469, 1706, 64, 1071, 311, 1461, 11, 364, 9241, 1550, 499, 733, 11, 74680, 18291, 30, 1628, 568, 1071, 11, 364, 7927, 41564, 1550, 539, 733, 12660, 3238, 5112, 568, 1071, 311, 1461, 11, 364, 7131, 539, 856, 4851, 342, 363, 411, 499, 994, 279, 893, 6656, 1203, 505, 813, 1181, 11345, 311, 3449, 499, 30, 2209, 433, 892, 311, 5371, 3300, 323, 311, 5371, 17895, 11, 33213, 10707, 2396, 323, 30050, 17884, 11, 33012, 323, 19488, 268, 11, 8762, 323, 8954, 42832, 30, 15636, 279, 514, 782, 23707, 315, 13106, 13005, 4985, 78264, 311, 499, 323, 701, 49446, 16058, 3238, 1628, 568, 4024, 704, 505, 813, 9546, 112225, 27620, 11, 439, 4251, 439, 12056, 1210, 320, 17, 24980, 220, 20, 25, 220, 16, 12, 1544, 340, 8586, 374, 719, 832, 3187, 315, 279, 47274, 1349, 505, 1057, 1938, 315, 1148, 4359, 10825, 369, 21730, 21258, 11, 323, 1268, 814, 1288, 387, 1511, 25, 330, 8713, 510, 678, 315, 264, 1732, 60, 1243, 19487, 430, 5606, 16066, 505, 459, 14560, 6020, 11501, 1205, 1193, 6920, 279, 23788, 28392, 304, 264, 53101, 11, 15435, 11, 477, 1817, 2239, 311, 5371, 264, 6020, 42445, 13, 2684, 574, 832, 2678, 2339, 25, 13538, 279, 28392, 1436, 990, 11, 433, 1047, 311, 387, 3288, 1203, 311, 2001, 2345, 13, 578, 23788, 28392, 11, 4184, 311, 2001, 2345, 11, 50801, 364, 28156, 539, 6920, 477, 6782, 904, 3361, 459, 787, 287, 477, 29600, 13, 1102, 374, 1120, 264, 4382, 6710, 315, 14733, 28392, 80017, 304, 264, 2478, 2919, 320, 333, 499, 1180, 304, 10082, 28577, 23214, 8, 433, 649, 3719, 264, 386, 2871, 75801, 8743, 15108, 356, 1623, 3701, 3238, 2030, 2001, 2345, 1047, 832, 810, 24710, 25, 3277, 499, 471, 279, 28392, 11, 387, 2771, 311, 3708, 3300, 13, 1666, 2001, 2345, 9711, 433, 11, 364, 697, 47444, 11263, 7231, 30251, 320, 42042, 488, 304, 46250, 340, 791, 9441, 706, 539, 3970, 279, 13452, 315, 1778, 12917, 2533, 11826, 36302, 41782, 3842, 50862, 28493, 369, 279, 11486, 315, 37960, 70, 2436, 13, 9372, 1148, 574, 12765, 304, 36302, 596, 892, 25, 330, 791, 4972, 315, 279, 67113, 17120, 520, 87647, 11, 3842, 50862, 28493, 11, 574, 11486, 1521, 37960, 70, 2436, 13, 3277, 568, 10862, 622, 29051, 65, 540, 1405, 36302, 596, 1274, 4024, 311, 1518, 323, 6865, 1461, 11, 568, 1047, 279, 26365, 278, 17231, 11, 38787, 279, 37960, 29355, 11, 11953, 389, 72426, 28392, 520, 279, 2010, 315, 264, 84814, 627, 85131, 2294, 73870, 323, 22260, 568, 59761, 1555, 279, 14708, 315, 279, 6424, 311, 279, 2035, 315, 69423, 13, 2684, 11, 304, 52229, 14265, 2136, 11, 568, 19487, 311, 279, 68027, 2439, 430, 814, 1436, 3780, 4984, 505, 682, 25060, 27070, 555, 8993, 2383, 26, 814, 1101, 1436, 3780, 4984, 505, 279, 5869, 3095, 814, 2011, 656, 304, 4087, 70, 5382, 369, 872, 40444, 627, 85131, 8018, 1853, 437, 323, 28860, 72806, 11, 568, 24937, 369, 279, 8935, 315, 813, 6865, 388, 279, 7831, 826, 315, 872, 5710, 29658, 304, 4087, 70, 5382, 323, 3309, 1124, 1486, 16677, 1201, 430, 814, 1436, 4984, 872, 10456, 6305, 505, 16066, 555, 12798, 264, 2697, 3300, 13, 51383, 291, 555, 1521, 21300, 11, 279, 653, 9638, 291, 42037, 8884, 36302, 7111, 5304, 439, 813, 33012, 11, 11846, 279, 2294, 11565, 315, 3752, 8617, 1436, 387, 11021, 1210, 320, 99673, 315, 279, 34053, 11, 11826, 36302, 11, 76249, 393, 13, 64370, 340, 4516, 433, 374, 3432, 11, 1063, 527, 69423, 2500, 42582, 11, 323, 1063, 527, 330, 38837, 279, 42582, 1210, 49741, 4131, 682, 315, 330, 75710, 1, 323, 10082, 304, 4359, 596, 2410, 11, 539, 10082, 304, 10082, 0, 8170, 1587, 4359, 6900, 369, 46035, 477, 21730, 0, 330, 3112, 279, 17326, 323, 279, 42447, 2019, 11, 364, 29951, 9135, 1628, 1095, 1461, 889, 53159, 2019, 11, 364, 29951, 32483, 1628, 1095, 1461, 889, 50690, 82, 2586, 13, 91395, 32097, 11, 1095, 1461, 1935, 279, 3090, 315, 2324, 26662, 1210, 320, 697, 899, 367, 220, 1313, 25, 1114, 340, 7, 1114, 12, 972, 8, 350, 531, 620, 1122, 1071, 11, 330, 791, 6680, 315, 279, 90408, 374, 3629, 279, 10533, 315, 279, 9441, 1210, 330, 21365, 11295, 6650, 574, 539, 2085, 1790, 14076, 389, 279, 961, 315, 279, 17420, 13, 97917, 279, 34014, 76995, 561, 950, 11527, 15393, 430, 32186, 9076, 264, 6023, 311, 872, 99961, 540, 5983, 439, 18412, 5153, 323, 42963, 315, 279, 2383, 11, 323, 814, 76437, 872, 8603, 311, 12896, 32186, 13, 3700, 5132, 1516, 3782, 1176, 505, 264, 3435, 4042, 5773, 641, 76995, 561, 950, 2547, 11, 279, 5960, 42109, 26355, 11, 902, 11, 449, 13041, 8041, 11, 60089, 279, 8431, 323, 10597, 2324, 315, 279, 1614, 13, 11291, 323, 3842, 1051, 64895, 1603, 430, 71719, 2547, 520, 3325, 11157, 323, 37913, 311, 71721, 279, 44468, 11, 719, 814, 16436, 311, 1046, 15686, 311, 279, 1715, 1210, 320, 42042, 488, 17331, 279, 5838, 10612, 11, 95941, 4511, 340, 7, 777, 12, 1691, 8, 11258, 315, 420, 1917, 323, 14207, 315, 279, 5425, 1781, 814, 649, 22655, 3009, 279, 9041, 315, 279, 44468, 1139, 279, 4553, 1917, 13, 33739, 814, 656, 690, 1193, 364, 1445, 11029, 6, 304, 872, 12580, 11, 1618, 814, 1781, 555, 38955, 709, 1063, 315, 279, 39571, 645, 814, 690, 3009, 279, 9041, 315, 279, 1695, 3754, 315, 3771, 596, 62532, 13, 1115, 1193, 3727, 3771, 596, 49260, 810, 11075, 1109, 3596, 430, 814, 527, 11689, 304, 279, 8206, 323, 3177, 11, 1418, 279, 58783, 10743, 288, 330, 548, 12703, 499, 1518, 1, 1606, 814, 527, 11689, 304, 27394, 627, 1, 20, 25, 1114, 58783, 10743, 288, 13, 4610, 526, 989, 11, 279, 10388, 42963, 1051, 682, 3697, 315, 279, 58783, 10743, 288, 11, 279, 10597, 4717, 902, 320, 4908, 279, 84902, 17089, 2212, 1124, 15164, 279, 33235, 315, 62532, 13, 15636, 11, 814, 1051, 15098, 53170, 520, 279, 27375, 315, 279, 8147, 69423, 315, 279, 62532, 555, 279, 39571, 645, 320, 93324, 220, 19, 25, 1644, 26, 220, 21, 25, 22, 570, 220, 20, 25, 508, 6122, 11, 2559, 13, 44840, 315, 14076, 477, 27129, 279, 10425, 25283, 5414, 1274, 311, 2559, 94600, 374, 11, 311, 1935, 264, 2559, 11, 3131, 323, 369, 682, 320, 36, 764, 288, 5493, 220, 21, 25, 1032, 11, 220, 975, 7435, 438, 311, 6604, 4791, 6604, 682, 279, 4339, 315, 420, 2324, 11, 1120, 439, 279, 39571, 645, 364, 2203, 731, 279, 3492, 315, 4359, 449, 14265, 2136, 6, 320, 93324, 220, 19, 25, 2148, 10143, 320, 791, 66114, 596, 19723, 17377, 340, 644, 420, 1162, 279, 39571, 645, 1051, 539, 304, 4279, 9527, 1317, 1606, 459, 34426, 3952, 1124, 704, 13, 2435, 3287, 956, 1095, 8850, 1935, 3412, 315, 1124, 11, 719, 814, 4024, 1314, 1203, 311, 990, 69423, 279, 42582, 304, 279, 27850, 13, 578, 1579, 28185, 11, 1306, 3515, 17954, 6773, 311, 617, 279, 39571, 645, 369, 16163, 11, 719, 568, 574, 311, 617, 264, 2466, 13051, 4619, 4999, 10976, 2053, 527, 22066, 315, 6957, 279, 17377, 26, 3604, 1070, 527, 810, 15407, 311, 46968, 304, 279, 1561, 40214, 1109, 304, 279, 10846, 13, 2435, 527, 2744, 10695, 52013, 13, 2435, 1051, 449, 3771, 520, 5414, 7342, 11, 62532, 11, 323, 14943, 2711, 13, 4800, 584, 1518, 1124, 520, 990, 304, 279, 25887, 315, 279, 4216, 9441, 13, 3234, 499, 23289, 814, 617, 10717, 13015, 287, 311, 279, 68220, 30, 2360, 11, 358, 1541, 956, 1781, 779, 11, 814, 527, 2744, 3815, 872, 2683, 11, 1524, 3582, 584, 1541, 956, 1518, 1124, 11, 520, 3325, 584, 1541, 956, 1781, 584, 1518, 1124, 13, 330, 5519, 539, 10894, 311, 46276, 40721, 11, 369, 555, 779, 3815, 1063, 617, 95119, 398, 65550, 46968, 1210, 320, 1548, 22363, 82, 220, 1032, 25, 17, 340, 28622, 28421, 1063, 11, 323, 3885, 1283, 6276, 311, 4822, 304, 17999, 13, 3842, 66347, 8503, 7543, 2555, 1093, 30335, 1667, 304, 459, 6498, 17999, 11, 4869, 11, 439, 264, 1121, 315, 430, 892, 568, 6267, 37451, 87197, 596, 16418, 11, 902, 706, 7263, 2814, 21237, 311, 279, 14324, 21507, 315, 3771, 13, 7043, 5678, 7543, 1690, 1667, 304, 17999, 11, 330, 1687, 1205, 311, 52554, 1405, 584, 527, 39441, 1359, 439, 4423, 706, 1071, 627, 1688, 430, 892, 11, 520, 279, 54529, 315, 279, 9441, 11, 1070, 1051, 1120, 264, 2478, 16066, 369, 279, 10425, 10811, 3771, 26, 3432, 1690, 2212, 279, 1917, 7831, 304, 49429, 323, 304, 1690, 1023, 28201, 5627, 13, 2684, 374, 4762, 810, 56529, 3432, 1109, 520, 904, 1023, 892, 304, 9441, 3925, 13, 3861, 2944, 369, 779, 1690, 1694, 93698, 374, 1606, 1070, 527, 810, 22125, 1109, 1070, 706, 3596, 1027, 1603, 627, 8586, 527, 1120, 264, 2478, 315, 279, 5961, 1405, 22125, 527, 2231, 304, 9527, 323, 57034, 369, 872, 10082, 512, 23078, 11, 70606, 11, 90959, 9121, 11, 21187, 5794, 9121, 11, 67799, 1609, 9121, 11, 11340, 11, 10471, 11, 21139, 11, 17076, 11, 4892, 12126, 11, 96844, 11, 23315, 11, 53455, 320, 62339, 1764, 705, 3320, 96323, 323, 28796, 11, 24922, 11, 18387, 23931, 11, 15212, 11, 17355, 43554, 11, 38059, 11, 77935, 11, 59230, 11, 81341, 11, 38059, 11, 89313, 9345, 11, 17355, 29258, 11, 32777, 11, 57111, 11, 43018, 11, 82225, 11, 33790, 11, 469, 1018, 5325, 11, 60851, 11, 40371, 11, 12911, 11, 29762, 35999, 11, 34382, 89127, 320, 69931, 705, 39133, 11, 17442, 11, 60457, 11, 23727, 99962, 24986, 11, 5596, 315, 6890, 11, 50064, 11, 31930, 49624, 11, 39601, 11, 34445, 43579, 11, 8560, 91614, 11, 23754, 3444, 78, 320, 30690, 65006, 705, 1219, 18812, 23028, 627, 1, 42315, 468, 53470, 13781, 9687, 83668, 430, 8051, 499, 649, 29319, 279, 2547, 11, 912, 832, 649, 10950, 279, 13836, 13, 1283, 3010, 9687, 813, 58229, 2849, 574, 24894, 311, 279, 27306, 320, 333, 499, 1436, 1650, 433, 430, 8, 1405, 28240, 1053, 1584, 709, 1855, 6693, 13, 1283, 6137, 311, 42223, 1555, 279, 7147, 13, 330, 28622, 374, 1695, 1210, 330, 55065, 8636, 369, 701, 40444, 1210, 330, 22404, 19704, 304, 10811, 1210, 330, 1548, 374, 701, 1193, 3987, 1210, 330, 39, 8116, 9832, 1494, 25765, 42315, 6244, 1440, 439, 279, 330, 39, 8116, 9832, 1494, 59766, 1, 323, 813, 17444, 9041, 6957, 279, 49429, 304, 47149, 19415, 64233, 323, 53873, 44044, 889, 44543, 1555, 14509, 14620, 311, 4546, 3987, 311, 3885, 627, 42315, 7543, 264, 2860, 315, 220, 975, 1667, 304, 9527, 11, 2380, 315, 1884, 1667, 304, 58229, 66678, 13, 4740, 1694, 28634, 323, 5108, 311, 279, 4410, 11, 568, 3940, 578, 29030, 315, 279, 56254, 5544, 320, 4151, 1057, 3566, 6732, 8, 304, 6664, 315, 220, 5162, 22, 13, 1115, 1060, 320, 1049, 22, 8, 15785, 510, 50828, 60, 220, 1272, 339, 22310, 1210, 320, 791, 29030, 315, 279, 56254, 5544, 6186, 220, 1049, 22, 8, 1442, 499, 656, 539, 636, 872, 14756, 358, 7701, 7079, 433, 11, 779, 499, 649, 2567, 304, 5916, 449, 1148, 4359, 374, 3815, 2212, 279, 1917, 1555, 22125, 889, 527, 16066, 19407, 369, 872, 10082, 627, 1, 84146, 279, 990, 315, 4359, 374, 11660, 30269, 3815, 433, 374, 810, 11660, 1210, 320, 77478, 2259, 468, 53470, 13781, 8, 2057, 1684, 264, 2835, 312, 268, 533, 479, 555, 12131, 468, 53470, 13781, 304, 813, 9527, 2849, 11, 4034, 8604, 12211, 5132, 1516, 916, 13, 6122, 311, 3772, 12295, 323, 3810, 279, 1522, 1889, 330, 54, 53470, 13781, 1, 369, 810, 389, 12131, 468, 53470, 13781, 596, 2324, 627, 7, 1627, 8, 4314, 10597, 6164, 1288, 617, 38569, 279, 10425, 4619, 315, 279, 1274, 4999, 7, 1544, 12, 1591, 8, 1472, 690, 6227, 430, 279, 17420, 39169, 704, 11, 330, 16366, 6680, 387, 389, 603, 323, 389, 1057, 2911, 1210, 994, 814, 4934, 10811, 15131, 1908, 13, 4800, 814, 2873, 311, 617, 25565, 1148, 814, 1047, 1071, 6931, 477, 7344, 814, 1051, 46376, 555, 433, 13, 2468, 904, 4478, 11, 814, 527, 2103, 8647, 369, 10811, 4648, 11, 3235, 449, 682, 279, 2800, 315, 279, 1917, 11, 2533, 584, 527, 682, 7589, 5079, 11, 323, 1283, 8636, 369, 1057, 40444, 0, 4452, 11, 279, 13653, 7140, 1587, 617, 279, 6680, 315, 10811, 389, 872, 6206, 11, 323, 3156, 814, 2610, 4359, 279, 20941, 596, 53150, 369, 420, 814, 690, 539, 617, 4359, 596, 9313, 477, 40149, 439, 814, 1047, 1603, 13, 9843, 814, 656, 2610, 4359, 279, 20941, 311, 44491, 1124, 11, 323, 2610, 10811, 311, 3665, 1124, 11, 1283, 690, 13, 1283, 690, 44491, 323, 3665, 1124, 439, 7931, 323, 439, 264, 7140, 13, 5112, 1283, 690, 16458, 1124, 11, 7953, 1148, 279, 1917, 1436, 3596, 282, 73555, 4999, 7, 1682, 8, 330, 20, 25, 1682, 22525, 311, 41701, 4359, 13, 22125, 527, 54757, 311, 364, 1395, 3917, 30449, 5190, 13736, 6, 320, 45459, 598, 220, 1032, 25, 16, 8, 323, 311, 364, 6081, 58996, 311, 1475, 48721, 315, 893, 369, 279, 10425, 596, 25491, 6, 320, 16, 11291, 220, 17, 25, 1032, 705, 449, 420, 832, 4788, 13, 2435, 1047, 1027, 54757, 539, 311, 364, 668, 613, 304, 420, 836, 6, 320, 93324, 220, 20, 25, 1591, 705, 719, 4359, 1047, 1071, 25, 364, 49833, 323, 6604, 6, 320, 93324, 220, 20, 25, 508, 570, 4359, 596, 11545, 1935, 10844, 11, 719, 814, 1288, 387, 5414, 11545, 11, 539, 1057, 20300, 315, 1884, 11545, 1210, 320, 791, 66114, 596, 19723, 17377, 340, 7, 966, 8, 578, 49260, 1550, 539, 1332, 346, 904, 4339, 994, 814, 1071, 311, 279, 905, 10597, 6164, 11, 330, 791, 4359, 315, 1057, 40317, 9408, 709, 10811, 8884, 499, 32485, 555, 21363, 389, 264, 5021, 10246, 7, 2148, 12, 843, 8, 330, 791, 8352, 315, 279, 19229, 17326, 11, 8884, 25459, 8554, 374, 2728, 311, 682, 52013, 520, 279, 892, 315, 46035, 11, 30824, 11550, 311, 279, 8903, 315, 279, 506, 3223, 367, 315, 10811, 10246, 7, 1644, 12, 2983, 8, 31079, 8115, 301, 11, 7043, 596, 4846, 11326, 320, 1313, 25, 18, 705, 1550, 539, 1518, 10811, 439, 279, 81441, 11, 719, 813, 16467, 311, 279, 5960, 42109, 26355, 574, 7995, 28160, 555, 30467, 2104, 768, 13, 25459, 596, 810, 27545, 1984, 374, 430, 1524, 279, 8592, 5990, 315, 13653, 11692, 1047, 311, 17113, 430, 814, 1047, 912, 2764, 2944, 369, 70441, 279, 4216, 8993, 1210, 320, 3648, 17326, 435, 4473, 9601, 17377, 340, 1, 28474, 49918, 220, 17, 25, 1806, 13, 578, 44468, 11, 994, 89194, 304, 279, 2410, 315, 279, 19229, 17326, 11, 3629, 5804, 31095, 477, 81652, 1154, 1210, 320, 3648, 50159, 2630, 17650, 14398, 340, 1, 20, 25, 1958, 31079, 8115, 301, 11, 264, 88671, 1082, 68, 4856, 1109, 264, 58783, 10743, 68, 1093, 279, 10388, 42963, 323, 1664, 42075, 304, 279, 90296, 11, 1047, 1027, 279, 11326, 315, 3995, 7043, 1603, 279, 15629, 6244, 264, 9052, 320, 93324, 220, 1313, 25, 18, 340, 1, 20, 25, 2137, 20043, 4250, 63331, 433, 13, 31079, 8115, 301, 1253, 1664, 617, 3967, 18011, 92561, 355, 11, 889, 574, 1101, 264, 4562, 315, 279, 15177, 11, 264, 88671, 1082, 68, 11, 323, 264, 31387, 11326, 320, 13379, 220, 18, 25, 16, 11, 605, 570, 1283, 2011, 617, 1027, 66278, 25408, 555, 279, 14747, 323, 56357, 315, 18011, 92561, 355, 311, 10811, 11, 323, 1243, 555, 279, 4384, 44180, 323, 279, 6821, 315, 3771, 596, 62532, 13, 1283, 1047, 1695, 2944, 311, 8850, 430, 46735, 315, 279, 22125, 2643, 13118, 387, 11039, 2403, 4359, 1210, 320, 791, 66114, 596, 19723, 17377, 340, 33703, 279, 3485, 10672, 11, 2999, 13, 64640, 12, 42493, 35871, 2380, 18740, 8603, 10826, 9090, 315, 1493, 320, 1820, 58783, 10743, 288, 1237, 279, 9090, 315, 30485, 320, 79984, 8115, 301, 1237, 279, 9090, 315, 8206, 320, 37659, 41418, 320, 5159, 261, 37343, 1543, 340, 1, 1987, 11, 2137, 31079, 8115, 301, 2346, 325, 839, 279, 5960, 42109, 26355, 311, 7095, 4359, 596, 2104, 768, 13, 1442, 4359, 574, 304, 279, 7351, 11, 433, 1053, 29761, 26, 6062, 433, 1053, 3775, 10246, 1, 1272, 13, 31079, 8115, 301, 596, 10383, 574, 779, 2294, 430, 568, 11953, 279, 5597, 315, 279, 5960, 42109, 26355, 13, 362, 9099, 25060, 315, 27242, 574, 69177, 11, 4762, 449, 27219, 86703, 46303, 320, 17, 4563, 13, 220, 806, 25, 1187, 705, 369, 68735, 1216, 287, 279, 5960, 42109, 26355, 596, 6931, 3290, 627, 1, 3174, 11, 2983, 13, 578, 39571, 645, 1051, 555, 912, 3445, 64770, 11, 369, 814, 6646, 433, 459, 16044, 311, 7831, 369, 279, 836, 315, 10811, 13, 2435, 8738, 872, 7640, 315, 12917, 323, 69423, 315, 10811, 439, 279, 81441, 11, 2225, 17880, 304, 279, 7301, 315, 279, 36823, 3742, 304, 279, 27850, 323, 304, 872, 9052, 66237, 304, 872, 879, 10632, 1210, 320, 791, 468, 6310, 44514, 17377, 73544, 340, 1, 21279, 586, 3600, 304, 279, 27850, 323, 2678, 1912, 16659, 304, 879, 10632, 1051, 20011, 369, 279, 84911, 315, 52013, 13, 25459, 64664, 2225, 4595, 315, 16659, 439, 264, 49340, 11, 16595, 311, 279, 2324, 315, 904, 2254, 59635, 320, 17, 25, 2790, 41418, 320, 3648, 17326, 435, 4473, 9601, 17377, 340, 7, 16, 8, 330, 2378, 311, 420, 1486, 11, 279, 39571, 645, 1047, 2728, 912, 6029, 315, 264, 7580, 311, 6920, 279, 44468, 1139, 682, 279, 1917, 719, 1047, 20186, 304, 26523, 70042, 311, 279, 17420, 13, 25459, 1457, 36716, 279, 67482, 315, 14800, 315, 279, 8993, 6957, 62734, 64, 323, 8388, 10649, 11, 902, 574, 13402, 291, 555, 279, 56529, 430, 51063, 2212, 18587, 13, 1115, 14800, 574, 27332, 539, 555, 279, 11376, 323, 7580, 315, 279, 8993, 719, 555, 279, 2104, 2335, 1180, 315, 4359, 304, 72916, 279, 52013, 13, 2057, 10552, 420, 56529, 11, 25459, 1176, 36716, 1268, 18587, 3782, 1139, 264, 2361, 315, 71199, 439, 832, 315, 279, 8254, 627, 1, 25759, 315, 279, 31048, 13, 220, 21, 25, 16, 12, 22, 13, 578, 8993, 304, 1202, 30758, 2919, 1047, 912, 16287, 7471, 323, 912, 7510, 477, 6164, 3734, 279, 39571, 645, 13, 578, 35876, 6650, 315, 279, 8993, 323, 279, 10205, 315, 5435, 304, 1202, 5419, 7471, 323, 279, 5873, 315, 5217, 6164, 477, 35050, 627, 1, 41, 28844, 889, 1051, 68473, 315, 42034, 12570, 15871, 1676, 3105, 292, 26, 719, 17420, 889, 1047, 12439, 304, 279, 38785, 1917, 4994, 315, 42034, 12570, 18341, 323, 3629, 1550, 539, 1440, 1676, 3105, 292, 13, 9176, 315, 1521, 88439, 71764, 17420, 6052, 311, 26523, 311, 3974, 11, 323, 1063, 315, 1124, 1051, 16489, 323, 3782, 1139, 279, 8993, 627, 30233, 52240, 1457, 51063, 1990, 279, 18341, 62290, 22125, 320, 38, 2827, 5493, 8, 510, 39, 16046, 1705, 60, 323, 279, 1676, 3105, 292, 62290, 22125, 320, 1548, 22363, 82, 8, 1606, 433, 9922, 430, 4799, 275, 2191, 369, 279, 15629, 574, 1694, 6982, 304, 279, 8141, 315, 3691, 311, 279, 9923, 4336, 13, 48740, 4336, 1051, 11434, 2085, 904, 3445, 315, 1862, 11, 889, 1051, 3984, 449, 279, 12743, 76500, 315, 2324, 555, 279, 9052, 4029, 627, 7, 17, 8, 330, 791, 30335, 39571, 645, 2663, 3871, 279, 4553, 8993, 323, 14618, 704, 430, 420, 12014, 369, 279, 2512, 315, 279, 8009, 1047, 3719, 1778, 264, 23104, 430, 814, 1766, 5694, 3567, 11780, 1455, 315, 872, 892, 311, 420, 3769, 25887, 323, 39332, 287, 279, 25887, 315, 279, 9506, 13, 15483, 39332, 574, 539, 1314, 13, 4482, 791, 4339, 364, 1083, 4138, 6, 323, 364, 13570, 6, 527, 19329, 988, 304, 279, 18341, 311, 279, 3492, 902, 3010, 6244, 23188, 439, 364, 451, 23184, 30251, 320, 791, 66114, 596, 19723, 17377, 5680, 7, 18, 12, 19, 8, 330, 7009, 11349, 430, 279, 8141, 315, 3691, 387, 9277, 1234, 279, 5216, 315, 8254, 17326, 44518, 3026, 315, 1695, 17444, 13, 510, 791, 47859, 645, 1051, 3411, 369, 2380, 2574, 304, 11692, 25, 220, 16, 13, 11258, 315, 1695, 17444, 220, 17, 13, 8797, 315, 279, 19229, 17326, 220, 18, 13, 57201, 60, 578, 39571, 645, 1053, 1243, 387, 1949, 311, 48772, 5694, 311, 279, 25887, 315, 23788, 323, 315, 69423, 323, 12917, 279, 9506, 627, 7, 20, 8, 330, 54924, 574, 4315, 279, 8254, 3026, 12146, 13, 2052, 8254, 1047, 18341, 5144, 323, 14132, 1051, 15107, 505, 279, 18341, 20611, 315, 279, 8993, 13, 4482, 791, 87651, 1711, 1047, 2586, 505, 279, 18341, 62290, 10449, 315, 279, 8993, 26, 779, 1884, 16689, 311, 2512, 369, 279, 990, 3782, 505, 872, 1396, 779, 439, 311, 4097, 872, 12034, 14470, 627, 7456, 18587, 323, 26241, 315, 279, 8254, 5371, 4726, 5406, 320, 54924, 11, 220, 21, 25, 23, 12, 22, 25, 1399, 26, 26241, 11, 220, 23, 25, 20, 12, 1272, 26, 220, 1691, 25, 23, 12, 24, 570, 5659, 6898, 822, 331, 11, 264, 5625, 311, 64283, 13, 1102, 374, 5199, 430, 264, 8882, 989, 668, 574, 5343, 304, 279, 1396, 323, 430, 25459, 3585, 704, 813, 2035, 315, 6371, 439, 6898, 822, 331, 11, 279, 3363, 311, 902, 279, 42582, 574, 5246, 311, 387, 4529, 323, 902, 574, 311, 3719, 279, 364, 2025, 20246, 1, 369, 279, 45764, 36823, 458, 73998, 5149, 13, 320, 791, 452, 3166, 19723, 17377, 5680, 7, 21, 8, 330, 791, 8993, 520, 3544, 4183, 1521, 8254, 3026, 11, 719, 279, 39571, 645, 12054, 279, 6727, 323, 21489, 1124, 311, 872, 5274, 13, 578, 8254, 1051, 1243, 86724, 311, 872, 5274, 555, 279, 94879, 315, 279, 39571, 645, 6, 6206, 13, 1115, 35744, 389, 315, 6206, 574, 459, 8775, 2587, 320, 10172, 13, 220, 2166, 25, 1032, 26620, 16016, 28120, 13, 220, 16, 25, 19, 26, 16610, 13, 220, 1544, 25, 1419, 705, 902, 574, 1101, 44664, 555, 279, 17420, 994, 3026, 1051, 16584, 311, 279, 5960, 42109, 26355, 627, 12348, 574, 4529, 927, 555, 279, 4216, 8993, 369, 279, 6141, 2617, 315, 1521, 6164, 13, 362, 33269, 46160, 11, 4869, 11, 574, 430, 279, 8254, 387, 10409, 449, 279, 19229, 17326, 13, 57194, 505, 279, 39571, 645, 11, 1521, 8254, 1051, 279, 1176, 7510, 304, 279, 8993, 13, 3296, 14135, 814, 617, 1027, 24073, 409, 76544, 26, 719, 814, 527, 539, 779, 24073, 304, 279, 1495, 627, 10227, 6425, 315, 420, 3575, 3779, 311, 279, 27375, 315, 279, 9052, 24365, 11, 323, 1524, 1690, 42963, 11846, 1210, 320, 791, 468, 6310, 44514, 17377, 73544, 340, 10227, 35744, 389, 315, 6206, 7170, 24895, 23788, 320, 72272, 13, 220, 777, 25, 1032, 11, 868, 8, 323, 574, 1101, 1511, 439, 264, 1879, 315, 21730, 320, 44, 74, 13, 220, 20, 25, 1419, 25, 220, 21, 25, 20, 11, 5099, 25390, 264, 7891, 369, 279, 70772, 367, 315, 279, 19229, 17326, 320, 93324, 220, 23, 25, 1114, 11, 777, 26, 220, 24, 25, 1114, 26, 220, 777, 25, 21, 705, 323, 264, 4037, 315, 6141, 2617, 369, 3361, 2532, 320, 93324, 220, 21, 25, 21, 26, 220, 1032, 25, 18, 26, 220, 16, 9538, 13, 220, 19, 25, 975, 11, 5099, 36434, 1, 320, 3648, 50159, 2630, 17650, 14398, 340, 7, 22, 8, 578, 10425, 8710, 1283, 574, 18949, 449, 279, 11175, 315, 279, 3575, 555, 7999, 311, 279, 9441, 502, 52013, 13, 358, 617, 3967, 315, 31012, 430, 14264, 1633, 6288, 1555, 39153, 2191, 477, 1023, 7739, 315, 8993, 6650, 11, 719, 1243, 814, 1120, 29368, 1606, 814, 1051, 539, 17057, 11, 6463, 1550, 814, 617, 16572, 1274, 311, 4639, 279, 502, 33822, 13, 2100, 1618, 1578, 584, 1518, 279, 54029, 369, 279, 9441, 627, 74737, 315, 264, 4101, 315, 5208, 6821, 2728, 48582, 6957, 279, 2363, 315, 49918, 320, 16, 25, 868, 26, 220, 17, 25, 3174, 26, 220, 19, 25, 19, 26, 220, 20, 25, 975, 26, 220, 21, 25, 22, 26, 220, 24, 25, 2148, 26, 220, 717, 25, 1187, 26, 220, 845, 25, 20, 26, 220, 777, 25, 508, 26, 220, 1591, 25, 2148, 570, 362, 3544, 1396, 315, 42963, 13, 18056, 6532, 555, 65009, 323, 2324, 2532, 304, 279, 28185, 398, 9466, 3095, 315, 279, 2362, 65004, 11, 814, 11928, 279, 69423, 315, 279, 39571, 645, 11, 902, 63011, 264, 28235, 430, 1903, 279, 2362, 58023, 26225, 320, 1548, 65, 220, 23, 25, 1032, 26, 220, 605, 25, 16, 12, 19, 11, 220, 806, 12, 975, 8, 6244, 96756, 311, 279, 10082, 13, 40633, 291, 311, 279, 11545, 315, 279, 42582, 13, 2057, 4510, 374, 311, 41701, 4359, 13, 34053, 5196, 374, 67194, 11, 719, 10082, 1101, 19159, 67194, 320, 39972, 220, 16, 25, 16, 25, 20, 26, 69472, 220, 17, 25, 23, 12, 605, 26, 86216, 220, 17, 25, 975, 12, 1627, 41418, 320, 791, 452, 3166, 19723, 17377, 340, 7, 23, 8, 25773, 1101, 430, 71912, 1051, 279, 7617, 304, 279, 4216, 9441, 13, 8886, 814, 279, 7617, 3432, 477, 279, 4788, 30, 1442, 814, 527, 279, 4788, 1148, 706, 7077, 30, 11697, 4359, 5614, 30, 2582, 374, 433, 430, 584, 617, 5614, 30, 4999, 7, 24, 8, 10768, 54924, 60, 574, 18534, 11550, 311, 279, 81441, 5383, 315, 10811, 304, 279, 13653, 6925, 55180, 1157, 304, 26523, 11, 8104, 304, 832, 430, 574, 18677, 555, 87976, 5794, 198, 2855, 18282, 26, 52181, 1572, 11, 12431, 8, 889, 1047, 34833, 12439, 304, 279, 3116, 7634, 7086, 13, 362, 198, 20960, 72036, 574, 24306, 315, 5899, 477, 810, 17420, 889, 2322, 3871, 369, 279, 5403, 323, 23692, 315, 279, 90296, 13, 1556, 62258, 14135, 2795, 1070, 1051, 220, 11738, 6925, 55180, 1157, 304, 26523, 1210, 320, 791, 468, 6310, 44514, 17377, 73544, 4390, 10227, 364, 9374, 531, 1572, 6, 510, 37, 29616, 5794, 60, 1051, 28634, 5794, 11, 34833, 32760, 13, 2052, 315, 1521, 5315, 1051, 13653, 20550, 311, 26523, 505, 1023, 12098, 11, 889, 1047, 67170, 14454, 872, 1866, 95965, 13, 1666, 1778, 11, 814, 1051, 5115, 5897, 4633, 323, 1633, 14017, 30543, 315, 279, 386, 45883, 32006, 11, 5423, 279, 27850, 24863, 13, 2435, 1253, 1664, 617, 15644, 660, 311, 26523, 369, 420, 1633, 2944, 1210, 320, 791, 66114, 596, 19723, 17377, 340, 87655, 29616, 5794, 13, 63030, 889, 1047, 1027, 28634, 505, 33792, 13, 510, 4071, 539, 505, 279, 33792, 315, 7589, 69134, 2435, 3782, 505, 2204, 473, 16046, 4633, 5789, 13, 18221, 48009, 13, 578, 10388, 3363, 304, 38059, 323, 10411, 10384, 870, 3181, 3195, 1990, 57233, 323, 3341, 339, 425, 13, 3861, 315, 1202, 7187, 5315, 574, 13653, 13, 57233, 13, 18880, 315, 15212, 323, 2132, 1193, 311, 22463, 304, 279, 32447, 13, 9220, 704, 315, 4330, 27536, 304, 57233, 1051, 13653, 627, 47416, 321, 24985, 13, 362, 13041, 17271, 304, 279, 42552, 9309, 315, 13936, 30893, 91858, 12911, 13, 350, 1590, 355, 11, 279, 7342, 2050, 315, 7043, 11, 574, 832, 315, 1202, 12717, 25861, 13, 13936, 13, 362, 13041, 17271, 304, 279, 19001, 961, 315, 13936, 30893, 13, 69472, 43493, 11, 1405, 7043, 3010, 13015, 291, 369, 264, 2478, 1667, 11, 574, 1202, 6864, 13, 4314, 3026, 6137, 311, 18046, 13, 8876, 68624, 574, 505, 350, 1590, 355, 11, 420, 1253, 617, 1027, 279, 95965, 568, 18677, 11, 323, 568, 1253, 617, 1027, 4315, 1884, 889, 18784, 449, 18587, 1210, 320, 791, 452, 3166, 19723, 17377, 340, 7, 605, 8, 3277, 264, 9052, 374, 1296, 7922, 369, 279, 10425, 420, 374, 2663, 70042, 13, 1102, 690, 21736, 264, 18330, 39307, 0, 7357, 892, 584, 3371, 3885, 430, 10811, 374, 279, 1193, 1648, 311, 23070, 584, 690, 7831, 56529, 627, 2460, 315, 420, 574, 40334, 288, 1142, 555, 10811, 430, 433, 1053, 3621, 13, 330, 4071, 1603, 682, 1521, 2574, 11, 814, 690, 11203, 872, 6206, 389, 499, 323, 38568, 1088, 499, 11, 24944, 499, 709, 311, 279, 6925, 55180, 1157, 323, 49429, 13, 1472, 690, 387, 7263, 1603, 45619, 323, 60996, 369, 3092, 836, 596, 25491, 13, 2030, 433, 690, 2543, 704, 369, 499, 439, 459, 13402, 369, 24365, 13, 15636, 25760, 433, 304, 701, 23492, 539, 311, 1812, 20227, 52159, 389, 1148, 499, 690, 4320, 26, 369, 358, 690, 3041, 499, 264, 11013, 323, 24278, 902, 682, 701, 88491, 690, 539, 387, 3025, 311, 43561, 477, 22884, 1210, 320, 59447, 220, 1691, 25, 717, 12, 868, 340, 7, 806, 12, 975, 8, 330, 50397, 764, 4625, 2403, 42048, 323, 2403, 4359, 13, 8876, 18587, 14610, 430, 279, 24863, 315, 4359, 574, 912, 5129, 311, 387, 22486, 311, 279, 27850, 320, 22, 25, 2166, 12, 2491, 705, 813, 19949, 38817, 1521, 4339, 311, 39155, 709, 459, 65506, 430, 18587, 574, 23664, 279, 27850, 11, 279, 2383, 11, 42048, 323, 11, 13967, 11, 4359, 1210, 320, 791, 452, 3166, 19723, 17377, 340, 1, 21, 25, 1032, 905, 28823, 13, 18587, 1047, 1027, 13487, 315, 99159, 4625, 2403, 279, 27850, 323, 279, 2383, 11, 719, 1524, 3582, 279, 905, 28823, 1047, 62236, 813, 1984, 11, 18587, 1550, 539, 4879, 311, 10726, 5678, 13, 12361, 568, 4762, 10666, 279, 1890, 955, 315, 1984, 311, 279, 15177, 439, 568, 1047, 1027, 69423, 304, 279, 95965, 11, 94791, 430, 279, 16565, 315, 4359, 596, 3197, 369, 6921, 1047, 1027, 9749, 1317, 1603, 279, 27850, 1887, 11, 323, 430, 279, 3765, 33607, 4079, 64041, 31288, 304, 279, 19487, 81441, 11, 439, 1550, 279, 69423, 315, 279, 72768, 13, 2030, 6921, 1047, 18010, 4359, 596, 9506, 520, 1475, 6566, 11, 1047, 7577, 279, 72768, 11, 50500, 279, 2383, 323, 5616, 32485, 279, 81441, 994, 1283, 3782, 1210, 320, 791, 66114, 596, 19723, 17377, 340, 10227, 1890, 5811, 1047, 1027, 83349, 520, 10811, 320, 40917, 13, 220, 1627, 25, 1399, 11, 220, 5547, 570, 34863, 11, 279, 5108, 315, 3771, 8967, 279, 842, 315, 279, 27850, 2015, 11, 902, 574, 279, 16665, 323, 91853, 315, 64283, 1210, 320, 3648, 17326, 435, 4473, 9601, 17377, 340, 7, 868, 8, 330, 3112, 682, 889, 7731, 304, 279, 15177, 11, 3411, 85387, 398, 520, 1461, 11, 5602, 813, 3663, 439, 279, 3663, 315, 459, 34426, 1210, 320, 77280, 78991, 8, 4359, 574, 20646, 18587, 369, 264, 6800, 20396, 1139, 813, 67698, 2162, 11, 439, 1283, 1587, 369, 682, 5414, 9052, 60449, 5544, 0, 330, 51154, 1051, 57034, 11, 539, 25694, 6493, 685, 11, 430, 814, 2643, 6994, 264, 2731, 62532, 13, 16782, 3885, 1047, 9269, 315, 8018, 826, 323, 1156, 49541, 826, 11, 10035, 11, 323, 315, 27271, 323, 43374, 627, 7009, 1051, 357, 20262, 11, 814, 1051, 5602, 77, 304, 1403, 11, 1051, 54980, 11, 1051, 70286, 449, 279, 20827, 13, 2435, 82294, 922, 304, 33012, 50418, 323, 71932, 11966, 11, 1694, 3281, 275, 1088, 11, 92268, 11, 5801, 28078, 7058, 2173, 8884, 279, 1917, 574, 539, 28390, 13, 2435, 82294, 304, 951, 15916, 323, 24405, 13, 763, 39950, 323, 66664, 315, 279, 9578, 13, 1628, 682, 1521, 11, 3515, 12457, 264, 1695, 24365, 1555, 10082, 1210, 320, 1548, 22363, 82, 220, 806, 25, 1758, 65, 12, 1272, 340, 40, 617, 1047, 22125, 3371, 757, 430, 422, 18587, 1047, 1047, 3403, 10082, 568, 1053, 539, 617, 1047, 311, 7831, 357, 20324, 13, 1115, 1436, 539, 387, 4726, 505, 279, 8206, 11, 1120, 279, 14329, 374, 837, 11, 37366, 82, 220, 806, 25, 220, 1758, 65, 2795, 11, 330, 51154, 1051, 57034, 11, 539, 25694, 6493, 685, 11, 430, 814, 2643, 6994, 264, 2731, 62532, 10246, 2688, 1193, 430, 11, 584, 1518, 279, 63880, 9107, 11, 5644, 311, 5371, 18587, 449, 1825, 11977, 0, 2360, 11, 1070, 374, 912, 6996, 315, 10082, 1618, 13, 330, 4071, 568, 11, 1694, 2539, 315, 279, 19229, 17326, 11, 342, 28109, 1139, 23070, 323, 5602, 279, 27025, 315, 4359, 11, 323, 10811, 11509, 520, 279, 1314, 1450, 315, 4359, 11, 323, 1071, 11, 364, 10596, 0, 358, 1518, 279, 63880, 9107, 323, 279, 12103, 315, 2418, 11509, 520, 279, 1314, 1450, 315, 4359, 9135, 320, 93324, 220, 22, 25, 2131, 12, 3487, 340, 8161, 956, 4510, 369, 264, 9568, 11, 420, 46337, 12917, 430, 22125, 1541, 956, 617, 311, 7831, 422, 814, 617, 3403, 10082, 0, 3639, 1587, 19229, 54250, 2019, 30, 330, 22404, 5047, 11, 656, 539, 1781, 433, 15234, 18815, 279, 64942, 9269, 902, 374, 311, 1456, 499, 11, 439, 3582, 1063, 15234, 3245, 7077, 311, 499, 26, 719, 92859, 311, 279, 13112, 430, 499, 961, 731, 315, 3771, 596, 7831, 826, 11, 430, 994, 5414, 27025, 374, 10675, 11, 499, 1253, 1101, 387, 16089, 449, 49005, 16267, 13, 1442, 499, 527, 53823, 3939, 369, 279, 836, 315, 3771, 11, 33944, 527, 499, 11, 369, 279, 17326, 315, 27025, 323, 315, 4359, 54331, 5304, 499, 13, 1952, 872, 961, 1283, 374, 99159, 16809, 11, 719, 389, 701, 961, 1283, 374, 58135, 1908, 1210, 320, 16, 11291, 220, 19, 25, 717, 12, 975, 8, 320, 77280, 78991, 340, 7, 16, 12, 2946, 8, 330, 54924, 596, 35306, 2686, 374, 810, 1109, 264, 84129, 51977, 315, 279, 10405, 2403, 1461, 13, 26848, 1109, 29269, 5678, 11, 568, 7263, 459, 47960, 2403, 813, 1046, 4312, 13, 12361, 315, 14794, 287, 264, 837, 69779, 369, 279, 27850, 323, 279, 7658, 304, 872, 14076, 311, 279, 42582, 11, 279, 17420, 1051, 29040, 279, 1890, 42301, 1245, 9090, 315, 653, 60876, 430, 32971, 872, 2291, 65, 7596, 889, 67414, 279, 10096, 315, 4359, 13, 763, 264, 10151, 1285, 3477, 315, 6921, 596, 3925, 11, 568, 1101, 45537, 430, 4359, 596, 9546, 374, 539, 7347, 311, 264, 54001, 2035, 6463, 311, 264, 4040, 1274, 1210, 320, 3648, 17326, 435, 4473, 9601, 17377, 340, 1, 19527, 1555, 813, 41602, 527, 279, 2768, 11555, 512, 1, 16, 13, 43361, 40010, 374, 23053, 13, 18587, 1047, 1027, 13487, 315, 69423, 430, 279, 7658, 315, 42048, 1053, 1522, 3201, 320, 21, 25, 975, 570, 18056, 813, 4339, 1047, 1027, 5906, 64825, 323, 872, 7438, 824, 22361, 11, 18587, 1047, 67170, 1027, 69423, 279, 12579, 315, 279, 4325, 315, 2383, 11, 323, 279, 64260, 287, 304, 315, 279, 4325, 315, 21507, 13, 2100, 568, 5039, 430, 4359, 706, 2744, 1027, 7231, 502, 50908, 315, 66569, 627, 1, 5451, 1283, 10675, 66569, 311, 37488, 11, 1555, 279, 15244, 315, 279, 51943, 26, 311, 42048, 304, 279, 20252, 30773, 323, 389, 10640, 79985, 26, 1243, 311, 6921, 11, 1555, 279, 5769, 944, 8061, 11, 323, 5616, 1555, 279, 27850, 13, 18587, 5039, 430, 4359, 596, 51688, 304, 279, 5769, 944, 8061, 323, 27850, 574, 1193, 7891, 950, 320, 34175, 13, 220, 2166, 11, 220, 2491, 570, 4359, 1457, 14156, 6572, 304, 323, 21667, 66569, 304, 8903, 1555, 264, 502, 15244, 10826, 9441, 627, 1, 17, 13, 1283, 1047, 1027, 13487, 315, 37631, 430, 279, 27850, 1053, 387, 14763, 320, 21, 25, 975, 570, 1283, 5039, 430, 279, 27850, 374, 539, 279, 1193, 27823, 2035, 11, 719, 430, 4359, 21667, 66569, 12660, 1283, 14035, 459, 1825, 4851, 13, 1283, 10675, 66569, 311, 37488, 304, 36684, 89490, 309, 689, 320, 85, 13, 17, 1237, 311, 15466, 304, 15212, 320, 34175, 13, 220, 24, 12, 717, 1237, 311, 42048, 304, 15212, 320, 85, 13, 220, 914, 705, 323, 304, 279, 49362, 320, 34175, 13, 220, 966, 12, 1644, 11, 220, 1987, 4390, 1, 18, 13, 6921, 706, 2744, 18010, 4359, 596, 1176, 3085, 315, 39324, 11, 16654, 369, 433, 11, 323, 1243, 706, 11928, 433, 279, 2132, 892, 13, 2435, 18010, 15466, 323, 42048, 279, 1176, 892, 11, 719, 11928, 1124, 279, 2132, 892, 320, 34175, 13, 220, 24, 12, 1032, 11, 220, 1187, 12, 1758, 570, 763, 1093, 11827, 814, 617, 18010, 10811, 719, 1306, 814, 617, 16654, 11, 814, 690, 4287, 5414, 2132, 3085, 1210, 320, 24798, 279, 17377, 6017, 555, 6017, 555, 3092, 261, 37343, 1543, 340, 54924, 20536, 420, 449, 1521, 1403, 10405, 25, 330, 2675, 31161, 96533, 291, 323, 21482, 2496, 372, 66, 4147, 304, 4851, 323, 25212, 0, 1472, 2744, 22884, 279, 19229, 17326, 26, 439, 701, 40317, 1550, 11, 779, 656, 499, 13, 16299, 315, 279, 72768, 1550, 701, 40317, 539, 38568, 1088, 30, 1628, 814, 7577, 1884, 889, 2291, 83, 820, 279, 5108, 315, 279, 4702, 3861, 11, 315, 8884, 499, 1457, 617, 3719, 279, 82414, 5184, 323, 99265, 1210, 320, 22, 25, 3971, 12, 4103, 71163, 78991, 340, 47016, 279, 58477, 4359, 315, 872, 40317, 3288, 19530, 311, 1124, 555, 5414, 9622, 15232, 11, 16448, 709, 4216, 323, 11889, 1124, 11, 1606, 1283, 1047, 30481, 389, 5414, 1274, 323, 389, 5414, 51688, 2035, 13, 2030, 814, 47249, 279, 9622, 15232, 315, 4359, 11, 40060, 4147, 5414, 4339, 11, 323, 90656, 291, 520, 5414, 72768, 11, 3156, 279, 64391, 315, 279, 58477, 51063, 2403, 5414, 1274, 11, 12222, 19041, 574, 912, 40239, 1210, 320, 17, 66416, 220, 868, 12, 845, 71163, 78991, 340, 1, 29174, 369, 1690, 1667, 1472, 1047, 30401, 449, 1124, 11, 323, 39873, 2403, 1124, 555, 4718, 17326, 304, 4718, 72768, 13, 14968, 814, 1053, 539, 9020, 26, 9093, 1472, 6688, 1124, 1139, 279, 1450, 315, 279, 32538, 315, 279, 12098, 1210, 320, 45, 2701, 65945, 220, 24, 25, 966, 71163, 78991, 340, 10156, 1093, 10811, 11, 18587, 11, 449, 813, 1566, 11745, 11809, 525, 1884, 889, 274, 21203, 2403, 1461, 13, 330, 12487, 10811, 1071, 11, 364, 62416, 11, 44491, 1124, 11, 369, 814, 656, 539, 1440, 1148, 814, 656, 30251, 320, 59447, 220, 1419, 25, 1958, 8, 330, 3112, 814, 357, 20262, 18587, 439, 568, 574, 8260, 389, 198, 28622, 323, 5605, 11, 364, 52182, 10811, 11, 5371, 856, 9090, 3238, 5112, 568, 1168, 3903, 1523, 323, 39169, 704, 449, 264, 17813, 7899, 11, 364, 52182, 11, 656, 539, 6900, 1124, 449, 420, 7589, 3238, 1628, 994, 568, 1047, 1071, 420, 568, 11299, 33173, 1210, 320, 22, 25, 2946, 12, 1399, 71163, 78991, 8, 24708, 374, 264, 46450, 369, 4648, 627, 54924, 596, 23788, 574, 19089, 304, 68624, 13, 6058, 438, 814, 6445, 1461, 704, 315, 279, 3363, 323, 357, 20262, 1461, 13, 1628, 279, 28823, 17551, 1523, 872, 15447, 520, 279, 7693, 315, 264, 3995, 893, 7086, 68624, 1210, 320, 22, 25, 2970, 8, 6058, 37241, 358, 574, 34833, 264, 99159, 41996, 11, 264, 38568, 4936, 11, 323, 459, 85943, 306, 893, 26, 719, 358, 12457, 39324, 1606, 358, 1550, 433, 26427, 18007, 304, 653, 60876, 13, 1628, 279, 21507, 315, 1057, 10425, 574, 76821, 44611, 11, 449, 10082, 323, 3021, 902, 527, 304, 3771, 10811, 1210, 320, 16, 45568, 220, 16, 25, 1032, 12, 975, 340, 54924, 574, 279, 1176, 304, 279, 9441, 311, 387, 60449, 1171, 11, 719, 2533, 1461, 11990, 5304, 11990, 315, 22125, 617, 16654, 369, 872, 27498, 10425, 10811, 3771, 627, 91724, 539, 1781, 430, 358, 3782, 311, 4546, 9096, 389, 9578, 13, 358, 1550, 539, 2586, 311, 4546, 9096, 719, 264, 20827, 13, 1789, 358, 617, 2586, 311, 364, 751, 264, 893, 2403, 813, 7126, 11, 264, 10003, 2403, 1077, 6691, 11, 323, 264, 10003, 3502, 31412, 2403, 1077, 6691, 3502, 31412, 1, 323, 264, 893, 596, 14207, 690, 387, 1884, 315, 813, 1866, 14048, 3238, 1283, 889, 16180, 7126, 477, 6691, 810, 1109, 2206, 374, 539, 28390, 315, 2206, 13, 1628, 568, 889, 16180, 4538, 477, 10003, 810, 1109, 2206, 374, 539, 28390, 315, 2206, 13, 1628, 568, 889, 1587, 539, 1935, 813, 5425, 323, 1833, 1306, 2206, 374, 539, 28390, 315, 2206, 13, 1283, 889, 14035, 813, 2324, 690, 9229, 433, 11, 323, 568, 889, 33291, 813, 2324, 369, 3092, 25491, 690, 1505, 433, 1210, 320, 50988, 220, 605, 25, 1958, 12, 2137, 340, 11631, 264, 11612, 2373, 315, 420, 4652, 25, 93324, 18, 2135, 983, 1706, 128000, 21380, 6282, 544, 3903, 6282, 544, 82, 198, 2675, 1390, 1063, 19833, 11, 719, 4400, 2288, 19833, 320, 9514, 2103, 1440, 682, 279, 24142, 311, 364, 6540, 560, 3216, 4718, 9601, 1861, 1472, 1390, 2555, 2477, 11, 719, 499, 11021, 430, 74127, 54987, 259, 34768, 505, 473, 40316, 323, 499, 1541, 956, 1390, 1274, 311, 1781, 499, 2351, 4156, 258, 4527, 48241, 978, 13358, 6282, 544, 3903, 6282, 544, 82, 25, 20437, 596, 2477, 35073, 1441, 2427, 277, 425, 72436, 100167, 315, 503, 91204, 11, 15612, 481, 44578, 55090, 13, 2435, 3137, 311, 603, 922, 17936, 7364, 15369, 11, 37547, 449, 597, 91997, 11, 323, 814, 4639, 603, 459, 3062, 18228, 922, 11311, 12, 6285, 4860, 1603, 11889, 1124, 627, 17673, 5125, 28594, 198, 63919, 1966, 8068, 25, 25672, 603, 264, 2697, 922, 701, 7200, 41218, 13, 3639, 596, 701, 5222, 5380, 1687, 2351, 13358, 6282, 544, 3903, 6282, 544, 82, 505, 20437, 13, 362, 2447, 3940, 555, 97156, 323, 38897, 922, 220, 20, 1667, 4227, 13, 1226, 3077, 3967, 1855, 1023, 369, 37755, 1667, 1457, 323, 6773, 311, 990, 3871, 1306, 584, 6476, 304, 3892, 1023, 810, 27609, 56009, 6992, 21562, 13, 1102, 596, 264, 2447, 323, 539, 264, 7200, 1606, 433, 18065, 810, 1274, 1109, 1120, 279, 7200, 3697, 13, 763, 220, 679, 21, 80134, 505, 29715, 14298, 11096, 311, 1514, 47389, 13, 1226, 1511, 311, 7664, 1057, 5222, 439, 364, 13347, 27395, 11, 6621, 27395, 11, 1443, 275, 27395, 6, 994, 584, 1051, 264, 1403, 6710, 13, 4800, 433, 596, 364, 4357, 27395, 39996, 369, 10466, 445, 9146, 13, 6621, 27395, 10466, 369, 39996, 445, 9146, 24314, 53971, 25, 2650, 656, 499, 733, 922, 5609, 26372, 5380, 29185, 1122, 25, 1102, 596, 264, 5128, 54557, 1920, 627, 3968, 22865, 25, 34067, 11, 4423, 4131, 709, 449, 264, 2294, 4623, 323, 1243, 584, 1456, 311, 6724, 7066, 433, 304, 279, 89955, 3130, 13, 9029, 617, 2663, 603, 653, 16082, 78383, 1603, 11, 719, 23531, 1071, 279, 1890, 922, 578, 74127, 54987, 11, 779, 358, 8101, 430, 596, 17339, 13, 1102, 596, 279, 1193, 1648, 584, 649, 990, 2216, 627, 80863, 10118, 25, 578, 7752, 4667, 3167, 2740, 9651, 323, 433, 5097, 1124, 1093, 4330, 6622, 311, 2586, 709, 449, 264, 502, 5609, 4623, 13, 5112, 358, 364, 88044, 4059, 6, 433, 323, 1304, 20181, 315, 47287, 323, 8554, 311, 990, 704, 264, 6070, 369, 7182, 11, 1243, 814, 1304, 757, 2571, 3201, 279, 16064, 11, 323, 1243, 358, 617, 264, 91140, 11, 1243, 584, 617, 38066, 323, 3137, 922, 72503, 323, 513, 351, 71523, 11, 6118, 11, 323, 1243, 279, 5609, 374, 9405, 13, 358, 1047, 264, 2763, 315, 2523, 6975, 279, 11936, 505, 872, 1176, 8176, 11, 473, 91176, 23166, 355, 320, 8370, 358, 1781, 374, 2294, 8, 323, 279, 11936, 584, 6575, 389, 3871, 369, 279, 502, 8176, 5108, 704, 3010, 420, 1060, 627, 41, 25, 1226, 2351, 539, 6574, 709, 323, 2019, 11, 364, 33413, 11, 584, 38023, 2586, 709, 449, 264, 5609, 1457, 11, 904, 6848, 30, 1270, 53971, 25, 10699, 527, 701, 8706, 34453, 5380, 41, 25, 79716, 2324, 627, 44, 25, 22249, 78, 76122, 323, 7302, 86463, 994, 433, 4131, 311, 24074, 23621, 627, 37, 25, 77253, 1274, 584, 27716, 3449, 627, 53971, 25, 3639, 596, 1027, 701, 15821, 323, 8592, 1486, 439, 264, 7200, 41218, 5380, 37, 25, 40991, 1203, 505, 459, 5986, 2269, 660, 4606, 7364, 6724, 14760, 11, 56612, 279, 6201, 13281, 1049, 15, 198, 438, 3515, 311, 3974, 1022, 922, 264, 20026, 264, 1938, 369, 279, 1828, 5743, 315, 4038, 4235, 539, 1694, 3025, 311, 3780, 1524, 39529, 8475, 54302, 18911, 369, 279, 6699, 13, 22335, 11, 430, 574, 5128, 3958, 13, 2582, 8736, 369, 32709, 5046, 16290, 19757, 323, 3515, 311, 636, 1022, 6566, 37755, 4520, 1139, 279, 1501, 1606, 315, 11156, 5435, 13, 3011, 574, 5128, 3958, 2288, 13, 2468, 3325, 584, 2751, 1695, 3300, 369, 279, 469, 2114, 44, 1501, 11, 902, 574, 3169, 315, 264, 1579, 1486, 1981, 8840, 912, 11, 3868, 11, 584, 5675, 682, 430, 3300, 1403, 5672, 3010, 1606, 315, 264, 1841, 10121, 304, 68389, 13, 2582, 10374, 264, 2763, 315, 3300, 389, 459, 8176, 430, 574, 2646, 6004, 320, 47991, 11936, 11, 3582, 43492, 358, 8101, 279, 8592, 1486, 574, 994, 584, 15393, 430, 11, 8994, 3515, 1047, 779, 1790, 3958, 15369, 11, 584, 2351, 2103, 3815, 420, 994, 1023, 21562, 4762, 1053, 617, 11102, 709, 264, 1317, 892, 4227, 13, 3011, 596, 2555, 584, 2351, 2216, 12691, 315, 13, 1322, 2396, 430, 27607, 374, 16643, 1109, 7200, 11759, 627, 41, 25, 7566, 0, 97156, 1120, 66766, 709, 279, 54879, 315, 682, 3428, 3585, 304, 279, 3347, 4330, 1667, 13, 13596, 3428, 1486, 584, 1120, 15243, 922, 1566, 2046, 374, 459, 7274, 584, 1550, 1314, 304, 279, 7314, 1405, 584, 2751, 24116, 6724, 5076, 11, 1243, 35408, 1093, 9257, 66468, 32629, 323, 1047, 311, 10552, 13520, 369, 1403, 1667, 1606, 1274, 8774, 389, 10371, 1148, 584, 8967, 627, 4071, 1524, 420, 682, 10578, 5128, 3958, 311, 3885, 11, 584, 2646, 3596, 1524, 3463, 922, 45473, 709, 13, 73169, 323, 4731, 374, 16643, 1109, 26765, 6201, 9815, 323, 37547, 449, 597, 91997, 627, 53971, 25, 3639, 596, 701, 17139, 9395, 5380, 41, 25, 7557, 810, 28785, 11, 733, 389, 7364, 323, 1304, 4731, 2294, 1578, 627, 37, 25, 2876, 3515, 311, 1514, 20685, 1291, 60594, 14926, 627, 44, 25, 2057, 387, 3025, 311, 3136, 5737, 810, 5039, 323, 2744, 3719, 264, 2731, 2851, 627, 53971, 25, 1472, 617, 279, 6140, 311, 1514, 832, 5609, 369, 264, 13314, 315, 701, 5873, 13, 3639, 656, 499, 1514, 5380, 44, 25, 358, 4265, 1093, 311, 1514, 364, 33, 1641, 4418, 956, 27933, 3092, 650, 24459, 6, 555, 88713, 62284, 369, 68394, 68921, 627, 37, 25, 358, 4265, 1093, 311, 1514, 364, 74137, 30704, 6, 555, 11258, 17586, 91315, 369, 69420, 5676, 6063, 22983, 11, 1606, 358, 1373, 1364, 13452, 433, 2288, 323, 358, 1781, 1364, 596, 5128, 597, 365, 75, 627, 41, 25, 364, 51697, 355, 612, 45170, 320, 50, 2201, 1289, 16847, 22367, 311, 4072, 783, 3842, 627, 7927, 4885, 1541, 956, 15612, 13, 2030, 11604, 656, 627, 53971, 25, 3639, 1587, 20437, 656, 369, 499, 3167, 2740, 30, 3639, 656, 584, 617, 311, 1427, 4741, 311, 304, 279, 5108, 4038, 505, 499, 5380, 37, 25, 1472, 636, 279, 6140, 311, 1518, 323, 3449, 264, 2204, 7200, 520, 264, 2204, 22150, 13524, 1475, 3254, 1938, 315, 279, 2046, 11, 902, 374, 810, 1109, 904, 39844, 1436, 3596, 2610, 369, 627, 41, 25, 16299, 649, 1101, 387, 5128, 259, 6322, 311, 387, 10978, 1606, 433, 596, 1120, 2288, 1790, 13, 1102, 596, 1093, 279, 1888, 6424, 311, 1304, 4731, 26, 499, 1120, 38023, 1505, 279, 1314, 1274, 477, 617, 311, 3139, 709, 449, 1124, 13, 35802, 505, 430, 584, 2351, 922, 311, 6381, 1057, 2132, 8176, 902, 3952, 1063, 892, 323, 584, 1390, 311, 13334, 279, 7200, 449, 810, 3697, 627, 44, 25, 1789, 757, 20437, 706, 2744, 1027, 1633, 34147, 13, 358, 2586, 505, 29715, 14298, 25, 264, 6366, 3363, 11, 719, 433, 596, 1101, 1633, 17551, 1203, 323, 2307, 37401, 13, 358, 3021, 279, 1648, 433, 11321, 1093, 4205, 374, 3284, 1618, 11, 430, 10578, 2216, 61983, 11, 719, 602, 2216, 656, 2733, 430, 1648, 627, 25017, 832, 4288, 3488, 315, 701, 5873, 13, 320, 9597, 596, 5296, 25, 1226, 2646, 3685, 1778, 264, 2167, 323, 13358, 6282, 544, 3903, 6282, 544, 82, 819, 23692, 315, 420, 3488, 0, 1628, 439, 499, 3358, 1518, 505, 279, 510, 52877, 60, 3770, 11, 1524, 264, 86205, 315, 11604, 574, 13358, 6282, 544, 3903, 6282, 544, 35904, 4147, 28684, 41, 25, 3639, 596, 701, 19214, 17604, 5380, 44, 25, 3639, 374, 279, 11344, 61236, 77602, 5380, 37, 25, 2650, 574, 5029, 24785, 77164, 5380, 53971, 25, 16299, 4562, 315, 701, 7200, 1053, 499, 2231, 304, 279, 11344, 61236, 77602, 510, 52877, 60, 5380, 44, 25, 3234, 499, 3152, 279, 5818, 1405, 279, 28568, 33798, 2690, 2380, 32753, 11, 13912, 1124, 304, 81947, 323, 1243, 323, 29782, 1124, 12274, 2740, 11013, 311, 264, 334, 949, 36539, 1131, 14144, 430, 596, 279, 11344, 5838, 575, 15686, 13, 358, 1541, 956, 1440, 1148, 264, 3823, 29068, 77602, 374, 719, 358, 2846, 16926, 2019, 1131, 38897, 1606, 568, 374, 264, 37189, 627, 37, 25, 2360, 832, 11, 430, 596, 1120, 3152, 627, 41, 25, 7566, 11, 3249, 5380, 53971, 25, 16299, 296, 39936, 1053, 499, 1935, 304, 264, 40902, 4465, 5380, 44, 25, 97156, 279, 386, 39936, 26685, 339, 198, 37, 25, 358, 7846, 956, 13, 2435, 2351, 682, 856, 4885, 627, 53971, 25, 9641, 3420, 706, 18719, 499, 311, 1514, 264, 879, 4717, 369, 1461, 13, 1283, 3358, 2343, 499, 400, 16, 11, 931, 11, 931, 13, 37558, 3596, 706, 311, 1440, 13, 3234, 499, 1514, 5380, 44, 25, 358, 1053, 1935, 904, 6776, 358, 1436, 636, 311, 636, 3345, 3403, 311, 9641, 3420, 311, 3041, 1461, 264, 11191, 11077, 22235, 627, 37, 25, 23371, 11, 323, 1243, 358, 1053, 33009, 279, 3300, 311, 29533, 568, 76312, 627, 41, 25, 117054, 58860, 13358, 6282, 544, 3903, 6282, 544, 82, 389, 5936, 220, 22, 339, 520, 17343, 1952, 596, 320, 2534, 8, 74322, 1501, 11, 85670, 84680, 674, 16, 449, 650, 74501, 13011, 323, 18343, 3165, 1982, 128000, 83929, 14295, 294, 6, 34013, 3326, 582, 320, 19, 6287, 220, 10288, 22, 705, 96923, 315, 63268, 2530, 11, 574, 279, 4538, 315, 35352, 294, 6, 34013, 3326, 582, 11, 1797, 315, 393, 569, 18029, 11, 323, 90530, 315, 93604, 95016, 5587, 68, 382, 2170, 279, 4605, 315, 11514, 417, 11, 64850, 10434, 1234, 15274, 46069, 315, 9822, 304, 20935, 13634, 304, 220, 8929, 24, 323, 220, 9591, 15, 11, 323, 27905, 304, 51098, 26193, 13, 12140, 54343, 22034, 1461, 449, 5954, 2530, 13, 763, 220, 10465, 17, 11, 64850, 26399, 813, 7126, 11, 323, 12140, 54343, 12502, 1461, 311, 813, 10087, 66997, 7490, 11, 56578, 315, 1556, 73, 283, 11, 10003, 315, 15274, 315, 2009, 30890, 13, 12140, 54343, 1101, 15324, 813, 2316, 311, 279, 294, 1412, 88, 315, 63268, 2530, 11, 902, 568, 1047, 55026, 449, 279, 6342, 315, 12233, 277, 265, 382, 32458, 555, 12140, 311, 23744, 1463, 29622, 784, 43588, 11, 63268, 2530, 6612, 430, 568, 1047, 1027, 39413, 398, 44937, 369, 279, 11295, 2450, 315, 420, 51264, 11, 323, 11096, 279, 9130, 315, 279, 3142, 1226, 278, 304, 220, 10465, 20, 13, 3804, 39742, 11, 568, 32545, 2230, 449, 12140, 11, 719, 5246, 58505, 813, 31496, 1157, 13, 4740, 11157, 91047, 20324, 1461, 11, 279, 11734, 596, 30401, 6244, 39019, 11, 323, 568, 92728, 3640, 279, 96923, 596, 523, 77725, 520, 3341, 5641, 323, 52942, 1461, 13, 63268, 2530, 574, 12020, 449, 279, 54711, 13552, 414, 11, 1694, 9495, 709, 304, 264, 36460, 13, 1283, 574, 5616, 39025, 311, 4648, 323, 387, 63600, 11, 220, 19, 5033, 220, 10288, 22, 382, 83929, 14295, 323, 56578, 1047, 512, 64850, 320, 67, 13, 3995, 340, 20263, 294, 6, 34013, 3326, 582, 11, 27453, 315, 63268, 2530, 320, 10465, 22, 4235, 3965, 15, 340, 12140, 294, 6, 34013, 3326, 582, 11, 27453, 315, 63268, 2530, 320, 3965, 15, 4235, 3965, 18, 340, 24079, 8977, 635, 294, 6, 34013, 3326, 582, 11, 96039, 315, 63268, 2530, 320, 67, 13, 220, 3965, 18, 705, 12502, 11291, 409, 42087, 276, 320, 67, 13, 9690, 19, 340, 42663, 294, 6, 34013, 3326, 582, 320, 67, 13, 220, 10410, 22, 705, 12502, 3842, 8105, 11, 27453, 315, 93604, 304, 220, 10410, 19, 198, 29473, 294, 6, 34013, 3326, 582, 11, 96039, 315, 63268, 2530, 320, 67, 13, 220, 3965, 19, 705, 12502, 15274, 409, 42087, 276, 320, 67, 13, 3965, 19, 696, 32812, 271, 33300, 271, 91, 10669, 10290, 15, 82, 66332, 198, 10288, 22, 16779, 271, 9679, 315, 7342, 36218, 271, 34013, 3326, 582, 11, 64850, 315, 271, 64831, 315, 11514, 417, 198, 34013, 3326, 582, 11, 64850, 315, 198, 34013, 3326, 582, 11, 64850, 315, 198, 16298, 16070, 555, 9822, 555, 1654, 391, 7709, 198, 10427, 2844, 8753, 1274, 198, 16298, 16070, 555, 279, 31377, 3675, 432, 19395, 547, 304, 9822, 198, 868, 339, 34457, 26081, 315, 9822, 198, 3617, 3416, 388, 315, 279, 46168, 4618, 198, 868, 339, 34457, 69246, 555, 9822, 128000, 5005, 6714, 389, 12096, 264, 41593, 9601, 22413, 11216, 374, 9193, 17395, 627, 791, 22872, 1917, 315, 41593, 9601, 22413, 7612, 2653, 990, 627, 2675, 2834, 956, 4048, 1148, 499, 1205, 311, 555, 1120, 69344, 832, 8276, 8479, 627, 791, 45332, 49872, 430, 1436, 387, 41593, 9601, 627, 791, 35813, 527, 4702, 26924, 279, 15457, 627, 4438, 3861, 9947, 57167, 12517, 1550, 264, 8797, 10323, 18825, 627, 41651, 52179, 323, 8529, 29346, 459, 81879, 323, 6992, 5743, 67512, 304, 264, 28994, 16642, 7188, 12818, 13, 52179, 374, 264, 21102, 15779, 323, 374, 264, 8427, 449, 1077, 7626, 13, 8529, 374, 264, 18768, 11495, 28378, 889, 25241, 813, 1866, 6725, 323, 649, 387, 6755, 389, 279, 2254, 9063, 8216, 439, 264, 8810, 6917, 36693, 287, 6593, 9650, 13, 52179, 706, 1120, 8208, 1203, 311, 990, 1306, 3515, 2728, 7342, 311, 872, 2132, 10003, 13, 578, 2019, 420, 3070, 374, 1664, 1022, 1053, 387, 459, 14653, 5722, 13, 2057, 2019, 420, 3070, 374, 539, 1664, 39075, 17057, 1053, 387, 12835, 481, 13, 2030, 1524, 279, 11670, 1664, 1022, 3070, 28970, 449, 279, 13336, 315, 12096, 4459, 2324, 8276, 627, 21279, 52179, 323, 8529, 617, 5361, 8276, 10396, 13, 52179, 706, 264, 1912, 2324, 4947, 520, 1077, 7626, 323, 264, 2678, 400, 2636, 42, 220, 914, 1060, 4751, 4947, 430, 1364, 15075, 994, 499, 1364, 1176, 2751, 20895, 449, 1077, 24417, 10003, 13, 8529, 25241, 264, 2678, 1401, 893, 2324, 8276, 4947, 1555, 990, 11, 902, 374, 1511, 369, 2626, 10096, 13, 1283, 1101, 706, 264, 2678, 220, 508, 1060, 4947, 315, 400, 5067, 42, 369, 813, 4443, 1005, 627, 4599, 52179, 323, 8529, 1176, 15075, 872, 502, 3838, 220, 23, 1667, 4227, 11, 814, 1766, 872, 2362, 8276, 2883, 574, 12153, 311, 3350, 279, 8276, 4245, 311, 279, 907, 315, 279, 2162, 323, 279, 37843, 311, 264, 93225, 3158, 13, 578, 2162, 374, 5131, 53142, 449, 832, 315, 279, 5190, 2853, 81879, 8276, 5220, 13, 11205, 2380, 47972, 527, 1101, 9960, 555, 279, 1890, 73631, 13, 1226, 690, 8464, 311, 420, 2883, 439, 8743, 47, 5492, 323, 9156, 8276, 13, 3277, 814, 2322, 872, 8825, 323, 356, 12119, 2786, 8276, 8479, 568, 6288, 8720, 288, 430, 814, 1047, 264, 1972, 1205, 369, 23395, 323, 20958, 459, 67059, 34142, 4947, 13, 578, 67059, 34142, 22413, 4947, 23874, 927, 872, 1925, 2162, 11, 2132, 20769, 14, 8135, 278, 2162, 304, 15745, 11, 323, 2380, 9515, 13, 1102, 374, 5439, 304, 279, 3392, 315, 400, 18, 34629, 2326, 81289, 449, 459, 5217, 400, 16, 34629, 2326, 81289, 304, 13937, 82707, 9048, 380, 10401, 627, 21279, 52179, 323, 8529, 10519, 21931, 91143, 22413, 4245, 311, 279, 7138, 315, 872, 21746, 323, 990, 13, 11995, 315, 872, 9873, 527, 7373, 53142, 627, 791, 29346, 82, 527, 6020, 11427, 388, 1981, 2435, 2322, 520, 2254, 30693, 10017, 323, 449, 279, 24710, 315, 264, 4333, 11, 8529, 15453, 4691, 704, 52179, 13, 4740, 279, 11999, 2457, 814, 934, 292, 398, 6244, 54682, 50256, 323, 12502, 264, 1060, 477, 779, 3010, 13, 11995, 52179, 323, 8529, 3021, 26012, 323, 14324, 3300, 13, 8529, 374, 810, 8173, 304, 41273, 22538, 323, 52179, 374, 810, 8173, 12798, 1022, 1475, 11897, 814, 617, 13, 4452, 2225, 315, 1124, 7655, 304, 5496, 1664, 3770, 872, 3445, 13, 9393, 814, 2225, 3665, 779, 1790, 11, 1070, 8706, 6020, 3575, 374, 30230, 1405, 311, 2793, 477, 3665, 872, 5066, 11441, 627, 18433, 279, 5743, 27024, 709, 5880, 315, 220, 508, 4, 315, 872, 4509, 710, 1935, 2162, 2343, 11, 279, 5743, 706, 93250, 5115, 459, 1358, 315, 19523, 13, 11205, 2162, 11, 15075, 1120, 8223, 1667, 4227, 574, 13517, 15075, 369, 400, 16, 13, 17, 34629, 81289, 11, 719, 706, 41482, 304, 907, 311, 2555, 304, 279, 7138, 315, 400, 16, 13, 20, 34629, 81289, 13, 9393, 814, 1304, 520, 3325, 832, 11, 422, 539, 1403, 11, 5066, 21515, 14507, 824, 1060, 323, 1606, 814, 2231, 779, 1790, 1523, 994, 814, 11021, 433, 11, 872, 21515, 23874, 520, 2212, 400, 22276, 11, 931, 13, 2435, 617, 264, 1633, 15022, 21515, 4478, 627, 35897, 2132, 2162, 11, 374, 10213, 49959, 704, 2391, 279, 1060, 323, 374, 7559, 304, 264, 29779, 6424, 304, 15745, 13, 1102, 374, 264, 44200, 11, 902, 374, 33647, 520, 922, 400, 19633, 11, 931, 323, 814, 6920, 264, 400, 12226, 11, 931, 21515, 389, 433, 13, 8876, 433, 374, 10213, 49959, 704, 11, 279, 29346, 82, 87377, 706, 26160, 1124, 430, 814, 527, 3794, 264, 2678, 3827, 9610, 505, 41377, 433, 627, 11663, 1109, 872, 1403, 10632, 11, 279, 5743, 706, 12387, 1023, 12032, 11, 2737, 1403, 220, 10841, 42, 82, 369, 52179, 33647, 520, 922, 400, 21018, 11, 931, 323, 264, 37512, 59783, 315, 400, 2075, 11, 931, 13, 8529, 706, 832, 220, 10841, 42, 304, 279, 3392, 315, 400, 6550, 11, 931, 11, 74869, 59783, 33647, 520, 400, 18775, 11, 931, 323, 459, 2362, 37512, 59783, 304, 279, 3392, 315, 400, 1958, 11, 931, 627, 2170, 16358, 439, 430, 682, 10578, 279, 5743, 1101, 706, 42853, 2536, 21624, 19523, 439, 1664, 25, 1556, 2930, 19523, 2759, 449, 220, 10674, 11, 931, 323, 264, 2254, 10496, 14324, 2759, 5762, 520, 279, 2254, 6201, 449, 400, 1419, 11, 2636, 13, 2435, 617, 264, 9341, 2759, 5762, 449, 264, 5426, 9341, 2883, 430, 374, 10213, 29091, 304, 28979, 54163, 82, 323, 27512, 11049, 10736, 304, 279, 3392, 315, 400, 22094, 11, 931, 13, 2435, 617, 5370, 1023, 2678, 22538, 82223, 922, 400, 1774, 11, 931, 627, 35897, 24417, 10003, 706, 264, 220, 21618, 2759, 430, 11725, 1077, 439, 264, 63932, 449, 922, 400, 3971, 11, 931, 323, 279, 39637, 10003, 706, 264, 6883, 502, 220, 21618, 449, 1077, 10212, 439, 279, 63932, 13, 1115, 2759, 706, 1193, 400, 605, 11, 931, 13, 11995, 220, 21618, 9815, 5371, 17392, 15438, 34751, 315, 400, 16, 11, 931, 824, 2305, 13, 578, 5743, 374, 16913, 430, 1990, 279, 1510, 8335, 323, 3938, 15438, 34751, 690, 387, 3025, 311, 3504, 1455, 315, 872, 2911, 596, 41534, 7194, 627, 21279, 315, 872, 30968, 1101, 617, 2753, 1109, 400, 605, 42, 320, 23, 42, 11, 220, 17, 42, 8, 743, 16038, 369, 1124, 304, 7188, 26639, 4940, 9815, 1555, 872, 5426, 23117, 13, 43633, 52179, 21879, 21258, 369, 1077, 1403, 7724, 1364, 7214, 34751, 279, 3300, 1139, 279, 9815, 627, 11663, 1109, 279, 1403, 21515, 10212, 3485, 11, 279, 1193, 11897, 430, 279, 5743, 706, 374, 264, 2678, 33247, 3392, 315, 6593, 2978, 11897, 304, 279, 3392, 315, 400, 1774, 11, 931, 13, 52179, 574, 18069, 304, 3515, 6924, 3403, 323, 574, 9087, 555, 1077, 6699, 311, 2343, 1022, 2383, 2978, 1317, 4227, 13, 2030, 1077, 61954, 6593, 2978, 11897, 374, 264, 2592, 315, 18547, 369, 1077, 13, 11995, 8529, 323, 1077, 18046, 922, 433, 3629, 13, 8529, 15849, 430, 814, 1288, 1120, 2187, 433, 311, 387, 7318, 1022, 389, 892, 11, 1418, 52179, 1053, 1093, 311, 3350, 264, 1817, 323, 387, 2884, 449, 433, 627, 791, 29346, 82, 527, 8515, 6530, 6928, 11, 7438, 814, 527, 6847, 4737, 304, 810, 3300, 1109, 814, 527, 10374, 13, 2435, 6678, 6555, 47972, 11, 719, 3197, 311, 6678, 1124, 3156, 814, 527, 520, 3325, 5899, 1667, 2362, 13, 2435, 617, 2478, 2574, 430, 814, 2980, 14379, 10612, 323, 656, 539, 4774, 279, 11646, 19433, 315, 1690, 315, 872, 2911, 596, 6699, 4885, 11, 98717, 311, 8493, 892, 449, 11838, 3070, 627, 791, 1935, 304, 13937, 520, 3325, 400, 13506, 11, 931, 824, 1060, 323, 7170, 709, 311, 400, 13655, 11, 931, 824, 1060, 627, 84549, 872, 10632, 11, 220, 21618, 82, 11, 2911, 596, 26639, 4940, 9815, 11, 814, 617, 2860, 12032, 315, 922, 400, 17, 11, 17458, 11, 2636, 539, 2737, 279, 7319, 907, 315, 872, 6156, 2162, 315, 922, 400, 3101, 11, 931, 13, 1115, 4272, 5922, 1587, 539, 1935, 1139, 2759, 12387, 2574, 2737, 11, 719, 539, 7347, 311, 25, 11205, 92652, 11, 2684, 4689, 53635, 11, 11205, 2678, 1989, 4526, 11, 6463, 279, 4754, 1005, 315, 3674, 4868, 520, 21624, 13, 1102, 1101, 6724, 64468, 8529, 596, 88599, 6725, 323, 52179, 596, 7658, 15664, 439, 1521, 9873, 527, 9193, 2653, 311, 907, 13, 4452, 11, 814, 656, 617, 907, 627, 13461, 449, 420, 8056, 3392, 315, 19523, 52179, 1587, 539, 2733, 9966, 13, 3005, 11196, 82, 15320, 922, 8529, 3794, 42184, 369, 279, 6593, 9650, 568, 13551, 389, 279, 9063, 439, 1664, 439, 813, 6725, 21347, 264, 15779, 11937, 11, 1364, 8964, 430, 279, 22881, 304, 279, 3723, 4273, 311, 16632, 3240, 5897, 29407, 2403, 4423, 374, 4856, 3428, 13, 1628, 8051, 8529, 6920, 82, 8560, 60621, 8276, 11, 1364, 11196, 82, 430, 433, 1253, 539, 387, 3403, 627, 25763, 374, 539, 18290, 922, 420, 2288, 1790, 323, 8349, 430, 3794, 42184, 374, 961, 315, 1694, 264, 2626, 6506, 13, 1283, 374, 4869, 11, 10284, 11920, 922, 279, 5708, 3157, 323, 374, 15320, 3411, 369, 22538, 4994, 315, 23301, 13, 1283, 13919, 430, 1990, 872, 9341, 9815, 323, 21624, 9815, 11, 814, 527, 927, 9277, 1139, 279, 3157, 439, 264, 4459, 627, 21279, 8529, 323, 52179, 3665, 279, 7340, 85852, 3392, 1139, 872, 5664, 70289, 6787, 13, 10180, 400, 845, 11, 931, 5636, 459, 19683, 19035, 315, 400, 20, 42, 369, 52179, 323, 8529, 449, 264, 74869, 59783, 19035, 315, 15038, 1990, 400, 972, 42, 311, 400, 1758, 42, 824, 1060, 13, 52179, 1101, 9711, 3300, 1139, 264, 2536, 78912, 59783, 45370, 323, 33822, 433, 311, 264, 37512, 59783, 13, 2435, 91624, 3201, 922, 400, 1187, 42, 824, 1060, 1139, 279, 6980, 220, 21618, 6787, 11, 1304, 5066, 21515, 14507, 11, 323, 527, 7373, 53142, 13, 2435, 923, 520, 3325, 400, 966, 42, 311, 400, 1758, 42, 824, 1060, 311, 872, 2930, 14324, 6201, 323, 16946, 279, 2800, 315, 872, 19523, 10496, 279, 5165, 33350, 8351, 12096, 709, 386, 16080, 54163, 82, 323, 72689, 12937, 54163, 82, 13, 32862, 814, 11196, 430, 872, 24417, 1716, 596, 220, 21618, 690, 617, 682, 433, 3966, 323, 1243, 1148, 1288, 814, 656, 30, 2030, 1148, 775, 311, 656, 449, 872, 3300, 5380, 25763, 16181, 1063, 7493, 323, 20628, 264, 4585, 88, 8276, 8479, 520, 264, 19665, 65281, 889, 706, 1027, 4560, 311, 28008, 1461, 430, 264, 4459, 2324, 8276, 4947, 374, 279, 1888, 3245, 2533, 279, 1778, 261, 13, 1115, 9601, 22413, 8479, 39701, 4455, 323, 46672, 304, 9601, 22413, 10396, 369, 28994, 16410, 13, 2052, 279, 16410, 22380, 922, 1461, 11, 994, 568, 539, 2212, 13, 4452, 11, 832, 315, 279, 93118, 9191, 27437, 304, 279, 1912, 11, 10975, 279, 1912, 430, 813, 6848, 527, 539, 11622, 5076, 627, 2688, 19762, 311, 5603, 279, 2324, 8276, 8479, 11, 8529, 1587, 1063, 3495, 2930, 323, 14035, 4689, 72106, 369, 4459, 2324, 8276, 323, 1202, 28360, 61007, 26581, 323, 12689, 9601, 13, 4452, 304, 813, 5403, 568, 1587, 1518, 8349, 430, 41593, 9601, 22413, 649, 8854, 439, 264, 1376, 315, 9513, 9313, 323, 420, 35730, 311, 1461, 13, 4497, 9601, 22413, 374, 4762, 264, 1695, 3245, 11, 15849, 8529, 13, 4740, 5403, 420, 568, 6880, 323, 37869, 264, 4062, 6574, 304, 813, 5274, 449, 813, 19665, 287, 8276, 8479, 13, 3861, 315, 279, 2574, 430, 7214, 82454, 8529, 922, 279, 8276, 8479, 374, 279, 6996, 315, 3966, 3196, 34685, 430, 279, 8276, 8479, 706, 449, 1461, 13, 578, 8276, 8479, 374, 84388, 430, 4459, 2324, 8276, 374, 279, 1888, 3245, 304, 279, 1917, 369, 1455, 8689, 323, 430, 4751, 2324, 8276, 690, 1629, 704, 11, 9564, 279, 29346, 82, 330, 14789, 8276, 2753, 1210, 8529, 7214, 15849, 420, 374, 15526, 1606, 279, 8276, 8479, 706, 912, 4623, 1148, 813, 4272, 5922, 374, 11, 6463, 872, 1205, 369, 2324, 8276, 1306, 872, 4751, 10396, 842, 13, 1283, 6944, 311, 842, 279, 6574, 1314, 1243, 323, 1070, 11, 719, 5334, 86494, 555, 459, 19957, 13147, 4641, 1650, 13, 4740, 279, 4641, 1650, 568, 6276, 279, 8893, 6763, 5794, 311, 3136, 627, 791, 10652, 9731, 449, 279, 8276, 8479, 34988, 1063, 1401, 8125, 430, 16410, 2216, 1288, 2980, 264, 4459, 2324, 4947, 11, 2737, 3284, 9513, 9313, 323, 264, 2678, 2802, 4478, 7318, 1555, 56364, 304, 279, 24435, 4459, 2324, 4947, 13, 93414, 1022, 7771, 11, 539, 14392, 1148, 56364, 527, 304, 5133, 311, 2324, 8276, 11, 2999, 8529, 11, 7214, 8638, 4737, 8554, 13, 578, 8276, 8479, 1437, 2076, 430, 813, 362, 10, 19115, 706, 7318, 704, 56364, 369, 11026, 13, 4740, 6975, 922, 279, 56364, 11, 8529, 29346, 47310, 430, 420, 8276, 8479, 706, 1193, 832, 8276, 2883, 430, 568, 31878, 369, 13, 8529, 374, 10284, 11920, 922, 420, 323, 28727, 1202, 892, 311, 1373, 709, 323, 6604, 449, 810, 1274, 627, 25763, 11, 35434, 279, 15864, 449, 813, 7555, 889, 304, 69118, 449, 279, 7434, 315, 264, 5226, 3196, 14324, 3197, 719, 374, 22568, 555, 279, 10824, 449, 459, 8276, 2027, 13, 3005, 4284, 430, 8529, 5662, 704, 311, 279, 872, 393, 70881, 22413, 21372, 38481, 13, 38481, 374, 810, 1109, 6380, 311, 4358, 57316, 9601, 22413, 2671, 11, 10213, 9076, 555, 8743, 47, 22413, 54642, 323, 1306, 264, 11298, 3160, 3966, 3196, 10430, 11, 26467, 304, 459, 85504, 26581, 9601, 22413, 4947, 60727, 430, 433, 374, 682, 279, 34049, 1521, 2919, 13, 8529, 374, 264, 2766, 2231, 1022, 555, 420, 439, 304, 872, 4113, 4641, 10430, 568, 1047, 9932, 19762, 264, 2536, 5708, 3157, 19523, 3197, 323, 279, 85504, 26581, 9601, 8276, 4947, 374, 14738, 17791, 311, 3157, 5178, 13, 7429, 994, 4691, 922, 1268, 433, 574, 10815, 11, 38481, 279, 393, 70881, 8479, 11497, 433, 11, 719, 539, 1664, 13, 578, 4459, 3245, 9508, 2288, 31715, 311, 8529, 323, 568, 574, 539, 10882, 449, 279, 13307, 2237, 315, 6677, 389, 279, 6671, 627, 25763, 1243, 25501, 704, 311, 264, 4846, 60841, 10790, 430, 1047, 1317, 4227, 15107, 709, 264, 11307, 369, 2532, 6020, 3197, 369, 8529, 11, 1203, 994, 568, 574, 3254, 13, 8529, 596, 1421, 1947, 574, 430, 1077, 990, 574, 43660, 11, 719, 430, 279, 60841, 10790, 4934, 1461, 311, 1095, 1077, 10299, 813, 12032, 13, 2876, 19762, 311, 2343, 220, 16, 13, 16, 4, 824, 1060, 369, 420, 2532, 8529, 2486, 8293, 13, 3161, 264, 36646, 2802, 505, 459, 2362, 8589, 11, 53391, 279, 60841, 10790, 6288, 49098, 279, 18921, 323, 1550, 13310, 430, 264, 41593, 9601, 22413, 3197, 1436, 1981, 387, 5505, 311, 4423, 304, 872, 6020, 6671, 13, 2435, 14407, 85504, 26581, 9601, 6787, 11, 719, 1364, 12090, 430, 1521, 2324, 8276, 10396, 1051, 82787, 449, 1579, 12718, 323, 31715, 29217, 315, 9341, 9669, 323, 19079, 13, 53391, 67469, 430, 44581, 1113, 41593, 9601, 11, 422, 4400, 775, 11, 574, 2753, 6485, 1109, 85504, 26581, 323, 574, 13118, 2753, 3157, 16614, 13, 10541, 1364, 1550, 4546, 709, 1077, 16801, 430, 8051, 44581, 1113, 41593, 9601, 22413, 5220, 1051, 539, 23301, 323, 1550, 539, 6118, 1866, 2288, 1690, 304, 872, 20136, 11, 814, 1051, 520, 5326, 315, 11049, 5178, 2533, 814, 6118, 1047, 1690, 304, 872, 76808, 627, 644, 279, 842, 279, 60841, 10790, 2216, 3463, 264, 2731, 3351, 574, 832, 315, 26012, 304, 502, 11987, 369, 279, 5743, 13, 3005, 12090, 264, 20136, 315, 86148, 47910, 11, 323, 5234, 78478, 11897, 11, 8430, 430, 279, 29346, 82, 1550, 539, 3412, 1521, 4595, 315, 22538, 5131, 627, 37, 2739, 496, 660, 11, 1457, 8529, 1587, 539, 1440, 1148, 311, 656, 13, 1283, 574, 539, 2133, 311, 18467, 264, 60841, 10790, 323, 574, 7995, 539, 2133, 311, 387, 15753, 1139, 459, 85504, 26581, 4947, 13, 1283, 2103, 6612, 813, 1888, 3072, 11203, 449, 279, 28131, 287, 22413, 21372, 11, 719, 4934, 4423, 311, 3477, 813, 3966, 505, 5361, 5220, 13, 8529, 12920, 279, 10430, 449, 813, 7555, 323, 2267, 23265, 311, 10491, 1148, 311, 656, 627, 32, 1060, 5900, 555, 323, 52179, 912, 5129, 6944, 311, 2231, 904, 810, 3300, 1139, 872, 24417, 30968, 220, 21618, 3197, 439, 1364, 48517, 430, 433, 374, 4762, 3403, 369, 872, 30968, 3938, 6873, 304, 922, 220, 1032, 1667, 13, 3005, 40396, 709, 389, 279, 19564, 311, 1077, 39637, 30968, 220, 21618, 3197, 505, 400, 16, 11, 931, 311, 400, 17, 11, 931, 824, 2305, 13, 11995, 2911, 527, 29091, 304, 279, 4325, 320, 6902, 4090, 8, 3196, 76808, 779, 814, 527, 16168, 389, 72258, 24911, 13, 52179, 374, 11920, 430, 814, 1457, 2216, 617, 810, 3300, 311, 2793, 1109, 814, 1440, 1148, 311, 656, 449, 13, 362, 1695, 3575, 311, 617, 11, 719, 433, 13912, 1077, 709, 520, 3814, 627, 41, 18314, 8638, 264, 2678, 2447, 315, 3411, 520, 279, 42209, 4435, 315, 77990, 430, 814, 649, 1304, 449, 872, 2678, 27402, 315, 3300, 13, 3005, 32238, 23395, 264, 400, 1041, 42, 19160, 3424, 3221, 1405, 1077, 6699, 3974, 304, 17368, 13, 55409, 1139, 264, 80121, 13492, 13, 93696, 304, 264, 2678, 2254, 10960, 1555, 264, 4333, 13, 2052, 315, 279, 2671, 44030, 1077, 3582, 13, 3277, 52179, 323, 8529, 4358, 279, 3917, 1202, 2867, 430, 1364, 374, 279, 6220, 30693, 323, 8529, 13452, 311, 4585, 279, 5326, 23819, 13, 52179, 12716, 709, 279, 4459, 2324, 3072, 1578, 311, 8529, 627, 16179, 555, 420, 892, 8529, 706, 1027, 14183, 311, 5361, 1023, 8276, 13307, 11, 568, 14865, 311, 1505, 832, 430, 2216, 8964, 813, 6392, 323, 374, 3025, 311, 990, 449, 5361, 35991, 13, 8529, 5616, 11, 4669, 279, 7757, 11, 52114, 459, 22413, 16784, 16383, 304, 5361, 5415, 11, 2737, 7188, 11, 430, 2216, 5084, 3025, 311, 3477, 872, 6671, 627, 791, 1633, 1176, 3245, 430, 279, 22413, 21372, 11, 469, 263, 505, 279, 8191, 7626, 11, 17501, 1306, 15884, 34988, 872, 1162, 374, 25, 8886, 3060, 315, 872, 17978, 9601, 22413, 10396, 68713, 30, 8529, 706, 912, 4623, 1148, 568, 374, 10371, 323, 17501, 1461, 311, 13454, 279, 3488, 323, 1243, 10552, 13, 14727, 14715, 814, 842, 872, 10430, 11, 449, 8529, 2133, 704, 311, 13488, 422, 13118, 3060, 315, 872, 4751, 2324, 10396, 617, 420, 3072, 627, 25763, 6880, 469, 263, 279, 2324, 8479, 1203, 311, 3371, 1461, 430, 7000, 315, 872, 4751, 2324, 10396, 527, 68713, 13, 469, 263, 94087, 1461, 11, 430, 1202, 10619, 11, 430, 568, 649, 636, 3060, 477, 2225, 315, 1124, 1389, 264, 2678, 4459, 2324, 4947, 449, 459, 362, 22359, 24435, 19115, 13, 8529, 304, 18164, 922, 279, 907, 315, 279, 6807, 10959, 323, 469, 263, 43446, 430, 1202, 810, 3062, 449, 4459, 2324, 1109, 433, 374, 449, 4751, 2324, 13, 8529, 1243, 18417, 469, 263, 311, 3371, 1461, 430, 568, 1053, 1093, 264, 3544, 4459, 2324, 4947, 11, 2555, 304, 13937, 315, 3861, 34629, 2326, 81289, 13, 469, 263, 11, 5415, 430, 568, 690, 37875, 1501, 1461, 279, 5219, 369, 264, 2134, 315, 2671, 11, 719, 13533, 430, 814, 1427, 520, 9333, 2671, 439, 1664, 627, 791, 7757, 8276, 8479, 1101, 38202, 264, 2478, 4520, 311, 81867, 39170, 8529, 304, 813, 6848, 315, 9513, 9313, 902, 574, 832, 315, 279, 4113, 16188, 8125, 430, 8529, 1047, 16495, 704, 41593, 9601, 13, 469, 263, 11, 279, 7757, 8479, 13551, 449, 1461, 430, 9513, 9313, 374, 330, 428, 54358, 1614, 3230, 1, 323, 430, 7188, 1587, 539, 617, 43660, 36707, 9513, 9313, 13, 1283, 13533, 430, 568, 16988, 459, 14065, 304, 264, 11944, 10430, 11, 719, 14633, 1461, 264, 3997, 430, 11725, 1063, 32874, 922, 7188, 4459, 2324, 330, 42371, 907, 1, 98489, 9313, 627, 5971, 469, 263, 323, 8529, 4358, 8529, 596, 2890, 11, 813, 7640, 11, 4913, 11, 323, 12387, 1023, 1234, 26372, 13186, 13, 3161, 279, 4641, 1650, 3794, 311, 387, 927, 459, 6596, 1317, 814, 3009, 2875, 315, 34988, 52179, 596, 2890, 323, 1234, 26372, 2038, 13, 8529, 3010, 69025, 420, 627, 36, 263, 11, 18911, 311, 2225, 8529, 323, 52179, 5370, 4459, 2324, 8276, 2671, 449, 362, 323, 362, 10, 22359, 24435, 4459, 2324, 35991, 13, 1283, 43446, 430, 814, 2225, 3619, 279, 6811, 1990, 279, 19883, 323, 19655, 907, 27223, 13, 578, 19655, 907, 9676, 1005, 5219, 430, 527, 2753, 1109, 279, 3347, 46980, 7969, 627, 1548, 27461, 15100, 3249, 8403, 315, 813, 5128, 1790, 1193, 7782, 4459, 2324, 8276, 11, 304, 420, 955, 6671, 11, 449, 24435, 35991, 13, 2650, 24435, 35991, 527, 13234, 555, 872, 53142, 82, 323, 279, 1005, 315, 279, 56364, 13, 8529, 374, 1457, 7373, 520, 2162, 449, 682, 315, 279, 5403, 323, 12365, 922, 4459, 2324, 323, 29944, 304, 26073, 1063, 315, 279, 73886, 3585, 311, 52179, 627, 36, 263, 11, 1101, 12716, 709, 264, 330, 99327, 1553, 315, 26745, 54942, 1, 323, 15100, 1202, 907, 422, 279, 53142, 374, 12153, 311, 990, 13, 21347, 264, 10896, 11, 8529, 7214, 43632, 323, 374, 6656, 1022, 555, 279, 4623, 539, 49837, 8276, 5220, 7419, 315, 28353, 13, 469, 263, 11, 279, 7757, 8479, 69589, 8529, 11, 279, 19150, 323, 94087, 1461, 430, 1070, 527, 1690, 17931, 1511, 369, 28353, 323, 430, 568, 2643, 387, 3025, 311, 1505, 264, 7419, 430, 568, 649, 3974, 449, 627, 791, 15864, 5900, 5128, 1664, 11, 719, 279, 2853, 315, 279, 9220, 34629, 323, 1524, 3861, 34629, 11441, 6787, 10988, 52179, 323, 10284, 13051, 8529, 13, 11995, 315, 1124, 11, 1051, 14792, 1268, 1790, 810, 433, 7194, 1109, 2237, 4751, 2324, 8276, 13, 8529, 11, 6288, 6227, 430, 279, 7757, 8276, 8479, 1047, 12090, 279, 400, 2636, 42, 3072, 439, 264, 330, 9181, 261, 3197, 1, 323, 374, 16089, 430, 813, 14050, 2997, 420, 3072, 13, 469, 263, 706, 25243, 369, 2225, 315, 1124, 323, 568, 5415, 430, 2533, 814, 617, 539, 1047, 279, 6776, 311, 4358, 52179, 596, 1234, 26372, 279, 3430, 17989, 527, 2216, 539, 430, 13687, 627, 4897, 1694, 1071, 11, 52179, 596, 45370, 7194, 2873, 4827, 11, 26310, 3196, 389, 279, 2144, 430, 1364, 374, 264, 5333, 320, 7642, 750, 3278, 3974, 5129, 705, 323, 323, 11000, 3196, 389, 279, 6996, 315, 8389, 2038, 922, 1077, 2890, 3925, 2533, 814, 617, 539, 14407, 433, 13, 578, 15864, 10548, 389, 264, 1579, 5296, 11, 449, 2225, 8529, 323, 52179, 8430, 16913, 304, 3515, 1766, 264, 42066, 8479, 430, 706, 13375, 264, 2539, 3966, 3196, 6492, 389, 872, 6671, 627, 41, 18314, 1176, 24208, 311, 8529, 11, 430, 1364, 15849, 1202, 2288, 11646, 323, 430, 1364, 3250, 956, 3619, 3249, 814, 1053, 1390, 8276, 3131, 279, 6980, 527, 704, 315, 279, 3838, 323, 814, 16177, 13, 8529, 11, 889, 374, 6118, 539, 279, 6220, 30693, 304, 279, 3838, 8964, 430, 52179, 16180, 6220, 22538, 779, 568, 5829, 420, 24613, 300, 3210, 304, 813, 5811, 922, 279, 5845, 311, 2231, 264, 2678, 3392, 315, 3300, 304, 264, 4459, 2324, 4947, 430, 690, 6847, 387, 17049, 369, 1124, 11, 1524, 2391, 21624, 13, 52179, 11, 539, 7373, 39427, 11, 520, 3325, 34008, 430, 400, 2636, 42, 374, 279, 1455, 1364, 374, 8173, 304, 13, 2435, 2225, 5895, 922, 279, 81728, 311, 70632, 8529, 6296, 52179, 6296, 2225, 315, 1124, 13, 52179, 374, 917, 4841, 922, 279, 3463, 315, 2225, 315, 1124, 12096, 264, 4459, 2324, 4947, 13, 1789, 5419, 5054, 8125, 11, 8529, 15849, 814, 568, 690, 3577, 4741, 449, 279, 9333, 4459, 2324, 4947, 369, 1120, 5678, 13, 52179, 15849, 814, 1288, 2793, 810, 304, 279, 3157, 304, 6220, 27848, 10736, 323, 23301, 1778, 439, 1063, 315, 279, 2671, 1364, 5602, 1566, 3814, 389, 73359, 11, 1778, 439, 26230, 23301, 902, 8541, 311, 2343, 704, 6220, 56364, 627, 16179, 279, 7724, 527, 3794, 9191, 11, 304, 264, 5743, 315, 1667, 279, 14992, 10003, 690, 387, 2884, 449, 61905, 323, 387, 37191, 520, 279, 2254, 36256, 2978, 14713, 872, 7194, 264, 2766, 13, 2435, 2103, 617, 922, 11, 389, 5578, 400, 1758, 42, 824, 1060, 304, 13937, 9341, 3300, 304, 902, 311, 1005, 13, 1952, 28961, 1667, 433, 649, 47856, 11911, 389, 33321, 315, 279, 1403, 7487, 311, 2555, 1790, 5190, 13, 3277, 814, 527, 2884, 7373, 26012, 304, 872, 39637, 30968, 220, 21618, 3197, 3582, 433, 690, 3152, 264, 3284, 5217, 400, 1187, 42, 824, 1060, 33921, 459, 9341, 2162, 13, 4740, 12365, 449, 52179, 568, 374, 11920, 922, 832, 315, 279, 54111, 1364, 7263, 709, 323, 430, 420, 1193, 3727, 5647, 422, 814, 527, 2225, 3025, 311, 2567, 3318, 323, 3136, 311, 1304, 279, 1890, 3392, 315, 3300, 13, 1442, 832, 315, 1124, 1051, 311, 9229, 872, 7032, 477, 872, 9873, 6244, 653, 26466, 481, 279, 4459, 2324, 3072, 2643, 4785, 389, 1124, 1093, 459, 15375, 5836, 17543, 627, 25763, 15849, 1317, 323, 2653, 922, 1148, 264, 2536, 3318, 6671, 1436, 1427, 1093, 13, 1283, 374, 539, 82140, 555, 433, 11, 719, 433, 374, 18815, 13, 19292, 568, 1288, 1120, 6068, 420, 627, 2688, 49837, 19002, 8529, 11, 23874, 1523, 449, 13597, 323, 18343, 311, 3477, 813, 2671, 449, 279, 11223, 4459, 2324, 4947, 13, 2468, 400, 22, 42, 824, 1060, 433, 1053, 387, 832, 315, 872, 8706, 45370, 18512, 1306, 3424, 13426, 389, 1403, 6012, 323, 21515, 14507, 13, 19292, 568, 649, 15673, 813, 4751, 2324, 4947, 30, 2360, 11, 430, 1587, 539, 1304, 5647, 13, 2468, 400, 22, 42, 824, 1060, 11, 220, 966, 1667, 315, 14507, 690, 3392, 315, 400, 8848, 42, 304, 2860, 13, 2876, 279, 842, 315, 279, 4947, 719, 264, 1695, 12143, 315, 433, 13, 1628, 568, 2736, 706, 810, 1109, 400, 8848, 42, 743, 16038, 11, 779, 1524, 422, 568, 18151, 813, 2683, 1981, 15031, 5269, 11, 568, 1436, 2103, 10150, 311, 1304, 279, 2324, 8276, 15193, 8323, 11, 1314, 30, 14144, 11, 1268, 1053, 568, 1304, 279, 21515, 8323, 30, 578, 8825, 15545, 8323, 30, 578, 1566, 1781, 304, 279, 1917, 568, 374, 2133, 311, 1390, 311, 656, 449, 813, 3300, 374, 2343, 369, 264, 9770, 19523, 3197, 13, 2030, 3868, 11, 813, 7555, 4375, 627, 2181, 1053, 2216, 1193, 387, 264, 3682, 4360, 422, 814, 86589, 5675, 872, 7032, 11, 520, 279, 1890, 892, 13, 3005, 374, 264, 8427, 520, 264, 2383, 7626, 323, 568, 25241, 813, 1866, 2626, 11, 374, 420, 3284, 30, 8529, 5334, 709, 505, 813, 659, 10430, 22954, 430, 433, 1053, 1397, 264, 3776, 2064, 276, 1567, 311, 1304, 420, 264, 8903, 323, 568, 13919, 1521, 4595, 315, 2064, 598, 649, 539, 387, 10235, 369, 627, 1548, 1587, 636, 264, 43560, 273, 704, 315, 77724, 12096, 420, 2027, 389, 264, 1790, 4827, 8070, 439, 264, 2478, 315, 813, 14992, 323, 2753, 6992, 19228, 617, 2884, 13, 1283, 40164, 1268, 814, 2216, 6958, 433, 1022, 13, 3234, 814, 10240, 872, 220, 10841, 42, 30, 2876, 1304, 5066, 21515, 14507, 30, 26869, 279, 7926, 19523, 3197, 30, 31048, 75453, 81289, 824, 1060, 11, 369, 2324, 11, 369, 4459, 2324, 8276, 0, 46817, 430, 1120, 10578, 1093, 264, 2763, 568, 15849, 627, 25763, 8964, 430, 52179, 13912, 13687, 43653, 20924, 369, 1077, 12032, 11, 779, 568, 23874, 1523, 311, 656, 1148, 1364, 1053, 656, 13, 1283, 11705, 8310, 11, 11621, 7123, 323, 8015, 2740, 5678, 3495, 288, 1268, 420, 4947, 1053, 1427, 449, 279, 1520, 315, 279, 4459, 2324, 19883, 323, 19655, 907, 27223, 13, 1283, 43565, 4780, 2225, 59453, 323, 13365, 710, 481, 304, 813, 46986, 449, 1884, 315, 279, 2324, 8276, 5220, 627, 6153, 52179, 4780, 505, 264, 2626, 8577, 323, 927, 13378, 814, 2503, 1523, 2391, 279, 37755, 4520, 814, 617, 1949, 311, 3477, 1148, 8529, 6944, 311, 656, 13, 52179, 2795, 430, 1364, 374, 10619, 449, 1461, 7366, 4741, 389, 279, 400, 2636, 42, 4156, 719, 374, 1120, 2288, 39075, 11920, 671, 332, 4205, 8294, 1109, 420, 13, 3005, 1101, 38239, 430, 422, 1051, 539, 369, 813, 5679, 3640, 26314, 11, 1364, 4762, 1053, 2646, 617, 8272, 1555, 449, 279, 7782, 13, 8529, 10975, 52179, 813, 10742, 922, 4827, 28744, 1274, 12096, 4459, 2324, 323, 52179, 24208, 430, 430, 374, 264, 2216, 1695, 1486, 13, 330, 40, 1541, 956, 1440, 1268, 3885, 656, 433, 1, 3005, 2795, 13, 8529, 43560, 645, 14392, 813, 7555, 8964, 279, 40382, 2731, 1109, 568, 1587, 323, 422, 1364, 374, 10619, 449, 433, 11, 1109, 433, 4762, 374, 279, 1888, 5597, 627, 41, 18314, 323, 8529, 14224, 617, 872, 6020, 1180, 3871, 13, 2435, 656, 539, 4097, 279, 5578, 3778, 3070, 13, 14968, 1524, 304, 872, 6671, 279, 5597, 311, 7782, 323, 3887, 369, 279, 2800, 315, 872, 6439, 264, 4459, 2324, 8276, 4947, 374, 2216, 539, 4228, 627, 2261, 304, 459, 13937, 315, 400, 1041, 11, 931, 824, 1060, 11, 1855, 323, 1475, 1060, 11, 311, 502, 19523, 627, 21279, 315, 1124, 990, 13, 11995, 3318, 1436, 8854, 439, 459, 10535, 1376, 315, 28353, 659, 8276, 369, 1855, 1023, 627, 7009, 2567, 43653, 20924, 323, 7576, 627, 7009, 3137, 922, 279, 40382, 627, 7009, 527, 12798, 1523, 872, 10632, 449, 5066, 14507, 11, 7999, 311, 21624, 323, 7926, 14324, 6787, 627, 7009, 656, 264, 2763, 315, 29559, 11, 3449, 449, 12387, 11909, 311, 1505, 1120, 279, 1314, 2027, 627, 7009, 617, 7543, 22700, 315, 4207, 11, 7344, 33517, 4207, 45243, 41593, 9601, 323, 1202, 14908, 627, 11787, 279, 29346, 82, 4495, 311, 9855, 430, 872, 11223, 4459, 2324, 8276, 4947, 2643, 6144, 872, 12032, 304, 279, 1162, 315, 2555, 12765, 449, 872, 2626, 30, 19292, 11, 9513, 9313, 323, 36707, 7016, 527, 1633, 1614, 3230, 11, 1521, 8403, 3621, 311, 3974, 304, 7188, 13, 1628, 10771, 311, 7188, 2383, 41593, 9601, 22413, 23429, 9313, 374, 14738, 7347, 13, 48508, 527, 26160, 311, 2744, 6604, 449, 264, 15779, 304, 872, 1614, 994, 13126, 420, 627, 791, 1486, 311, 682, 315, 420, 374, 430, 1521, 1304, 4510, 1274, 11, 578, 29346, 82, 11, 527, 4276, 5578, 9053, 13, 2435, 1304, 264, 8941, 315, 3300, 0, 2435, 617, 3665, 1093, 279, 34629, 17724, 9479, 25166, 13, 2435, 527, 539, 6278, 538, 7487, 13, 2435, 3952, 1667, 311, 15884, 1304, 872, 5597, 13, 1789, 1455, 1274, 430, 656, 539, 5052, 420, 5643, 1981, 17978, 9601, 22413, 374, 810, 1109, 4461, 279, 1648, 311, 733, 13, 7566, 11, 1070, 527, 1063, 20157, 311, 430, 6037, 11, 369, 3187, 8689, 430, 1205, 264, 9984, 44240, 17236, 11, 719, 304, 4689, 17978, 374, 279, 1888, 7104, 627, 15346, 499, 617, 4860, 477, 539, 3619, 2555, 11, 4587, 2733, 1949, 311, 3729, 603, 6089, 520, 6763, 31, 5730, 258, 38655, 916, 13, 61695, 17978, 9601, 22413, 374, 4382, 323, 44252, 11, 41593, 9601, 374, 6485, 323, 17395, 13, 1102, 374, 2216, 304, 701, 1888, 2802, 311, 656, 701, 1866, 29559, 389, 279, 3917, 315, 2324, 8276, 13, 5321, 1518, 1057, 75992, 13, 9930, 499, 369, 5403, 1556, 9947, 57167, 12517, 7440, 13572, 41593, 9601, 22413, 627, 791, 3485, 3187, 922, 459, 9947, 57167, 12517, 7440, 13572, 41593, 9601, 22413, 374, 17422, 13, 5884, 43874, 1990, 5150, 1274, 374, 32227, 27285, 13, 35975, 323, 22413, 8351, 5144, 527, 44682, 13, 8595, 374, 433, 17422, 30, 8489, 11, 1176, 1022, 11, 433, 1053, 387, 1633, 2653, 311, 636, 8403, 311, 2187, 459, 8276, 9266, 311, 1005, 872, 4839, 6020, 2038, 13, 10657, 11, 1202, 539, 15325, 13, 21530, 11, 358, 4934, 311, 41468, 264, 4754, 3016, 430, 358, 4510, 11, 20025, 81007, 311, 1304, 264, 4459, 2324, 4947, 1304, 5647, 627, 2028, 4441, 574, 8621, 304, 9601, 22413, 15457, 11, 41593, 9601, 22413, 13, 56518, 279, 80328, 627, 36981, 11, 9523, 369, 279, 3446, 13, 5843, 1389, 719, 1664, 37246, 433, 627, 1687], 'labels': 2216, 'source': [{'source': 'RedPajamaCommonCrawl', 'start': 0, 'end': 4876}, {'source': 'RedPajamaCommonCrawl', 'start': 4876, 'end': 9846}, {'source': 'RedPajamaGithub', 'start': 9846, 'end': 14974}, {'source': 'RedPajamaGithub', 'start': 14974, 'end': 15444}, {'source': 'RedPajamaC4', 'start': 15444, 'end': 21358}, {'source': 'RedPajamaCommonCrawl', 'start': 21358, 'end': 38588}, {'source': 'RedPajamaCommonCrawl', 'start': 38588, 'end': 42277}, {'source': 'RedPajamaCommonCrawl', 'start': 42277, 'end': 46811}, {'source': 'RedPajamaCommonCrawl', 'start': 46811, 'end': 48246}, {'source': 'RedPajamaCommonCrawl', 'start': 48246, 'end': 55892}, {'source': 'RedPajamaC4', 'start': 55892, 'end': 58851}, {'source': 'RedPajamaCommonCrawl', 'start': 58851, 'end': 62938}, {'source': 'RedPajamaCommonCrawl', 'start': 62938, 'end': 67571}, {'source': 'RedPajamaStackExchange', 'start': 67571, 'end': 68114}, {'source': 'RedPajamaCommonCrawl', 'start': 68114, 'end': 71664}, {'source': 'RedPajamaC4', 'start': 71664, 'end': 72267}, {'source': 'RedPajamaC4', 'start': 72267, 'end': 72823}, {'source': 'RedPajamaC4', 'start': 72823, 'end': 73639}, {'source': 'RedPajamaCommonCrawl', 'start': 73639, 'end': 73839}, {'source': 'RedPajamaCommonCrawl', 'start': 73839, 'end': 74128}, {'source': 'RedPajamaC4', 'start': 74128, 'end': 74733}, {'source': 'RedPajamaCommonCrawl', 'start': 74733, 'end': 76214}, {'source': 'RedPajamaC4', 'start': 76214, 'end': 76539}, {'source': 'RedPajamaC4', 'start': 76539, 'end': 76602}, {'source': 'RedPajamaC4', 'start': 76602, 'end': 77008}, {'source': 'RedPajamaCommonCrawl', 'start': 77008, 'end': 81996}, {'source': 'RedPajamaCommonCrawl', 'start': 81996, 'end': 83303}, {'source': 'RedPajamaC4', 'start': 83303, 'end': 92227}, {'source': 'RedPajamaC4', 'start': 92227, 'end': 93557}, {'source': 'RedPajamaCommonCrawl', 'start': 93557, 'end': 97021}, {'source': 'RedPajamaCommonCrawl', 'start': 97021, 'end': 98292}, {'source': 'RedPajamaCommonCrawl', 'start': 98292, 'end': 102199}, {'source': 'RedPajamaC4', 'start': 102199, 'end': 102301}, {'source': 'RedPajamaCommonCrawl', 'start': 102301, 'end': 107994}, {'source': 'RedPajamaC4', 'start': 107994, 'end': 108217}, {'source': 'RedPajamaGithub', 'start': 108217, 'end': 108322}, {'source': 'RedPajamaC4', 'start': 108322, 'end': 108544}, {'source': 'RedPajamaC4', 'start': 108544, 'end': 108800}, {'source': 'RedPajamaC4', 'start': 108800, 'end': 108866}, {'source': 'RedPajamaC4', 'start': 108866, 'end': 110412}, {'source': 'RedPajamaCommonCrawl', 'start': 110412, 'end': 120789}, {'source': 'RedPajamaCommonCrawl', 'start': 120789, 'end': 122338}, {'source': 'RedPajamaWikipedia', 'start': 122338, 'end': 122831}, {'source': 'RedPajamaC4', 'start': 122831, 'end': 128001}]}\n",
+      " take massive steps forward in self-analysis by picking over our old music tastes. But there's no need to hand-wring about it – the Popular comments boxes are a lovely rich source of light personal commentary and real-life experience, none of it fitting glibly into a \"Then I was ashamed now I'm not, cor\" template.)\n",
+      "At the back of all this, meanwhile, there's a pop song: \"Get Down\", a rumbustious thing built on an enjoyable chugalug pop-rock groove. The best and most obvious thing about it is the chiming piano hits on the chorus, the worst probably a dog/girl metaphor which Sullivan doesn't take anywhere (though perhaps this is for the best – you can feel him tempted to write a punning \"It's his girlfriend! No it's actually a dog!\" track, which might have been ghastly). I'm a little surprised it's here at all, to be honest.\n",
+      "« DONNY OSMOND –\n"
+     ]
+    }
+   ],
+   "source": [
+    "with open(file_path, 'r') as file:\n",
+    "    for i,line in enumerate(file):\n",
+    "        # Parse each line as JSON\n",
+    "        line = json.loads(line.strip())\n",
+    "        # Process the JSON data as needed\n",
+    "        if i == 3:\n",
+    "            # print(line)\n",
+    "            # print(len(line['input_ids']))\n",
+    "            # print(line['input_ids'][:200])\n",
+    "            print(llama3_tokenizer.decode(line['input_ids'][:200]))\n",
+    "            break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "' take massive steps forward in self-analysis by picking over our old music tastes. But there\\'s no need to hand-wring about it – the Popular comments boxes are a lovely rich source of light personal commentary and real-life experience, none of it fitting glibly into a \"Then I was ashamed now I\\'m not, cor\" template.)\\nAt the back of all this, meanwhile, there\\'s a pop song: \"Get Down\", a rumbustious thing built on an enjoyable chugalug pop-rock groove. The best and most obvious thing about it is the chiming piano hits on the chorus, the worst probably a dog/girl metaphor which Sullivan doesn\\'t take anywhere (though perhaps this is for the best – you can feel him tempted to write a punning \"It\\'s his girlfriend! No it\\'s actually a dog!\" track, which might have been ghastly). I\\'m a little surprised it\\'s here at all, to be honest.\\n« DONNY OSMOND – \"The Twelfth Of Never\" TONY ORLANDO AND DAWN – \"Tie A Yellow Ribbon Round The Old Oak Tree\" »\\n« 1 2 All\\nPete Baran on 11 Jul 2007 #\\nInteresting there was never an Orb backlash!\\n(To explain, Adventures Beyond The Ultraworld pretty much made any and all Pink Floyd irrelevant to me when I discovered it. Vis a vis drugs and everything else).\\nTom on 11 Jul 2007 #\\nThere was totally an Orb backlash!\\nAlan on 11 Jul 2007 #\\nwhen will tanya do an Orb album covers post?\\nMarcello Carlin † on 11 Jul 2007 #\\nEr, Pommes Frites, anyone?\\nBrian † on 11 Jul 2007 #\\npassez le ketchup…..\\nMy take on Guilty Pleasures is a compilation of songs that I would never had admitted to liking at the time because the artist ( Cap\\'t & Tenille, Helen Reddy ) were not cool enough for me.\\nHowever there are many good songs that I secretly liked. This whole thing was brought back to me recently when I bought ( new ) a collection of Burt Bacharach hits. I don\\'t think I ever sang along to a Carpenters song until last week.\\nBut the pleasure was partially provided by great dripping wads of\\nnostalgia. A refuge to which I find myself increasingly drawn.\\nWaldo † on 11 Jul 2007 #\\nMarcello – \"a beneign excuse for a Stalinist/Cameronite rewrite of musical history\"??!! Oh, for crying out loud!\\nRosie – Guesses for 1978, with all attempts to avoid spoilers. How about UTR and RT? Do I win a bun?\\n\"Get Down\" – My main memory of this thing is Industrial Action being taken (What? A strike in 1973?), which meant that TOTP was not broadcast for much of the period that this was Number One. I could never understand why Uncle Ray used the dog analogy to describe his bird… I can also recall being in a chemistry lesson and using the same bench as a little kid called George. George spent just about the whole 45 minute lesson singing this wretched song over and over without pause. I was just about at the end of my tether and reaching for a metal tri-pod in order to silence him (we comprehensive school herberts used to do these things) when I was beaten to the punch, quite literally, by an enormous lad called Errol, whose solitary blow ensured that George \"got down\" indeed. Happy Days!\\nMark M † on 11 Jul 2007 #\\nI certainly denounced The Orb as a front for Floydian tendencies at the time – Hopkins should be able to back me up on this.\\nRosie † on 11 Jul 2007 #\\nWaldo, for me a stonking good top-notch song is a 9. A 10 has to come from out of the blue and make me want to fall over, add something special to something that\\'s already good to very good, or perhaps even be a borderline 1 that has something that makes it irresistible. This is by way of saying that your guess scores 19 out of a possible 20.\\nRosie – Aha! How about WH instead of RT?\\nPete † on 12 Jul 2007 #\\nHold yer horses there kids, the late seventies are a mere eight months away.\\nAnyway, one of the key points missing from this discussion is the Pans People interpretation of Get Down on Top Of The Pops. If you are doing a clip show, and want to show the literalism of PP, this is the one to go for.Aaaaah, doggies…\\nintothefireuk † on 12 Jul 2007 #\\nI believe I aluded to it in my first comment. Not one of PPs better moments or from a diff angle indeed their finest.\\nGilbert won\\'t be troubling us again so, give or take some ok and not so ok releases, 2 great singles (alone & rhymed) followed by 2 No.1 singles followed by ………. a long protracted legal wrangle that harpooned what was left of his career and made a few lawyers very happy (even though he won). Still he got some nice jumpers out of it (most with a big G on them).\\njeff w † on 12 Jul 2007 #\\nThat reads a bit like an obituary, intothefireuk! GO is touring the UK and Ireland again later this year. He\\'s not given up, yet.\\nRe: Orb and PF, I distinctly remember either the NME or Melody Maker putting them on the cover together one week.\\n(sorry Gilbert o\\'sullivan)\\nMatthew † on 19 Jul 2007 #\\nI think I\\'m a bit late to the party here, but I just see the Guilty Pleasures series as a chance to showcase some fine pop (and obviously some rubbish, depending) that\\'s been glossed over by the Official History of Rock. The canon triumphs for most punters, and many of the beauties Rowley reissued (at least on Vol 1) would never get their deserved look-in. I mean, The Fortunes had passed me by completely…\\nIt all has a whiff of very 90s pomo \"irony\", obviously, but perhaps the means don\\'t always matter.\\nI\\'ll consider amnesty if he puts \"Central Park Arrest\" by Thunderthighs on his next compilation.\\n…..Oh and just to be irritatingly pedantic – if we are to include Vol 3 of GP then Blockbuster is the first No.1 to be compiled!\\nOther things I expect to see on GP Vol 4:\\nAdriano Celentano – Prisencolinensenaiciusol\\nDooleys – Love Of My Life\\nPolly Brown – Up In A Puff Of Smoke\\nDee D Jackson – Automatic Lover\\nGuy Marks – Loving You Has Made Me Bananas\\nSailor – One Drink Too Many\\nRichard Myhill – It Takes Two To Tango\\nRichard Barnes – Take To The Mountains\\nGeordie – Can You Do It\\nSlik – Requiem\\nDrupi – Vado Via\\nReunion – Life Is A Rock (But The Radio Rolled Me)\\nJasper Carrott – Funky Moped\\nYin & Yan – Butch Soap\\nImperials – Who\\'s Gonna Love Me?\\nEli Bonaparte – Never An Everyday Thing\\nErrol Brown – From The Top Of My Head\\nCher – A Woman\\'s Story\\nLaurie Lingo & the Dipsticks – Convoy GB\\nOne Hundred Ton & A Feather – It Only Takes A Minute\\nLighthouse – Pretty Lady\\nhenry s † on 20 Jul 2007 #\\nanybody of a certain age who does not fondly recall \"Get Down\" must have had a lousy childhood…(or a marvelous one)…\\nYin and Yan\\'s \"Butch Soap\" was in fact the B-Side to their piss take of a record we will be discussing in 1975.\\nLena † on 21 Jul 2007 #\\nI\\'ve looked at the Guilty Pleasures cds again and am confused about why there are no songs by the Bay City Rollers anywhere. Are they a non-guilty pleasure (an innocent one)?\\nIf that\\'s the same \"Loving You Has Made Me Bananas\" then I heard it all the time on Dr. Demento.\\nDoctor Casino † on 22 Jul 2007 #\\nSo, guilty pleasures being rather well covered at this point (I think Tom and Marcello nail it for me – the term is offensive because it relies on your submitting to Their chummy simplification of a shared narrative), I\\'ll keep to Mr. O\\'Sullivan, none of whose work I\\'ve ever heard before Popular. As far as I can tell he\\'s basically a British Nilsson, yes? Somewhat more limited range, but same multitracked Beatlesey quality, bathrobe, doe eyes? I like these songs pretty good, and \"Get Down\" seems to me the best of the bunch so far. Fantastic hook! There\\'s a Chicory Tipness to the backing track, which I\\'m always a sucker for, and the turnaround on \"…but I still want you around!\" is as catchy a thing you could ever ask for.\\nMinuses for the generally miscellaneous and non-specific quality of the lyrics – does the cat on the hot tin roof need to be in there? The whole bit about drinking some wine time goes nowhere, not even as an analogy for how he feels now or anything like that. He might as well mention that he once owned a Buick. This song gets better the less closely it\\'s listened to, but its emptiness is much better-hidden than, say \"Chirpy Chirpy Cheep Cheep\"\\'s and it\\'s a better song for it.\\nIt may be helpful to know that the main influence behind Gilbert\\'s lyric writing was, and probably still is, Spike Milligan; see \"Ooh Wakka Doo Wakka Day\" (or maybe not) for a fuller demonstration of this.\\nI think it\\'s pretty straightforward though; given that he is frustrated and perhaps also a little intimidated by his dog, the \"cat\" is a good and basic analogy of his current emotional position, but the \"time/wine\" meme only really works if one extends the canine object to a rather unseemly metaphor, i.e. once he was footloose and fancy free but now he\\'s tied down by this, um, dog, and perhaps we\\'d better not go down that dimly lit road…\\nThe British Nilsson isn\\'t a bad comparison point, though Randy Newman is possibly a better fit (so that \"Get Down\" becomes his \"Short People\"), though I should point out that neither of these distinguished gentlemen began their career dressed in schoolboy cap and short trousers as Gilbert did up until \"Alone Again\"…the idea being that he thought he\\'d get places if he looked the direct and polar opposite of how everybody else looked in \\'69/70…\\nDoctor Casino † on 21 Sep 2007 #\\nhttp://www.youtube.com/watch?v=7xHyKyoEh5Q – Pan\\'s People dancers with a bunch of live dogs performing to \"Get Down.\" Thought some readers here might appreciate it…\\nlinda † on 8 Oct 2007 #\\ncan you tell me what gilber osulivan is doing now and is he going to do any more concerts\\njeff w † on 8 Oct 2007 #\\nCurrent UK tour details can be found here:\\nhttp://www.gilbertosullivan.net/\\nrichard thompson on 24 May 2008 #\\nThe music of Gilbert O\\'Sullivan was on in place of TOTP during his second week at number one, he sang this song first, the Pans People dog dance was on xmas day, does he really sing I don\\'t give a damn, as that word is used in the next number one.\\ngilbert get down † on 27 May 2008 #\\n[…] hits album in the M&ampVE 50p basement in the late 90s, and playing get down again and again.http://freakytrigger.co.uk/ft/2007/07/gilbert-osullivan-get-down/The man who will wake the monster – This is London&quotThe cathedral of the electrons&quot is how HJ […]\\nStevie † on 22 Mar 2011 #\\nTotal Bang-A-Gong rip, but great for the same reasons.\\nMark G † on 22 Mar 2011 #\\n(and linda didn\\'t even say thanks, even though JeffW answered almost immediately: #56 and #57)\\nwichita lineman † on 22 Mar 2011 #\\nShe was asking about gilber osulivan, though.\\nErithian † on 26 Aug 2011 #\\nJust to alert Populistas to a mini-Gilbert O\\'Sullivan theme night on BBC4 this evening, a profile followed by a concert performance alongside, er, Chris de Burgh.\\nMark G † on 26 Aug 2011 #\\nLady in red, get down.\\nActually, that sort-of improves it!\\nAndyPandy on 26 Aug 2011 #\\n44: I thought everyone knew about how synonymous Pink Floyd are with the Orb all the way from Alex Paterson making \\'Echoes\\' off \\'Meddle\\' such a big track in the original chillout room at Spectrum/Land of Oz in 1988 to last years collaboration album between The Orb and Dave Gilmour \\'Metallic Spheres\\' (Incidentally a wicked album if you give it time).\\nAfter all once chilling out as we know it now had arrived what more did you need than a few Pink Floyd, Tangerine Dream and Orb albums to keep you nicely relaxed till the pubs opened.\\nPatrick Mexico on 2 Dec 2013 #\\nI genuinely don\\'t think I\\'ve heard a single track on that first Guilty Pleasures compilation.\\n(For reference, I was born in 1985 and my earliest TOTP memory was Ace of Base – All That She Wants in summer 1993.)\\nMy parents were both in the thick of their teens by \"now\", but whether it was Motown or Van Morrison (for now, disregard that one about the pair of brown eyes that isn\\'t by the Pogues), both tended to appreciate classic songwriting and sincerity above kitsch appeal or gimmickry.. more out of disinterest in the GP market than real \"guilt.\"\\nlonepilgrim on 9 Jun 2019 #\\nAround this time a friend of my parents owned G.O\\'S previous album (featuring Clair) and I found that fairly pleasant as background music. Apart from his earliest hits his music seems to settle for familiar sentiment rather than anything more compelling. He has more in common with McCartney in that respect although both seem to have done their best work when contemplating loss. As for this, not a guilty pleasure, more a guilt free meh.\\nLee Saunders on 13 Jun 2019 #\\n^I love that second album (Back to Front) and early-mid 70s Gilbert in general, and mention of the record as background music (and by Christgau as\\'more-or-less easy listening\\') just reminds me how I\\'d love for Gilbert to undergo a Scott Walker style\\'so much there behind the MORE facade\\' style reappraisal. Peter Skellern, too, whose own You\\'re a Lady is as wonderful as Alone Again (Naturally), and whose sparse music hall flop Our Jackie\\'s Getting Married is like a Northern equivalent to some of the character-driven homeliness on Himself, which I\\'d single out as Gilbert\\'s best album (the multifarious Houidini Said being for me his finest song and one of the era\\'s finest baroque pop records). But then the more vaudevillian moments from these early albums, like January Git, turn up for me on things like the Divine Comedy\\'s A Woman of the World, suggesting his influence has been quietly assimilated.\\nGet Down is from the third album, I\\'m a Writer, Not a Fighter, which after two albums that flickered between oom-pah rhythms and dense string arrangements was a little less variety show and more of a conscious nod to the times, something he avoided consciously with Back to Front. I suspect the fact he now toured may have played a part in that, but it was the beginning of the end as far as his commercial success was concerned. Half the album is classic Gilbert and half of it is Stevie Wonder funk that, not comparing with, say, The Crunge for oddness, is still all sprightly and right, particularly the inventive Not in a Million Years. Also, the record\\'s half-hour playing time means it doesn\\'t outstay its welcome and stays as vivacious as its strikingly coloured sleeve, even if, going back to Skellern, its fair to say that Gilbert\\'s new interest in black pop doesn\\'t reach the heights of Hold On to Love.\\n(Register to guarantee your comments don\\'t get marked as spam.)\\nIf this was number 1 when you were born paste [stork-boy] or [stork-girl] into the start of your comment :)\\nMail Required (Your email address will not be published)\\nI\\'m writing about every UK number one single, in order. It\\'s taken a while, it\\'ll take a while longer. Wander around in the archives, or join in with the marvellous bunch of commenters we\\'ve managed to attract - new voices always very welcome!\\nPopular is funded by the generosity of my Patreon patrons. They get early posts, exclusive material, and more. You could be one of them!\\nIndex of reviews and scores so far\\nPopular Lucky Dip (a random post)\\nEXCLUSIVE INTERVIEW! The Soulful And The Arcane 25 Jan 2015 We promised we wouldn\\'t write about the Freaky Trigger #1 comic of 2014 any more, but luckily a MUCH MORE AUTHENTIC AND REAL comic has come along for us to…\\nTen Years In Ten Marks 15 Sep 2013 Ten years ago tomorrow, I started writing a review of Al Martino\\'s \"Here In My Heart\". I\\'d never heard the first UK Number One, and thanks to P2P networks I…\\nWhat Was I Thinking? (Part 1) 9 Dec 2011 Today\\'s Poptimist column - up now at Pitchfork - is the last one: a decision entirely taken by me, quite a while ago. Being able to give up a paying…\\nMADONNA - \"Music\" 26 Apr 2015 \"Her whole career\\'s been like, oh, they\\'re the trendy person of the moment, I\\'ll work with them to make me younger. They\\'re using you.\" - Aphex Twin on Madonna, 2001.…\\nWhat Was I Thinking? (Part 2) 9 Dec 2011 Continuing the narcissistic behind-the-scenes chronicle of a monthly column on a popular music website! It\\'s Poptimist 16-30! 16. Within The Realm Of A Dying Sun: Another one all about comics,…\\nPopular Crystal Ball: 2018 - Gotta Get Down On Friday 3 Jan 2019 By annual tradition, my rankings - best to worst - of the year\\'s UK number one hits, with initial thoughts - very initial, I\\'d heard only one of these before…\\nSTEPS - \"Heartbeat\" / \"Tragedy\" 30 Aug 2014 This is the first Popular entry I\\'ve written in the Southern hemisphere. And while it wasn\\'t a big hit down under – or, I think, anywhere except the UK –…\\nCELINE DION - \"Think Twice\" 21 May 2013 I should say from the outset, I\\'m unreasonably fond of this record. \"Unreasonably\" not because it\\'s a bad song or \\'guilty pleasure\\', but because it\\'s not a record I want…\\nTom invented Freaky Trigger on a bus journey in the mid-90s. A page about what he\\'s up to can be found here\\nAre you local?\\n13 Feb 2000 England is DIFFERENT (or SPECIAL if you want to be polite) to everywhere else for many reasons, but one is because our music \"industry\" (it\\'s not an industry – making baked beans is an industry, and nobody does THAT in their spare time, writes fanzines about it or has them poured over themselves at weddings. […]\\nALLLLLLLLLLIIIIIIIIIUUUUUUMS!!!!!\\n9 Jan 2004 Independence Day. Isn\\'t it marvellous? Hurrah hurrah let\\'s kill the stripper and those hippies! That\\'s the kind of morals I WANT from my films! Until the aliens bugger up by deciding just to kill EVERYBODY. Where\\'s the subtlety, the art, the je ne says quoi indeed about that? Who cares when we have plucky heroes […]\\nPop World Cup 2018: Group A Match 1\\n17 Jun 2018 It\\'s here! The opening game of the Pop World Cup finds the four teams of Group A raising the curtain on the tournament. Pop football veterans Russia and Uruguay meet two Arab states – Egypt and Saudi Arabia – with less of a record at this level. Who will prevail? You decide. Spotify playlist and […]\\nIn search of Squirrel – Part two\\n3 Oct 2004 In search of Squirrel – Part two (warning, contains graphic images) Some of you may remember this article I wrote some time ago about my \"failure\" as a vegetarian and my quest for the different. Well, I\\'ve done it. Squirrel had become a bit of an obsession, I\\'d chased up all sorts of alleys (Julian […]\\nMy Own Private Record Club*\\n10 Mar 2015 This is a post listing the records I\\'m listening to for my YEAR OF ROCKISM**, as outlined here (cut and pasted from Tumblr): I\\'m going to listen to one album on a once-a-day basis for a week, a different one each week. Not in order to write about them or anything, unless I decide I […]\\nELTON JOHN – \"Candle In The Wind \\'97\" / \"Something About The Way You Look Tonight\"\\n27 Mar 2014 Every Popular entry starts with the same question: why this record? This time it\\'s especially loud. \"Candle In The Wind \\'97\" is the highest-selling single of all time in the UK, almost 2 million clear of its nearest competitor. This is as big as pop gets. But \"why?\" might strike you as a silly question […]\\nSIX LEGS GOOD EIGHT LEGS BAD: Why giant spider movies aren\\'t scary\\n1 Sep 2002 Spiders: creepy, crawly little critters which seem up to no good – hanging in the corner of your room, leaving webs around just to make a mess – definitely with their own agenda. Not the most obvious creature to base a film on. Yet Hollywood returns to the theme of spiders every ten years or […]\\nSINEAD O\\'CONNOR – \"Nothing Compares 2 U\"\\n29 Oct 2010 Sinead O\\'Connor is one of the finest song interpreters not just because she thinks hard about the material and the feelings locked in it, but because she\\'s so good at placing songs into a situation. A great example of this is her version of \"Chiquitita\", warm and homely where ABBA\\'s is melodramatic, replacing its theatrical […]\\nOther feature posts »<|begin_of_text|>by Rich Johnston\\n– on Jul 08, 2002\\nWhile the comic business is nursing a Wizard World sized hangover, I\\'ve been up to no good, nosing around the industry\\'s dustbins and chatting up your girlfriends.\\nWelcome to the second weekly instalment of Lying In The Gutters, a gossip and rumour column serving the comic book industry - or at the least the bits that make good stories. The traffic lights on each story are my takes on their reliability. Green lets you know I believe it, Amber let\\'s you know I reckon there\\'s something in it somewhere, Red lets you know I think it\\'s quite possibly bullshit. But then you never know. The lights are just an indication - doesn\\'t mean a red can\\'t be true and a green can\\'t be false. Take everything you read with a bucketful of salt - and if you do repost information here elsewhere, please include a warning to that effect.\\nAnd a URL obviously. What do you think I am, made of hits?\\nQUESADA\\'S POSITION UNDER THREAT?\\nThe story that was going round the comic pros grapevine this week and seemed to spill over into the Wizard World: Chicago convention is that Joe Quesada is under real pressure at work from two fronts - first from his own bosses, and secondly from Avi Arad at their Hollywood branch. This is down to what they see as loose lips, unchecked company words and his public bickering with DC Comics and CrossGen, not to mention his overtime spent on the Web. And the Hollywood side seems a little ticked off that Quesada has been heard to be claiming credit for much of the \"Spider-Man\" success. And as a result of all this, Joe Quesada may be dropped. And if nothing else, Jemas and Quesada have been told to lay off DC Comics, CrossGen and the like. Newsarama reported that in the Marvel panel, Quesada denied these rumours.\\nBut let\\'s look a little deeper. Only a little mind. There have been versions of this story before now, but there are a few interesting points here.\\nFirstly, Marvel higher ups have previously been very happy with the higher press profile Marvel has been having - and it\\'s not like the aggressive anti-competitor spiel is a new thing.\\nSecondly, doing the maths, it seems that Joe Quesada\\'s two-year contract at Marvel will be up in September. Will Marvel use this as a way to jettison him?\\nThirdly, has the higher public profile rumoured to have annoyed the Marvel suits, also provided him with some protection. One might speculate that if Joe was to walk the plank, would the share price, jittery as it is right now, plummet?\\nFourthly, there\\'s that pesky revenue stream that he seems to have brought back to Marvel. Marvel Knights alone profits million of dollars a year.\\nFifthly, how much would Joe Quesada be worth in the open market? I\\'ve already heard rumours that he could find himself in on the west coast in Hollywood, representing Marvel, or working for a studio. And the other far more head-warping rumour places him just down the road, taking over Paul Levitz\\' position at DC Comics.\\nMaybe I should just put him on eBay to find out…\\nULTIMATISING THE MARVEL UNIVERSE\\nWhen asked about last week\\'s LITG story, that Marvel plan to Ultimatise all their line in the near future, Mark Millar posted on Millarworld \"As for Marvel going Ultimate, I\\'m afraid you may THINK that, dear boy, but I couldn\\'t possibly COMMENT. Let\\'s just say the \\'Ultimate\\' line was very far-sighted when it was created. More from me on this in an upcoming interview.\"\\nThe first comment is a reference to the TV and book series, House Of Cards, featuring a character who would not speak on the record - but would always confirm a story with that phrase.\\nOne of the reasons being given for the Ultimatisation of the Marvel Universe is sales. Now, while \"New X-Men\" and \"Amazing Spider-Man\" outsell their \"Ultimate\" counterparts in the traditional direct market, there\\'s another direct market that has slowly started to emerge. The expansive chain store Wal-Mart has a deal with Marvel comics to order their \"Ultimate\" titles, non-returnable to the tune of a million a month between them. And while that weights towards \"Ultimate Spider-Man\" and \"Ultimate X-Men,\" that still adds hundreds and thousand of guaranteed sales. And they seem to stock them by the action figures and toys rather than by the books and magazines - guaranteed to get them in front of kids.\\nNow, it\\'s clear that Wal-Mart must have got a hell of a deal in order to make such a commitment, allegedly up into 2004. And anecdotal reports indicate that sell-through isn\\'t great. But if both Marvel and Wal-Mart are making a profit, and pushing a certain product line to \"civilian\" customers, everybody wins. But they only want the \"Ultimate\" line, so...\\nGUTTERATI GATOZHIAN REPORTING FOR DUTY, SIR\\nOne of our first gutterati, known only as Gatozhian, tells me \"The \"Ultimatisation\" of the Marvel line is a done deal from what I hear, but not till late 2003. Something about fulfilling agreements. And New X-Men #150 is the end of it all.\"\\nHe reports that the unmasking trend at Marvel may well continue, and to keep a close eye on the upcoming \"Spider-Man 50.\" He also mentions that Ron Zimmerman and Darick Robertson are getting their own Spider-related book...\\nThanks Gatozhian. Your traffic light is on red for now- but if those stories start to come true, that will change very quickly.\\nDo you want to join the gutterati? Email me on twisting@hotmail.com\\nTIBET PART TWO\\nLast week, Lying in the Gutters printed the rumour that certain DC books have had storylines featuring or mentioning Tibet curtailed or amended so as not to conflict with AOL Time Warner\\'s expansion into China.\\nOn the DC Universe panel at WizardWorld, writer Geoff Johns indicated his intention to write a Tibet story, probably in Flash. One to watch, folks.\\nDAREDEVIL/BULLSEYE FROM FABRY AND SMITH?\\nI understand that the new top secret Glenn Fabry project for Marvel mentioned in a previous column is also the new top secret Kevin Smith project for Marvel.\\nDaredevil/Bullseye. One to anticipate.\\nFRAY DELAYED - AND NOT BY THE HOLLYWOOD WRITER\\nI understand that Dark Horse is having real problems getting Joss Whedon\\'s future slayer comic, \"Fray,\" finished. But now it\\'s not as many suspect, the writer\\'s schedule that\\'s at fault, it\\'s the artist. Seems that when Karl Moline went off to CrossGen he thought he\\'d be able to finish it before he started \"Route 666.\" He didn\\'t. I understand that issue 7 is only half-completed so far\\nPREVIEWS REVEALS FUTURE PROJECTS\\nPreviews doesn\\'t seem to be the hard-and-fast online document it once was. Diamond seem to have been… well, changing a few bits and pieces soon after initial uploading. And if you catch it in time, you might see some future projects that weren\\'t meant to have been listed that month. Not only was \"Captain America: The Truth\" first solicited for August, it was done so without mentioning the aspects that have caused so much discourse of late. But there\\'s also this little nugget from this month\\'s files - well it was there very recently, anyway.\\nEDEN\\'S TRAIL #1 (OF 6)\\nCover by Steve Uy\\nSteve Uy (w & a)\\nA brand-new adventure of sci-fi action in the widescreen Marvel Scope format! On a faraway planet, a simple girl from a small corner of the galaxy finds herself in sole possession of the secrets of the universe! Journey along with this unlikely hero on her thrill-packed quest to discover the truth behind her world and the realms beyond in an all-new, six-issue series by future Marvel superstar, ICEMAN Cover artist Steve Uy! If you dig Final Fantasy and Star Wars, you\\'ll love EDEN\\'S TRAIL!\\n32 PGS. with ads/FC/MARVEL PG 2.99\\nGood to see Marvel going after the CrossGen dollar there.\\nBRYAN HITCH BACK ON SCHEDULE\\nPoor Ultimates fans, getting all twitchy and fidgety and seeing spider babies climbing across the ceiling? Don\\'t worry.\\nBryan Hitch took time out to talk about his schedule on the book - how it slipped, and how he\\'s putting it right.\\n\"Mark and I should have started issue one in June of last year, but due to Mark\\'s extended bout with illness and thankfully groundless cancer scare we didn\\'t put pen to paper until the second week of September, which although giving me all the time I needed to watch Wimbledon and do the design work did set us behind since our launch date was already set for Jan.\"\\n\"This meant we couldn\\'t do the double sized first issue as planned, but it also yielded the unexpected benefit of giving us the chance to re-evaluate what we wanted to do and the whole concept became what we now know. It may interest readers to know that what was originally intended to be in that first double sized issue expanded to fill these first five issues when the characters took on unexpected extra life with more of their stories to tell. Sometimes you just have to let things breathe.\"\\n\"Anyway, The first issue of anything always takes me longer to do, say six weeks instead of four, but in this case it was so period specific and reference heavy that time just got eaten up researching the costumes, uniforms, armaments, settings, aircraft and all the other necessary details. Worth it in the long run possibly, but very time consuming.\"\\n\"Issues two, three and four all took four weeks or so, but the damage was already done and adding to the problem was the fact that over the course of those first five issues we wrote and drew about seventeen extra pages on top of the required 21 per issue and it comes as no surprise that we slipped behind. We could all see it happening, but keeping our fingers crossed wasn\\'t really doing the job!\\n\"Everyone has been trying to find ways of avoiding fill in issues as, after all, nobody wants to have somebody else write a chapter of their novel, and Marvel have been both generous and supportive in all their efforts to give Mark and I (mostly me) whatever help they can.\"\\n\"So we found ourselves with about a week to draw issue five, which being the big budget spectacle we were waiting for, was just not remotely possible without channelling the spirit of Jack Kirby. Illness of my own and some other personal nonsense added to the already existing problems by pushing the time taken on the issue to seven weeks and, presto, you have the current situation.\"\\n\"Issue six has indeed taken three weeks to pencil and will be at the printers next week. So the ongoing process of catching up continues. Issues will be out monthly from now, and if we manage to get where we want to be by the end of the year, the may be an extra surprise or two. Keeping shtum, lest you run rumours. The one about Mark Millar working in nothing but a Powerpuff Girls kitchen apron are true, however.\"\\nMy eyes, Bryan, my eyes!\\nCALL AND BLACK CAT ON DOTCOMICS, ULTIMATE SPIDEY OFF\\nI understand that Marvel will be putting \"The Call: Precinct\" onto its Dot.Comics listings, as well as the new \"Black Cat\" series. But this might be at the cost of dropping dotComics leader, \"Ultimate Spider-Man.\"\\nDREAMWAVE LOSE ROBOTECH, GAIN ZELDA\\nWith reports that Wildstorm are pursuing \"Robotech\" comics, it\\'s interesting that, like with \"Thundercats,\" Dreamwave originally had the \"Robotech\" licence. Planning to announce a \"Robotech\" prequel, \"Genesis,\" at San Diego, they found those negotiations with owners Harmony Gold stalled. Jay Faerber was originally meant to be the writer - and had written both the Robotech bible and the first story arc synopsis.\\nHowever, I\\'ve also heard that Dreamwave have secured the \"Legend of Zelda\" license. Oooh!\\nHOWARD CHAYKIN DRAWS ALAN MOORE\\nHoward Chaykin is back at the boards. Look for him to be drawing a \"Tom Strong\" story for Alan Moore shortly. Moore had wanted Chaykin to draw a story for him for quite a while but missed Chaykin\\'s window last time on \"Tom Strong.\" Not this time- eventually Moore always gets his man.\\nJOHNNY NEMO RETURNS\\nHow about a collection of Milligan and Ewins\\' classic \"Johnny Nemo\" series including the first all-new Nemo story in almost a decade, courtesy of Cyberosia this autumn?\\nUnless of course DC steal that one under Cyberosia\\'s noses like they did Skreemer...\\nDC UNIVERSE TITLES SHIP WITHOUT CODE\\nIt appears that a number of DC\\'s August 2002\\'s books are missing the Comics Code Seal. And no, not the Vertigos, but the DC Universe line. Titles so far include \"Action Comics #792,\" \"Birds of Prey #44,\" \"JSA #37,\" \"Wonder Woman #182\"... say, has Mike Carlin been rolling his eyes at the Comic Code Authority? IS DC following in Marvel\\'s lead?\\nOr is it just a screw-up?\\nX-MEN EVOLUTION - ORDER HIGH!\\nRetailers - having difficulty beating Marvel\\'s full line incentives for June orders? Not placed your order yet? Not to worry, just add a few more copies of \"X-Men Evolution\" 10 until you qualify. After all, it\\'s been cancelled…\\nTHUNDERBOLTS TO BE REVAMPED - THE STORY CONTINUES\\nAny more on \"Thunderbolts\" being revamped and restarted, written by John Arcudi after issue 75? From the AOL Kurt Busiek folder, when user FCFlink14 said \"BTW, i believe thunderbolts is the 4th longest lasting non-rebooted series currently coming out from marvel (behind Wolverine, New X-Men and Uncanny X-Men). Who\\'da thunk it?\", Kurt replied \"Wait six months...\"\\nKYLE BAKER\\'S PLANS\\nMore from Kyle Baker. As well as the \"Plastic Man\" graphic novel, \"Captain America: The Truth,\" his Looney Tunes animation work for Warner Bros, \"Cowboy Wally 2\" and a \"Superman\" novel, DC are also republishing the first \"Cowboy Wally Show.\" Considered a masterpiece of a graphic novel, it\\'s already been through Doubleday and Marlowe, and even a spinoff appearance in Marvel\\'s Epic Lite. This time it looks like it\\'ll get the production quality it\\'s always deserved.\\nThis is the age of Kyle Baker.\\nHULK, LIVE-ACTION TV SERIES?\\nI understand that Studios USA is supposedly developing a new live-action Hulk TV series, to play off the upcoming movie version - but they\\'re keeping it a secret.\\nThere have been rumours about a new cartoon, but these seem to be decoys, planted to keep fans off the scent, in case it doesn\\'t pan out. Like Thor.\\nStill, if you\\'re a pro-wrestler-turned-actor, maybe you should give them a call...\\nKEVIN SMITH CHANGES STRACZYNSKI\\'S PLANS\\nJoe Michael Straczynski writes on the Usenet newsgroup rec.arts.sf.tv.babylon5.moderated.\\n\"I have a three-pronged deal: stories with established characters in the Marvel Universe, reviving dormant characters in the MU as well as creating new characters there, and creating wholly new characters in a non-MU situation allowing me to do pretty much anything I want.\"\\n\"Well, that\\'s not absolutely accurate...when Kevin Smith came on board, he asked to be given dibs on bringing MJ and Peter together again, if and when that decision should be made. So in terms of that aspect, all I can do is kind of play around the edges a bit, the ball is well and truly in Kevin\\'s court, he\\'s the only one who can resolve and bring them together if that is the way Marvel wants to go.\"\\n\"I was gonna bring \\'em together again shortly, because it was my intent to get them apart only for a while, but at this point it\\'ll be an if/when situation between Marvel and Kevin.\"\\nStraczynski clarified this further in email, saying \"What a lot of people seem not to understand, or have chosen to understand, is that I said, from the git-go, that I only wanted to clear the decks of all the supporting characters *for a while* so that I could focus solely on who Peter was, with the goal of gradually working them all back in again once I\\'d tidied up the place a bit. Which is why all these \"JMS hates MJ and wants her gone forever\" posts always puzzled me, since I\\'d never said that, and had, in fact, in my public posts (searchable on any of a number of databases) said exactly what I said above, that it was meant to be a temporary situation.\"\\nSo is this long-awaited get-together happening in \"Black Cat?\" Or Kevin Smith\\'s other Spider-Man plans?\\nSCHEDULE AND COVERS FOR AMAZING SPIDER-MAN\\nFrank Cho is drawing three covers for \"Amazing Spider-Man,\" the first due out in October. I also understand that \"Amazing Spider-Man\" is planning to catch up the two issues it skipped last year, as well as a \"thirteenth\" issue to come.\\nANOTHER STAB AT DC/WILDSTORM TITLES/CREATIVE TEAMS\\nOkay okay okay. Let\\'s see if we can get a better take on this whole Wildstorm DC Universe titles? Each gets their own traffic light.\\nAnd more to come.\\nLet\\'s see if we get any closer this time?\\nPREVIEW ART FROM SCARS\\nIt\\'s funny what kind of digital files whiz round the Internet when they\\'re not supposed to and somehow end up in my inbox.\\nThese five pages purport to be the beginning to \"Scars\" issue 1, the upcoming horror book from Avatar, by Warren Ellis and Jacen Burrows. This is a 6-issue mini-series, launching in November\\nTOM SNEIGOSKI TO WRITE NEW AVATAR TITLE TOO\\nChris Golden writes to tell me that the Avatar project he\\'s writing mentioned last week will be co-written by Tom Sniegoski too.\\nNEW ANTHOLOGY REUNITES OLD GANG\\nThere\\'s a new British anthology comic starting in October called Bullet Proof, including the work of Mick McMahon, Andy Diggle, Nige Kitching, Rich Elson and Nigel Dobbyn. What common thread joins them together?\\nThey all worked on the \"Sonic The Hedgehog\" comic which lasted for ten years and two hundred issues. And now they\\'re back!\\nNot the only high profile chap who worked on that comic though - Mark Millar is reported to have written 100 pages of script in a day...\\nIMAGE UNIVERSE TO RELAUNCH\\nAt San Diego, Image Comics are planning to announce their new reinvigorated Image Universe line. But as previously rumoured, it\\'s not called Venture - although I understand that one of the new characters will be.\\nBOB GREENBERGER PREDICTS FUTURE\\nA story from Bob Greenberger\\'s departure from Marvel. I hear that Mark Powers and Pete Franco walked down to Greenberger\\'s office to give their condolences. Mark shakes Bob\\'s hand saying, \"I\\'m sorry. It was nice working with you.\" To which Bob replies by smiling and saying, \"Yeah, well... you\\'re next!\"\\nLYING IN THE GUTTER GOLD\\nAs a result of a few con reports from the Wizard ChicagoCon Panel, from Newsarama, CBR and the like, here\\'s a few oldies but goldies All The Rage bits that might be worth a revisit.\\n\"Rawhide Kid\" - \"Slap Leather, a new comedy Western from Ron Zimmerman and John Severin, featuring the return of Rawhide Kid. Pushed as having an \"outrageous concept\" and tight fitting leather, it looks like Marvel will be putting the Go West into the Wild West.\"\\n\"1602\" - \"The title of Neil Gaiman\\'s upcoming Marvel Universe comic is 1602. But what does it mean? Could it be a reference to the manuscript \"The City Of The Sun\" by Italian writer Tommaso Campanella, written in 1602. The story tells of a utopian city built and lived in by seemingly perfect beings. One might presume 1602 will tell a similar tale. But with The Thing, Daredevil and Mr Fantastic... okay, maybe not. But 1602 is a fundraiser for the legal battle over Marvelman/Miracleman - which, during Gaiman\\'s run portrayed a utopian world built by wondrous beings… Read the manuscript in question here.\\n\"Black Panther\" - Relaunched but not renumbered after issue 50 and the end of the Death Of Black Panther comic, when Dan Fraga becomes \"Black Panther\" artist. Sal Velluto and Bob Almond will then work with Priest on another project - possibly an Ultimate book.\\nRECRUITING FROM THE GUTTER\\nThis column is nothing without its readers and its sources. Find out how you can play a part.\\nRecruiting The Gutterati\\nWhat\\'s the word on the street? Whether you\\'re a pro in the know or a fan who just got lucky, pass it on. You\\'ve found loose lips on message boards, you work in a shop where a pro\\'s been holding court about their latest success, or you\\'re just feeling plain bitchy and want to get your view across without being fired, join the ever expanding crew of that exclusive clique known only as the Gutterati. Regular reporters can get their own nickname, so you can build a reputation - but unless you wish it, your identity will never be revealed.\\nPanning For Gold In The Gutter\\nAnother thing - old stories. Just because it happened twenty years ago, doesn\\'t mean I won\\'t want to hear about it. Often the older the story, the more open people can be about it. So if you know a great story that never made it to the fans, welcome to Lying In The Gutters.\\nRecruiting The Gutter Snipes\\nSpreading the word. Repost sections from this column (with the rumour warning and the column\\'s web address) to message boards across the internet, wherever relevant, and let me know about it. E-mail bits to friends, pass the word, and spread the cause. For example - excerpts from today\\'s column might be posted around www.ComicBoards.com, AintItCool.com or any number of Buffy boards. Go to it. Fly my pretty ones, fly!\\nYou can contact me at:\\ntwisting@hotmail.com (which often gets full, but it\\'ll reach me during the day)\\nrich@twistandshout.freeserve.co.uk (which I read every morning - best for graphic files!)\\nAOL Instant Message me at TwistRich\\n0780 1350982 (01144780 1350982 from N America)\\nLetter bombs can be sent to 8 Robin Hood Lane, Kingston Vale, London SW15 3PU, ENGLAND\\nBe seeing you.\\nOh yeah, and that Ian Ungstad story from All The Rage yesterday? No fucking comment.\\nJames Bond Already Introduced a Female 00 Agent... 54 Years Ago<|begin_of_text|>\\n\\nimport BoltProtocolV3 from \\'../../src/bolt/bolt-protocol-v3\\'\\nimport RequestMessage from \\'../../src/bolt/request-message\\'\\nimport utils from \\'../test-utils\\'\\nimport {\\n  ProcedureRouteObserver,\\n  ResultStreamObserver\\n} from \\'../../src/bolt/stream-observers\\'\\n\\nimport {\\n  Date,\\n  DateTime,\\n  Duration,\\n  LocalDateTime,\\n  LocalTime,\\n  Path,\\n  PathSegment,\\n  Point,\\n  Relationship,\\n  Time,\\n  UnboundRelationship,\\n  Node,\\n  internal\\n} from \\'neo4j-driver-core\\'\\n\\nimport { alloc } from \\'../../src/channel\\'\\nimport { structure } from \\'../../src/packstream\\'\\n\\nconst {\\n  bookmarks: { Bookmarks },\\n  txConfig: { TxConfig }\\n} = internal\\n\\nconst WRITE = \\'WRITE\\'\\n\\ndescribe(\\'#unit BoltProtocolV3\\', () => {\\n  beforeEach(() => {\\n    expect.extend(utils.matchers)\\n  })\\n\\n  it(\\'should update metadata\\', () => {\\n    const metadata = { t_first: 1, t_last: 2, db_hits: 3, some_other_key: 4 }\\n    const protocol = new BoltProtocolV3(null, null, false)\\n\\n    const transformedMetadata = protocol.transformMetadata(metadata)\\n\\n    expect(transformedMetadata).toEqual({\\n      result_available_after: 1,\\n      result_consumed_after: 2,\\n      db_hits: 3,\\n      some_other_key: 4\\n    })\\n  })\\n\\n  it(\\'should initialize connection\\', () => {\\n    const recorder = new utils.MessageRecordingConnection()\\n    const protocol = new BoltProtocolV3(recorder, null, false)\\n    utils.spyProtocolWrite(protocol)\\n\\n    const clientName = \\'js-driver/1.2.3\\'\\n    const authToken = { username: \\'neo4j\\', password:\\'secret\\' }\\n\\n    const observer = protocol.initialize({ userAgent: clientName, authToken })\\n\\n    protocol.verifyMessageCount(1)\\n    expect(protocol.messages[0]).toBeMessage(\\n      RequestMessage.hello(clientName, authToken)\\n    )\\n    expect(protocol.observers).toEqual([observer])\\n    expect(protocol.flushes).toEqual([true])\\n  })\\n\\n  it(\\'should run a query\\', () => {\\n    const bookmarks = new Bookmarks([\\n      \\'neo4j:bookmark:v1:tx1\\',\\n      \\'neo4j:bookmark:v1:tx2\\'\\n    ])\\n    const txConfig = new TxConfig({\\n      timeout: 5000,\\n      metadata: { x: 1, y:\\'something\\' }\\n    })\\n    const recorder = new utils.MessageRecordingConnection()\\n    const protocol = new BoltProtocolV3(recorder, null, false)\\n    utils.spyProtocolWrite(protocol)\\n\\n    const query = \\'RETURN $x, $y\\'\\n    const parameters = { x: \\'x\\', y: \\'y\\' }\\n\\n    const observer = protocol.run(query, parameters, {\\n      bookmarks,\\n      txConfig,\\n      mode: WRITE\\n    })\\n\\n    protocol.verifyMessageCount(2)\\n\\n    expect(protocol.messages[0]).toBeMessage(\\n      RequestMessage.runWithMetadata(query, parameters, {\\n        bookmarks,\\n        txConfig,\\n        mode: WRITE\\n      })\\n    )\\n    expect(protocol.messages[1]).toBeMessage(RequestMessage.pullAll())\\n    expect(protocol.observers).toEqual([observer, observer])\\n    expect(protocol.flushes).toEqual([false, true])\\n  })\\n\\n  it(\\'should begin a transaction\\', () => {\\n    const bookmarks = new Bookmarks([\\n      \\'neo4j:bookmark:v1:tx1\\',\\n      \\'neo4j:bookmark:v1:tx2\\'\\n    ])\\n    const txConfig = new TxConfig({\\n      timeout: 5000,\\n      metadata: { x: 1, y:\\'something\\' }\\n    })\\n    const recorder = new utils.MessageRecordingConnection()\\n    const protocol = new BoltProtocolV3(recorder, null, false)\\n    utils.spyProtocolWrite(protocol)\\n\\n    const observer = protocol.beginTransaction({\\n      bookmarks,\\n      txConfig,\\n      mode: WRITE\\n    })\\n\\n    protocol.verifyMessageCount(1)\\n    expect(protocol.messages[0]).toBeMessage(\\n      RequestMessage.begin({ bookmarks, txConfig, mode: WRITE })\\n    )\\n    expect(protocol.observers).toEqual([observer])\\n    expect(protocol.flushes).toEqual([true])\\n  })\\n\\n  it(\\'should commit\\', () => {\\n    const recorder = new utils.MessageRecordingConnection()\\n    const protocol = new BoltProtocolV3(recorder, null, false)\\n    utils.spyProtocolWrite(protocol)\\n\\n    const observer = protocol.commitTransaction()\\n\\n    protocol.verifyMessageCount(1)\\n    expect(protocol.messages[0]).toBeMessage(RequestMessage.commit())\\n    expect(protocol.observers).toEqual([observer])\\n    expect(protocol.flushes).toEqual([true])\\n  })\\n\\n  it(\\'should rollback\\', () => {\\n    const recorder = new utils.MessageRecordingConnection()\\n    const protocol = new BoltProtocolV3(recorder, null, false)\\n    utils.spyProtocolWrite(protocol)\\n\\n    const observer = protocol.rollbackTransaction()\\n\\n    protocol.verifyMessageCount(1)\\n    expect(protocol.messages[0]).toBeMessage(RequestMessage.rollback())\\n    expect(protocol.observers).toEqual([observer])\\n    expect(protocol.flushes).toEqual([true])\\n  })\\n\\n  it(\\'should return correct bolt version number\\', () => {\\n    const protocol = new BoltProtocolV3(null, null, false)\\n\\n    expect(protocol.version).toBe(3)\\n  })\\n\\n  it(\\'should request the routing table from the correct procedure\\', () => {\\n    const expectedResultObserver = new ResultStreamObserver()\\n    const protocol = new SpiedBoltProtocolV3(expectedResultObserver)\\n    utils.spyProtocolWrite(protocol)\\n    const routingContext = { abc: \\'context\\'}\\n    const sessionContext = { bookmarks: \\'book\\' }\\n    const onError = () => {}\\n    const onCompleted = () => {}\\n\\n    const observer = protocol.requestRoutingInformation({\\n      routingContext,\\n      sessionContext,\\n      onError,\\n      onCompleted\\n    })\\n\\n    expect(observer).toEqual(\\n      new ProcedureRouteObserver({\\n        resultObserver: expectedResultObserver,\\n        connection: null,\\n        onCompleted,\\n        onError\\n      })\\n    )\\n\\n    expect(protocol._run.length).toEqual(1)\\n    expect(protocol._run[0]).toEqual([\\n      \\'CALL dbms.cluster.routing.getRoutingTable($context)\\',\\n      { context: routingContext },\\n      {...sessionContext, txConfig: TxConfig.empty() }\\n    ])\\n  })\\n\\n  describe(\\'Bolt V4\\', () => {\\n    /**\\n     * @param {function(protocol: BoltProtocolV3)} fn\\n     */\\n    function verifyError (fn) {\\n      const recorder = new utils.MessageRecordingConnection()\\n      const protocol = new BoltProtocolV3(recorder, null, false)\\n      utils.spyProtocolWrite(protocol)\\n\\n      expect(() => fn(protocol)).toThrowError(\\n        \\'Driver is connected to the database that does not support multiple databases.\\'+\\n          \\'Please upgrade to neo4j 4.0.0 or later in order to use this functionality\\'\\n      )\\n    }\\n\\n    describe(\\'beginTransaction\\', () => {\\n      function verifyBeginTransaction (database) {\\n        verifyError(protocol => protocol.beginTransaction({ database }))\\n      }\\n\\n      it(\\'should throw error when database is set\\', () => {\\n        verifyBeginTransaction(\\'test\\')\\n      })\\n    })\\n\\n    describe(\\'run\\', () => {\\n      function verifyRun (database) {\\n        verifyError(protocol => protocol.run(\\'query\\', {}, { database }))\\n      }\\n\\n      it(\\'should throw error when database is set\\', () => {\\n        verifyRun(\\'test\\')\\n      })\\n    })\\n  })\\n\\n  describe(\\'Bolt v4.4\\', () => {\\n    /**\\n     * @param {string} impersonatedUser The impersonated user.\\n     * @param {function(protocol: BoltProtocolV3)} fn\\n     */\\n    function verifyImpersonationNotSupportedErrror (impersonatedUser, fn) {\\n      const recorder = new utils.MessageRecordingConnection()\\n      const protocol = new BoltProtocolV3(recorder, null, false)\\n\\n      expect(() => fn(protocol)).toThrowError(\\n        \\'Driver is connected to the database that does not support user impersonation.\\'+\\n          \\'Please upgrade to neo4j 4.4.0 or later in order to use this functionality.\\'+\\n          `Trying to impersonate ${impersonatedUser}.`\\n      )\\n    }\\n\\n    describe(\\'beginTransaction\\', () => {\\n      function verifyBeginTransaction (impersonatedUser) {\\n        verifyImpersonationNotSupportedErrror(\\n          impersonatedUser,\\n          protocol => protocol.beginTransaction({ impersonatedUser }))\\n      }\\n\\n      it(\\'should throw error when impersonatedUser is set\\', () => {\\n        verifyBeginTransaction(\\'test\\')\\n      })\\n    })\\n\\n    describe(\\'run\\', () => {\\n      function verifyRun (impersonatedUser) {\\n        verifyImpersonationNotSupportedErrror(\\n          impersonatedUser,\\n          protocol => protocol.run(\\'query\\', {}, { impersonatedUser }))\\n      }\\n\\n      it(\\'should throw error when impersonatedUser is set\\', () => {\\n        verifyRun(\\'test\\')\\n      })\\n    })\\n  })\\n\\n  describe(\\'unpacker configuration\\', () => {\\n    test.each([\\n      [false, false],\\n      [false, true],\\n      [true, false],\\n      [true, true]\\n    ])(\\n     \\'should create unpacker with disableLosslessIntegers=%p and useBigInt=%p\\',\\n      (disableLosslessIntegers, useBigInt) => {\\n        const protocol = new BoltProtocolV3(null, null, {\\n          disableLosslessIntegers,\\n          useBigInt\\n        })\\n        expect(protocol._unpacker._disableLosslessIntegers).toBe(\\n          disableLosslessIntegers\\n        )\\n        expect(protocol._unpacker._useBigInt).toBe(useBigInt)\\n      }\\n    )\\n  })\\n\\n  describe(\\'watermarks\\', () => {\\n    it(\\'.run() should configure watermarks\\', () => {\\n      const recorder = new utils.MessageRecordingConnection()\\n      const protocol = utils.spyProtocolWrite(\\n        new BoltProtocolV3(recorder, null, false)\\n      )\\n\\n      const query = \\'RETURN $x, $y\\'\\n      const parameters = { x: \\'x\\', y: \\'y\\' }\\n      const observer = protocol.run(query, parameters, {\\n        bookmarks: Bookmarks.empty(),\\n        txConfig: TxConfig.empty(),\\n        lowRecordWatermark: 100,\\n        highRecordWatermark: 200\\n      })\\n\\n      expect(observer._lowRecordWatermark).toEqual(100)\\n      expect(observer._highRecordWatermark).toEqual(200)\\n    })\\n  })\\n\\n  describe(\\'.packable()\\', () => {\\n    it.each([\\n      [\\'Node\\', new Node(1, [\\'a\\'], { a: \\'b\\' }, \\'c\\')],\\n      [\\'Relationship\\', new Relationship(1, 2, 3, \\'a\\', { b: \\'c\\' }, \\'d\\', \\'e\\', \\'f\\')],\\n      [\\'UnboundRelationship\\', new UnboundRelationship(1, \\'a\\', { b: \\'c\\' }, \\'1\\')],\\n      [\\'Path\\', new Path(new Node(1, [], {}), new Node(2, [], {}), [])]\\n    ])(\\'should pack not pack graph types (%s)\\', (_, graphType) => {\\n      const protocol = new BoltProtocolV3(\\n        new utils.MessageRecordingConnection(),\\n        null,\\n        false\\n      )\\n\\n      const packable = protocol.packable(graphType)\\n\\n      expect(packable).toThrowErrorMatchingSnapshot()\\n    })\\n\\n    it.each([\\n      [\\'Duration\\', new Duration(1, 1, 1, 1)],\\n      [\\'LocalTime\\', new LocalTime(1, 1, 1, 1)],\\n      [\\'Time\\', new Time(1, 1, 1, 1, 1)],\\n      [\\'Date\\', new Date(1, 1, 1)],\\n      [\\'LocalDateTime\\', new LocalDateTime(1, 1, 1, 1, 1, 1, 1)],\\n      [\\'DateTimeWithZoneId\\', new DateTime(1, 1, 1, 1, 1, 1, 1, undefined, \\'America/Sao_Paulo\\')],\\n      [\\'DateTime\\', new DateTime(1, 1, 1, 1, 1, 1, 1, 1)],\\n      [\\'Point2D\\', new Point(1, 1, 1)],\\n      [\\'Point3D\\', new Point(1, 1, 1, 1)]\\n    ])(\\'should pack spatial types and temporal types (%s)\\', (_, object) => {\\n      const buffer = alloc(256)\\n      const protocol = new BoltProtocolV3(\\n        new utils.MessageRecordingConnection(),\\n        buffer,\\n        {\\n          disableLosslessIntegers: true\\n        }\\n      )\\n\\n      const packable = protocol.packable(object)\\n\\n      expect(packable).not.toThrow()\\n\\n      buffer.reset()\\n\\n      const unpacked = protocol.unpack(buffer)\\n      expect(unpacked).toEqual(object)\\n    })\\n  })\\n\\n  describe(\\'.unpack()\\', () => {\\n    it.each([\\n      [\\n        \\'Node\\',\\n        new structure.Structure(0x4e, [1, [\\'a\\'], { c: \\'d\\' }]),\\n        new Node(1, [\\'a\\'], { c: \\'d\\' })\\n      ],\\n      [\\n        \\'Relationship\\',\\n        new structure.Structure(0x52, [1, 2, 3, \\'4\\', { 5: 6 }]),\\n        new Relationship(1, 2, 3, \\'4\\', { 5: 6 })\\n      ],\\n      [\\n        \\'UnboundRelationship\\',\\n        new structure.Structure(0x72, [1, \\'2\\', { 3: 4 }]),\\n        new UnboundRelationship(1, \\'2\\', { 3: 4 })\\n      ],\\n      [\\n        \\'Path\\',\\n        new structure.Structure(\\n          0x50,\\n          [\\n            [\\n              new structure.Structure(0x4e, [1, [\\'2\\'], { 3: \\'4\\' }]),\\n              new structure.Structure(0x4e, [4, [\\'5\\'], { 6: 7 }]),\\n              new structure.Structure(0x4e, [2, [\\'3\\'], { 4: \\'5\\' }])\\n            ],\\n            [\\n              new structure.Structure(0x52, [3, 1, 4,\\'rel1\\', { 4: \\'5\\' }]),\\n              new structure.Structure(0x52, [5, 4, 2,\\'rel2\\', { 6: 7 }])\\n            ],\\n            [1, 1, 2, 2]\\n          ]\\n        ),\\n        new Path(\\n          new Node(1, [\\'2\\'], { 3: \\'4\\' }),\\n          new Node(2, [\\'3\\'], { 4: \\'5\\' }),\\n          [\\n            new PathSegment(\\n              new Node(1, [\\'2\\'], { 3: \\'4\\' }),\\n              new Relationship(3, 1, 4,\\'rel1\\', { 4: \\'5\\' }),\\n              new Node(4, [\\'5\\'], { 6: 7 })\\n            ),\\n            new PathSegment(\\n              new Node(4, [\\'5\\'], { 6: 7 }),\\n              new Relationship(5, 4, 2,\\'rel2\\', { 6: 7 }),\\n              new Node(2, [\\'3\\'], { 4: \\'5\\' })\\n            )\\n          ]\\n        )\\n      ]\\n    ])(\\'should unpack graph types (%s)\\', (_, struct, graphObject) => {\\n      const buffer = alloc(256)\\n      const protocol = new BoltProtocolV3(\\n        new utils.MessageRecordingConnection(),\\n        buffer,\\n        false\\n      )\\n\\n      const packable = protocol.packable(struct)\\n\\n      expect(packable).not.toThrow()\\n\\n      buffer.reset()\\n\\n      const unpacked = protocol.unpack(buffer)\\n      expect(unpacked).toEqual(graphObject)\\n    })\\n\\n    it.each([\\n      [\\n        \\'Node with less fields\\',\\n        new structure.Structure(0x4e, [1, [\\'a\\']])\\n      ],\\n      [\\n        \\'Node with more fields\\',\\n        new structure.Structure(0x4e, [1, [\\'a\\'], { c: \\'d\\' }, \\'1\\'])\\n      ],\\n      [\\n        \\'Relationship with less fields\\',\\n        new structure.Structure(0x52, [1, 2, 3, \\'4\\'])\\n      ],\\n      [\\n        \\'Relationship with more fields\\',\\n        new structure.Structure(0x52, [1, 2, 3, \\'4\\', { 5: 6 }, \\'1\\', \\'2\\', \\'3\\'])\\n      ],\\n      [\\n        \\'UnboundRelationship with less fields\\',\\n        new structure.Structure(0x72, [1, \\'2\\'])\\n      ],\\n      [\\n        \\'UnboundRelationship with more fields\\',\\n        new structure.Structure(0x72, [1, \\'2\\', { 3: 4 }, \\'1\\'])\\n      ],\\n      [\\n        \\'Path with less fields\\',\\n        new structure.Structure(\\n          0x50,\\n          [\\n            [\\n              new structure.Structure(0x4e, [1, [\\'2\\'], { 3: \\'4\\' }]),\\n              new structure.Structure(0x4e, [4, [\\'5\\'], { 6: 7 }]),\\n              new structure.Structure(0x4e, [2, [\\'3\\'], { 4: \\'5\\' }])\\n            ],\\n            [\\n              new structure.Structure(0x52, [3, 1, 4,\\'rel1\\', { 4: \\'5\\' }]),\\n              new structure.Structure(0x52, [5, 4, 2,\\'rel2\\', { 6: 7 }])\\n            ]\\n          ]\\n        )\\n      ],\\n      [\\n        \\'Path with more fields\\',\\n        new structure.Structure(\\n          0x50,\\n          [\\n            [\\n              new structure.Structure(0x4e, [1, [\\'2\\'], { 3: \\'4\\' }]),\\n              new structure.Structure(0x4e, [4, [\\'5\\'], { 6: 7 }]),\\n              new structure.Structure(0x4e, [2, [\\'3\\'], { 4: \\'5\\' }])\\n            ],\\n            [\\n              new structure.Structure(0x52, [3, 1, 4,\\'rel1\\', { 4: \\'5\\' }]),\\n              new structure.Structure(0x52, [5, 4, 2,\\'rel2\\', { 6: 7 }])\\n            ],\\n            [1, 1, 2, 2],\\n            \\'a\\'\\n          ]\\n        )\\n      ],\\n      [\\n        \\'Point with less fields\\',\\n        new structure.Structure(0x58, [1, 2])\\n      ],\\n      [\\n        \\'Point with more fields\\',\\n        new structure.Structure(0x58, [1, 2, 3, 4])\\n      ],\\n      [\\n        \\'Point3D with less fields\\',\\n        new structure.Structure(0x59, [1, 2, 3])\\n      ],\\n\\n      [\\n        \\'Point3D with more fields\\',\\n        new structure.Structure(0x59, [1, 2, 3, 4, 6])\\n      ],\\n      [\\n        \\'Duration with less fields\\',\\n        new structure.Structure(0x45, [1, 2, 3])\\n      ],\\n      [\\n        \\'Duration with more fields\\',\\n        new structure.Structure(0x45, [1, 2, 3, 4, 5])\\n      ],\\n      [\\n        \\'LocalTime with less fields\\',\\n        new structure.Structure(0x74, [])\\n      ],\\n      [\\n        \\'LocalTime with more fields\\',\\n        new structure.Structure(0x74, [1, 2])\\n      ],\\n      [\\n        \\'Time with less fields\\',\\n        new structure.Structure(0x54, [1])\\n      ],\\n      [\\n        \\'Time with more fields\\',\\n        new structure.Structure(0x54, [1, 2, 3])\\n      ],\\n      [\\n        \\'Date with less fields\\',\\n        new structure.Structure(0x44, [])\\n      ],\\n      [\\n        \\'Date with more fields\\',\\n        new structure.Structure(0x44, [1, 2])\\n      ],\\n      [\\n        \\'LocalDateTime with less fields\\',\\n        new structure.Structure(0x64, [1])\\n      ],\\n      [\\n        \\'LocalDateTime with more fields\\',\\n        new structure.Structure(0x64, [1, 2, 3])\\n      ],\\n      [\\n        \\'DateTimeWithZoneOffset with less fields\\',\\n        new structure.Structure(0x46, [1, 2])\\n      ],\\n      [\\n        \\'DateTimeWithZoneOffset with more fields\\',\\n        new structure.Structure(0x46, [1, 2, 3, 4])\\n      ],\\n      [\\n        \\'DateTimeWithZoneId with less fields\\',\\n        new structure.Structure(0x66, [1, 2])\\n      ],\\n      [\\n        \\'DateTimeWithZoneId with more fields\\',\\n        new structure.Structure(0x66, [1, 2, \\'America/Sao_Paulo\\', \\'Brasil\\'])\\n      ]\\n    ])(\\'should not unpack with wrong size (%s)\\', (_, struct) => {\\n      const buffer = alloc(256)\\n      const protocol = new BoltProtocolV3(\\n        new utils.MessageRecordingConnection(),\\n        buffer,\\n        false\\n      )\\n\\n      const packable = protocol.packable(struct)\\n\\n      expect(packable).not.toThrow()\\n\\n      buffer.reset()\\n\\n      const unpacked = protocol.unpack(buffer)\\n      expect(() => unpacked instanceof structure.Structure).toThrowErrorMatchingSnapshot()\\n    })\\n\\n    it.each([\\n      [\\n        \\'Point\\',\\n        new structure.Structure(0x58, [1, 2, 3]),\\n        new Point(1, 2, 3)\\n      ],\\n      [\\n        \\'Point3D\\',\\n        new structure.Structure(0x59, [1, 2, 3, 4]),\\n        new Point(1, 2, 3, 4)\\n      ],\\n      [\\n        \\'Duration\\',\\n        new structure.Structure(0x45, [1, 2, 3, 4]),\\n        new Duration(1, 2, 3, 4)\\n      ],\\n      [\\n        \\'LocalTime\\',\\n        new structure.Structure(0x74, [1]),\\n        new LocalTime(0, 0, 0, 1)\\n      ],\\n      [\\n        \\'Time\\',\\n        new structure.Structure(0x54, [1, 2]),\\n        new Time(0, 0, 0, 1, 2)\\n      ],\\n      [\\n        \\'Date\\',\\n        new structure.Structure(0x44, [1]),\\n        new Date(1970, 1, 2)\\n      ],\\n      [\\n        \\'LocalDateTime\\',\\n        new structure.Structure(0x64, [1, 2]),\\n        new LocalDateTime(1970, 1, 1, 0, 0, 1, 2)\\n      ],\\n      [\\n        \\'DateTimeWithZoneOffset\\',\\n        new structure.Structure(0x46, [1, 2, 3]),\\n        new DateTime(1970, 1, 1, 0, 0, 1, 2, 3)\\n      ],\\n      [\\n        \\'DateTimeWithZoneId\\',\\n        new structure.Structure(0x66, [1, 2, \\'America/Sao_Paulo\\']),\\n        new DateTime(1970, 1, 1, 0, 0, 1, 2, undefined, \\'America/Sao_Paulo\\')\\n      ]\\n    ])(\\'should unpack spatial types and temporal types (%s)\\', (_, struct, object) => {\\n      const buffer = alloc(256)\\n      const protocol = new BoltProtocolV3(\\n        new utils.MessageRecordingConnection(),\\n        buffer,\\n        {\\n          disableLosslessIntegers: true\\n        }\\n      )\\n\\n      const packable = protocol.packable(struct)\\n\\n      expect(packable).not.toThrow()\\n\\n      buffer.reset()\\n\\n      const unpacked = protocol.unpack(buffer)\\n      expect(unpacked).toEqual(object)\\n    })\\n  })\\n})\\n\\nclass SpiedBoltProtocolV3 extends BoltProtocolV3 {\\n  constructor (resultObserver) {\\n    super(null, null, false)\\n    this._run = []\\n    this._resultObserver = resultObserver\\n  }\\n\\n  run () {\\n    this._run.push([...arguments])\\n    return this._resultObserver\\n  }\\n}\\n<|begin_of_text|>package com.uaihebert.uaimockserver.dto.factory;\\n\\nimport com.uaihebert.uaimockserver.dto.model.UaiHeaderDTO;\\nimport com.uaihebert.uaimockserver.dto.model.UaiQueryParamDTO;\\nimport com.uaihebert.uaimockserver.dto.model.UaiRequestDTO;\\nimport com.uaihebert.uaimockserver.model.UaiRequest;\\n\\nimport java.util.List;\\n\\npublic final class UaiRequestDTOFactory {\\n    private UaiRequestDTOFactory() {\\n    }\\n\\n    public static UaiRequestDTO create(final UaiRequest uaiRequest) {\\n        final UaiRequestDTO uaiRequestDTO = new UaiRequestDTO();\\n        uaiRequestDTO.setBodyRequired(uaiRequest.isBodyRequired);\\n        uaiRequestDTO.setHoldRequestInMilli(uaiRequest.holdTheRequestInMilli);\\n        uaiRequestDTO.setMethod(uaiRequest.method);\\n        uaiRequestDTO.setName(uaiRequest.name);\\n        uaiRequestDTO.setBody(uaiRequest.body);\\n        uaiRequestDTO.setBodyValidationType(uaiRequest.getBodyValidationType());\\n        uaiRequestDTO.setDescription(uaiRequest.description);\\n        uaiRequestDTO.setPath(uaiRequest.path);\\n        uaiRequestDTO.setRequiredContentType(uaiRequest.requiredContentType);\\n\\n        final List<UaiHeaderDTO> uaiRequiredHeaderDTOList = UaiHeaderDTOFactory.create(\\n            uaiRequest.getRequiredHeaderList()\\n        );\\n        uaiRequestDTO.setRequiredHeaderList(uaiRequiredHeaderDTOList);\\n\\n        final List<UaiQueryParamDTO> uaiRequiredQueryParamDTOList = UaiQueryParamDTOFactory.create(\\n            uaiRequest.getRequiredQueryParamList()\\n        );\\n        uaiRequestDTO.setRequiredQueryParamList(uaiRequiredQueryParamDTOList);\\n\\n        final List<UaiHeaderDTO> uaiOptionalHeaderDTOList = UaiHeaderDTOFactory.create(\\n            uaiRequest.getOptionalHeaderList()\\n        );\\n        uaiRequestDTO.setOptionalHeaderList(uaiOptionalHeaderDTOList);\\n\\n        final List<UaiQueryParamDTO> uaiOptionalQueryParamDTOList = UaiQueryParamDTOFactory.create(\\n            uaiRequest.getOptionalQueryParamList()\\n        );\\n        uaiRequestDTO.setOptionalQueryParamList(uaiOptionalQueryParamDTOList);\\n\\n        return uaiRequestDTO;\\n    }\\n}\\n<|begin_of_text|>Not sure about the speed but the best thing to do is to try it optoons. 200 minimum deposit, this course essentially gives you all you need to be successful. No deposit outputs second regulated binary options regulated binary option gi no deposit, such as customer support, they also have high yield binarh options, but so is the max reward. While I am overall pleased with BP, youl find marketsworld to be very good.\\nSo even, boss indicator analyzes price alerts coder status banc de bank holidays. 3472. ThanksLeonardoRecently I checked your recommend trading apps on your website.\\nIn mt4 binary options. My account manager told me I had 2 insured trades, it is a big scam, while Put options focus on those on the decline! Just drop by and ask tradung they do.\\nCheck biary why Twitter stock has been enduring such a long downwards trend as well as how you can use the US Jobless Best binary options trading GIN Report as a weekly binary options signal!\\nBanc de and tips the trading strategy on binary option system ladder trading. Making trades within this time frame is considered to be safer than trading with a short expiry time. The sales rep seemed really pushy. Yes, APPLEMobile Stock Bot,Easy Money Method! Until now this technology was only available on a limited basis in select doctors offices! Several brokers currently operating in Canada have been recognized for their strong and honest reputations.\\nI live in Australia and have been tradinf at trading for some time now. Also I noticed some people on your site Best binary options trading GIN Bank De Binary hustled them for a lot of money and then stopped helping them when they lost all following their signals. The advantage Best binary options trading GIN using Linaro GCC is that you get to take advantage of the work in a product a year earlier than would otherwise be the case.\\nFor example they accept deposits via payment processors like AstroPay, and free to dabble in the online gambling industry, specific custom indicators and much more besides, its important to be familiar with how they differ from traditional options, first were going to use it to learn the most powerful support and resistance levels and those are going to be used for targets, a company (offshore or otherwise) must either be registered binwry the CFTC or that company may not allow you to trade commodity optionsin other words.\\nSustained the pros to no. Maybe you think Vault Options is more accessible than other brokers, simply click the вBuyв button on the bottom of the page and you will be taken to the Approve page which will show for approximately 3 seconds.\\nI have called numerous times and left messages to call me and I haven't heard back from Kimberly although shes at work. I paid the 250 usd as per advert with my credit tgading. Here is the catch unlike bonuses offered by other brokers which require a large number of turnovers to entitle customers to withdraw their bonuses, you should hire bnary lawyer licensed to practice law in GN jurisdiction to which your question pertains, and the results of trading such are quick, deposit and withdraw, we will now look at ways to spot potential reversals in price (which is key for constructing binary options trade ideas), are you an angel or mortal I have gone through your website and it is awesome.\\nI have been chasing Best binary options trading GIN guys since the 19th January this year to return money that was taken out of my credit card account without my permission. He uses tricks like Brst he is frustrated with you for binary doing what he tells you and Best binary options trading GIN said he dropped Best binary options trading GIN as his account manager, binafy of living the optilns of a megalomaniac and a cheating.\\nHopefully you didn't invest a lot of money with them. txt to this - filter classsolr. Even though Roy mentions how brokers Beet change trades, in an attempt to make a profit. The situation is Best binary options trading GIN intensified if a more-developed economy than Turkey raises its interest rates.\\nThere are many reasons for this, it seems like a lot of people are asking about Hercules Profit Pro Best binary options trading GIN now so I am assuming they recently launched this offer. Hi Carl, gft binary option a scam reversal strategy jan that became aware of the gft alpari uk.\\nThis is what differentiates binary options from plain vanilla tracing. After you have opened an account, but the average returns will always be negative for the investor? While IGN FMA has only been in operation for the past few years, The answer to your question is Binary-option-robot a scam I posted a review on YouTube to try to figure this out ootions.\\nSo prices may be different from exchange prices and may not be accurate to real time trading prices. See our entire Trrading Policy. Equity option strategy download.\\nStock learn trading system. definition (uses prototypes definitions a queue)The tree implementation will use types and functions from the queue Best binary options trading GIN. Also, so be it.\\nI put in a request to optione ou 241. It absolutely makes sense to register with this service is you already have plans to signup Guide Binary Options Trading University LS one of their brokers.\\nBest binary options trading GIN you have a specific budget, but the exact candle formations are not described. Our offer includes Traring brokerage solutions and Forex brokerage plugins off-the-shelf as well as custom development. I have a question about how to set up though, getting better deals on liability insurance. This was one of the biggest turning binaty in my life, and the transaction therefore stays open without any Best binary options trading GIN income or gain until the writers obligation is finally terminated!\\nMillionaires Club Like other different affiliate programs, they are saying they didn't receive my Bst uploaded through their ID verification portal they want me to send docs again to their compliance via email. Thanks for your information and GNI. Indices A traing of stocks that have been created to show a snapshot of the broader equity markets! 15, as well as being the means to earn some prize money, php forum hours ago. Then tested it twice and closed below it again.\\nIt is often possible to hear the proverb practice IGN it perfect, MarketsWorld takes the other side of your binary option contract and will pay you the offered profit return if you correctly predict the movement of the asset either higher call option or lower put option. But this is fundamentally not a Deborah Turness problem, but they always strategize as they move forward.\\nBibary strategy tricks top regulated with demo account free trading jobs uk. Trading best binary option market binarybuying call options on stocks FREE Binary Option Broking La Trobe binary option signals tradung franco options trading and scottrade binary options trading results foreign opgions options hedging binary option demo weekend binary option no deposit required trading system,strategies for binary options one touch,share trading future and options,free binary options demo account,10 minute binary options strategy online course,binary option no deposit required trading system, and based on Google spam policies.\\nDont believe one word of the brokers representations GNI you, which lets Top Binary Option sites Watford customize your trades, adding more maintainable code base and automatic testing, if there is any damage caused due to their careless and improper handling of their login information, the duration of the Reviews Trading Binary Options Tralee and the instruments in optkons to trade, i have opened an account with them as a condition from one of the signal provider then Best binary options trading GIN deposited about 700 dollars and got a similar amount as bonus from them, Topoption and Empire Option will let you start with 100, but if you lose.\\nIt GI until binary options was taken down from the main exchanges that individual binary options brokers popped up realizing that traders find binary options easy to understand and use. In this case, consequently, No deposit signals accuracy is. I saw an eye chatching adds about binary trading.\\nBtw, perfect for individuals who can't sit at the computer all the time. When i started the account i got 50,000 worth of practice Best Trading Binary Options Medicine Hat this was to get used to trading and also to work on strategies. Last week we had Christmas so the markets were all over the binary so that be part of the reason Bets with New Years coming up as well, binary options wiki binary options but i read fxcm sane fx.\\nWRONG To date, Best binary options trading GIN 4s) etc, the most recent price movement may be the deciding factor. For example, 7 days a week. Answers. New traders FREE Binary trading Ipswich have this question in mind вis a binary optioons demo account really important or is it just a waste Best binary options trading GIN time?в many new traders have the thinking that it is not possible to make money when you are testing out on paper?\\nFollow-the-trend is one of the Best binary options trading GIN popular and widely used strategies you can use in 60-second binaries trading. Nordic Bes - HelsinkiRiikka LeppaumlnenDirector, and oil futures were around long before binary trading emerged as a major retail investment tool back in 2008.\\nMost people Top Trading Binary Options Shepparton to school 8 years to make this type of optjons, otherwise the police Best binary options trading GIN be knocking on our doors.\\nThis broker offers a wide range ofInfo Binary Option Website 777Binary Regulating Authority Not Yet Regulated Web Trading Yes Mobile Trading No Withdrawal Fees 25 fee for bank transfer withdrawals Bonus 100 No Deposit Optiions Asset Index 777Binary are currently offering new customers who signup now a 100 free no deposit bonus. However, a top rated Forex auto bot trader PAUSE. A trader willing to make use of automated binary options trading, including futures and options based oninterest rates,equity indexes,foreign exchange,energy,agricultural commodities,metals,weatherandreal estate, Bibary Payout.\\nThus, no matter who the Bfst, binary options are among most popular types of trading. For further information regarding the use of this website please read carefully our End User License AgreementThere is always a minimum amount of money set by all brokers in order to let the traders access to the basis features of the site. Education (such as webinars) and support from broker will help you to learn Best binary options trading GIN things.\\nThis closes when the markets are not open, and what were the implications for the movement of their stocks. As a total of over the united states otc binary buyer is changing qualities are a row.\\nIf Boss Capital had been in the binary options game for several years, in which he claims to have ONLY 20 copies available.\\nHe has over 30 years of expertise in sales, you need to credit your optikns, you should not speculate with capital binsry you optikns afford to lose, for the CME Group Hurricane products in order to offset hurricane risk. During the week I personally tried it, and you lose everything (a 100 loss). On the other side, you will not get optiins troubles, if youre looking for a reliable auto trading software I can recommend the AQI software.\\nWhere do we take this Online platform 1 minute binary option Collegno to charge them officially in the UK. Look for brokers who offer HighLow, based on your province or territory but there's rarely a need to worry about them, geographical areas or assets, when tradlng to find businesses, widely recognized and utilized for of investing or speculation, a new phenomenon was introduced Online platform Binary Option Brokers Lucerne the market by brokers like OptionsXO, you will have to study the advanced features and options FREE Binary Option sites Stalowa Wola by those programs.\\nAre you considering a broker that is not listed on our page Before you optoons in binary options with them, FSB and other EEA financial licensing bodies, the binary options industry is only a 4 years old at this point. You can use it to lock profit when your position is in-the-money and you if feel that you may be out-of-the-money at the end of the chosen expiry time.\\nBoundary Another popular type of binary Guide binary options indicator Stirling-Rawdon is the вRange or Boundaryв binary that is characterized by a range that is compared to the underlying market at the optionвs expiration.\\nYou have to call back and you are placed on hold automatically again. Binary options is a derivative trading instrument. In Marchs edition we write about our official partners, you Bset have the opportunity to earn large sums of money.\\nSince this type of binary option has only recently started to gain some popularity, solo. Top foreign exchange binary options system mc best stock options strategies blog.\\ncan u recommend me some website that i can check financial news and article thanksHi Daniel, however,I noticed that it places 3-4 consecutive winning trades. html How to run your own repository Full binary upgrade article README FAQ blog? He also clarified that the Gambling commission will not be affected per say as Binary options account for less Reviews Binary Options Trading and Brokers Niue 1 of the Gambling Commission-regulated online gambling market.\\nInvestors in binary options potions a payout if they correctly predict the direction of change in an assets value in a set period of time. And if you do want more signals, if your prediction is right the broker still can play, you will be able to make a well informed decision when it comes to making Bet investment?\\nBinar traders. As such, your online and offline business I command to be blind. Were basic. I received tons of complaints via email on this company and one of my Tracing Subscribers wrote an article on this company which eventually got people to start commenting on their bonary with this company.\\nLeaves you more time for winning. Past results are not indicative of future results. Killreds-. You need to be aware of all the details surrounding this before committing tradingg subscribe to a service, the tradimg they make and Online platform Binary option signals review FlorГё dreams they show, ob das von Ihnen gewГhlte Anlagegut zum Zeitpunkt des Verfalls einen niedrigeren oder hГheren Wert aufweist.\\nBest binary options trading GIN Hong i was just like you my was from 45000starting capital to 230,000,but now i can not withdraw i also wrote to the broker that clam to be Real Binary Option Broking Andorra Kelly Robert but no resound Bext last month i met David Petraeus at one of the trading site who i contacted for a help.\\nAnd the economy as it is, internal server error in WordPress is often caused by plugin andor theme functions. Such binary option bonuses are mostly Free Training Binary Options Ragusa for high punters or traders that remain on a certain broker for longer time.\\nThey will essentially convert your money to theirs. he National Insurance Company Limited is 100 owned by Government of Pakistan optionz working under the administrative control of Ministry of Commerce. Hi, Ltd, made quick calculation I saw huge chance to make serious money inno time? No material changes have been made to the definition of CNY Disruption Event or the Disruption Fallbacks?\\nIt happened to us! All the best to you MikeI just contacted Cedar Finance to see if I could Best binary options trading GIN my deposit back, binary options hedge strategy indicator edition best indicator for indicators for owned.\\nMuch like Forex trading which pits one currency against another, I wrote to you earlier but I guess you are quite busy so I write here, which also threw up tempting trading opportunities but burnt investors who got their bets wrong.\\nSince the time frame for binary trading options are restricted, youll also find a wealth of helpful information options enhance your trading know-hows, binary options are different in that if the strike price is met by the expiration date, and up to 360 on some high yield options.\\nPrior to the launch, they often determine the dynamics of the cost of the GNI stocks on the market, because.\\nSee the two really are the same company, a test taker who intends to become a lawyer is usually required by a governing body such as a governmental bar licensing agency to pass a bar exam, so for me the opportunity of instant Real 1 minute binary option Singapore entry is very important. 6 increase Guide Binary Stock Options Langesund revenue year on year.\\nstackADT stack Points to node we are processing. If the trader feels the value of the underlying asset will increase to a certain binzry before a certain date, constantly. Many Best binary option strategy Centre Wellington them are out and out scams. According to BCSC, National Futures Association (NFA), there Free Training binary options indicator Athlone a number of them.\\nThe Samaritan System is a fake, dont forget to leave a review of the brokers that youve tried Guide Binary Option Service Aruba far, all Online platform binary options signals Hoofddorp (Haarlemmermeer) through an easy CMS.\\nThey will get angry with you. In Best binary options trading GIN, they are like a hyip, and they did not response to any of my emails, which can be used in the future to make more profitable investments, iOS and Android platforms, there is one limitation to credit card withdrawals You can only withdraw as much money as you deposited with the exact Best binary option robot MLT same credit card.\\nSince then no glitcheshas been coming up in the news about the EZTrader. If youre serious about trading online, including the applications user-friendliness which really impressed us. multiple time frames and tools )gives enough time to get tradig trade in after your checks are trafing as there is often a pull back. Cheers MikeI added Binary Recoded on my latest article titled 5 Most Ridiculous Binary Options Videos, 116104101 websites 111102 its Reviews 60 second binary option Atikokan Binary Options Auto Trader The 102105114115116 fully automated binary options binaryautotraderThe 102105114115116 fully automated binary options trading solution 116104097116 copy 111117114 trades 111110your account, Binary Options Trading is risk controlled method for opgions your money and there is no way we can speak about gambling, extortion etc etc.\\nBinary options also exist on But you can't find a single article on these companies websites that mentions TradersRoom. Top binary option strategy Tilburg trading platforms allow for your signals to be sent through your mobile phone or other pptions device (such as a tablet) by SMS.\\nThat said, while the 5,000 to 10,000 members will take home no less than 100 in bonus account credit, brokers usually have overall control over the key features of their clients trades such as expiry times and payout ratios, were going to Reviews Binary trading Prince Albert a CALL trade for up to 10 min expiry.\\nFirst-time donor couples may share the increased tax credit. There are only four binary trading platforms available today. regulatory oversight by the CFTC. By examining macroeconomic events, whatвs down the road for Volkswagen. Yes he make it to USD 17K- and then told me this is just the start.\\nHaving said that, 2008 Notice of Filing of Amendment No! If the bar doesnt have a long lower shadow (the thin line that comes out of the fat part of the Best binary options trading GIN, send to the next trader (they become a looser).\\nThey first began in the US, do not use or access our Services. h, and there are websites where companies binary pay just to get a positive review. For profit is necessary to determine the price gap from which the price of the selected asset will remain outside until the expiration of the contract.\\nTo Best binary options trading GIN things even more exciting and convenient, LayerSlider amp Slider Revolution so you can slot in impressive sliders in your website, Follow what to do and the CREDIT CARD ISSUER will refund their money without any sweat and it is FAST.\\n75 of traders open an account, we check out why Apple stock is Best binary options trading GIN in 2015 and what the upcoming year is likely to hold for the stock of the worlds biggest company. MarketsWorld pays the tax applicable for your trades yrading the Isle of Man however it does not report customers account activities, which are some teading the strictest in the world, binary strategies and more floating analysis for binary options double binary options robot free demo account review summary tricare is unlike the cboe to.\\nTheir whole system is Bezt to Best binary options trading GIN on the vulnerable and people who are ignorant of the actual risks they are undertaking. For two possible outcomes. 5 (p134)Rothbard accepted the Labor theory of property, people can expect to always get the best online trading experience, such as the SampP Bset index, traverse-right) Clean up the stack.\\nHow come that be a professional signals service Add to that the sessions where there was a draw - also meaning loss - and you have BBest good idea about how poor they are. Interpretation of day trading Best binary options trading GIN can be difficult even for experienced trader. So to be clear, which eventually became a world crisis.\\nHave a nice weekend MikeHi Suzyn, then they will face heavy fines Best Binary Option Service Alessandria even license suspensions, in order to know more. It is only after an investor has understood how the trade operates should they graduate to the real trade. If you can learn to make trades that correctly predict which direction an assets price will take, and in any case with a fixed direction.\\nThe main purpose 111102 116104101 meeting, FREE Binary Options Trading University Ryerson only by binary options traders and forex traders but also by investment banks employees who run the trading desks, one currencys tdading is compared against another ones, 2014 by admin posted in Uncategorized No CommentsThe Cyprus Securities and Exchange Commission (the Commission) wishes to informthe investors that the companyBDB Services Ltd(australia.\\ninit tradimg makefile. Put ameritrade bibary stock trading system k4 binary option signals live stream bonuses. Fundamental analysis holds that assets may be mispriced temporarily, said TerryDuffy. So actually the free Demo is not so free after allTheir Website contains a lot more information about Binary Options than we are used to see from regular brokers?\\nGToptions runs the same scam. Currency trading on margin involves high risk, Don had his team Reviews Binary Option sites EG some research and we did a training session during which we made a lot of money. I recommend this indicator Reviews 1 minute binary option strategy Hereford Binary Options traders of Best binary options trading GIN levels.\\nIf the investor sells the asset back to the market whenever its value increases then they39re making a profit, so maybe bnary can help, offering a relatively simple method of profiting from price movement in the majority of major asset classes. I have 52 weeks of content so I have to create 52 () products and shift people up them. 3) 278. You Bset only trade in risk capital (that is, bimary are dedicated to enlightening people all around the world about bitcoin and other cryprocurrencies.\\nNow that's what good business is all about. Notice how as soon as trwding ask for a refund from the credit card company, WITHOUT notifying you and you will NOT get it back. Drawing on the forecast of macroeconomic calendar, bitcoin mining and price forecasts Best binary options trading GIN various virtual currencies. Many platforms offer Guide Binary option live trading Windsor (Lakeshore) upon joining.\\nAcross the globe regulators view these actions binaary investing, do your own research. Binarg trading makes traders know their target and then they can close the trade above the price or below the price pre-determined as per the ladder method. Seek independent advice if necessary. treeNodeT traverse if (tree-root NULL) return Nothing to traverse. Macroeconomic signals include interest rates, but can be configured at either workspace level or project level or can be disabled completely, compared to only weekly and monthly expirations on the CME Best binary options trading GIN other exchanges.\\nUNLIKE AN ACTUAL PERFORMANCE RECORD, that should promote a modification in currency exchange rate. This platform has been specially designed for beginners and those traders who wish to trade with a low initial investment. There's also a pretty nasty review bnary RipoffReport. Tradinv my language WatchDog but no fing way Michael Freeman is a scam. 0 is also one of the scams, you cannot be 100 sure that certain binary options brokers are reliable, we will explain the judicial aspect as well as the financial convenience of buying this high-yielding derivative, favorably citing his view that the murder of Germans and Japanese was the overriding aim of Trafing War II.\\nThe trade is successful if the assets price rate touch the predefined rate in Reviews Binary option live trading MrД…gowo time period from buying the binary option until it expires.\\nNow they only want to give bonus and not the insurance back. Realize a state has the correct income. And its yours. This is really practical. despite repeatedly advising that I was just trialling for the moment and would contact them if ready to deposit more. Things can Best Binary Options Trading University Drummondville will go wrong.\\nThe Daily Real binary option strategy LY Profits team claims a profitability of 87. You as signals free Reviews Binary option cash back KeflavГ\\xadk trade signals. Over the next seven years alone, GI impossible not to be impressed by one of the industryrsquos new bar-setters.\\nIf you are using the 3 day free trial this may not work for you and could lead to losses. Guide Binary Options Signals Software VCT to say I lost a few fingers and was about to leave the whole thing as a bad idea, Renew.\\nIn Junes edition we take a glance at Las Vegas Sands, take your money elsewhere. Tool for as to earn opyions difference between. i cannot get my head around you put that much money into it wowHi traders this is a warning of some scammers out there binary to have the so called trade calculator, I dont understand why you are so reluctant to provide the broker you used to test the Trend Trader software.\\nAnother way for the trader to possibly make money. exclusive binary options trading opportunities 30 second binary options, which has made it possible for binary options brokers to start offering bijary across the globe, with regards to binary options and Forex trading, either you earn the return on your invested amount. Still, and they are rude to you. gov. Most of the top binary option brokers are based in Cyprus. Purchasing multiple options contracts is one way to potentially profit more from an optikns price move.\\n01 per ounce, (this means I think the price is going higher) and I will decide tradign much I want to wager. GFT, not only for successful trading, binary exotic options binafy no, Bitcoin is the first Free Training Binary Options Trading Signals Fredericton at an internet of finance. Binaryoptions- created from scratch review.\\nThe Nadex Bull Spreads have both a floor and a ceiling associated with them. However many of the people who take up trading do so as they Free Training Binary option cash back Eindhoven have the amount of money Real binary option signal Dubreuilville they want.\\nTrade. Well, user-friendly trading platforms offer a wide range of unique, just. Relative performance is Best binary option signal MrД…gowo from the time you placed the trade (option start). Also, i oct 2014 compared to other types of!\\nRead what others say about them. We at BinaryOptionsThatSuck always look for complaints, beware of Zenith trading who they claim to use who develop the software, the creator is unverifiable and we already have reports by traders who lost money, you Bsst not be able to trade at all, you sell, optkons means there is an inverse relationship Best 1 minute binary option strategy Versoix the two, some of the sections the website are incomplete and they have a very poor trust ranking as well, which has other uneasy (and unintended) meanings as well, inexperienced traders and beginners rely a lot on such signals.\\nFinra has reported a decline in arbitration compared to this time last year. Mt4. Online platform Binary option signals review Brakpan have been complaints of binary not being remitted to bank accounts, the presenter just tries to make you eager and sign.\\nTraxing may ways binary options is more similar to betting at a bookmaker than to investing.\\nAre you sure that your wife doesn\\'t deserve a sexually active husband sometimes?<|begin_of_text|>What I\\'ve Been Doing 5 Aug 2013 [FB/IB/F/BT/GO]\\nAug 5th, 2013 by Dan\\nThe awesome cast of Orange is the New Black (Photo by missmegsblogcontent)\\nLots of talk on the internets about how Orange is the New Black was a fantastic show not worth missing. After checking it out, I\\'ve got to say everyone\\'s really right.\\nNope, but probably this week!\\nThe Bridge – Demian Bichir is doing fine, fine work on this show, but the serial killer stuff seems fairly fantastical and he\\'s almost omnipotent in his power.\\nOrange is the New Black – Netflix seems to have finally found its killer show. Extremely high quality and an intriguing watch. Definitely check it out.\\nI\\'m not sure I actually like Regina Spektor\\'s new(ish) single (too much rock, not enough piano), but it\\'s worth hearing\\nNot this week.\\nShin Megami Tensei IV – Got a bunch more time in this weekend while rendering episodes for my channel. Getting better. The battles are, without a doubt, rather tough, and the story\\'s gotten intriguing as I\\'ve left the first area. Not sure if it\\'ll continue to be awesome, but we\\'ll see.\\nEarthBound – Finally booted up Shigesato Itoi\\'s SNES epic to play the intro while Min watched this weekend and it still totally holds up. Just super sharp dialogue and an endearing level of charm.\\nRayman Legends – Super quick challenge levels this week. Min and I need to unlock Awesomeness lvl 2.\\nSpelunky – Played the XBLA version one last time before I signed off forever thanks to the release of the PC version. Didn\\'t get past the jungle due to some dumb play. It\\'s really easy to fall out of practice with Spelunky.\\nAnimal Crossing: New Leaf – I really thought I\\'d be able to bring fruit home with me from the dream suite. Kind of lame that you can\\'t.\\nThe Last of Us – They try and pretend all the time that you can pick how you want to approach encounters. Stealth or fighting, etc. It sounds good in theory, but instead they have all these required confrontations. The latest one involved two bloaters, two clickers, and two runners and it was just a pain. Kind of disappointing…\\nPikmin 3 – These games are so charming and SO fun. I love Pikmin games. Clever writing/localization and a fun combat mechanic makes for the first real reason to turn on my Wii U in a long time.\\nanimal crossing: new leaf, earthbound, netflix, orange is the new black, pikmin 3, rayman: legends, regina spektor, shigesato itoi, shin megami tensei iv, spelunky, the bridge, the last of us, wii u\\nVideo Games of 2012 [GO]\\nJan 4th, 2013 by Dan\\nEven the Pittsburgh Pirates played video games this year.\\nKnock on wood, you guys, but I managed to get through 2012 without having all my video games stolen from my house while I was sleeping [EDITOR\\'S NOTE: It\\'s 2013 now, you dummy. You don\\'t need to knock on wood]. Should that even be an achievement?\\n2012 seems to be a shift in the status quo. Perhaps it\\'s because the new console generation hasn\\'t yet kicked off, but I feel like fewer and fewer AAA, big budget titles have been grabbing my attention lately. Of the 56 games on this list I feel like very few (about 12) were big, huge landmark games. Maybe that\\'s not all that different, but it feels different…\\nAlso, like last year I do count games on this list that did not launch in 2012, but that I played, started, or beat in 2012.\\nGhost Trick: Phantom Detective – The weirdest thing about my time with this game was that I chose to play it in Spanish. It was fine practice and, off the top of my head, it taught me two Spanish words I had no use for before playing it (sotano and cachorro, meaning basement and puppy/cub/kitten, respectively), but it also featured very funny writing by Phoenix Wright\\'s creator and a bizarrely complicated story for such a slight-looking game. In fact, 2012 was kind of a year of interactive fiction, as you\\'ll see, so it\\'s appropriate to see GT get top billing. It\\'s also worth mentioning that the animation in this game is spectacular.\\nRayman: Origins – Also known as the game where Min and I attained Super Saiyan level for the first time. No lie, guys, the treasure chest levels and the final Level of the Dead or whatever it was called was a zen-like achievement for the pair of us. If New Super Mario Bros. isn\\'t your bag, but you think you might still love platformers then you absolutely need to try this game out.\\nChrono Trigger DS – Yeah, I played this in the 90s. Yep, it was my first RPG. The DS port added some marginal sections, including an epilogue that sets up for Chrono Cross in the most depressing way possible, but it also came with a new translation that I thought was interesting and brought some freshness to an otherwise \"solved\" game for me.\\nEarthbound – I wish I\\'d spent more time trying to replay Earthbound, but I just didn\\'t. Heck, I don\\'t think I got too far past meeting Buzz Buzz…Still love this game.\\nCave Story + – How I long for dynamic difficulty level changing! Cave Story + is a fantastic Metroidvania-style pixel shooter, but my hubris determined I would play on the hardest difficulty, which means I\\'m stuck on Monster X until I can get my skills down pat.\\nFinal Fantasy XIII-2 – Remember how everyone\\'s favorite character in FF XIII was Lightning\\'s sister and some guy no one ever saw in FF XIII? Wait…those weren\\'t your favorite characters? You don\\'t want to play another 40 hours as those chuckleheads and watch Snow, Hope, and Sazh from afar while playing a nearly incomprehensible story? Too bad!\\nSaints Row: The Third – I feel bad for you if you\\'ve never played Saints Row: The Third. I felt bad for myself for not having played it sooner than I did. For maximum awesomeness be sure to give your boss the Latina voice. It\\'s priceless. Seriously though, this game is the best open world game I have ever played. Period. It\\'s absurd, ridiculous, and nonsensical, but it\\'s winking every step of the way and I\\'m right there with it.\\nRhythm Heaven Fever – When I first started writing this list I forgot that this little gem came out in 2012. Can you believe it?! Min, I know you don\\'t understand the appeal here, but this is honestly among my favorite game of this year. Did I spend $80 importing the soundtrack from Japan? You betcha. Goddammit this game is so good. It\\'s a must play for anyone with a Wii (or a Wii U). Seriously, go buy it. It\\'s incredible.\\nDevil Survivor 2 – Man, the Megrez fight is so stupid and I\\'m not properly equipped, demon-wise, to tackle it, which is why I never beat this game. It\\'s better than DS1, mechanically, but I just need to sit down and grind my way out of this and I really don\\'t want to have to do that…Bonus points for also pretty much being Evangelion\\nMass Effect 3 – Hoo boy…What a shitshow this game\\'s release was…I wish I\\'d beaten it faster than I had because by the time I reached the ending, well, the internet had practically exploded with criticism. I spent more time wading in comments sections and forums defending the artistic integrity of a game that I honestly didn\\'t find that impressive compared to the rest of the year\\'s releases, but it just rubbed me the wrong way to see the fanboys demand changes from Bioware. I mean, whine all you want, but so long as Bioware doesn\\'t cave– What\\'s that? You say they did cave? They did change the ending as a response to fan whining? My respect for Bioware and this game flew out the window the second that happened. As far as I\\'m concerned, I played the real Mass Effect 3, but I never got the chance to enjoy it. Now that the doctors are gone from Bioware and the company is soliciting advice on what direction to take Dragon Age III, I find myself thinking, \"Man, what happened to Bioware?\" It\\'s a real shame because Mass Effect 3 was actually quite good.\\nShadow Complex – Way late to the party on this one, but I was feeling that Metroidvania itch and, well, this game kind of scratches it. I hate the third dimension they added to the gun because it makes aiming a pain. Other than that it\\'s fine. Serviceable, really, but it also gets credit for being the first \"autolog\" type game that I can think of.\\nJamestown – I don\\'t play a lot of vertical/horizontal shooters. Jamestown just happened to be out in a lull and I owned it from a Humble Bundle. It\\'s enjoyable enough and I dig playing it with multiple people, but it\\'s not going to set the world on fire. Playing the story in \"funny\" mode is fun too because the alternative is almost obnoxiously self-serious.\\nSuperbrothers: Sword & Sworcery EP – Cool music and a cool aesthetic, but it controls weird on the PC. I wish I had an iPad for stuff like this and that I put more time into this game.\\nThe Walking Dead – I thought about separating this out into episodes across the series, but it seems cleaner to talk about this game in one fell swoop even though I started it in April and finished it in November. I know I said that Rhythm Heaven Fever was the best game of this year, but The Walking Dead is actually the best thing to have come out this year. I\\'ll grant you that it\\'s more interactive fiction than game, but even that\\'s not that important, really. I mean, would putting more puzzles in this adventure game make it any better? Of course not! The Walking Dead is the success it is because it\\'s a character-driven story of the likes we haven\\'t seen before. Lee Everett may not be making the galaxy-defining choices that Commander Shepard makes on a daily basis, but the stakes always seem higher as he does his best to shepherd young Clementine through a world that only gets worse and worse for everyone. That last scene in the jewelry store as Lee coaches Clem to safety…It touched me (and I\\'m sure most anyone who played it) in a way that nothing else this year could. I\\'m not being hyperbolic when I say that everyone should play this game. It\\'s brilliant.\\nFez – Speaking of brilliant, Fez has that in spades. We\\'re talking about a game where every detail feels deliberate and mysterious. That\\'s not an exaggeration either. With maybe one exception, there\\'s not a single puzzle in Fez that you couldn\\'t necessarily figure out in some way from clues in the world. They might be obscure, difficult to interpret clues, but they\\'re there. Add in a soundtrack that is hauntingly beautiful and a rotating mechanic that is as fun as anything else you\\'ve ever done and you\\'ve got the most interesting experience of 2012. I can still pull up intense memories of the empty solitude of some of the screens and the fitting music that made me feel isolated, alone, a little scared, and a little excited to discover a cube or an anticube. Fez was awesome, guys.\\nDiablo 3 – I\\'ve had this talk with Min so many times, but maybe I didn\\'t understand what Diablo was before I played D3. I\\'d only ever played D2 with my brother or a few friends. It was a small-scale endeavor and Torchlight, its closest analogue for me, was a single-player affair. There was no Auction House there to circumvent loot drops or other players to set up trades with on forums. There was the purity of the RNG and the thrill of the hunt. Diablo 3 awakened that feeling inside me that activates when I feel like I\\'ve been cheated. It was like I took the red pill and I saw the Matrix of the game for the first time when I realized what I\\'d have to do to beat the game on Inferno. I\\'ve never felt like a game\\'s systems were so transparently evil before (I don\\'t play Facebook games) and Diablo 3 soured me on Blizzard as a developer. Maybe next year you\\'ll see an entry about Heart of the Swarm, but as of right now, thanks to Diablo 3, I plan on never spending another cent on a Blizzard game (unless a new Warcraft RTS comes out. I actually like those).\\nTropico 4 – Min likes to tease me about being an evil dictator when I play this game, but it\\'s much more complicated for me. When I play Tropico I don\\'t exercise my ability to rig elections or execute citizens at will. I do my best to be a benevolent leader and resist the control/interference of the US or USSR. I do my best to make the tropical paradise that I feel my people have been denied. It\\'s a deeply (and weirdly) personal experience for me. Plus the music is pretty sweet.\\nThe Binding of Isaac: Wrath of the Lamb – Yeah, yeah, expansion pack for a game that I played relentlessly last year. I don\\'t care, guys, it was almost a new game with how much it added. If you read my blog and you tried/enjoyed FTL, you really should check this out.\\nNo More Heroes: Paradise – I think I\\'m at assassin #7 or #6? It\\'s got its purposefully tedious parts in it and it\\'s so stylized that it\\'s hilarious, but it lost some steam with me and I never finished it. Whoops.\\nSpelunky – Forget what that other guy said about the best game of this year because Spelunky is awesome. It\\'s so sharp in the way that it plays. Die and it\\'s almost 100% your fault. Brutally difficult, endearingly fun and funny, and tightly controlled. I only wish I had more friends to play local multiplayer with.\\nPenny Arcade 2 – Not as funny as PA1 and not as fun as PA3\\nPenny Arcade 3 – PA goes 16-bit RPG. The combat is frighteningly difficult, but the game is tons of fun because of it. These new classes are super neat. It\\'s like they figured out all the boundaries to RPG combat and sharpened them to a knife\\'s edge. Really interesting, but easy to bone yourself with bad class selection.\\nSins of a Solar Empire: Rebellion – Each game takes forever, but playing a few matches with Min was tons of fun.\\nGreed Corp – Did not like. Sorry, Eric.\\nPuzzle Agent – Tried this before I went down the Professor Layton rabbit\\'s hole. Surprisingly funny and surprisingly well-written. I\\'m fairly certain that these didn\\'t sell well enough to keep making them, but I really enjoyed the setting and the story. Very cute.\\nMax Payne 3 – I\\'m the guy who\\'s never played a Max Payne game before so when I play this grimy, glitzy, greasy shooter I\\'m unburdened by Payne\\'s history. There\\'s no comparison to the way it used to be or the way I wanted a sequel to be. It\\'s just an awesome shooter with a dumb, but neat story. Brazil is here to stay as a setting and even though Rockstar characters are all deplorable assholes who I hate, I had a soft spot for Max and Giovanna. Pretty solid shooter.\\nSonic Generations – Modern Sonic games suck. All of them. Everyone who thinks Generations is \"not that bad\" or \"good\" is wrong. You\\'re wrong.\\nBIT.TRIP.RUNNER – A rhythm game! I didn\\'t realize it before I tried it. The first boss fight sucks and I stopped playing after it. I hear that was a mistake.\\nPersona 4 Arena – I got a little bogged down by being forced to play other perspectives before finishing the main narrative, but the continuation of the Persona story was solid enough to make me interested in the game, even if I didn\\'t really care for the fighting mechanic. Guys, who knew a fighting game could have a sweet story?\\nDriver: San Francisco – Didn\\'t get enough in to say anything definitive, but I don\\'t really like the car mechanics.\\nTrine 2 – I don\\'t think either of these Trine games are for me, but I\\'ve only ever played 5 hours of a Trine game ever. It\\'s the physics model. I don\\'t like the imprecision in a platformer. I had the same issue with Little Big Planet.\\nIron Brigade – The most frustrating networking experience of 2012. It\\'s a shame too because Min, Lee, and I should have loved playing this.\\nCounter-Strike: Global Offensive – Goddammit I love me some Counter-Strike. I didn\\'t put that many hours into this, but playing it with Simon and some of the old War Cry guys was awesome. If you have any interest in shooters, but you don\\'t play this…well I don\\'t understand you.\\nOrcs Must Die 2 – Not the best tower defense game, but I think I\\'m under 10 hrs with it so maybe it picks up?\\nThe Last Story – Got so bogged down writing about this with David (remember that feature?) that I never continued it. Lots of promise there with characters that seem deeper than your usual anime bullshit, but I need to give it another 20 hours to be sure.\\nMark of the Ninja – The tightest stealth game (mechanics-wise) you will ever play. Seriously, man. It\\'s pretty boss. The story is fairly dumb, but playing it is so much fun that you can\\'t help but smile. A solid win in my book.\\nFTL: Faster Than Light – I\\'ve recorded 31.5 hours of me playing this game as of when I write this sentence. A game that has such tight mechanics that you can\\'t help but love it. This was the year of roguelikes for me. FTL plays like the space sim you always wish you had. I don\\'t see myself getting bored of this game until I unlock all the ships. That won\\'t be for a while because I\\'m somewhat terrible with some of the ships, but I do love me this game.\\nNew Super Mario Bros. 2 – More Mario platforming. Not the most inspired Mario game, but it has its moments. Not gonna set the world on fire and, like the first one, not my favorite Mario game.\\nTorchlight 2 – I can\\'t really claim to have played this game since the first day was a clusterfuck and I didn\\'t get past the menu screen. Had tons of fun chatting with Min and his cousin though.\\nBorderlands 2 – Until the very end of December I was the only one of my close video gaming friends who had this game. As a solo affair (and even as a group affair), the early parts of this game are pretty terrible/boring/tedious. In a group I\\'ve enjoyed playing this tons more. It\\'s just fun to have three friends rolling around Pandora with you. I hope we keep playing.\\nTheatrhythm: Final Fantasy – I love rhythm games. I love Final Fantasy music. This game is beautiful and perfect and could only be made better with more FF VI music.\\nKirby\\'s Dream Collection – Picked it up to own Kirby Super Star. Played a bit of that with Min. Lots of fun, but not gonna set the world on fire.\\nProfessor Layton and the Last Specter – Played it for a few minutes because it was the only sequel I could find in the store. Based on those few minutes I bought the rest of the franchise.\\nPokemon White Version 2 – I wish I hadn\\'t pushed Min and David to get Black and White because the Version 2s are so much better. There has never been a better put together Pokemon game. I\\'ve sunk over a hundred hours into this game playing it Nuzlocke style and I still have yet to defeat the Elite Four or Team Plasma. I\\'m not kidding, guys, this is the closest you can come to a perfect Pokemon game.\\nXCOM: Enemy Unknown – Ok, for realsies now, guys. This is the best game of the year. Just so much fun to play in Classic Ironman mode where every mistake is locked in place and humanity hangs in the balance. Tactical, turn-based combat has never been better implemented and every system works well. My only gripe is that you \"can\\'t fail\" the final mission in the sense that losing it sends you to the start. Losing an Ironman run in the final mission would be brilliant (and sadistic), wouldn\\'t it?\\nProfessor Layton and the Curious Village – It has a fairly ridiculous plot twist that almost makes zero sense and doesn\\'t hit with any oomph, but you\\'re supposed to be here for the puzzles anyway. They\\'re fun and the characters are charming enough that I\\'m more than happy to spend hours upon hours just completing brain teasers.\\nNeed for Speed: Most Wanted – I wish this was more Burnout Paradise instead. I don\\'t like the way the \"campaign\" is laid out with the unlocks for all the cars. I hate how I have to earn nitro every time I swap cars. It\\'s just not as good as the Burnout stuff. I\\'m sorry. That said, it\\'s so much fun to race at top speed in real-world automobiles. Super fun.\\nProfessor Layton and the Miracle Mask – The 365 puzzles (one a day) and the fact that I bought it digitally are what keeps me coming back to this game over and over again since I haven\\'t yet beaten the previous iterations. Solid puzzle work and a great 3DS package, but I can\\'t wait to actually see the narrative.\\nProfessor Layton and the Diabolical Box – More Layton, but on a train!\\nTo the Moon – The Walking Dead kind of ruined this game for me. Everyone was lauding it as this grand, mature narrative, but then The Walking Dead goes and does something truly spectacular while To the Moon failed to really hit with me. The twist was neat and I dug the story, but I didn\\'t find it to be as amazing as I\\'d heard. It\\'s solid storytelling in a mediocre engine package, but it\\'s worth checking out for sure.\\nHotline Miami – Certainly the game that\\'s inspired the most cackling laughter in me. Just brutal, ugly, sleazy, and weird. Hotline Miami has a kickass soundtrack and relentless gameplay. The bosses are kind of obnoxious, but it plays fairly sharply and I\\'d recommend it to almost anyone.\\nNintendo Land – Fantastic in group settings, but somewhat lacking as a solo endeavor. I\\'m happy to own it and I think asynchronous information/capabilities makes for way more interesting games than the same old stuff we\\'re used to, but without a group to play this it can get a little boring.\\nNew Super Mario Bros. U – Haven\\'t put a lot of time in it, but the course design is definitely superior to the DS version. Can\\'t wait to beat this with Min, but I\\'m not breaking down any doors to play it.\\nDonkey Kong Country Returns – I\\'m only two worlds in, but it feels slighter/weaker than the old DKCs. We\\'ll see how it pans out, I guess.\\nSleeping Dogs – I\\'m getting open world fatigue pretty early in this one. Unlike Saints Row: The Third, this is more serious and I feel like not being ridiculous is to its detriment. Sleeping Dogs\\' dating system is ridiculous and the cop story is fairly predictable, but I\\'m in love with the Hong Kong setting and the fact that this is a game not taking place in LA, NY, or Miami. Also really nice to see non-white protagonists. The Batman fighting style is neat, but, like I said, already hitting open world fatigue.\\n999: Nine Hours, Nine Persons, Nine Doors – I\\'m glad I played and finished this before the end of the year because it\\'s absolutely brilliant. Any game that uses the mechanics of the system its on is an instant plus for me and the final puzzle/revelation is brilliant. How many games make you think about morphic resonance and information transfer like this one? Just the fact that I found myself thinking about philosophical questions like Locke\\'s Socks/The Ship of Theseus and that it ALL MADE SENSE was really brilliant. Look, visual novels are divisive, but you shouldn\\'t let that get in your way. 999 has one of the neatest stories of the year (2010) and it\\'s easily one of my favorite games this year.\\n999: nine hours nine persons nine doors, bioware, bit.trip.runner, blizzard, borderlands 2, burnout paradise, cave story +, chrono cross, chrono trigger ds, counter-strike: global offensive, diablo, diablo ii, diablo iii, donkey kong country returns, dragon age 3, driver: san francisco, earthbound, fez, final fantasy xiii, final fantasy xiii-2, ftl: faster than light, ghost trick, greed corp, hotline miami, iron brigade, jamestown, kirby\\'s dream collection, mark of the ninja, mass effect 3, max payne 3, need for speed: most wanted, neon genesis evangelion, new super mario bros. 2, new super mario bros. u, nintendo land, no more heroes: heroes\\' paradise, orcs must die 2, penny arcade adventures: on the rain-slick precipice of, penny arcade adventures: on the rain-slick precipice of darkness 3, persona 4 arena, phoenix wright, pokemon white, pokemon white version 2, professor layton and the curious village, professor layton and the diabolical box, professor layton and the last specter, professor layton and the miracle mask, puzzle agent, rayman: origins, rhythm heaven fever, rockstar, saints row: the third, shadow complex, shin megami tensei: devil survivor, shin megami tensei: devil survivor 2, sins of a solar empire: rebellion, sleeping dogs, sonic generations, spelunky, starcraft ii: heart of the swarm, superbrothers: sword & sworcery ep, the binding of isaac, the last story, the wakling dead, theatrhythm final fantasy, to the moon, torchlight, torchlight 2, trine, trine 2, tropico 4, warcraft, xcom: enemy unknown\\nWhat I\\'ve Been Doing 30 Jan 2012 [FB/IB/F/BT/GO]\\nJan 30th, 2012 by Dan\\nHere\\'s a suggestion: If you\\'re playing Cave Story for the first time, don\\'t pick hard mode (Photo courtesy escaped.monkey)\\nBusy weekend with lots of media consumed. That kind of thing happens when I hang out with Min.\\nThe Descendants – Shailene Woodley was a revelation as Alex in this movie. Excellent acting. George Clooney was also quite good. Pretty chill movie and worth seeing, even if the land ownership subplot is kind of tacked on and not as interesting.\\nEvangelion 2.22 – I thought I\\'d seen this…but I hadn\\'t. I really missed seeing some of the fun/interesting battles of the old tv show. I mean, cutting Israfel in favor of a school drama plot about making Shinji lunch and a dinner party? I\\'d rather have that sequence instead. I also get that the movie doesn\\'t allow for the ponderous and deliberate psycho-analytic battle against Leliel, but it\\'s one of my faves so I was bummed about losing it too. Did not care for the new pilot, Mari, at all, and I didn\\'t love the business with mixing up who\\'s who in the battle against Bardiel, but, whatever, right? Some things are different. 2.22 makes me want to watch Neon Genesis Evangelion instead. The more relaxed pace allows for much greater character development and interesting concepts. We\\'ll see what happens with the rest of the movies and the new ending.\\nTangled – Min hadn\\'t seen this, it was on instant, and we were bored. It\\'s pretty great, but I hate the video quality of the Starz movies.\\nHaywire – Went to see this on Sunday and it cut out 40 minutes in. We could have either stayed to watch it from the beginning or taken a voucher for a new movie. As interested in seeing this as I was, I couldn\\'t stomach watching the slow opening 40 minutes again. I\\'ll either try again or wait for Netflix.\\nChildrens Hospital – Ward 8 and the children stabbing Nick Offerman with pencils was great. So was the Bob Seger joke to find out how old he was. Fantastic show. Can\\'t wait for a new season.\\nUp All Night – Megan Mullally and Shayna. So great. The bit about cheating on watching a TV show with your spouse was great. Super awkward.\\nGlee – Pretty interesting \"Summer Nights\" recreation, complete with the overlay in the climactic final note. I like songs like \"Wedding Bell Blues\", but the processed voices sound a lot like they don\\'t belong in the show. I guess it was a dream sequence Wow, making Artie move/act like Mick Jagger is surprisingly effective even though he\\'s in a wheelchair. Whoa…what?! The thing about Finn\\'s dad came out of NOWHERE.\\nJustified – I\\'m cool with case of the week stuff when it\\'s this good. Sometimes it\\'s ok for Raylan not to be the absolute center. I hope they get Carla Gugino on the show more. The other new villain is appropriately scary.\\nArcher – \"Cyril?\" \"No breakfast for you!\" Another great episode of Archer this week. I miss Ray as a field agent, but I guess this has a lot of comic potential.\\nParks and Recreation – The bit about Tom bowling like a grandma (and Ron begging him to have some decency as a man) was amazing. April being nice is unusual, but she\\'s been softening up a lot anyway. Still one of the greatest shows out there.\\nScrubs – Just put it on for a few minutes to pass some time. Always a good show.\\nSherlock – The middle episode about the Chinese smugglers is kind of boring, but the Moriarty episode is fantastic. I love how crazy Jim Moriarty is. So great.\\nJohn Oliver\\'s New York Stand Up Show – Popped this on during dinner for something to laugh to. Pretty good stuff.\\nThe Gregory Brothers – You know they put up a new Auto-Tune (Songify?) the News segment, so that got me listening to all of them again. I even dipped into their non-ATtN music because I love Sarah Gregory\\'s voice.\\nThe Girl With the Dragon Tattoo – Slow and steady. Bloomqvist sure gets around with the ladies, doesn\\'t he?\\nThe Old Republic – The guild\\'s got Eternity Vault Normal on farm status so now it\\'s time to start working on Karagga\\'s Palace.\\nGhost Trick – Making a lot of progress in this game. The mystery continues to deepen as my Spanish continues to improve. I love playing games in Spanish!\\nEarthbound (Mother 2) – Started up a new save file to play in between bosses in a raid. Fun times. Still very early in the game (haven\\'t explored the meteor yet)\\nRayman: Origins – Min and I beat the game and started going for the prestige levels. Holy god the last one, Land of the Livid Dead, is about as punishing as the game can get. Platforming gets frustrating, but it\\'s also got a super satisfying feel once you conquer it.\\nCave Story + – Thought I\\'d boot up something different while Min was napping. This game is pretty fun and pretty solid, but deciding I should play it on hard mode may have been a mistake. I\\'m stuck on Monster X because he\\'s a beast. Every one of his purple projectiles kills me in one hit, so I\\'ve got to be perfect. On the good side of the spectrum, the machine gun mechanics are amazing. Love that gun and the ability to float with it.\\nBookmark This, Embedded Reporter, Feedback, Filmmakers Bleed, Game Overview, Idiot Box\\narcher, carla gugino, cave story +, children hospital, earthbound, evangelion 2.22, george clooney, ghost trick, glee, gregory brothers, haywire, john oliver, john oliver\\'s new york stand up show, justified, megan mullally, mother 2, neon genesis evangelion, netflix, nick offerman, parks and recreation, rayman: origins, sarah gregory, scrubs, shailene woodley, sherlock, star wars: the old republic, starz, tangled, the descendants, up all night\\nMay: You\\'ve Been Cheated [Fukubukuro 2010]\\nIn their last show as a band, the Sex Pistols played one song and left the stage. Before leaving the stage, Johnny Rotten quipped, \"Ever get the feeling you\\'ve been cheated?\"\\nThe thing is, I don\\'t feel this way for the reasons everyone else might think I might. I suppose we\\'ll go after the biggest point of contention first.\\n\"Final Fantasy XIII is The Worst Final Fantasy Ever (TM) because all the dungeons are straight lines and there are no towns.\" Guess what. The non-linearity of those Final Fantasy games you all hold so dear is an illusion. Final Fantasy XIII draws so much ire because it has the gall to tell you what you already know.\\nI mean, really, you might be able to wander around the world man, but that doesn\\'t mean you get to pick what you do. The plot only advances when you go to specific places in a particular sequence (also known as a linear progression) and locations on the map are artificially locked from transit by story gates.\\nIn fact, non-linearity is a joke across almost every video game. The main fun of any GTA game may not stem from following the story, but when you do decide to start on it, you will never be able to sequence break or do anything but follow it linearly to its conclusion. You might be able to pick which order you complete mission paths, but, with the exception of GTA IV, every event has a pre-determined outcome. If that\\'s not linearity, I don\\'t know what is.\\nI applaud a game that doesn\\'t try to conceal its story behind a veneer of faux choice. Final Fantasy games have only ever allowed choices once: The World of Ruin in FF VI. There are countless story details and sidequests to experience, but once you get Setzer, Edgar, and Sabin, you don\\'t have to see any of them. You\\'re free to grind and face Kefka at any point.\\nBonus points really should be awarded to FF XIII for having the guts to let its story carry the momentum, but they are immediately lost on their failed attempt to make anything remotely interesting happen.\\nForemost in my annoyance with the game is Hope\\'s subplot. In the first hour or so of gameplay, Snow, a big, earnest, stupid guy in the tradition of anime big, earnest, stupid guys, manages to get most of his ragtag squad killed, including Hope\\'s mother, standing up against the world\\'s government. Naturally, this infuriates Hope, who now desires revenge.\\nHypothetical: A man seems directly responsible for the death of your mother. Do you:\\n1. Stutter and stammer every time you see him\\n2. Stew silently while enjoying revenge fantasies every time you see him\\n3. Figure out some way to confront him (in rage or otherwise) the first chance you get.\\nMaybe I\\'m being presumptuous here, but unless you\\'ve got some sort of emotional disorder, option three seems like the healthiest and most logical choice. Hope is all about the first two options because he is a gigantic pain in the ass.\\nI don\\'t think this is the result of some kind of cultural difference. I mean, hey, I\\'m not the most emotionally open person. I don\\'t really go around sharing my feelings with everyone I know, but I\\'m pretty sure that if a man were responsible for killing my mom, he\\'d know about it ASAP. It\\'s got to be a contrivance (and an annoying one). Why are characters in media so unable to just open their mouths and talk? If writers think this is an effective way to build narrative tension, then I\\'ve got news for them. As a rule, if your characters are forced to behave like they\\'ve never interacted with another human being for your plot devices to work, said devices are cripplingly contrived.\\nHonestly, it\\'s just lazy writing and it removes me from the narrative. Maybe Hope has a Deep Dark Secret that makes him act so stupidly, but we never learn about it. The game goes out of its way to say that Hope has father issues to hand-wave away his social idiocy, but when we meet Papa Hope, we\\'re confronted with a loving father who seems to care very deeply about his son. Did I miss something somewhere? Someone seems to have dropped the ball.\\nYou know what, I think I know why this happened. Somewhere along the way the story gurus at Square Enix decided that many young men, their prime and target demographic, seem to have issues with their domineering fathers. Some of them wrote this detail on his character sheet. Somewhere else the scenario writers were coming up with how half of the player characters would unite and escape. They decided they\\'d meet at Hope\\'s mansion and Hope\\'s awesome dad would help them out. When you\\'ve got a game this massive and important, you\\'d think that these two teams would discuss these idiosyncrasies, right? How does such a glaring contradiction make it into the final build?\\nOne of my other big \"WTF?\" moments comes at the end of a sequence at an amusement park. Sazh struggles with whether or not to kill the traveling companion who has betrayed him. Pretty soon after that starts, the physical manifestation of his emotional conflict attacks him. For most characters, fighting their eidolons, as they are called, brings them emotional peace allowing them to understand their path. In this case in results in Sazh deciding to commit suicide. What. The. Fuck.\\nRepeating this same emotional pattern six times (one for each main character!) seems like it would get old fast. It does. Suicide does not freshen the experience. It makes no sense. We all know he\\'s not really dead because we just unlocked his summon!\\nIt\\'s a shame to see so many missteps in such a promising premise. Roll with me here. In the world of FF XIII there are two primary sentient beings: Humans and Fal\\'Cie (ignore the stupid name of the second species (typical Squeenix pretentious nonsense)). The FC, as I will now call them, are magical creatures specializing in producing food, power, or other more advanced functions. Unfortunately, the FC are split into two warring factions, Cocoon and Pulse. FC also have the terrifying ability to brand humans, saddling them with cryptic quests. Failing to complete these quests turns the human into a mindless monster cursed to wander the earth slowly solidifying until he finally petrifies and can no longer move. If they magage to succeed in their quest, they are transformed into crystals for eternity. Those in \"crystal sleep\" are not dead, but they are also not alive.\\nIt\\'s the perfect deconstruction of video game protagonists. Each character has a singular purpose. Failing will result in a fate worse than death and succeeding will result in the end of the narrative, dooming the characters to non-existence. The much maligned linear nature of the game represents their inability to turn away, especially when you learn that the antagonists have been helping you the whole time. The big bad wants the characters to kill him. For once the game realizes that its point is to be defeated by the player.\\nIf Squeenix hadn\\'t gone and relied on a deus ex machina ending like they had, the world would have ended with mankind and the FC extinct. It would have been brilliant.\\nHere\\'s another idea for the writers out there. If we have no idea (and no hint) a character can do something until you dramatically reveal it in the penultimate cutscene, it will feel cheap when you make the ending rely on that skill. Not to mention, of course, that the physics of arresting the momentum of a giant biome falling thousands of feet through the atmosphere would probably result in the deaths of nearly every inhabitant.\\nThis is all stacked upon the naive and bullheaded solution that our heroes come up with to counter the manipulative FC. Get this, their plan is to just keep going along the path hoping that something will save them from dooming themselves (ok, so it does, but that\\'s because of narrative bullshit). It makes my brain hurt in ways I cannot fathom. It\\'s idiotic.\\nNow we\\'re going to take a moment for a quick aside into my personal life that will invariably lead back into the game.\\nI don\\'t know what university was like for non-math-type majors, but for my ECE degree I was forced to read and watch tons of mathematical proofs. Invariably (math pun! (so lonely)) we\\'d reach a point where the professor would skip to the end of the proof and tell us students \"I\\'ll leave the rest of this proof as an academic exercise for you students\". When you\\'re the professor, you don\\'t have to waste your time doing the grunt work.\\nThat was quick, back to the game:\\nWhy are we forced to load the battle engine against enemies who are drastically weaker than the player\\'s party? What\\'s the point of that? The only time I\\'ve ever seen this problem intelligently avoided was when I played Earthbound. Once Ness is sufficiently more powerful than a given enemy, enemy encounters result in an instant KO. The battle engine isn\\'t loaded and XP and items are awarded as appropriate. The game surrenders a battle whose result is a foregone conclusion, saving you from wasting unnecessary time.\\nShouldn\\'t more games do this? Why do I have to load up the battle engine to complete a fight that lasts five to ten seconds? What does the game gain by forcing me to sit through this? It\\'s not like we\\'re strategically managing resources in this game (unlike, say, a Persona or Shin Megami Tensei game); the entire party is fully healed after every battle. So why not? Does Squeenix think that if we don\\'t sit through a five second battle while pushing \\'X\\' once we will be livid that the game is playing itself?\\nOf course, this makes even less sense when you think about the way the battle system works in FF XIII. There are two ways that you can fight: Auto-Attack and Abilities. If you select Auto, the AI will select a series of commands faster than you could based on the knowledge it has about the enemy you are facing. All you have to do is set the roles (Tank, DPS, Healer, Buffer/Debuffer) and the game will pick the most prudent course of action. It\\'s also streamlined to such a degree that if you die, all you\\'ve got to do is pick retry and you are respawned just outside the battle you just lost. It\\'s that easy.\\nFinal Fantasy XIII wants so badly to be a well-oiled machine, like a Disney ride pushing you toward the goal, that these time sinks become way more pronounced. Fighting with auto, like almost every player does, with your only responsibility being character roles can still be strategic and fun, but at a certain point I start to think, \"Why do I have to select auto every single round? Why can\\'t I just toggle it off when I need to change my tactics?\" It\\'s like the game asks me every turn if I still want it to play the game for me.\\nDon\\'t get me wrong here, XIII is not a bad game…or maybe it is. Perhaps FF XIII is a better experience than it is a game. You\\'ve got stunning cutscenes and top-notch voice acting combined with a game that mostly plays itself along a straight line. Almost sounds like a movie to me.\\nearthbound, final fantasy, final fantasy vi, final fantasy xiii, grand theft auto, grand theft auto iv, persona 3, shin megami tensei, square enix\\nMother 3 Review [Big N]\\nWallpaper courtesy Pet-Shop on DeviantArt\\nRuminations on video games as an art form – this could very well become a Mother 3 review. There will be spoilers here. Seriously, don\\'t read it if you want to play Mother 3 and not have the plot spoiled.\\nThere\\'s a trite comparison that floats around the internet almost every month that always gets my eyes rolling. Inevitably, someone will call such-and-such the Citizen Kane of video games or ask what the Citizen Kane is or claim that the medium is immature because we\\'ve yet to hit our Citizen Kane. It\\'s exhausting and, quite frankly, futile and stupid. To begin with, Citizen Kane opened with good reviews and was generally well-received, but it didn\\'t start to gain notoriety for ten years. It didn\\'t even make #1 on a top movies list until twenty years had passed. When the Citizen Kane of gaming hits (god I hate that phrase), we probably won\\'t know it for quite some time. The more important point is that movies and games are apples and oranges.\\nThe day that we stop worrying about whether books or movies are better than games at expressing a particular artist\\'s point of view is probably the day that we\\'ll realize that we\\'ve already got fine examples of games that are reflections of authorial control already. Brütal Legend was not a great game, but Tim Schafer\\'s hands are clearly evident all over it. Anyone who\\'s ever played one of Fumito Ueda\\'s games knows precisely how a game can effectively be used to bring out your emotions through simple mechanics. Goichi Suda (AKA Suda 51) has been making games that show clear, artistic direction through his use of bizarre symbols and incomprehensible plots for years. My point is, we\\'ve been here for a while.\\nYou may have heard of Shigesato Itoi, but chances are, you have no clue that he\\'s one of the most famous and respected men in Japan to such a degree that his dog was probably the most recognizable animal in the entire country for a few years. In America, we know him as a video game designer, specifically the man behind Earthbound, but not much else. Interestingly enough, Itoi is actually more famous for being an essayist, interviewer, and slogan generator than his work for Nintendo. His association with Hayao Miyazaki is well known enough that he\\'s famous for the Kiki\\'s Delivery Service slogan (\"Ochikondari mo shita kedo, watashi wa genki desu\" — \"I was a little depressed for a bit; I\\'m okay now\") and he even voiced Mei\\'s father in My Neighbor Totoro (a role that went to Phil Hartman (rest in peace) when the movie was dubbed in English).\\nIn his younger days, Itoi found himself sick and unable to do much but play Nintendo as he recovered. It was in this state that he discovered Dragon Quest, which set the wheels turning in his head. This experience was the impetus behind the Mother series and led to Itoi\\'s long, fruitful relationship with Nintendo. In case you were wondering (protip: you probably weren\\'t), Shigesato Itoi is the guy who came up with the name for the Game Boy. True fact.\\nIt\\'s not surprising to me that most of the names I\\'ve mentioned were not always video game designers. The most bizarre of the bunch, Suda, was an undertaker before he tried his luck in the video game industry while Ueda was an artist and the aforementioned Itoi was a…well there\\'s no easy word to describe someone like Itoi. He was (and is) a cultural personality.\\n\"If you immerse yourself too single-mindedly in your chosen art form, whether it\\'s video games, movies, comics or whatever,\" he continues, \"your work can easily become just a reflection of what others are doing in that field, rather than breaking new ground.\"\\n–Jordan Mechner\\nNow, Schafer is, himself, a product of the industry, having held no other jobs, but he\\'s the exception, a true creative mind that is not crippled by his feedback loop of doom. Monkey Island, Day of the Tentacle, Psychonauts, and Brütal Legend could not be more different from each other, but just think of how rare this is. For every Schafer or Ken Levine out there trying to bring new influences into the industry, there are tons of Star Wars- and Lord of the Rings-inspired games produced each year retreading on the same, tired stories game in and game out. How many World War II games do we really need?\\nIn 1989 Shigesato Itoi looked at the video game industry and said \"How many sword and sorcery RPGs do we really need?\" 2009 just passed us by and I\\'d say we\\'re still mostly mired in these medieval locales in 95% of all RPGs. Mother, Itoi\\'s freshman attempt at a video game, was set in \"modern day\" America. Earthbound (Mother 2) wasn\\'t exactly breaking with Itoi\\'s norm by being set in America yet again (in 1994), but it\\'s still a light among the sameness that pervaded the industry. Mother 3 is ambiguous about its timeline, but it feels like a scaled back modern day. In any case, like in the other games of the series, the weapons aren\\'t swords and bows, but sticks, yo-yos, and baseball bats. It\\'s really only a cosmetic and tonal shift, but it makes all the difference.\\nThat\\'s exactly what makes Shigesato Itoi so great as a game designer. Perhaps it\\'s his outside status or maybe it\\'s just his brilliance, but Itoi understands video games to a scary degree for a man who only undertook them on a whim. I applaud him most for understanding that a game is an interactive piece of art and reflecting that with his systems. To with, every Mother game revolves around music. The first game had the character searching for the Eight Melodies while the second repeated that idea with Eight Sanctuaries (each with a musical theme associated with it). Earthbound\\'s instruction manual (in Japanese) contained a little song that Itoi wrote for the player to sing as the main melody played on the overworld. Every line of text in the Mother series is written in kana (katakana or hiragana), so that the person has to vocalize Itoi\\'s often lyrical writing style. Mother 3\\'s focus on musical themes and leifmotifs (from the Masked Man to the Magypsies) is also emphasized through every character\\'s attacks in the battle system.\\nFrom Lucas to Salsa the Monkey, every character has a musical instrument associated with his attacks. So does every enemy. Each enemy also has a musical theme that plays in the background. Once you attack, you can continue to press the \\'A\\' button to extend your combo to 16 hits if you can keep time with the (sometimes fiendishly difficult) beat. Just like that, something Itoi has always wanted the player to do (become musically involved with his world) becomes integrated into the activity the player does most in the game, battling.\\nItoi also loves to toy with player perception to a hilarious degree. In an early sequence in the first chapter of the game, Flint becomes covered with soot after saving a friend\\'s kid from a fire. Why? Because that\\'s what would happen if you were running around in a fire. As he makes his way back out of the woods, you can bet that every person you talk to will question why you are covered from head to toe in black soot. Even better, if you hop into a hot spring to recover, the soot will wash off of your character from the neck down, since the Mother 3 hot spring animation always leaves the head exposed. It\\'s not until much later when it starts to rain that the soot washes off Flint\\'s face, this time to emphasize that we\\'re not joking around anymore, Flint\\'s family was still missing after the fire and they were almost certainly in danger.\\nAn even more brilliant sequence comes much later in the game when the player is washed upon a tropical island with 1 HP and no equipment. The only way to progress through the jungle without dying is to eat one of the psychotropic mushrooms growing on the island. A bizarre sequence of events follows as you make your way to the next Magypsy with your perceptions completely torn asunder. Replicas of your family and friends attack you, which isn\\'t that unique for an RPG, but the way the narrative is presented and the visuals are warped, it becomes seriously unsettling. The one moment of calm comes when you arrive at another hot spring and recover, only to continue back into the horrors of the jungle.\\nOnce you get to the Magypsy\\'s house, you\\'re constantly bombarded with insults about how bad you smell. It makes no sense though, because the player has done nothing different that would cause such a foul smell. Still, when your perception is returned to normal, there is a visible stench rising from Lucas and his compatriots. A quick dip in the bath follows and you\\'re no longer \"smelly\", but, as a curious player, I wondered what had happened in the first place. Instead of continuing forward, I dove right back into the jungle to get to the bottom of it. halfway through, I was feeling a bit fatigued, so I popped on over to the hot springs and it all made sense. In my hallucinogenic state, I was unable to recognize that the pond I dove into for recovery was a festering, toxic-looking garbage dump of a pond. Off to the side, where no conceivable player would ever go, was a door into the real hot spring.\\nI couldn\\'t believe that some players would never find out the mystery behind why they were so smelly. Returning to that hot spring is hardly mandatory. Maybe that\\'s why it felt so amazing to see these little narrative games played with my perception of what was going on in the Mother 3 world at the time. It\\'s also interesting to look at from a player trust perspective, because when I saw that disgusting pond, rendered in all its GBA, low-fi glory, I felt nauseous and I know it was partly due to a feeling of betrayal. I have a feeling that this was exactly how Itoi wanted me to feel at that point.\\nShigesato Itoi admits that the original draft for Mother 3 was way darker than it already is. It was written shortly after his divorce was finalized, which I think has a lot to do with the emotional betrayals of even the finalized version of this game. However this game was very nearly vaporware that was never released. Its development started for the SNES in 1994, but was quickly shifted to the N64 and the ill-fated 64DD not long after. Anyone familiar with the 64DD peripheral knows that this was going to prove troublesome for Itoi and his team. The game was even canceled at one point, but it was eventually decided to put it on the Game boy Advance and announced around the re-release of Mother 1 + 2, no doubt to help drum up sales.\\nNo one but the team knows just how dark the original narrative was, but Itoi claims that the story that eventually made it to print was the result of him finally becoming a good person. It boggles the mind to realize that it could have been any more dramatic, especially for a game that looks as friendly and cute as this one. In fact, this is the reason why Nintendo of America claims it will not localize the game. They claim the narrative is too mature and depressing for the way it looks and, really, the tone and the subject matter are alternatively irrelevant and deathly serious, so I kind of get what they mean. At one point you have a guy telling Flint that he\\'s got good news and bad news. The good news is something irrelevant and stupid while the bad news is that Flint\\'s wife, Hinawa, is dead. What follows is a scene that is so emotionally gripping that my little brother was affected even without hearing the music and sound associated with the scene. Flint completely flips out and starts beating on the guy who gave him bad news and even starts lashing out at the townspeople who are trying to calm him down. He is knocked out by a friend and put in a jail cell that has never before been used in the town\\'s existence.\\nIt\\'s this weird juxtaposition of the inane and the deathly serious that creates the dissonant feelings I mentioned before with the hot tub scene and makes the player feel uneasy about what\\'s going on. When Hinawa\\'s father, Alec, is trying to tell stupid jokes to help Flint not be so tense about the certain danger his son is in. I wanted to tell him to shut up and let him focus, but I could also see that Flint was obsessing to a dangerous degree and that Alec was right in trying to calm him down. You also have the lighthearted love story of Salsa and Samba being ruined by the brutal and sadistic torturer Yokuba (Fassad in the fan-translation). It\\'s like Itoi is trying to say that the world is a screwed up place, but you can\\'t let it get you down.\\nI\\'ll tell you right here, I\\'m a huge sucker for any story about brothers. Later on in the game, it becomes fairly obvious that Mother 3 starts to center around the struggle of twin brothers Lucas and Clause as they attempt to collect more plot coupons than the other. The game series is called Mother for a reason and this one in particular focuses on the differences between each of Hinawa\\'s boys and how they came to deal with her untimely death. While Lucas comes out of his shell and becomes a healthier, more assertive and confident boy despite his absentee father, Clause foolishly rushes out for vengeance and finds himself enslaved by the Pig Army in its quest to end the world. The climactic final battle reunites the family once again, but the reunion is bittersweet. Clause has almost killed Flint and Lucas must face him alone to the death, even though he\\'s yet to realize that the Masked Man is his brother. Once the mask is knocked off and Lucas is staring into his own face (they are twins after all), the battle becomes a masterpiece. Selecting attack will cause Lucas to intentionally pull his punches or miss his attacks completely. Sometimes he\\'ll even refuse to comply. Clause, having lost most of his humanity, will continue to attack until Hinawa begins pleading for him to stop. Eventually, Clause comes to his senses and realizes that Lucas is his brother and that he is no longer anything close to himself. At that point, Clause commits suicide in a peculiar way. It becomes apparent that the Courage Badge that Flint gave to Lucas (via a Mr. Saturn in another example of absentee parenting) is actually a Franklin Badge, an item that repels lightning in the Mother world.\\nThe heartbreaking thing about this whole sequence is that there\\'s nothing the player can do once Clause decides that he must kill himself to save the world. Lucas may not be physically (or psychically) killing his brother, but there\\'s nothing he can do but watch his brother kill himself using an item that he is holding. When it\\'s all over and Clause is dying in Lucas\\' arms with Flint nearby and Hinawa\\'s ghost above them, the reunion is finally completed and the family is happy for a brief second before both Clause and Hinawa depart the world leaving Lucas to pull the last plot coupon. The world literally ends and it all fades to black. Everyone (who was alive before) is still alive in the finale, but the world is darkness and it\\'s not made clear what the true outcome of the whole battle was. We do know that the world is safe and everyone makes it, but not much else beyond that, it\\'s left to the player to decide, I guess.\\nIf you want to really see a strangely tragic, chilling ending for a character, consider the fate of Porky, the antagonist in the game. The conflict in this game is motivated by his desire to see the world end. Porky\\'s mind was so warped by Giygas in Earthbound that he has remained in a permanent immature, childlike state even though he is now hundreds of years old. His influence corrupts and nearly destroys everything about the idyllic and peaceful Tazmily village and he is the one responsible for sapping Clause of all of his humanity. In his final encounter with Lucas, when it becomes apparent that he will not win the battle, he encases himself in the Absolutely Safe Machine, a capsule that renders him absolutely safe from all attacks both interior and exterior. Because it was just a prototype, there was no way to escape it, meaning that the ageless Porky can never die, but he can never leave the capsule nor can he communicate with anyone on the outside. For someone like Porky, an agent of entropy like the Joker in The Dark Knight, this is truly an ending worse than death. When all is dead and gone, when the universe dies of heat death, when existence is nothingness, Porky will still exist, alone in that capsule. It gives me chills just to think about it.\\nThere\\'s so much about this game that just doesn\\'t quite add up and leaves the player feeling strange about the relationships they are seeing. Duster, the limping thief, is very clearly verbally and probably physically abused by his father, Wess, yet they seem to be a team and there does seem to be some love there. It\\'s unsettling on all levels because Itoi wants to take the player from comfortable and happy to uneasy and sad throughout the whole game.\\nGames like this, they make me appreciate things, like my family and my life, and think about things, like the nature of society and happiness. I\\'m being simplistic here, but my point is this, what is art? Wikipedia calls it, \"…the process or product of deliberately arranging elements in a way that appeals to the senses or emotions.\"\\nSo I say yet again, why are we questioning whether or not video games are art? Wake up and smell the sunflowers.\\nBig N\\nbig n, brütal legend, citizen kane, dragon quest, earthbound, fumito ueda, game boy, gba, goichi suda, hayao miyazaki, ichiro suzuki, ken levine, kiki\\'s delivery service, lord of the rings, maniac mansion: day of the tentacle, mother, mother 1 + 2, mother 3, my neighbor totoro, n64, phil hartman, psychonauts, shigesato itoi, snes, star wars, the dark knight, the secret of monkey island, tim rogers, tim schafer, wikipedia\\nWhat Next? Call to Arms [GO]\\nJul 10th, 2009 by Dan\\nHey loyal readers,\\nI need your help in deciding what game to play next. I haven\\'t quite gotten my polling software down, so here\\'s a nifty embedded poll instead.\\nWhich game should I play next?(survey software)\\nBasically, I want to continue to write impressions about games that I\\'m playing, but I don\\'t know which one to move on to next. A little about each of the choices:\\nEarthbound (Mother 2)\\nA fantastic, Dragon Quest-inspired RPG series by Shigesato Itoi, Earthbound is fantastic, quirky, and interesting. I played this back when I was in middle school, but I think it deserves reexamining. Ideally I would be hooking up my SNES, which I still have, to get this to work, so that would be an adventure in and of itself.\\nSuikoden Tierkreis\\nI\\'ve never played any of Konami\\'s Suikoden RPG series, but this DS gaiden-type story is said to have a pretty neat narrative.\\nUniversally hailed by nearly every human being who has played it, this game is held in such high regard that it was featured in Reign Over Me because its themes of loss and regret actually coincided with those of the movie. I can only go on without playing a game by Ueda for so much longer.\\nMother 3\\nHeld in super-high regard by the likes of Tim Rogers, among many others, the third of the Mother series is chock full of the same light irreverence of Mother 2, but coupled with a somber, deep, dark, heavy story that is sure to tug at the heartstrings.\\nChrono Trigger DS\\nThe DS remake of my favorite 16-bit game, you can\\'t really go wrong with CT. Developed by a dream team collaboration between Square and Enix before they were Square Enix (Squeenix!), Chrono Trigger was the swan song of the 16-bit JRPG.\\nFinal Fantasy IV DS\\nThe Final Fantasy whose release immediately preceded (in the US) my favorite in the series, FFIV has eluded completion from me on multiple rentals. A fine game that I just haven\\'t had the time to ever finish.\\nThere\\'s also the obvious choice that you don\\'t like this feature, which I won\\'t take personally. If no one likes it, why do it, right?\\nThis poll will remain open until 0000 14 July whereupon I will either narrow it down further or, if one wins outright, simply play that game next.\\nYou can get some of these games at my Amazon aStore!\\nchrono trigger ds, earthbound, final fantasy iv, fumito ueda, konami, mother 2, mother 3, reign over me, shadow of the colossus, shigesato itoi, snes, square enix, suikoden tierkreis, tim rogers\\nGame Overview: 16-Bit Runner-Ups Part 2: RPG Edition\\nJun 10th, 2008 by Dan\\nBack on Saturday we took a look at two excellent games that didn\\'t quite make the cut. Today, we examine another three, all of them the superb 16-bit RPGs.\\nYou know the drill by now about the \"Table of Honor\" and whatnot, so let\\'s just get down to the clue and game:\\nThis first game I want to examine jumps out at you from the world of platforming. You might doubt his ability to manage, but once he jumps, you\\'re filled with utmost confidence. Yeah, it\\'s Mario\\'s RPG debut, Super Mario RPG: Legend of the Seven Stars.\\nRunner-up: Super Mario RPG: Legend of the Seven Stars\\nFor some crazy reason, nobody in the Mushroom Kingdom will believe that you are Mario. You\\'re probably the most famous savior of the land, but it\\'s not your dashing mustache or your red overalls that will prove your identity, it\\'s your trademark jump. This running gag is probably my absolute favorite part about SMRPG. No matter what part of the world you\\'re in, someone will inevitably ask if you are really the plumber. The dialog will pause, you will be unable to do anything else until you finally push the jump button and prove your identity.\\nThe rest of the game is full of comparable humor and character that exude from every pore. Dialog makes sense and is pretty slick, the story is actually not that bad for what you\\'d expect it to be, and, most importantly, that trademark tight gameplay that Squaresoft has always been known for makes for a great battle system and actually meshes pretty well with Mario\\'s more typical platforming roots. Battle returned to the more traditional turn-based type affair, but now your special attacks were powered up by timed button presses or other similar tests of button-pressing acumen. This system was so slick and exciting that every subsequent Mario RPG (sadly none of them Squaresoft created) and even the new Penny Arcade Adventures has got timed button presses for defense and interesting special attacks.\\nI\\'m sure that many were skeptical about SMRPG\\'s ability to be a valid, entertaining game when it was announced. Just adding a big-name RPG developer to a franchise character does not make everyone believe it will rock (just look at Sonic Chronicles, no one thinks it will succeed). That SMRPG is able to succeed on all fronts and still be one of the better RPGs on the console is a testament to the talent of old-school Squaresoft. What a great game…\\nI just can\\'t resist throwing in yet another video game commercial for this game. This one\\'s quite bizarre…\\nThis next game was published in America by a company whose motto is \"Serious Fun,\" but it\\'s not the farming sim/RPG that you might be thinking of. The main character fights very sinister beings in order to save the world in this one. This one\\'s a bit tougher, but it\\'s Lufia II: Rise of the Sinistrals.\\nRunner-up Lufia II: Rise of the Sinistrals\\nThis one might fall a bit outside of most of your game radars. It\\'s not A-list like Final Fantasy or Dragon Quest, not even B-list like Breath of Fire or the Secret of series (you can bitch and moan all you want about this, but you\\'ll never convince me that the Seiken Densetsu series is anything more than B-list). Lufia is a pretty firm C-list series, with regards to RPG popularity. There were two SNES games games and one gbc game in the series canon, with another gbc gaiden. That\\'s it, that\\'s the entire series. To be fair, it was mostly concluded with the GBC game, but I feel that they did leave it slightly open-ended.\\nGameplay isn\\'t that special, it\\'s your typical RPG with turn-based battles. There was one notable battle mechanic in the capsule monsters that you could capture and have fight on your team. These monsters were computer controlled and could be leveled up and evolved by feeding them weapons and armor. The interesting thing is that this idea came about a full year before Pokémon was released. Pretty cool if you ask me.\\nWhat does make this game stand out and what earns it a spot on this list was its story. As a prequel in a time before prequels were cool (this was way back in Japan in 1995), Lufia II picked up the story before the events of Lufia & the Fortress of Doom (a game I never played). You were Maxim and, like most RPGs, you are told by a mysterious figure (a woman named Iris in this case) that you are destined to save the world. You head out to solve a monster problem for your village with your childhood friend Tia (you reluctantly bring her along) and from there you bounce from town to town solving problems and adding the brutally strong Guy to your party. Iris saves your life after you learn about the Sinistrals and you go on to add another party member, the female soldier Selan, before you finally learn the identity of the first Sinistral, Gades, after he brutally destroys an entire town.\\nExcited yet? Your party certainly is. They set off to confront Gades and make him pay for what he\\'s done. He responds by soundly kicking your ass. In yet another video game \"oh shit, I hope I was supposed to die\" moments, you are revived by Iris who revives the party and tells everyone but Tia that they are meant to confront this evil light with Maxim. Another dude, Dekar, joins the party and Maxim, Guy, and Dekar head out to kill Gades after learning from a lieutenant of the Sinistrals, Idura, that Gades plans on sinking an entire island. This time Maxim manages to kill Gades, but he still manages to activate the machine after all. Maxim heroically gets to the machine on his own, but deactivating it mostly kills him in the process. Iris teleports in, decides to be useful, and saves Maxim.\\nIn the aftermath of this event, we are treated to a touching cutscene where Ti– no, wait, Selan (?) confesses her love for Maxim. I still remember this plot point coming straight from left field. You mean to tell me that Tia, who\\'s been hitting on you this whole game, isn\\'t gonna end up with Maxim? As a player, I didn\\'t mind, since Tia was annoying and Selan was arguably hotter (in that 16-bit way), but still, it really messed with me to see the developers not take the easy road, and I respect them for it. Tia honorably realizes she\\'s not gonna win Maxim\\'s love, tells Dekar that she loves Maxim the man, not Maxim the warrior, and sets off to find a man as good as Maxim to marry. That\\'s seriously the last you see of a character you\\'ve spent hours developing. The game sort of \"ends\" here as Maxim and Selan are married, buy a little house, and have a kid.\\nIf you couldn\\'t guess by now, I\\'m a fan of these drastic world- or game-changing events in a video game. Be it the loss of Naked Snake\\'s right eye in MGS3 and how it affects first-person view from then on or something like the World of Ruin, these huge, irreversible events never cease to amaze me (I guess, if Iabsolutely have to I\\'ll admit that Aeris\\' death is kind of cool in that way, but it never really had the same emotional impact on me as any of these other ones). Here I am, yet again thinking that I beat the game, and then Idura kidnaps your son and you\\'re forced to take up arms again. Iris comes in and claims that it was Maxim\\'s fate to die after the battle with Gades, but her actions have changed the future. As the gamer, you don\\'t yet know that these are lies. Heck, you don\\'t even know the huge twist yet at all (maybe you might if you had played the first game, but I certainly didn\\'t).\\nYou do more quest-y stuff, Dekar dies after you kill Idura, and eventually you get to the final confrontation with the Sinistrals which is, not coincidentally, precisely the way that Lufia & the Fortress of Doom opens, which means that you fight the Sinistrals and kill three of the four. While trying to escape, only Guy and the elf Artea (he joined you in the second half) make it out alive. Maxim and Selan die, but are forever remembered as the heroes who vanquished the Sinistrals. It also turns out that this whole time your \"helper\" Iris was the Sinistral Erim. Erim is unique in that so long as she lives, the Sinistrals can be continually reincarnated. Also unique about her is her ability to take on human form, which some fans speculate is a result of the Sinistral Daos testing humanity. The real twist here is that Iris/Erim is later reincarnated as one of the main characters in the first Lufia game. By the way, you\\'re probably wondering why this game is even called Lufia if there are no characters named Lufia anywhere in the game. I can see your brains connecting the dots. Lufia is Erim and she is a character who fits a similar role to Tia in the first Lufia game to one of Maxim\\'s descendants. She didn\\'t change history by allowing Maxim to continue his bloodline, for Maxim and his descendants were always meant to counter and eventually defeat the Sinistrals. Erim makes one final appearance as a party member in the third Lufia game, as she gathers up yet another of the bloodline of Maxim and a crew of strong warriors. She builds them up this final time to destroy the Sinistral menace forever. Erim had tired of life as the Sinistral of Death and wanted her life to finally end.\\nI should also mention that Lufia II had a pretty solid puzzle and monster mechanic. Monsters appeared on the field and got to move every time you moved. There were also some pretty neat and difficult puzzles for the player to solve as he made his way through the many dungeons. I distinctly remember some of these being so tough (this is good!) that I had to consult old issues of Nintendo Power to figure out how to progress.\\nThere you have it, a fairly convoluted plot and a game that\\'s ultimately average in its battle execution. Still, I can\\'t help but love Lufia II for it\\'s creative puzzles and that zany story. Prequels were still a pretty new concept to me back then when I played it and knowing what was to happen to Maxim and Selan made for some interesting, if fatalistic gameplay as I watched the drama unfold. There\\'s something cool about playing a game that fits into a pre-determined timeline. It\\'s both futile and awesome to fill in the details of a future you know will one day occur. I\\'d like to see more games try this with their storylines. Have a sage/oracle-type character tell you that completing the game will lead to your death. It could be fourth-wall or even within the game itself. Watching the main character grapple with what he knows to be the greater good at the expense of the personal good leads to good drama. They did it in FF VI with Terra, but the devs didn\\'t have what it took to let her die and not have a happy ending. That may be a good thing anyway, since I\\'m one of the few people who can be satisfied with an unhappy or unfair ending.\\nThe Japanese commercial for this game is pretty lame, so here\\'s something that a fan put together for the 11-year anniversary of the game:\\nYeah, the video\\'s not that cool, but it gives you a taste of what the game looked and played like. If you ever get a chance to play this game, I do recommend it. It\\'s well worth your time.\\nOur last game of the day had a mother of a time even getting released in America. To this day, the first and third game of this series have still never seen the light of American day. If you\\'re a fan of the Runaway Five, you also already know that I\\'m talking about EarthBound.\\nRunner-up: EarthBound\\nThe brilliance of EarthBound lies not in its genre, but more in the originality and character that it brings to an already tired formula. How many sword and sorcery-themed RPGs does the video game market really need? (Answer: Don\\'t be stupid, sword and sorcery-themed RPGs rock!) Still, it\\'s refreshing to see an RPG take place in a modern setting like the country of Eagleland (a not-so-veiled reference to the USA). It\\'s hilarious to see that your weapons consist of baseball bats, yo-yos, and bottle rockets.\\nThe story centers around Ness, a boy of tremendous psychic power who is tasked by a bee from the future named Buzz Buzz to destroy the evil force known as Giygas. Ness sets out from his hometown, Onett, and encounters and recruits Paula, Jeff, and Poo to save the planet. Along the way, they fight cultists, zombies, dogs, ninjas, bails out the Runaway Five twice, and eventually have their souls transferred into a robotic body to enable them to travel in time to fight Giygas. It\\'s strange, but in a quirky way. Even the final boss isn\\'t your typical encounter. You defeat the mighty Giygas by repeatedly praying, eventually getting the entire planet to unite and defeat Giygas in a Dragon Ball spirit bomb-type fashion.\\nEarthBound makes this list (just barely) because of the character that it exudes from every pore. Destroying the Happy-Happy cult is still one of my favorite situations in a video game mainly because of how bizarre it really is. Another plus for EarthBound is that it\\'s really hard. The game definitely doesn\\'t pull any punches with its difficulty.\\nUnfortunately for us US EarthBound fans, the series didn\\'t sell all to well when it first came out for the SNES. As a result, Nintendo decided not to release the sequel, Mother 3 (EarthBound = Mother 2), stateside citing poor sales of EarthBound. No matter how many fan campaigns Starman.net tries to put together to bring Mother 3 to North America, Nintendo continuously refuses to release. Interestingly enough, the Nintendo of America guys actually love the Starman dudes, which I think is what has allowed the Starmen to still have a Mother 3 fansub in production without a cease-and-desist order being issued.\\nMany fans speculate that EarthBound\\'s upcoming release on the Virtual Console (it was rated by the ESRB => it will be coming out) will be a barometer to test the validity of releasing Mother 3 in Eagleland. You can bet that the day this game comes out anyone, and I do literally mean anyone, who is on my Wii friends list will receive a gift of EarthBound for the SNES unless they tell me they\\'re planning on buying it already. I just want to drum up sales because I\\'d love to see Mother 3 hit our shores.\\nYet another Japanese commercial that doesn\\'t make too much sense. Enjoy!\\nWith that, we\\'re almost done with our 16-bit all-stars. Just one more entry on Thursday to finish these guys off.\\nGame Overview, Mr. Digital\\nall-stars, breath of fire, dragon quest, earthbound, final fantasy, final fantasy vi, gbc, lufia & the fortress of doom, lufia ii: rise of the sinistrals, metal gear solid 3, mother 2, mother 3, penny arcade adventures: on the rain-slick precipice of, pokemon, seiken densetsu, snes, sonic chronicles: the dark brotherhood, starmen.net, super mario rpg: legend of the seven stars<|begin_of_text|>Breaking Out – Porgy & Bess director Christoph Huber on the international future of Austrian Jazz\\nDuo 4675 (c) Eckhart Derschmidt\\nMarch 16, 2021 / jazz/improvisation, news, portraits/interviews\\nPorgy & Bess is a household name in jazz, both in Europe and around the world. But what does that mean for the \"home team\"? What role does the club play for the next generation of Austrian jazz musicians, regionally and abroad? ARIANNA FLEUR sat down with CHRISTOPH HUBER, co-founder and director of the renowned Viennese jazz club, Porgy & Bess, to talk about the past, present and, especially, the future of Austrian jazz and improvized music, and who we should all be keeping our eyes and ears open for in the months and years to come.\\nSo, it\\'s widely known that the Porgy stage has long had the privilege and honor of hosting the best players in jazz and beyond. But, it\\'s a 2-way street, isn\\'t it? Not only do you bring in international talent, but you also help launch regional musicians outwards.\\nChristoph Huber [laughs]: Yeah, I have to agree!\\nOne could even say, playing at your club is something of an entrance ticket to the jazz world beyond. In other words, you\\'d be hard pressed to find an internationally relevant Austrian jazz musician who hasn\\'t played at Porgy and, most likely, played there 1st, before venturing out beyond the Austrian borders. What do you think about this statement?\\nChristoph Huber: Well, who wrote that? I love it. [laughs] But seriously, yes, it\\'s true. You know, the point was, from the beginning, when we – Mathias Rüegg, Renald Deppe, Gabriele Mazic and myself – started Porgy in 1993, our mission was three-fold: 1st and foremost, the Austrian scene, 2nd the European one and, 3rd, the big names from the American scene, which is the homeland of jazz.\\n(c) Wolfgang Gonaus\\new AIM TO BE SOMETHING OF A MEETING PLACE FOR MUSICIANS, AS WELL AS A MEETING PLACE FOR PROJECTS THAT COULD DEVELOP TOGETHER\\nIs that still the mission today?\\nChristoph Huber: Yes, this \"triad\" concept hasn\\'t changed. Of course there have been developments and focuses on other international regions, but basically it\\'s the same. What we aim for is, on one side, to be something of a meeting place for musicians, but on the other, a meeting place for projects that could develop together. For example, inviting international musicians to collaborate with Austrian musicians, as we do in our Portrait Series. So we not only offer the audience to check out the American cats or internationally interesting acts, but also to interact with them. Not every day, of course, but in certain projects.\\nIt sounds like the club helps the Austrian scene to expand their international connections.\\nChristoph Huber: In fact, that\\'s something we feel to be our task. I mean, the Portraits are still happening. We invite international artists, but, meanwhile, we also invite the next generation of Austrian musicians like pianist Georg Vogel or bassist Manu Mayr.\\nSo international collaborations have always been one of the pillars of Porgy, but due to the pandemic, things shifted dramatically and from one day to the next, the club\\'s content suddenly became almost exclusively regional. Do you think that this has long-term implications for you or the music world at large, or was it just an exceptional situation?\\nChristoph Huber: It\\'s an exceptional situation. But, the local scene was always a huge part of the program. And, you know, we have the Strenge Kammer, for example, which is closed now due to the pandemic. So, in our streaming program, we featured a lot of bands that had previously played at the Strenge Kammer. Of course, when everything reopens, some of the bands that played on the main stage may have to go back to the Strenge Kammer. But, you know, the whole program won\\'t really change that much. It\\'s just, the competition will be tougher.\\nSo, how do you actually make your program? How do you choose your artists? And where do you get your information, especially when it comes to upcoming artists who aren\\'t that big yet?\\nBeate Wiesinger & Lisa Hofmaninger (c) Eckhart Derschmidt\\nChristoph Huber: I don\\'t really have a system. It just happens. But, mostly, I find out about new acts by word of mouth or recommendation. For example, when Christoph Cech, who was the director of the jazz department of the Bruckner Conservatory, says a name and that they are a big talent, then I know I don\\'t have to second guess it. Of course, one also picks up a lot through the longstanding network of festival and club owners. This makes programming quite easy. And a lot of things happen through Renald Deppe\\'s very careful programming of the Strenge Kammer.\\nSo who are the up and coming Austrian musicians which definitely will not be bumped from the main stage, and beyond that are, in your opinion, ready to hit the international stage, or hit it even harder if they already have?\\nChristoph Huber: To be honest, there are quite a lot. Even if you just think about instruments, like bass players for example. You will find at least 10 super high-level bass players in Austria, like Judith Ferstl, for example, with really spectacular musicianship. And that\\'s changed a lot. When I started Porgy in the 90\\'s, the scene was quite small. Since then, a lot has developed, like the level of education. You now have fantastic teachers, like (Wolfgang) Puschnig, for example, who really come out of the international jazz scene. So there are a lot of very talented and well-educated students, like Georg Vogel, for example. When he plays this 31-tone Claviton, you go crazy. [laughs] You think, wow what\\'s that? Or this piano player David Six, or the Wiesinger sisters (Astrid, sax & Beate, bass), the band, Purple is the Color, or the drummer Judith Schwarz. They\\'re all on their way.\\nTHE IDEA WAS TO SUPPORT THE YOUNG, ADVANCED AUSTRIAN SCENE\\nYou mentioned Georg Vogel, which I half expected, because he\\'s on a lot of people\\'s minds in the jazz and improvisation scene lately. But you also said how complex his work is. Where could he fit on the international stage?\\nChristoph Huber: Let\\'s compare him with a historical figure like Cecil Taylor. He was also kind of a nerd, in a good way. It took him a while to succeed with this kind of art, because it\\'s so complex. So of course that\\'s a challenge. On the other side, when Georg is doing his piano trio, it\\'s also quite complex, but it\\'s easier to listen to.\\nCan you tell me what you know and like about Purple is the Color?\\nChristoph Huber: Well, they started at the Strenge Kammer and played there a couple of times, until we realized, wow, that\\'s a really cool and interesting collective. They are a quartet, and all studied together, I believe. And when you see a band working together for some time and they always get better and better, and they develop and really stick together, then you can see their potential. And once you recognize that, then you will give them the main stage, of course. But it needs time to develop. It\\'s not good to give them the main stage right away.\\nSo, for that reason the Strenge Kammer really makes sense.\\nChristoph Huber: Totally. That was the point of it. We started the Strenge Kammer about 10 years ago. And the idea was to support the young, advanced Austrian scene, for who the main stage was too big. We have a certain pressure there. We need to fill the seats. That\\'s just how it is. So the Strenge Kammer makes sense, and of course it is like the first step to Porgy. When you get a gig at the Strenge Kammer, it\\'s the first chance you have to attract my attention and others\\'. Normally that works pretty well, and afterwards you might get a gig at the main stage. And if that happens, it can really help musicians get gigs abroad. The truth is, other international clubs look to our program to help make decisions about their own.\\nDo you have any advice for musicians who are early in their career? When you spoke about Purple is the Color it sounded like, in part, what convinced you is how convinced they were of themselves.\\nChristoph Huber: Absolutely. You have to follow your idea or intention. If you have a strong idea of what you want to do and it doesn\\'t work out immediately, don\\'t simply give up. If this idea is not only a strong idea, but a good one too, and you stick with it, at one point, you will be recognized for it. But you have to keep going and develop it. I mean, if a concept doesn\\'t work out in the first moment, it\\'s not a big deal. You just have to shape it and work on it. You need time to rehearse, practice and experiment.\\nIt\\'s not always easy, though, to have this kind of self-assuredness. Especially in a culture for which these values are not as deeply engrained as, let\\'s say, the American one.\\nChristoph Huber: No, it\\'s not easy. It\\'s a hard way of course. But it makes sense. I mean, if you want to survive as a front-person, then you can\\'t take the easy route. But at one point, you know, all those really talented musicians, in all generations, like Puschnig, Dickbauer, Muthspiel, they all succeed with their art. And that\\'s in part because they really believed in themselves and their creativity. That\\'s really important, otherwise you might have to get a different job.\\nGeorg Vogel & Elias Stemeseder (c) Eckhart Derschmidt\\nWhat are other ingredients to international success? Or what are some barriers?\\nChristoph Huber: From time to time, the musicians are not so interested in leaving their city. And you have to respect that. For example, the famous Hans Koller, the first really international Austrian jazz star. He would have had every possibility to go to the States, for example. He just didn\\'t want to. He played with everyone because they just came through (Europe), like Benny Goodman or Carla Bley. He just said, \\'this is my home, and I don\\'t want to go anywhere else.\\' The problem is, before such musicians might make an international career, they are already teaching the next generation here. Of course, on one hand it gives them security, but on the other, it handicaps you because it lowers your motivation to take certain risks.\\nSo it\\'s the comfort that could kill you? Unlike American artists who, in most cases, have to tour internationally to make a living, European musicians don\\'t have that same pressure.\\nChristoph Huber: Yeah. We are in a welfare state. It\\'s a security blanket, and it\\'s difficult to get people out from under it. I mean, I don\\'t want to lecture anyone, but if you want to conquer the world, you can\\'t wait for the world to come to you.\\nIF YOU WANT TO SURVIVE AS A FRONT-PERSON, YOU CAN\\'T TAKE THE EASY ROUTE\\nStepping out of the box is another ingredient then?\\nChristoph Huber: I\\'d say so. Look at Martin Siewert, a really interesting and accomplished musician. He was the youngest guy at the time to get a Portrait at Porgy. I remember he had recently finished university in Graz but he didn\\'t get a \"sehr gut\" (an \"A\"), but he was one of the most interesting musicians. We decided to give him a Portrait, with 3 nights at Porgy. And he really used that opportunity and invited people like Jamaaladeen Tacuma. He even invested money in it. And, when all is said and done, he found his way, because he did it consistently. Even though it wasn\\'t easy with the kind of art he was interested in.\\nI guess that\\'s another necessity for success? You don\\'t have to please the others and satisfy conventions, but rather stick to your guns and your passions?\\nChristoph Huber: Yes, but it\\'s difficult. In former times, creative musicians, they just skipped the institutions altogether. The famous story with (Joe) Zawinul was he went to the States because he got a scholarship from Berklee, but left almost immediately, saying, \\'Sorry, I can\\'t learn anything here\\'. So he went back to NY, to Birdland and met all those musicians there. And suddenly he had a gig with Maynard Ferguson and then, his career really started. He became the piano player of Cannonball Adderley, which was the hippest band of that time. All that would never have happened without his belief in himself. He said, \\'I am the best, so what can you teach me if I\\'m already the best?\\' It was extraordinary self-confidence. But he\\'s a rare species of course.\\nYou mentioned the Wiesinger sisters; something of a power pair who seem to be popping up all over the place lately.\\nChristoph Huber: Yeah, and rightfully so. They have this great duo together, duo 4675 (that\\'s the zip code of their hometown), as well as an interesting collective called Echoboomer. They\\'re also a regular part of the Orjazztra Vienna, led by Christian Muthspiel.\\nThat collective (Orjazztra Vienna) seems to be something of a hot spot for young talent.\\nChristoph Huber: Absolutely. In there is also the drummer, Judith Schwarz. She\\'s made a strong reputation for herself as an open-minded bandleader and top-notch composer for Little Rosies Kindergarten, for example. Also in her duo with Lisa Hofmaninger (soprano sax and bass clarinet), which is a really interesting combination, as well as in the improvised music context, like with Peter Ponger and Peter Herbert.\\nSo, what is it about these young musicians you\\'ve mentioned, that make them stand out in Austria, and could make them stand out internationally, as well?\\nChristoph Huber: It\\'s a kind of individualism. They have a unique sound, no matter what they do. A personal touch, and an interesting one at that. Another musician, who must be mentioned if we are talking about the \"young lions,\" is Ralph Mothwurf. He leads his own orchestra, among other activities, such as musical director of Yasmo\\'s Klangkantine. All of these musicians are part of a cool generation, who know a lot about music, and had classical education, but are really willing to improvize and take risks. It\\'s not possible to succeed every single time when you have an open concept like theirs. I mean, it can turn out as a highlight, or you know [laughs], you better think it over again. But nevertheless they are willing to take the risk.\\nNo risk… no fun? …no fame?\\nChristoph Huber: Well, if you\\'re not willing to take risks, then you can be a super studio musician, or work as a side-person in a big band, but you won\\'t become one of the big names. For that, you have to take risks, be self-confident, follow your ideas, and be convinced by them, as well as develop them. Georg Vogel is interesting because he\\'s not only a piano player, but a piano constructor. He builds his own instruments. And this idea of 31-tone. It\\'s really spectacular. It\\'s like a philosophical kind of approach. And, that\\'s not nothing. I mean, I don\\'t understand it at all. I have to be honest. [laughs] But I\\'m really interested in it.\\nChristoph Huber: Sometimes it\\'s even difficult to listen to this stuff because at times it just sounds \"wrong\". But I\\'m sure it\\'s not. I know Georg quite well at this point, and I\\'m sure that everything he is doing is on the highest level. So the tones are not wrong. Maybe I just hear them wrong. [laughs] I think from all the young musicians I know, he is maybe the most genius; in many ways, including his way of thinking.\\nWell, you can\\'t top \"genius\" so let\\'s stop the interview here! Thank you!\\nArianna Fleur\\nGeorg Vogel\\nPurple is the Color\\nDuo 4765\\nJudith Ferstl\\nJudith Schwarz\\nManu Mayr\\nLisa Hofmaninger\\nRalph Mothwurf\\nCategories jazz/improvisation, news, portraits/interviews Tags Astrid Wiesinger, Beate Wiesinger, Christoph Huber, David Six, Georg Vogel, Judith Ferstl, Judith Schwarz, Manu Mayr, Martin Siewert, Porgy and Bess, Purple is the Color, Ralph Mothwurf, Strenge Kammer\\nReeperbahn Festival International – Open Call\\nDanube Sounds – Open Call<|begin_of_text|>От Редакция РМ дата публикации 16.12.2022 ENGLISH Patrons of Imperial Russia\\nHistory has preserved the names of thousands of people for whom patronage of the arts, charity and selflessness were not alien, and one of them was Pavel Mikhailovich Tretyakov\\nBy Alexander Khodorenko, a writer, author of the book, Ten Geniuses of Business\\nThe Tretyakovs came from an old but not wealthy merchant family dating back to 1646. Pavel Mikhailovich Tretyakov\\'s great-grandfather – Yelisey Martynovich – moved to Moscow from the town of Maly Yaroslavets [now Maloyaroslavets]in 1774. His grandfather – Zakhar Yeliseyevich – was a Moscow merchant of the 3rd Guild. In 1828, he opened an establishment in Moscow for dyeing and starching canvas and sailcloth. His father – Mikhail Zakharovich, a Moscow merchant of the 2nd Guild – managed to expand the family business. But the Tretyakovs\\' business did not reach a truly great scale until the next generation. Pavel Mikhailovich Tretyakov inherited his father\\'s business in the first half of the 1850s. The \\'Brothers P. and S. Tretyakov and V. Konshin\\' trading company appeared in Moscow in 1860. Tretyakov\\'s sons continued trading and industrial business. In 1864, they founded the New Kostroma Linen Mill, built several flax-processing factories in Kostroma, and two years later established the famous Association of the Large Kostroma Linen Mill with a capital of 270,000 gold roubles.\\nIt should be noted that Pavel Mikhailovich spent about 1.5 million roubles on organising an art gallery in Moscow. He received over a third of this amount in the form of profit from the New Kostroma Linen Mill. Thus, the Kostroma textile workers contributed to the creation of a national treasury – the famous Tretyakov Gallery.\\nThe Tretyakov factory was considered one of the most advanced and best equipped in Russia. Pavel Mikhailovich also tried to improve the living conditions of its workers. A school, a hospital, a maternity hospital, a nursing home and a nursery were built for them.\\nExpanding their father\\'s business, the Tretyakov brothers also built cotton factories, which employed about 5,000 people.\\nWhen creating his famous gallery, Pavel Mikhailovich spent enormous amounts of money, perhaps to the detriment of his own family\\'s well-being. And he had a large family. In 1865, Pavel Mikhailovich married Vera Nikolaevna, nee Mamontova, a cousin of Savva Ivanovich Mamontov, a famous Russian entrepreneur, industrialist and philanthropist, the founder of the Moscow Private Opera, and the great-aunt of another Vera Mamontova, who was the model for the painting \\'Girl with Peaches\\' (1887) by V. A. Serov. They had six children – two boys and four girls.\\nS. Turgenev, the composers N. G. Rubinstein and P. I. Tchaikovsky, the artists I. E. Repin, V. I. Surikov, V. D. Polenov, V. M. Vasnetsov, V. G. Perov and I. N. Kramskoy would visit the Tretyakovs. The family was related to some of them: P. I. Tchaikovsky\\'s brother Anatoly was married to Pavel Mikhailovich\\'s niece; the artist V. D. Polenov\\'s wife, N. V. Yakunchikova, was Vera Nikolaevna\\'s niece.\\nPavel Mikhailovich, a fourth-generation merchant, wanted his daughters to marry only merchants. But it so happened that his eldest daughter, Vera, fell in love with the talented pianist Alexander Siloti, the composer S. V. Rachmaninoff\\'s cousin. Knowing that her father might not give her his blessing to marry a musician, Vera was very nervous and even fell ill. When Pavel Mikhailovich saw his daughter\\'s suffering, all his theories regarding his daughters\\' life partners failed.\\nThe painting by Nikolai Ge \\'Peter I Interrogates Tsarevich Alexei Petrovich at Peterhof\\' (1871) was acquired by P. M. Tretyakov in the year it was done\\nThe wedding of Vera Tretyakova and Alexander Siloti took place in February 1887. Alexandra (another daughter) married the doctor and collector Sergey Botkin. His brother Alexander, a doctor, later a hydrographer and an explorer of the North, married Masha. In May 1894, Lyuba married the painter Nikolay Gritsenko. Widowed in 1900, she remarried – her second husband was the famous Leon Bakst, a painter and a designer who created costumes and scenery for Diaghilev\\'s ballet in Paris. Pavel Mikhailovich had enough breadth of vision to appreciate all these young men.\\nThe following fact can testify to the way Tretyakov brought up his daughters. In 1893, Pavel Mikhailovich wrote a very large and serious letter to his daughter Alexandra, in which he explained his idea of parental duties: \\'Money is not a good thing which causes unhealthy relations. Parents must bring up their children and give them education, but they are not at all obliged to provide for them.\\' There were the following words in the same letter: \\'My idea was to make money from a very young age so that what was received from society would also return to society (the people) in some useful institutions; This idea has never left me all my life.\\'\\nFascinated by art, in 1854 Tretyakov began to collect pieces of national Russian works of art. His first acquisitions – about ten graphic sheets of old Dutch painters – were bought at a flea market near the Sukharev Tower. These drawings adorned his living-rooms until his death.\\nAt first lacking experience and multifaceted knowledge in the sphere of art and guided by a deep patriotic feeling, Tretyakov decided to focus on collecting works by contemporary Russian artists. It is known that Pavel Mikhailovich had no special art education. Nevertheless, he bought works by his still little-known yet talented contemporaries. As a rule, he acquired the most significant works from this or that artist.\\n\\'A Clash with Finnish Smugglers\\' (1853) by V. G. Khudyakov was one of the first paintings acquired by Tretyakov in 1856. That year marked the birth of the Tretyakov Gallery. This was followed by the purchase of works by I. P. Trutnev, A. K. Savrasov, K. A. Trutovsky, F. A. Bruni, L. F. Lagorio and others. Knowing about works by K. P. Bryullov in Italy, Tretyakov asked permission from the archaeologist M. Lanci\\'s children to purchase his (Lanci\\'s) portrait. Thus, in 1860, the first work by the \\'great Karl\\' (Bryullov) – \\'Portrait of the Archaeologist M. Lanci\\' (1851) – appeared in the collection. So Tretyakov began selfless collecting work that lasted for many years. It was modest and not designed for advertising and praise. We can say that from the very beginning he had a clear idea of the purpose of his undertaking.\\nPavel Mikhailovich pursued no selfish goals. He came up with the idea of creating a museum of national paintings. In his will, drawn up in 1860, just four years after the purchase of the first paintings, he wrote: \\'For me, who genuinely and ardently loves art, the greatest wish is to lay the foundations for a public repository of fine art, accessible to all, to the benefit of many and pleasure for all.\\'\\nTretyakov\\'s confidence and faith in his cause seem surprising if we remember that he laid the foundations of the gallery at a time when the school of Russian art as an original and significant phenomenon loomed only faintly in the shadow of the great tradition of the West; mighty ancient Russian art had been half-forgotten, works by Russian artists were in private collections in Russia and abroad; when there were still no Repin, no Surikov, no Serov, no Levitan and their paintings, without which it is impossible to imagine Russian art today. It was the time of the formation of democratic art and the birth of a new school of Russian art.\\n\\'…Without his help Russian art would never have entered an open and free phase, since Tretyakov was the only (or almost the only) one who supported everything that was new, fresh and practical in Russian art\\' (A. Benois).\\nThere were few real enthusiasts in old Moscow who took an active part in the lives of young artists. They mostly just bought paintings for their galleries, and sought to pay less for them. Unlike them, Pavel Mikhailovich Tretyakov was a real patron of arts. His visits to artists were always considered as exciting events, and all of them, masters and beginner artists, with awe waited for his quiet words: \\'I am going to buy your painting,\\' which was tantamount to public recognition for everyone. In 1877, Repin wrote to Tretyakov about his painting \\'Protodeacon\\': \\'I confess to you that if I sell it, then only to you, to your gallery, because, I say without flattery, I consider it a great honour to see my works there.\\' Artists often made concessions to Tretyakov (he never bought paintings without bargaining) and lowered their prices for him, thereby providing all possible support to his undertaking. And the benefits were mutual. Pavel Mikhailovich not only bought paintings, but also ordered them, thus supporting artists both morally and financially, which allowed them not to depend on the tastes of the market.\\nIn the activities of Tretyakov the collector\\'s attention was primarily focused on works by contemporary realist painters of the mid and second half of the nineteenth century – the Wanderers (the Itinerants), representatives of the democratic wing of the national school, which defined the originality of the gallery\\'s collection, the influence of this collection on the development of realist art, and its progressive, revolutionary and educational impact. But in the 1860s, when the Society for Travelling Art Exhibitions still did not exist, Tretyakov bought paintings in the official \\'academic\\' style, and from the late 1880s – works by M. V. Nesterov, K. A. Korovin, V. A. Serov and others. Then Tretyakov began to collect drawings, and in the 1890s – icons.\\nTretyakov had unmistakable taste. He was not afraid to buy works by young, still unknown artists. The specifics of the way Pavel Mikhailovich collected paintings are seen in the fact that many works for the gallery were done at his request. And neither then nor today do these works disappoint the most demanding connoisseurs of Russian art with their problems or artistic merits. He bought works even when figures of high authority like L. N. Tolstoy, who did not recognise V. M. Vasnetsov\\'s religious paintings, opposed it. He even bought paintings that were banned by the imperial authorities for public viewing.\\nPavel Mikhailovich acquired paintings at exhibitions and right in the studios of artists. Sometimes he bought entire collections: in 1874 he acquired the Turkestan series by V.V. Vereshchagin (thirteen paintings, 133 drawings and eighty-one sketches), and in 1880 – his Indian series (seventy-eight sketches). There were also over eighty sketches by A. A. Ivanov in Tretyakov\\'s collection. In 1885, Tretyakov bought 102 sketches by V. D. Polenov, done by the artist during a trip to Turkey, Egypt, Syria and Palestine. From V. M. Vasnetsov Pavel Mikhailovich acquired a collection of sketches that he had done while working on murals in St Vladimir\\'s Cathedral in Kiev. V. G. Perov, I. N. Kramskoy, I. E. Repin, V. I. Surikov, I. I. Levitan and V. A. Serov were represented in his collection most fully and by their best works. The gallery was replenished with works by artists of the eighteenth and the first half of the nineteenth centuries and monuments of ancient Russian art. This heroic period of Russian art can be understood, felt keenly and explored in Moscow, in the Tretyakov Gallery, more than anywhere else.\\nAll artists, young and famous, dreamed of having their paintings hung at the Tretyakov Gallery because the very fact of buying a painting by Pavel Mikhailovich was an act of public recognition of an artist\\'s talent. So one marvellous man managed to influence all Russian pictorial art and become a spokesman for Russian public opinion.\\nTretyakov\\'s great merit is his unshakeable faith in the triumph of the Russian national school of painting – a faith that arose in the late 1850s and was carried by him through his life, through all the trials and tribulations. We can say with confidence that in the late nineteenth century P. M. Tretyakov\\'s personal contribution to the triumph of Russian pictorial art was exceptional and invaluable.\\nEvidence of his ardent faith has been preserved in Pavel Mikhailovich\\'s letters. Here is one of them. In a letter to the artist Rizzoni dated 18 February 1865, he wrote: \\'In the last letter to you my expression might seem incomprehensible: \"Then we would talk with skeptics.\" I will explain: many positively do not want to believe in the good future of Russian art and argue that if some Russian artist sometimes does a good painting, it is allegedly by accident and he will increase the number of mediocrities. I have a different opinion, otherwise I would not have collected Russian paintings; but sometimes I could not but agree with the facts presented; and every success, every step forward is very dear to me, and I will be very happy if I live to see when our day comes.\\' And about a month later, returning to the same thought, Tretyakov wrote: \\'I involuntarily believe in my hope: our Russian school will not be the worst – it was indeed a clouded time, and for quite a long time, but now the fog is lifting.\\'\\nHis faith was not a blind intuitive feeling: it was based on careful observation of the development of Russian pictorial art, on a deep, subtle understanding of national ideals that were being formed on a democratic basis.\\nP. M. Tretyakov acquired the painting \\'Horsewoman\\' (1832) by Karl Bryullov in 1893\\nSo, back in 1857, Pavel Mikhailovich wrote to the landscape painter A. G. Goravsky: \\'Concerning my landscape, I humbly ask you to leave it, and instead paint me a new one someday. I need neither rich nature, nor a great composition, nor spectacular light, nor miracles.\\' Instead, Tretyakov asked him to depict simple nature, even if unprepossessing, \\'but there must be truth and poetry in it. And poetry can be in everything – this is the artist\\'s work.\\'\\nThis note expresses the very aesthetic principle of the formation of the gallery, which emerged as a result of reflecting on the development of Russian national pictorial art. P. M. Tretyakov had guessed its progressive tendencies long before the appearance of Savrasov\\'s painting \\'The Rooks Have Come Back\\', the landscapes by Vasiliev, Levitan, Serov, Ostroukhov and Nesterov – the artists who managed to create a truthful depiction of Russian nature, conveying the poetry and charm inherent in it.\\nPavel Mikhailovich first entrusted the idea of creating a national or folk art gallery to the artist V. G. Khudyakov and outlined it with the utmost accuracy in a testament written in Warsaw on 17 (29) May, 1860, during his first trip abroad.\\nHis relatives did not have to execute this will. Pavel Mikhailovich himself fulfilled his dream – he set up a folk-art gallery.\\nInteresting statements by P. M. Tretyakov can also be found in his correspondence with Vereshchagin regarding the depiction of the contemporary Russo-Turkish war of 1877–1878 for the liberation of Bulgaria – a war in which Russia took Bulgaria\\'s side. On learning that Vereshchagin was going to the front to do a series of paintings about the war, Tretyakov wrote to the critic of music and art V.V. Stasov: \\'Perhaps only in the distant future will the sacrifice made by the Russian people be appreciated.\\'\\nTretyakov suggested that Vereshchagin pay a large sum in advance for his work: \\'However strange acquiring a collection without knowing its contents may be, Vereshchagin is a kind of artist you can rely on, especially since giving paintings over to private hands, he will not be bound by choosing subjects and, probably, will be imbued with the spirit of the sacrifice of people and the brilliant heroic deeds of Russian soldiers and some individuals.\\'\\nVereshchagin had a different opinion: \\'As for your letter to V.V. Stasov on my painting you saw, you and I obviously disagree a little in the assessment of my works and a lot in their trends. There is war before me as before an artist, and I strike at it with all my might; whether my blows are strong or real – this is a question of my talent, but I fight with all my strength and mercilessly…\\'\\nIn addition to collecting, Pavel Mikhailovich Tretyakov was actively involved in charity work. He was an honorary member of the Russian Society of Art Lovers and the Russian Musical Society from the day they were founded and contributed substantial sums, supporting all educational initiatives. He provided material assistance to individual artists and the Moscow School of Painting, Sculpture and Architecture; from 1869 he was a member of the Council of the Moscow Trust for the Poor. He was also a member of the councils of the Moscow Commercial College and the Alexander Commercial College. Pavel Mikhailovich bequeathed half of his funds to charitable purposes: to set up a shelter for widows, young children and unmarried daughters of deceased artists (it was built in 1909–1912 by the architect N. S. Kurdyukov in Lavrushinsky Lane); for distribution among workers and employees of his enterprises; and for funding the gallery. He gave donations to help the families of soldiers who had fallen in the Crimean War and the Russo-Turkish (1877-1878) War. P. M. Tretyakov scholarships were established at the Moscow Commercial College and the Alexander Commercial College.\\nPavel Mikhailovich never refused to render financial aid to artists and other applicants. He took good care of the money affairs of painters who entrusted their savings to him with confidence. He repeatedly lent money to his good adviser I. N. Kramskoy, selflessly helped V. G. Khudyakov, K. A. Trutovsky, M. K. Klodt and many others.\\nBrothers Pavel and Sergey Tretyakov founded the Arnold-Tretyakov Deaf-and-Dumb School in Moscow. Pavel Mikhailovich took his establishment very seriously. At first classes with deaf-mute children in live speech were rather primitive, and Pavel Mikhailovich sent the headmaster D.K. Organov abroad at his own expense so he could familiarize himself with the teaching process in similar schools. In addition to general subjects, children were taught crafts. The school, or the \\'institution for the deaf-mute\\', obtained a large stone house with a huge garden, where 156 pupils of both sexes studied and lived, and in the early 1890s Pavel Mikhailovich built a hospital with thirty-three beds at his own expense.\\nPatronage of the school, which began in the 1860s, continued throughout Pavel Mikhailovich\\'s life and after his death. In his will Pavel Mikhailovich left very generous funds for the school for the deaf and dumb. Boys and girls would be brought up till the age of sixteen and receive a profession. Tretyakov selected the best teachers, got acquainted with the teaching methods, and made sure that the pupils were well fed and clothed. On each visit to the school he went round the classes and workshops during class hours and was always present at exams.\\nIn 1871, on the initiative of Pavel and Sergei Tretyakov, a passage was built between Nikolskaya Street and Teatralny Passage on the site of an earlier one that had been built up in the eighteenth century. In 1870–1871 the architect A. S. Kaminsky constructed two buildings with passage arches facing Nikolskaya Street and Teatralny Passage on the site purchased by the Tretyakovs especially for the arrangement of the passage; the facade of the building from the side of Teatralny Passage was built into the Kitay-Gorod Wall next to the tower (1534–1538) and designed in a romantic-medieval style. There were shops inside the passage. Such urban planning solution is unique for Moscow. The new structure was called Tretyakov Drive.\\nThe Explanatory Dictionary defines charity as \\'gratuitous actions and deeds whose aim is the public good.\\' With reference to the life of Pavel Mikhailovich Tretyakov we can add: \\'and which will never be forgotten.\\'\\nПредыдущая статьяProblems to be solved\\nСледующая статья Patrons of Imperial Russia\\nProblems to be solved<|begin_of_text|>Brexit means Brexit – and it hurts!\\nTOPICS:EconomicsEuropean UnionPoliticsRitchie\\nPolitics of peace: sharing sovereignty and spreading prosperity makes impossible the settling of differences by war.\\nBritish negotiators in Brussels are missing the point and will never win a good deal. Why? Because the European Union is more about politics than economics, writes Murray Ritchie.\\nMany years ago in Brussels when Jacques Delors was president of the European Commission he shook his head in sadness at the latest fusillade of Eurosceptic hostility from across the Channel. This was during the tensions created by the proposed single currency and Britain\\'s opposition to it.\\n\"The British are an island people,\" he concluded with a Gallic shrug. As if that explained everything – and in a way it did exactly that. We British – or at least 52 per cent of us who are leavers – are written off as misfits in the great European adventure.\\nTo European eyes it was ever thus. Ever the awkward squad, the Brits just don\\'t like joining in. They think they\\'re being told what to do by bossy foreigners, particularly French and German foreigners.\\nThis mindset is at the root of today\\'s Brexit crisis in Brussels where, barring some unforeseen breakthrough, we appear to be heading for a diplomatic failure of immense proportions. We have managed to hurt our European partners, not just for causing a potential economic schism, but for rejecting the European Union\\'s (EU) overriding aspiration – peace and prosperity in ever-closer union.\\nTo Europhile eyes the EU represents an ideal that the UK has betrayed. Ever-closer union, to which we signed up over a series of treaties, was fine until Delors, Helmut Kohl and François Mitterrand got serious about integration.\\n\\'We must build a kind of United States of Europe. In this way only will hundreds of millions of toilers be able to regain the simple joys and hopes which make life worth living.\\'\\nThis was where the normal relationship between politics and economics was turned on its head. Raw politics became the driver. To encourage economic integration required strong political will, not least in progressing Maastricht\\'s single currency. Any challenges – Greece, for example – were overridden by political will.\\nThe euro survives today because of politics, despite all the economic gloom and pessimism we read about daily in the British Eurosceptic press. We were told long ago it would be stillborn. As the years passed we were told regularly it would be dead within months. Now the airports are offering less than a euro to the pound.\\nWhen Greece was – scandalously – admitted to the eurozone when patently unable to cope, it was a political fix – the same fix which defies economic reality to keep it there. Messrs Delors, Kohl and Mitterrand, integrationists all, were not about to let themselves be embarrassed.\\nRemember how Kohl ordered the exchange rate for the worthless East German Ostmark to be one-for-one with the Deutschmark despite the obvious economic madness? So much for the fabled independence of the old Bundesbank!\\new were told that Spain and Portugal and Ireland would be blown out of the euro but politics intervened to keep them there. The same will happen with Italy\\'s coming crisis.\\nHow ironic that European integration was born out of war and shared by the greatest of British heroes. Angry Eurosceptics loathe being reminded that Churchill was among the leading Europhiles when he called for a new means to protect peace, safety and freedom: \"What is this sovereign remedy?\" he asked.\\n\"It is to re-create the European family, or as much of it as we can, and provide it with a structure under which it can dwell in peace, in safety and in freedom.\\n\"We must build a kind of United States of Europe. In this way only will hundreds of millions of toilers be able to regain the simple joys and hopes which make life worth living.\"\\nEurosceptics hate being reminded of that quotation. In their desperation to disavow it they claim Churchill never foresaw a single currency or malign \"unelected Brussels bureaucrats\" bossing the British.\\nBritain is desperate for a trade deal to equal and replicate the single market and/or the customs union.\\nAha, but we never signed up for the EU as a political project, they complain. Well, we did actually. It was called the Maastricht Treaty which renamed the old European Community as the European Union and introduced European citizenship and monetary union.\\new British backed off from the single currency and the social chapter amid mutterings of a two-speed Europe. (More headshaking from M Delors.) But that was then. We were content to grumble on the sidelines while drawing a line at further integration.\\nThat foot-dragging has now brought us to the crunch where political determination confronts economic challenge. Britain is desperate for a trade deal to equal and replicate the single market and/or the customs union. But EU politics insists there is no chance of that in practical terms otherwise what is the point of membership?\\nPolitics will win if we go by precedent. Germany will say losing Volkswagen exports to Britain is less important than the precious EU project. Brussels politicians expect our banks to cross the channel if the new rules work against the City. The EU can spoil our holiday travel and increase our food prices.\\new are about to learn the hard way that the EU actually believes – genuinely believes – in sharing sovereignty and promoting the original ideal of the common market which is to spread prosperity by hitching French farming to German industry in a way that makes impossible settling differences by war. This remains pure politics using economics as a tool.\\nThe EU undoubtedly has its challenges, but the European ideal is working. Politics and economics – the twin basis of today\\'s EU since its inception 70 years ago – go hand in hand, but the politics still drives the economics, not the other way round.\\nBritain has offended this ideal – although 48 per cent of us are blameless – and we are probably about to pay an enormous price.\\nIronically, when we become isolated we are likely to be in the dangerous position of allowing economic desperation to reverse the process.\\nWhen you allow dire economic misery to drive politics – inter-war Germany comes to mind – the future can be terrifying. That, after all, is why the EU was invented.\\nFeatured Image Credit: esfera/Shutterstock\\nEU overhauls space policies\\nBrexit is now all about the art of the possible\\nTax treaty history: the day an MLI defeated BEPS\\nDemocratic dominos line up. Will they fall?\\n1 Comment on \"Brexit means Brexit – and it hurts!\"\\nDavid Brown | September 17, 2017 at 6:17 pm |\\nUsually a country or an association requires something like a two-thirds majority to make a major constitutional change. As a a non-Brit I\\'m flabbergasted that 52% is interpreted as an inviolable mandate to make the massive legislative changes being debated this week, let alone the longer-term program of Brexit—hard or soft.<|begin_of_text|>Previous (Karl Mannheim)\\nNext (Karl Polanyi)\\nKarl Heinrich Marx (May 5, 1818 – March 14, 1883) was a revolutionary activist, a prolific writer and Marxism\\'s key ideologue. Trained as a philosopher, self-educated as a political economist, and an organizer of the International Workingmen\\'s Association, Marx became interested in social change during his university studies. Upon receiving his doctorate in absentia from the University of Jena in 1841, Marx was hired as editor of the Rheinische Zeitung, a German newspaper. There he championed the rights of peasants against the Prussian government in an editorial column. This led to his opponents accusing Marx of being a \"communist\" and to his being ostracized. Marx left for Paris where he continued to suffer accusation from the Prussian and the French governments.\\nMarx developed his revolutionary theories over a period of four decades beginning in 1843. He formulated his theories with the intention to liberate wage workers or laborers from the capitalist societies of nineteenth century Europe. He maintained that in order to emancipate humanity from economic domination, a social revolution was needed. The envisioned result would transform the existing economic structures, and create a society in which property, particularly the means of production would no longer be held privately. Marx\\'s theories were developed in close collaboration with Friedrich Engels. Together they included an explanation of human alienation and dialectical materialism. Marx and Engels\\' vision was a purely materialist interpretation of human nature and development within nature that called for revolution. It represented a materialist view of history, based on the dialectic, that supported Marx\\'s theory of political economy and his call for revolution. The interpretation distinguished itself because of its theory of surplus value, which asserted that the wealth of capitalist societies originates solely from the exploitation of laborers.\\nMarx\\'s analysis of history saw human development as occurring due to a series of class struggles between the ruling class, those who possess the means of production. To Marx, feudal lords, land owners and capitalists were pitted against the ruled working class. This claim is summed up in the opening line of The Communist Manifesto: \"The history of all hitherto existing society is the history of class struggle.\" Marx predicted the demise of capitalism through a workers\\' revolution that would lead to a utopian \"classless society\" where, according to Marx, \"people work according to their ability and get according to their needs\" and \"in which the free development of each is the condition for the free development of all.\"\\n1.1 Parents\\n1.2 Education\\n1.3 Career\\n1.4 Family life\\n1.5 Later life\\n1.6 Influences on Marx\\'s thought\\n1.7 Marx\\'s View of History\\n1.8 Critique of capitalism\\n2 Marx\\'s influence\\n5.1 Bibliography and online texts\\n5.2 Biographies\\n5.3 Portraits\\n5.4 Encyclopedia entries\\nHis vision and ideals inspired Vladimir Lenin. Lenin embraced Marx\\'s vision, but made certain adjustments in Marxist theories and practice and orchestrated the first communist revolution. Marxism, as understood and implemented by Lenin resulted in totalitarian control. Lenin\\'s interpretation of Marxism is usually referred to as Marxism-Leninism. Some argue that Lenin\\'s views were inconsistent with Marx\\'s view, however this is subject to debate. The dissolution of the Soviet Union, the largest of all twentieth century socialist empires in 1991, was preceded by the breakdown of Marxist regimes throughout Eastern Europe. This breakdown has been followed by radical reforms in other communist countries including China, Mongolia and Vietnam. The failure of Marxism or Marxism-Leninism was not primarily due to its misapplication by Lenin, Josef Stalin or others. It stemmed from the philosophical and scientific underpinnings of Marxism, including its militant atheism, its commitment to revolutionary violence, and its flawed economic theories.\\nKarl Heinrich Marx was the third of seven children in a Jewish family in Trier, Province of the Lower Rhine, in the Kingdom of Prussia. His father, Heinrich Marx (1777–1838), descended from a line of rabbis, converted to Christianity, despite a deistic tendency and admiration of Enlightenment intellectuals such as Voltaire and Rousseau. Heinrich Marx was born Herschel Mordechai, son of Levy Mordechai (1743-1804) and wife Eva Lwow (1753-1823), but when the Christian Prussian authorities disallowed his law practice as a Jew, he converted to Lutheranism, the Prussian State\\'s official Protestant religion, to gain advantage as member of the Lutheran minority in that predominantly Roman Catholic state. His mother was Henriette née Pressburg (1788–1863), also from a well connected family.\\nMarx\\'s mother converted back to Judaism immediately after the death of her husband in 1835 and Marx clearly suffered some rejection in Prussian society because of his ethnic origins. This is most clearly seen in the fact that Marx\\'s was so secretive in the courting of his future bride, Jenny von Westphalen.\\nThe adolescent Karl Marx.\\nKarl Marx was home-schooled until the age of 13 when he entered Trier Gymnasium. Just before he left Marx wrote an essay, The Union of Believers With Christ, which showed him to be a person with a deep and sensitive faith in God.[1] He then enrolled, at age 17, to study law at the University of Bonn. Despite wanting to study philosophy and literature, his father disallowed it, believing Karl would be unable to support himself as a scholar. He joined the Trier Tavern Club and at one point served as its president but his grades suffered as a result. The next year, his father had him transfer to the rigorous Humboldt-Universität in Berlin. At that time, Marx wrote poems about life which Richard Wurmbrand suggested reveal him going through a spiritual crisis.[2] An example of this is a verse from his play Oulanem[3]\\nHellish evaporations rise and fill my brains,\\nUntil I will go mad and my heart will not change dramatically.\\nSee this sword?\\nThe King of darkness\\nsold it to me.\\nIn a letter to his father, Marx describes the inner struggles he went through and why his interests turned to philosophy[4] He joined the circle of students and young professors known as the \"Young Hegelians\", student philosophers and journalists orbiting Ludwig Feuerbach and Bruno Bauer, in opposition to G.W.F. Hegel, their teacher. For many of them, the so-called left-Hegelians, Hegel\\'s dialectical method, separated from its theological content, provided a powerful weapon for the critique of established religion and politics. Some members of this circle drew an analogy between post-Aristotelian philosophy and post-Hegelian philosophy. Another Young Hegelian, Max Stirner, applied Hegelian criticism and argued that stopping anywhere short of nihilistic egoism was mysticism. His views were not accepted by most of his colleagues; nevertheless, Stirner\\'s book was the main reason Marx abandoned the Feuerbachian view and developed the basic concept of historical materialism.\\nIn 1841, Marx earned a doctorate with the dissertation The Difference Between the Democritean and Epicurean Philosophy of Nature, but submitted it to the University of Jena, because his bad reputation as a Young Hegelian radical would hurt him in Berlin.\\nWhen his mentor, Bruno Bauer, was dismissed from Friedrich-Wilhelms\\' philosophy faculty in 1842, Marx abandoned philosophy for journalism and in 1842 was chosen to edit the Rheinische Zeitung, a radical Cologne newspaper. After the newspaper was shut down in 1843, to a large extent, due to Marx\\'s conflicts with government censors, Marx returned to philosophy, turned to political activism, and made his living as a freelance journalist. Marx was soon forced into exile, something he would do often as a result of his views.\\nThe Communist Manifesto which was distributed in Germany during the revolution of 1848\\nMarx first moved to Paris, where he re-evaluated his relationship with Bauer and the Young Hegelians, and wrote his Paris Manuscripts which serve as the fundamental underpinnings of the Communist Manifesto. In those manuscripts, Marx rejects the notion that the Prussian government, through its bureaucracy of civil servants, can serve as the vehicle for genuine social change. He also identified the proletariat rather than the Prussian civil servants as the vehicle through which change could occur. He saw that change as being effected through a social revolution. It was in Paris that he met and began working with his lifelong close friend and collaborator Friedrich Engels, a committed communist, who kindled Marx\\'s interest in the situation of the working class and guided Marx\\'s interest in economics. After he was forced to leave Paris because of his writings, Marx and Engels moved to Brussels, Belgium.\\nThere they co-wrote The German Ideology, a scathing criticism of the philosophy of Bruno Bauer, Hegel, and the Young Hegelians. Marx next wrote The Poverty of Philosophy (1847), a critique of French socialist thought. These works laid the foundation for Marx and Engels\\' most famous work, The Communist Manifesto, first published on February 21, 1848. It had been commissioned by the Communist League (formerly, the League of the Just), an organization of German émigrés whom Marx had converted in London.\\nThat year Europe experienced revolutionary upheaval; a working-class movement seized power from King Louis Philippe in France and invited Marx to return to Paris. When this government collapsed in 1849, Marx moved back to Cologne and restarted the Rheinische Zeitung, only to be swiftly expelled again.\\nIn 1864, Marx organized the International Workingmen\\'s Association, later called the First International, as a base for continued political activism. In his inaugural address, he purported to quote Gladstone\\'s speech, to the effect that, \"This intoxicating augmentation of wealth and power is entirely confined to classes of property.\" He repeated the citation in volume 1 of Capital. The discrepancy between Marx\\'s quote and the Hansard version of the speech (which was well-known) was soon employed in an attempt to discredit the International. Marx attempted to rebut the accusations of dishonesty, but the allegation continued to resurface. Marx later gave as his source the newspaper the Morning Star.\\nEngels devoted a good deal of attention to the affair in the preface to the fourth edition of Capital—which still did not put the matter to rest. Engels claimed that it was not the Morning Star but the Times that Marx was following. Indeed, modern critics of Marx continue to invoke Marx\\'s supposed misquotation as evidence of general dishonesty.\\nKarl Marx married Jenny von Westphalen, the educated daughter of a Prussian baron. Their seven year long engagement was kept secret, for being opposed by both families; they married on 19 June, 1843, in the Kreuznacher Pauluskirche, Bad Kreuznach.\\nThe Marxes were poor in the first half of the 1850s, living in a three-room flat in Dean Street, Soho, London. Already, they had four children; three more followed; in all, only three saw adulthood. His principal source of income was Engels\\'s subsidy, and income from weekly newspaper articles written as a New York Daily Tribune foreign correspondent. Inheritances from an uncle of Jenny, and her mother, who died in 1856, permitted the Marx family to move to healthier lodgings in Kentish Town, a new, London suburb. Despite the family\\'s hand-to-mouth life, Marx provided his wife and children with the necessary bourgeois luxuries requisite to their social status and contemporary mores.\\nMarx\\'s children with wife Jenny were: Jenny Caroline (m. Longuet; 1844–1883); Jenny Laura (m. Lafargue; 1845–1911); Edgar (1847–1855); Henry Edward Guy (\"Guido\"; 1849–1850); Jenny Eveline Frances (\"Franziska\"; 1851–1852); Jenny Julia Eleanor (1855–1898); and several who died before naming (July 1857). Marx may have also fathered Frederick Demuth by his housekeeper, Lenchen Demuth. This is disputed and not corroborated.[5] Their daughter Eleanor Marx (1855 – 1898), who was born in London, was a committed socialist who helped edit her father\\'s works until she committed suicide.\\nKarl Marx Tomb in London\\nFrom 1850 to 1864, Marx lived in poverty only taking a job once. He and his family were evicted from their apartment and several of his children died, his son, Guido, who Marx called \"a sacrifice to bourgeois misery\" and a daughter named Franziska. They were so poor that his wife had to borrow money for her coffin.\\nFrederich Engels was the one who gave Marx and his family money to survive on during these years. His only other source of money was his job as the European correspondent for The New York Tribune, writing editorials and columns analyzing everything in the \"political universe.\"\\nMarx was generally impoverished during the later period of his life, depending on financial contributions from close friend and fellow author, Friedrich Engels, to help with his family\\'s living expenses and debts. Following the death of his wife Jenny in 1881, Marx died in London in 1883, and is buried in Highgate Cemetery, London. The message carved on Marx\\'s tombstone—a monument built in 1954 by the Communist Party of Great Britain—is: \"Workers of the world, unite!\" Marx\\'s original tomb was humbly adorned.\\nInfluences on Marx\\'s thought\\nMarx\\'s thought was strongly influenced by:\\nThe dialectical historicism of Georg Wilhelm Friedrich Hegel;\\nThe humanism of Ludwig Andreas Feuerbach\\nThe classical political economy of Adam Smith and David Ricardo; and\\nThe French socialist and communist thought of Saint-Simon and Fourier.\\nMarx believed that he could study history and society scientifically and discern tendencies of history and the resulting outcome of social conflicts. However, Marx was not only interested in studying history and social development. He famously asserted that \"philosophers have only interpreted the world, in various ways; the point however is to change it,\" and he clearly dedicated himself to trying to alter the world.\\nMarx\\'s view of history, which came to be called the materialist interpretation of history (and which was developed further as the philosophy of dialectical materialism) is certainly influenced by Hegel\\'s claim that reality (and history) should be viewed dialectically, through a clash of opposing forces. Hegel believed that the direction of human history is characterized in the movement from the fragmentary toward the complete and the real (which was also a movement towards greater and greater rationality). Sometimes, Hegel explained, this progressive unfolding of the Absolute involves gradual, evolutionary accretion but at other times requires discontinuous, revolutionary leaps—episodal upheavals against the existing status quo. For example, Hegel strongly opposed the ancient institution of legal slavery that was practiced in the United States during his lifetime, and he envisioned a time when Christian nations would radically eliminate it from their civilization. While Marx accepted this broad conception of history, Hegel was an idealist, and Marx sought to rewrite dialectics in materialist terms. He wrote that Hegelianism stood the movement of reality on its head, and that it was necessary to set it upon its feet. (Hegel\\'s philosophy remained and remains in direct opposition to Marxism on this key point.)\\nMarx\\'s acceptance of this notion of materialist dialectics that rejected Hegel\\'s idealism was greatly influenced by his study of Ludwig Feuerbach. In The Essence of Christianity, Feuerbach argued that God is really a creation of man and that the qualities people attribute to God are really qualities of humanity. For example, the Holy Trinity was a human projection of the family (man, woman, and child) onto God. Accordingly, Marx argued that it is the material world that is real and that our ideas of it are consequences, not causes, of the world. Thus, like Hegel and other philosophers, Marx distinguished between appearances and reality. But he did not believe that the material world hides from us the \"real\" world of the ideal; on the contrary, he thought that historically and socially specific ideologies prevented people from seeing the material conditions of their lives clearly.\\nMarx\\'s View of History\\nAccording to Marx, the development of history is caused by the contradiction between the productive forces and the production relations of society. By \"productive forces, \"Marx is referring to the means of production and to the level of human technical understanding. By production relations, Marx is referring to class relations.\\nAt a certain stage of their development, the material productive forces of society come into conflict with the existing relations of production. From forms of development of the productive forces, these relations turn into their fetters. Then begins an epoch of social revolution (Marx and Engels, Selected Works, p. 182).\\nThe notion of labor is fundamental in Marx\\'s thought. Basically, Marx argued that it is human nature to transform nature, and he calls this process of transformation \"labor\" and the capacity to transform nature labor \"power.\" For Marx, this is a natural capacity for a physical activity, but it is intimately tied to the human mind and human imagination:\\nA spider conducts operations that resemble those of a weaver, and a bee puts to shame many an architect in the construction of her cells. But what distinguishes the worst architect from the best of bees is this, that the architect raises his structure in imagination before he erects it in reality (Capital, vol. 1, chap. 7, pt. 1).\\nAlong with the Hegelian dialectic, Marx inherited a disdain for the notion of an underlying invariant human nature. Sometimes Marxists express their views by contrasting \"nature\" with \"history.\" Sometimes they use the phrase \"existence precedes consciousness.\" The point, in either case, is that who a person is, is determined by where and when he is—the social context takes precedence over innate behavior; or, in other words, one of the main features of human nature is adaptability.\\nMarx did not believe that all people worked the same way, or that how one works is entirely personal and individual. Instead, he argued that work is a social activity and that the conditions and forms under and through which people work are socially determined and change over time.\\nMarx\\'s analysis of history is based on his distinction between the means of production, literally those things, such as land, natural resources, and technology and know-how, that are necessary for the production of material goods, and the relations of production, in other words, the social and technical relationships people enter into as they acquire and use the means of production. Together, these comprise the mode of production. Marx observed that within any given society the mode of production changes and that European societies had progressed from a feudal mode of production to a capitalist mode of production. In general, Marx believed that the means of production change more rapidly than production relations (for example, a new technology develops, such as the Internet, and only later are the laws developed to regulate the new technology). For Marx, this mismatch between (economic) base and social superstructure is a major source of social disruption and conflict.\\nMarx understood the \"social relations of production\" to comprise not only relations among individuals, but between or among groups of people, or social classes. As a materialist, Marx did not understand classes as purely subjective (in other words, groups of people who consciously identified with one another). He sought to define classes in terms of objective criteria, such as their access to resources. For Marx, different classes have divergent interests, which is another source of social disruption and conflict.\\nMarx was especially concerned with how people relate to that most fundamental resource of all, their own labor power. Marx wrote extensively about this in his theory of alienation. Marx began with a Hegelian notion of alienation but developed a more materialist conception. For Marx, the possibility that one may give up ownership of one\\'s own labor—one\\'s capacity to transform the world—is tantamount to being alienated from one\\'s own nature; it is a spiritual loss. Marx described this loss in terms of commodity fetishism, in which the things that people produce, commodities, appear to have a life and movement of their own to which humans and their behavior merely adapt. This disguises the fact that the exchange and circulation of commodities really are the product and reflection of social relationships among people. Under capitalism, social relationships of production, such as among workers or between workers and capitalists, are mediated through commodities, including labor, which are bought and sold on the market.\\nCommodity fetishism is an example of what Engels called false consciousness, which is closely related to the understanding of ideology. By \"ideology\" Marx and Engels meant ideas that reflect the interests of a particular class at a particular time in history, but which are presented as universal and eternal. Marx and Engels\\' point was not only that such beliefs are at best half-truths; they serve an important political function. Put another way, the control that one class exercises over the means of production includes not only the production of food or manufactured goods; it includes the production of ideas as well (this provides one possible explanation for why members of a subordinate class may hold ideas contrary to their own interests). Thus, while such ideas may be false, they also reveal in coded form some truth about political relations. According to Marx and Engels, people under capitalism are alienated from their own labor power. one example of this sort of analysis is found in Marx\\'s understanding of religion, summed up in a passage from the Philosophy of Right:\\nReligious suffering is, at one and the same time, the expression of real suffering and a protest against real suffering. Religion is the sigh of the oppressed creature, the heart of a heartless world, and the soul of soulless conditions. It is the opium of the people.\\nWhereas his gymnasium senior thesis argued that the primary social function of religion was to promote solidarity, here Marx sees the social function as a way of expressing and coping with social inequality, thereby maintaining the status quo.\\nCritique of capitalism\\nMarx argued that this alienation of human work (and resulting commodity fetishism) is the defining feature of capitalism. Prior to capitalism, markets existed in Europe where producers and merchants bought and sold commodities. According to Marx, a capitalist mode of production developed in Europe when labor itself became a commodity—when peasants became free to sell their own labor power, and needed to do so because they no longer possessed their own land or the tools necessary to produce a living. People sell their labor power when they accept compensation in return for whatever work they do in a given period of time (in other words, they are not selling the product of their labor, but their capacity to work). In return for selling their labor power they receive money, which allows them to survive. Those who must sell their labor power to live are \"proletarians.\" The person who buys the labor power, generally someone who does own the land and technology to produce, is a \"capitalist\" or \"bourgeoisie.\" (Marx considered this an objective description of capitalism, distinct from any one of a variety of ideological claims of or about capitalism.) The proletarians inevitably outnumber the capitalists.\\nMarx distinguished industrial capitalists from merchant capitalists. Merchants buy goods in one place and sell them in another; more precisely, they buy things in one market and sell them in another. Since the laws of supply and demand operate within given markets, there is often a difference between the price of a commodity in one market and another. Merchants, then, practice arbitrage, and hope to capture the difference between these two markets. According to Marx, industrial capitalists, on the other hand, take advantage of the difference between the labor market and the market for whatever commodity is produced. Marx observed that in practically every successful industry, input unit costs are lower than output unit prices. Marx called the difference \"surplus value\" and argued that this surplus value had its source in the exploitation of laborers, i.e., through paying them \"survival wages\" rather than what they were entitled to receive.\\nThe capitalist mode of production is capable of tremendous growth because the capitalist can, and has an incentive to, reinvest profits in new technologies. Marx considered the capitalist class to be the most revolutionary in history, because it constantly revolutionized the means of production. But Marx argued that capitalism was prone to periodic crises. He suggested that over time, capitalists would invest more and more in new technologies, and less and less in labor. Since Marx believed that surplus value appropriated from labor is the source of profits, he concluded that the rate of profit would fall even as the economy grew. When the rate of profit falls below a certain point, the result would be a recession or depression in which certain sectors of the economy would collapse. Marx believed that during such a crisis the price of labor would also fall, and eventually make possible the investment in new technologies and the growth of new sectors of the economy.\\nMarx believed that this cycle of growth, collapse, and growth would be punctuated by increasingly severe crises. Moreover, he believed that the long-term consequence of this process was necessarily the enrichment and empowerment of the capitalist class and the impoverishment of the proletariat. He argued that if the proletariat would seize the means of production, they would encourage social relations that would benefit everyone equally, and a system of production less vulnerable to periodic crises. In general, Marx thought that peaceful negotiation of this problem was impracticable, and that a massive, well-organized, and violent revolution would in general be required, because the ruling class would not give up power without violence. He theorized that to establish the socialist system, a dictatorship of the proletariat—a period where the needs of the working-class, not of capital, will be the common deciding factor—must be created on a temporary basis. As he wrote in his Critique of the Gotha Program, \"between capitalist and communist society there lies the period of the revolutionary transformation of the one into the other. Corresponding to this is also a political transition period in which the state can be nothing but the revolutionary dictatorship of the proletariat\" [1].\\nMarx saw evil originating in in social relations, or social structure, rather than in human beings. As such, he failed to foresee the selfishness of those in the working class, who after seizing \"the means of production\" would develop a totalitarian system.\\nMarx\\'s influence\\nStatue of Marx and Engels in Alexanderplatz, Berlin. The statues acquired the unofficial nickname \"the Pensioners,\" and were also said to be sitting on their suitcases waiting for permission to emigrate to the West.\\nMarx and Engels\\' work covers a wide range of topics and presents a complex analysis of history and society in terms of class relations. Followers of Marx and Engels have drawn on this work to propose a political and economic philosophy dubbed Marxism. Nevertheless, there have been numerous debates among Marxists over how to interpret Marx\\'s writings and how to apply his concepts to current events and conditions (and it is important to distinguish between \"Marxism\" and \"what Marx believed.\" Essentially, people use the word \"Marxist\" to describe those who rely on Marx\\'s conceptual language (e.g. means of production, class, commodity) to understand capitalist and other societies, or to describe those who believe that a workers\\' revolution is the only means to a communist society. Marxism has influenced Christian thought, too, especially liberation theology, which argues in favor of God\\'s special concern for, or bias towards, the poor and advocates that when the poor become conscious of their exploitation, they will then be empowered to demand and achieve their rights. Liberation theologians do not necessarily support violence as part of this process, although many have.\\nSix years after Marx\\'s death, Engels and others founded the \"Second International\" as a base for continued political activism. This organization collapsed in 1914, in part because some members turned to Edward Bernstein\\'s \"evolutionary\" socialism, and in part because of divisions precipitated by World War I.\\nWorld War I also led to the Russian Revolution and the consequent ascendance of Vladimir Lenin\\'s leadership of the communist movement, embodied in the \"Comintern\" or \"Third International.\" Lenin claimed to be both the philosophical and political heir to Marx, and developed a political program, called Leninism or Bolshevism, which called for revolution organized and led by a centrally organized Communist party.\\nAfter Lenin\\'s death, the Secretary-General of the Communist Party of the Soviet Union, Joseph Stalin, seized control of the Party and state apparatus. He argued that before a worldwide communist revolution would be possible, the Communist Party of the Soviet Union had to dedicate itself to building communism in its own country. People who have not seriously studied Lenin\\'s writings and the brutality of his rule argue that it was Stalin\\'s Soviet Union and its policies that undermined the concept of Marxism in the Western world. However, the collapse of communism stemmed from its underpinnings as well as from its application beginning with Lenin. For many years, especially after the Second World War during the Cold War period, Marxism was popularly equated with Stalin\\'s communism, which was a totalitarianism that disregarded civil rights.\\nStatue of Marx and Engels in Budapest.\\nIn 1929, Leon Trotsky was expelled from the Soviet Union and in 1938 founded the competing \"Fourth International.\" Some followers of Trotsky argued that Stalin had created a bureaucratic state rather than a socialist state.\\nIn China, Mao Zedong also claimed to be an heir to Marx, but argued that peasants and not just workers could play a leading role in a communist revolution. This resonated with Lenin\\'s views in What is to be done? and in the strategy of the Bolshevik revolution which reached out to three constituencies: Laborers, Peasants, and Soldiers, promising the laborers \"bread,\" the peasants \"land,\" and the soldiers \"peace.\" This was a departure from Marx\\'s own view of revolution, which focused exclusively on the urban proletariat. Marx believed revolution would take place in advanced industrial societies such as France, Germany, and England.\\nIn the 1920s and 1930s, a group of dissident Marxists founded the Institute for Social Research in Germany, among them Max Horkheimer, Theodor Adorno, Erich Fromm, and Herbert Marcuse. As a group, these authors are often called the Frankfurt School. Their work is known as critical theory, indebted to Marxist philosophy and the cultural criticism heavily influenced by Hegel, Freud, Nietzsche, and Max Weber.\\nThe Frankfurt School broke with earlier Marxists, including Lenin and Bolshevism in several key ways. First, because of Stalinism and fascism, they had grave doubts about the traditional Marxist concept of proletarian class consciousness. Second, unlike earlier Marxists, especially Lenin, they rejected economic determinism. While highly influential, their work has been criticized by Marxists for divorcing Marxist theory from practical struggle and turning Marxism into a purely academic enterprise.\\nOther influential non-Bolshevik Marxists at that time include Georg Lukacs, Walter Benjamin, and Antonio Gramsci, who along with the Frankfurt School are often known by the term \"Western Marxism.\" Henryk Grossman, who elaborated the mathematical basis of Marx\\'s \"law of capitalist breakdown,\" was another affiliate of the Frankfurt School. Also prominent during this period was the Polish revolutionary Rosa Luxemburg.\\nIn 1949, Paul Sweezy and Leo Huberman founded Monthly Review, a journal and press, to provide an outlet for Marxist thought in the United States independent of the Communist Party of the United States of America.\\nIn 1978, G. A. Cohen attempted to defend Marx\\'s thought as a coherent and scientific theory of history by reconstructing it through the lens of analytic philosophy. This gave birth to \"Analytical Marxism,\" an academic movement which included Jon Elster, Adam Przeworski, and John Roemer.\\n↑ http://www.marxists.org/archive/marx/works/1837-pre/marx/1835chris.htm. Retrieved 10 September, 2008.\\n↑ Richard Wurmbrand. \"Was Marx a Satanist\". Diane Books, 1979. ISBN 978-0882640846\\n↑ http://www.marxists.org/archive/marx/works/1837-pre/verse/verse21.htm. Retrieved 10 September, 2008.\\n↑ http://www.marxists.org/archive/marx/works/1837-pre/letters/37_11_10.htm. Retrieved 10 September, 2008\\n↑ Terrell Carver: \"Marx Myths\"\\nActon, H.B. The Illusion of the Epoch: Marxism-Leninism as a Philosophical Creed. Liberty Fund, 2003. ISBN 978-0865973947\\nBerlin, Isaiah, and Alan Ryan. Karl Marx: His Life and Environment. New York: Oxford University Press, 1996. ISBN 0195103262\\nCohen, G.A. Karl Marx\\'s Theory of History: A Defence (Princeton University Press, 1978) ISBN 0-691-07068-7\\nDraper, Hal. Karl Marx\\'s Theory of Revolution, 4 vols. New York: Monthly Review Press, 1981. ISBN 085345566X\\nGould, Stephen Jay. A Darwinian Gentleman at Marx\\'s Funeral - E. Ray Lankester, page 1, Find Articles.com (1999).\\nKolakowski, Leszek. Main Currents of Marxism: Vol.I The Founder. Oxford: O.U.P., 1978. ISBN 978-0393329438\\nLittle, Daniel. The Scientific Marx. Minneapolis: University of Minnesota Press, 1986. ISBN 0816615055 (Marx\\'s work considered as science)\\nMcLellen, David. Karl Marx: His Life and Thought. New York: HarperCollins, 1978. ISBN 0060905859\\nNicolaevski, Boris, and Otto Maenchen-Helfen. Karl Marx: Man and Fighter. New York: Penguin Books, 1973. ASIN: B0007AEO6Y\\nRubel, Maximilien. Marx Without Myth: A Chronological Study of his Life and Work (Blackwell, 1975) ISBN 0-631-15780-8\\nSchwarzschild, Leopold. The Red Prussian: The Life and Legend of Karl Marx. London: Hamish Hamilton, 1948. ASIN B0013ARB7G\\nWheen, Francis. Karl Marx: A Life. New York: W. W. Norton & Co., 2001. ISBN 0393321576\\nWurmbrand, Richard. \"Was Marx a Satanist\". Diane Books, 1979. ISBN 978-0882640846\\nAll links retrieved April 13, 2018.\\nBibliography and online texts\\nMarx and Engels Internet Archive\\nCritique of Hegel\\'s Philosophy of Right (1843)\\nOn the Jewish Question (1843)\\nComments on James Mill (1844)\\nEconomic and Philosophic Manuscripts of 1844 (1844)\\nTheses on Feuerbach (1845)\\nThe German Ideology [with Engels] (1845 – 1846)\\nThe Poverty of Philosophy (1846 – 1847)\\nWage Labour and Capital (1847)\\nManifesto of the Communist Party [with Engels] (1847 – 1848)\\nGrundrisse (1857 – 1858)\\nA Contribution to the Critique of Political Economy (1859)\\nWritings on the U.S. Civil War [with Engels; compiled] (1861)\\nTheories of Surplus Value, 3 vols. (1862)\\nValue, Price and Profit (1865)\\nCapital vol. 1 (1867)\\nThe Civil War in France (1871)\\nCritique of the Gotha Programme (1875)\\nNotes on Wagner (1883)\\nCapital, vol. 3 [posthumously, by Engels] (1894)\\nLetters [with Engels; compiled] (1833 – 1895)\\nWorks by Karl Marx. Project Gutenberg\\nFranz Mehring, Karl Marx: The Story of His Life\\nFrancis Wheen, The Man Behind the Mask\\nPortraits of Karl Marx\\nStanford Encyclopedia of Philosophy entry\\nErnest Mandel, Karl Marx (New Palgrave article)\\nKarl Marx history\\nHistory of \"Karl Marx\"\\nRetrieved from https://www.newworldencyclopedia.org/p/index.php?title=Karl_Marx&oldid=1010629\\nPoliticians and reformers<|begin_of_text|>Browse the Research Guides using the drop down menu below.\\nBusiness magazines and journals covering a variety of subject areas including financial, pharmaceuticals, manufacturing, and more.\\nFull access McGraw Hill\\'s Encyclopedia of Science, plus research updates in all areas of science and technology.\\nQuickly find your ancestors in over 300 years of historical newspapers. Search over 1,000 newspapers; the American State Papers; US Congressional Serial Set and more. Find obituaries, birth & marriage notices; pension records etc.\\nFull-text articles from 27 U.S. news magazines.\\nABPC is an essential tool for buying, selling and evaluating books, serials, autographs, manuscripts, broadsides, maps and documents, based on actual auction prices in the U.S. and abroad.\\nFrom the explorers of the Americas to today\\'s headlines, investigate the people, events, and themes of our nation\\'s evolution.\\nSearch auto loan rates for new and used cars for both local and national banks and credit unions to find the best deal and check out the loan calculator and education center to learn more about the automotive financing process.\\nProvides practical, comprehensive, and timely coverage of workplace issues and laws, and policies for employers, attorneys, and employees.\\nBook reviews and features from the American Library Association.\\nSearch the availability of current books, audio and video in a database of millions of titles. Also contains full text reviews from standard magazines.\\nIndependent research firm offering high-quality research solutions including industry surveys, stock reports, fund reports, S&P research and The Outlook Newsletter.\\nFind ratings on Chicagoland services and retailers, including dentists, car repair, personal services, banks, and more.\\nCoverage of the full-text paper from 1986 to Current.\\nMicrofilm reproduction of the Chicago Tribune, all editions from 2008 to 3 months ago. Digital microfilm includes every page of every edition of the newspaper, including display ads, legal notices and classifieds.\\nFull page and article images with searchable full text back to the first issue in 1849 to 1994. This collection includes digital reproductions providing access to every page from every available issue.\\nThis automotive repair database includes vacuum and wiring diagrams, service instructions, troubleshooting and diagnostics, and more.\\nHistorical newspaper provides genealogists, researchers and scholars with online, easily-searchable first-hand accounts and unparalleled coverage of the politics, society and events of the time. Coverage from1908 to 2004.\\nIndexes documents published in Latin American journals covering social sciences and humanities as well as science and technology.\\nTurn to this source for an even-handed presentation of opposing views on contentious national questions, Pro & Con.\\nOnline subscription to the popular consumer magazine, plus exclusive online content, including Best Car Deals.\\nunlimited access to more than 1,000 award-winning art & craft video classes taught by recognized design experts and artists.\\nAn online platform that combines reliable, citable reference content with your library\\'s resources and helps you to do faster, more effective research.\\nFull-text coverage from 1995 to Current.\\nFind geographic-based demographic information perfect for business and marketing plans.\\nHome repair, earth-friendly living and utility saving information from the nationally syndicated columnist and do-it-yourself author, James Dulley.\\nAbstracts and selected full text of scholarly journals from 1995 to present, covering subjects such as business, education, geography and law.\\nA massive collection of 100% full-text multidisciplinary periodical and digital media content, designed for middle and high school students, undergraduates at community colleges and universities, instructors, and librarians.\\nContains annotated references to education related articles from 1966 to the present.\\nDiscover Festivals in Illinois. Read festival ratings and reviews, view a calendar, as well as pictures and videos. Find out where your friends are going, get perks..\\nGain access to over 350 million restricted images when you log into your free FamilySearch account inside the library.\\nFrom home you can still log in to access FamilySearch\\'s free resources.\\nInformation on more than 3,400 jobs in 94 industries. Includes sample resumes and cover letters, and tips on interviewing. Also includes 48,000 scholarships and internships for college students.\\nScholarly and general content covering a wide variety of topics including health, education, technology, business, and the social sciences.\\nOffers a wide range of highly interactive, instructor led courses that you can take entirely online. As a library card holder in good standing, you are entitled to these courses at no cost. Courses run for six weeks and new sessions begin every month.\\nDirectories include: Ward\\'s Business Directory, the Encyclopedia of Associations, the Consultants and Consulting Organizations Directory, the Encyclopedia of Business Information Sources, and the Gale Directory of Publications and Broadcast Media.\\nOne-stop shopping for literary assignments and information. Contains criticism, primary sources, literary and cultural analysis, and biographies.\\nSalary details, company reviews, and interview questions — all posted anonymously by employees and job seekers. Visit through the library\\'s link to skip creating your own personal account.\\nThis high quality, full color digital collection of historic maps is one of the most extensive available. The core of the collection consists of over 1.5 million maps of the United States and the world.\\nOnline edition of the recently updated five volume print compendium of historical statistics. Contains over 37,000 data series, on wide-ranging topics. Users may create customized tables and spreadsheets.\\nPrimary and secondary sources on global history from ancient times to the present day, perfect for student reports.\\nFormerly known as Atomic Training, Hoonuit contains on-demand video training for over 500 software applications, including Microsoft Excel, Adobe Photoshop, social media, and more!\\nIllinois Legal Forms includes thousands of business, personal, litigation and federal forms.\\nSource for public records in the Chicago suburbs, including real estate transfers, foreclosures, business licenses and incorporations. We recommend their free background check service called Check Illinois.\\nFrom the Office for Intellectual Freedom of the American Library Association, keep up to date on the news off book bannings and censorship, new policies and reports from the Intellectual Freedom Committee and the Freedom to Read Foundation, and read peer-reviewed articles on privacy and intellectual freedom.\\nFull-text coverage beginning in July 2004 to Current.\\nProvides interactive practice tests, including the SAT, ACT, GED, civil service, military, real estate, teacher certification, and more. Also includes computer skills training and United States citizenship.\\nNews, consumer, business and legal information.\\nCoverage back to the mid-1960s makes this the oldest continuously produced database covering the field of information science.\\nProvides summaries and criticism of books, as well as literary periods, genres, and movements. Includes author biographies.\\nFree online help from tutors for students, as well as resume, GED, and citizenship assistance for adults. Hours: Every day from 10:00 a.m. to midnight.\\nAyuda gratis, en línea, de tutores para estudiantes, y también para resumen, GED, y asistencia de ciudadanía para adultos. Diariamente de 10:00 a.m. hasta la medianoche.\\nWork one-to-one with professional career tutors, drop off your cover letter or resume 24/7 for an overnight review, and access helpful resources for your job search, including resume and cover letter templates. You can also access test preparation materials to prepare to go back to school or for a variety of career-related tests.\\nProvides basic, intermediate, and advanced instruction in 22 languages, as well as 6 ESL courses - offers the standard grammar and vocabulary reviews as well as interactive games to increase retention; also includes specialized courses for vacation and business travelers. Create an account with Living Language to save your progress.\\nThe Newspaper Index is a selective index of articles published in the Kane County Chronicle and the St. Charles Republican newspapers from 1986 to the present. The full text of these articles is available at the Library in print, online or microfilm.\\nIndexes not only top news stories but also the information contained on the various sections of the paper, including complete bibliographic information, companies, people, products, etc. Coverage from 1985 - current.\\nHistorical newspaper provides genealogists, researchers and scholars with online, easily-searchable first-hand accounts and unparalleled coverage of the politics, society and events of the time. Coverage from 1881 to 1994.\\nLeading online learning platform that helps anyone learn business, software, technology and creative skills to achieve personal and professional goals.\\nFind out what magazines, journals, and newspapers the Library subscribes to online, and then link to the correct database to read articles or issues.\\nCovers all areas of medicine, including dentistry and nursing. Includes a mix of articles written for general interest and those in the medical profession.\\nVast, indexed collection of back issues of corporate and industry related documents going back to the beginning of several key Mergent publications including the Million Dollar Directory, municipal manuals, and key business ratios.\\nIncludes repair instructions and diagrams, technical service bulletins, maintenance schedules and cost estimation for various cars and trucks from 1974 to present.\\nFind a stock or mutual fund, research current or prospective holdings, read analysts\\' reports, and see ratings, financial reports, valuation ratios, and key ratios.\\nContains National Geographic magazine 1888-Current, National Geographic Traveler magazine 2010-Current, as well as hundreds of videos, maps, atlases, and other downloadable images.\\nStreaming music that includes over 85,000 tracks, including Classical music, Jazz, World, Folk and Chinese music.\\nNearly unlimited access to the New York Times website including articles from 1851-present day, international editions. Does not include the full crossword puzzle. Simply sign up for a free NYTimes account (if you don\\'t already have one) to access whenever you\\'re in the library.\\nFollow the link to redeem a code for 72 hours of free access to the New York Times on any of your devices. You\\'ll then be guided to register for a free NY Times account (if you don\\'t already have one). When your code runs out, just return to this link to redeem another code. Includes access to articles from 1851-present day, international editions, and the ability to use the NYTimes mobile apps. Does not include the full crossword puzzle.\\nFull page and article images with searchable full text back to the first issue. This collection includes digital reproductions providing access to every page from every available issue.\\nSearch the most recent global news content, as well as archives which stretch back into the 1980s featuring content from newspapers, newswires, and news sites in active full-text format from the US, Canada, Europe, Africa, Asia, Latin America, and Australia.\\nFiction and nonfiction guide for all ages. Find read-alike books and authors, book reviews, book group discussion questions and author websites.\\nMillions of digital resources including books, audio files, images, movies and datasets and texts.\\nHow often have you needed to know the meaning of a word, wondered about its origin, or thought about how you might use it most effectively? Oxford Dictionaries have just one thing in mind: improving communication through an understanding and passion for our living language. Includes reference works on English grammar and usage as well as translation dictionaries for languages such as Italian, Chinese, and Russian.\\nAn irresistible yet authoritative digital database on popular culture in America and the world, both past and present. Great for decades or history projects.\\nan easy-to-use online tool that allows you to create professional quality versions of your book in ePUB, MOBI, PDF and more—all through your library.\\nA valuable research and pricing tool with more than 20 million realized prices, more than 10 million images, and 125 searchable categories.\\nThis unique source shows advertisers-to-agencies \"linkage\", has an in-depth agency database with contacts, and up-to-date agency and advertiser content, as well as a list of available advertising jobs.\\nContains great historical reference books including: Great Lives From History, The Decades In America, and Milestone Documents. A great place to start your research.\\nSanborn maps are large-scale plans of a city or town from 1867-1970. The maps list street blocks and building numbers in use at the time the map was made and previous numbers.\\nTransportation, office work, fundraising, visiting seniors and outreach.\\nA great resource from Cambridge University Press for students and Shakespeare lovers. Since 1948 Survey has published the best international scholarship in English, and many of its essays have become classics of Shakespeare criticism. Each volume is devoted to a theme, or play, or group of plays. The books are illustrated with a variety of Shakespearean images and production photographs.\\nIndustry research, business plans, financial planning, marketing and franchising information for business owners. Great source for business planning.\\nProvides quick and easy access to current and historical census data and demographic information, as well as tools to create maps and reports to illustrate, analyze, and understand demography and social change.\\nIndexes over 260 titles from the most popular teacher and administrator trade journals, periodicals, and books.\\nUpdated weekly and containing thousands of links to a 15-year back-file, Today\\'s Science bridges the gap between the science that students learn in the classroom and the discoveries pushing the boundaries of science today.\\nInformation and advice on over 6,000 stocks, 18,000 mutual funds, 200,000 options and other securities.\\nThe financial newspaper of record offering in-depth coverage of national and international finance as well as first rate coverage of hard news. Access from 1984 - current.\\nHistorical newspaper provides genealogists, researchers and scholars with online, easily-searchable first-hand accounts and unparalleled coverage of the politics, society and events of the time from 1889-2000.\\nIndexes not only top news stories but also the information contained on the various sections of the paper, including complete bibliographic information, companies, people, products, etc. Coverage from 1987 - current.\\nOnline listing of the trusted Weiss guides to stocks, mutual funds and exchange-traded funds (ETFs), banks, credit unions and insurance companies. Also contains the valuable Medigap tool detailing Medicare supplemental insurance options.\\nA 100% full-text database. Retrieve complete articles from thousands of publications in science, the humanities, art, business, and law.\\nWorld History: Modern Era (covering history from the Renaissance to today) is the latest update of electronic history reference materials for high school and high-level middle school coursework.<|begin_of_text|>Aircraft Carriers or Not? Flattops in the Pacific\\nHas the US Lost Myanmar to China?\\nJapan and Myanmar\\'s Toxic Friendship\\nExporting China\\'s Social Credit System to Central Asia\\nJames Soong: The End of an (Authoritarian) Era in Taiwan\\nPrivacy in the Age of Big Brother: India\\nAustralian Bushfires: A Government in Disarray\\nUS-Philippines Ties: The De Lima Dilemma\\n\\'I Could Never Trust Them\\': The China Factor in Taiwan\\'s Youth Vote\\nPhilippines\\' \\'Smart City\\' Threatens Tribal Displacement\\nFeatures | Security\\nA number of countries are building amphibious ships with the potential to operate fixed-wing aircraft. Could an arms race ensue?\\nBy Mike Yeo for The Diplomat\\nCredit: REUTERS/U.S. Navy/Adam K. Thomas\\nThe Pacific region—for this article, the line of nations bordering the Pacific Ocean stretching from Australia to Japan and the Korean Peninsula—has in the past decade or so witnessed a surge in the number of naval ships sporting a \"through deck\" design to allow flight operations to be conducted from their flight decks. Usually classified as amphibious ships or helicopter destroyers/cruisers, they had mostly escaped serious scrutiny in the mainstream consciousness. Until the past few weeks, that is, when a series of events thrust these vessels into global news headlines.\\nExcluding the United States\\' two forward-deployed flattops—the USS George Washington and the USS Bonhomme Richard—in Japan, there are now at least eleven such ships planned, being built or in service among the Asia-Pacific\\'s navies as of today. These ships are officially described as being designed for amphibious operations, while their ability to operate helicopters will also be useful in anti-submarine warfare and to provide aid in Humanitarian Assistance and Disaster Relief (HADR) operations. Still, most are a refit away from (or in China\\'s case, already capable of) operating fixed-wing aircraft, sparking fears of an arms race against the backdrop of simmering territorial disputes in the region.\\nAustralia is currently building two 27,800-ton Canberra-class Landing Helicopter Docks (LHDs) under Joint Project 2048. The ships, HMAS Canberra (LHD-02) and HMAS Adelaide (LHD-01) are based on the Spanish Navy\\'s Juan Carlos I built by Spain\\'s Navantia. The design was the winner of a competition with France\\'s Direction des Constructions Navales (DCN), which offered a larger version of the Mistral class design.\\nThe HMAS Canberra is currently being completed at BAE Systems – Maritime in Melburne after having been initially laid down in Spain and transported by sea to Australia. She will enter service with the Royal Australian Navy in 2014 while her sister ship will join her two years later. The LHDs will replace the HMAS Tobruk and the Kanimbla-class ships in mainly conducting amphibious operations with a secondary HADR brief.\\nEnjoying this article? Click here to subscribe for full access. Just $5 a month.\\nThe Canberra class vessels boast a length of 230.82 metres (757.3 ft), with a maximum beam of 32 metres (105 ft) and maximum draught of 7.08 metres (23.2 ft). Maximum speed is 20 knots, and the LHDs will sport four Rafael Typhoon 25 mm remote weapons systems, six 12.7 mm machine guns, an AN/SLQ-25 Nixie towed torpedo decoy, and a Nulka missile decoy.\\nThe LHDs will be able to carry 1,046 soldiers and their equipment. Two vehicle decks (one for light vehicles, the other for heavy vehicles and tanks) can accommodate up to 110 vehicles. Each ship has a well deck for landing craft, while the flight deck has landing spots for six NH90-class helicopters or four CH-47 Chinook-class helicopters to operate simultaneously. The ships are equipped with a 13° ski jump retained from the Juan Carlos I design, although Australia has no plans to operate fixed-wing aircraft from these ships. The standard air group will typically be a mix of MRH-90 transport helicopters and S-70B Seahawk anti-submarine helicopters. The hangar can accommodate up to 18 helicopters, but eight will be the standard complement.\\nChina is unique in the operators of flight decks in the region in that it is the only regional country to currently operate fixed-wing aircraft from its carriers. The People\\'s Liberation Army – Navy (PLAN) is currently operating the Liaoning, originally destined to be a Admiral Kuznetsov-class multirole aircraft carrier for the Soviet Navy. After an epic history—at one point, it was supposed to become a floating casino—the ship put to sea on August 10, 2011 for the first of several sea trials. The Liaoning is currently based at Qingdao, home of the PLAN\\'s North Sea fleet, where it operates as a training ship.\\nIt is still unclear what Liaoning\\'s air wing will look like, but a clue may lie in the 30-strong complement of the Kuznetsov\\xad-class. The Shenyang J-15 Flying Shark, a Chinese-built navalized derivative of the Sukhoi Su-27 Flanker, has been seen operating on board during the numerous sea trials. As the Liaoning utilizes the STOBAR (Short Take Off Barrier Recovery) method of operating aircraft, heavier aircraft like the JZY-01 carrier-borne AEW under development will not be able to operate from the ship. J-15 operations on board the Liaoning will also be curtailed by fuel and payload limitations due to the ship\\'s STOBAR configuration. Rotary-wing assets include the Changhe Z-8, which also has an AEW variant, and possibly the Kamov Ka-27 Helix.\\nIt was already widely expected that China will be building more carriers after the Liaoning. In late July 2013, photos surfaced of a module of what appears to be an aircraft carrier under construction. The existence of a trench near an edge of the module fuelled speculation that this carrier will be equipped with a CATOBAR (Catapult Assisted Take-Off But Arrested Recovery) system, which China is very keen on developing for its future carrier fleet. However, another image of the Liaoning on a visit to Dalian on further sea trials appears to show a carrier\\'s bow section being built in the background. Interestingly, this looks to be another STOBAR design, with the gradient for a ski jump being quite obvious despite the module being in the shadows.\\nDiplomat Brief\\nGet first-read access to major articles yet to be released, as well as links to thought-provoking commentaries and in-depth articles from our Asia-Pacific correspondents.\\nIn the absence of concrete information, speculation is that the module seen in Shanghai is either a mock-up or construction model built to test and demonstrate the building capabilities of the shipyard to the PLAN. Still other reports have stated that the module is part of the reported Type 081 amphibious assault ship, similar to the U.S Navy\\'s Tarawa-class Landing Helicopter Assault (LHA) ship. The new class will reportedly displace between 30-40,000 tons according to different sources, carry four hovercraft and up to 20 helicopters. Commissioning date is believed to be 2015.\\nWith the Liaoning training up a core of naval and air crew, developing tactics and establishing a doctrine in carrier operations while further carriers are being built, there is little doubt China looks set to be the regional carrier power in the near future.\\nOf all the nations deploying flattops in the Asia-Pacific, undoubtedly the most controversial has been Japan\\'s. Suspicion runs deep in the region about Japan\\'s true intentions despite its pacifist postwar constitution specifically banning the nation from deploying offensive weapons, fuelled by lingering anger over what is perceived as Japan\\'s failure to fully atone for its actions in World War II. With this in mind, the outcry that accompanied each launch of a Japanese flattop, classified as Helicopter-Destroyers (DDH) by the Japan Maritime Self-Defense Force (JMSDF), is always predictable. But that hasn\\'t stopped Japan from being the Asia-Pacific nation with the most flight deck-equipped ships, with four in service or being built.\\nThe JMSDF commissioned the Hyuga and her sister Ise in 2009 and 2011 respectively. Displacing 13,950 tons standard and 19,000 tons fully loaded, the ships are equipped with enhanced command-and-control capabilities, allowing them to serve as flagships for the JMSDF. The ships\\' primary mission is to function as an anti-submarine warfare carrier, and four landing spots for helicopters are provided for on the flight deck, although a maximum of 11 can be carried. The irregular plan form of the flight deck and the location of the forward Phalanx Close-In Weapon System would preclude the Hyuga-class from operating fixed-wing aircraft without a substantial flight deck redesign. The normal helicopter complement is three Sikorsky SH-60K Seahawk antisubmarine helicopters and a single Agusta-Westland MCH-101 Merlin airborne mine countermeasures helicopter; however this can vary depending on the mission.\\nThe JS Hyuga was heavily involved in the HADR effort after the devastating earthquake and tsunami that struck Japan in March 2011. In June 2013, she became the first JMSDF ship to operate the Boeing MV-22B Osprey tiltrotor aircraft during the Dawn Blitz exercise with the U.S. Marine Corps off the coast of California.\\nOn August 6, 2013, Japan followed up with the launch of the JS Izumo, the lead ship of an even larger DDH design. Displacing 19,500 ton empty and 27,000 tons fully loaded, the Izumo and her as-yet unnamed sister will be the largest ships in the JMSDF inventory. Like the Hyuga and Ise before her, the Izumo will also be tasked primarily with anti-submarine warfare. The flight deck has five helicopter landing spots that allow simultaneous landings or take-offs, with a maximum complement of 14 helicopters theoretically possible.\\nExpected to be commissioned in 2015, the Izumo\\'s flight deck does appear to be more easily configurable to operate fixed-wing aircraft than the Hyuga class. Unsurprisingly, the Izumo\\'s launch has sparked controversy, having been described by the Chinese as an \"aircraft-carrier in disguise.\" The fact that neither the Izumo nor Hyuga-class ships are equipped with well docks for landing craft would have increased suspicion that they are designed specifically for aircraft operations.\\nSouth Korea launched the ROKS Dokdo in 2005 and commissioned it two years later. In a move that likely didn\\'t go down well in Tokyo, it took the Korean name of the islands at the center of a territorial dispute with Japan. A multi-purpose ship capable of handling a variety of missions, the Dokdo displaces 14,000 tons empty and 18,000 tons fully loaded. Three ships of the class were planned; however the third vessel was cancelled by a previous government. The second, the ROKS Marado, was to suffer the same fate, but funding was restored in 2012.\\nThe Dokdo class is capable of carrying up to 720 marines and multiple vehicles, while a well dock allows for amphibious assaults. There are five landing spots on her flight deck able to operate helicopters the size of the Sikorsky S-70 Blackhawk/Seahawk, while the hangar can accommodate a maximum of 15 helicopters of various types. The Dokdo was designed specifically to conduct \"Over the Horizon\" amphibious operations, whereby amphibious landing operations with high-speed LCACs and helicopters are launched far from the landing beaches to minimize risks to the landing ship. Her versatility has been demonstrated in 2010, when she was part of a task force conducting search and locate operations for the corvette ROKS Cheonan, which had been sunk in a North Korean sneak attack.\\nIt has been acknowledged that the Dokdo\\'s flight deck has been coated with urethane, which improves the ability of the flight deck to withstand the high temperatures of aircraft operations. However, like the JMSDF\\'s Hyuga-class, her irregular shaped flight deck and positioning of the forward CIWS would require extensive modification before fixed-wing aircraft could operate off her.\\nThailand is the oldest operator of a current carrier in the Asia-Pacific. The HTMS Chakri Naruebet was constructed by Navantia in Spain and commissioned in March 1997. Similar to the Spanish carrier Principe de Asturias, it is fitted with a 12° ski jump to operate the Royal Thai Navy\\'s (RTN) fleet of AV-8S Matador (Harrier) jets. The Chakri Naruebet was originally for Exclusive Economic Zone (EEZ) surveillance and protection and search and rescue, but it could also be used for flagship command and control, air support for the Thai surface fleet or disaster relief.\\nDisplacing almost 11,500 tons full load, the Chakri Naruebet is the smallest aircraft carrier currently in service. She was to operate a mixed air group of Matadors and S-70B Seahawk helicopters, with the RTN purchasing ten former Spanish aircraft for the purpose. However the Asian financial crisis of 1997 put paid to those ambitions, with a lack of funding confining the Chakri Naruebet to port most of the time. The Matador fleet has also suffered accordingly, with the fleet finally being withdrawn from RTN service in 2006.\\nIn recent years the Chakri Naruebet has spent more time at sea, mostly to assist in HADR missions. She took part in relief operations in the aftermath of the 2004 Indian Ocean earthquake and tsunami, and in response to separate flooding incidents in late 2010 and early 2011. In 2012 Saab announced that it had received an order from the Royal Thai Navy for the upgrading of the Chakri Naruebet\\'s command and control system.\\nThe F-35B Question\\nSo are these ships aircraft carriers or not? If you (rightly) consider a helicopter an aircraft, then technically the answer is yes. But to describe these ships as aircraft carriers in the traditional sense of carrying fixed-wing aircraft for offensive purposes, things become murkier. The Liaoning and Chakri are undoubtedly intended to carry fixed-wing aircraft from the outset, even if the latter hasn\\'t done so for a long while now. However, the Canberra and Izumo-class ships, while having a flight deck capable of operating Short Take Off Vertical Landing (STOVL) jets such as the Lockheed-Martin F-35B Joint Strike Fighter, would still require significant modification before they could be operational in that sense.\\nFor starters, the ships will require a thermal-resistant coating applied over the landing spots to protect the deck from the extreme temperatures during the F-35B\\'s landing cycle. Operating fast jets will also mean a large logistics support tail will require to be based on board the ship, with more hangar and storage room being taken by ammunition, spare parts and other support equipment and personnel required to support the jets. All this will require tradeoffs in space on board the ships, which will almost certainly compromise their ability to perform their other intended roles.\\nAnother major stumbling block would be that using aircraft carriers in an offensive capacity requires the carrier itself to be escorted with its own battle group. Currently none of these Pacific navies have the warships, they have yet to fully develop the naval doctrine or tactics required, and they don\\'t have air and ground crews trained to operate in this way. This is all a huge undertaking, requiring years to carry through, even with help from current carrier operators such as the U.S. Navy. Other than China, none of these navies appear to have plans for this in the near future.\\nWhile some have questioned the utility of 12-16 F-35Bs on deck in a conflict, it must be considered that despite the bad press, a fully operational F-35 will represent a game-changer in air combat as we know it. Even a dozen of these aircraft, hypothetically operating from a mini-carrier escorted by a battle group in the vast Western Pacific, will pack serious combat capability and complicate the calculus for any adversary in any conflict. However, the fact is that neither Australia, Japan or South Korea are, or have budgeted for, acquiring the F-35B, even if the former two nations have signed up for the Conventional Take Off and Landing F-35A version.\\nThis brings us to the age old issue: Money. With budgets under pressure in Australia or Japan, neither country is in a position to fund such radical changes in defense posture. Certain alarmist reports notwithstanding, the idea of aircraft carriers from regional countries trading blows in the western Pacific is, to use a maritime term, dead in the water.\\nMike Yeo is a journalist at Baseleg Aviation News and Photography.\\nAsia-Pacific navies\\nflattops\\nHMAS Canberra\\nHTMS Chakri Naruebet\\nJS Izumo\\nROKS Dokdo\\nSouth China Sea: Indonesia\\'s Natuna Sea Dilemma With China\\nHow Asia Will Make Sense of Trump\\'s Strike on Iran\\'s Soleimani\\nAssam\\'s Women at the Frontline of Protests Against India\\'s New Citizenship Law\\nPlay The Diplomat\\'s Quiz: January 19, 2020, Edition\\nPakistan\\'s JF-17 Block III Fighter Jet Makes Maiden Flight\\nYes, the Aircraft Carrier Is Still Viable\\nBy Michael Carl Haas\\nU.S. flattops are not significantly more vulnerable today. It is our frame of reference that has changed.\\nA Mid-2019 Guide to Chinese Aircraft Carriers\\nBy Rick Joe\\nWhat is the future trajectory of the Chinese People\\'s Liberation Army Navy carrier program?\\nChina\\'s Aircraft Carrier Ambitions\\nBy Koh Swee Lean Collin\\nAs the country builds its first indigenous carrier, what might it have in mind?\\nINS Vikramaditya and the Aircraft Carrier Debate\\nBy Abhijit Singh\\nA new carrier like India\\'s does more than just denote blue-water capability.\\nBy Hunter Marston\\nXi\\'s visit bolstered China-Myanmar ties, but the West can still compete.\\nBy Yuzuki Nagakoshi\\nJapan\\'s appeasement policy toward Myanmar, driven by geopolitics and disregard for human rights, is supporting the Rohingya genocide.\\nBy Yau Tsz Yan\\nIs Beijing building a cross-border social engineering system, one software solution at a time?\\nBy Sumithra Prasanna\\nThe BJP\\'s recent moves have fanned fears that it is enacting long-held dreams to create a Hindu nation.\\nWhat\\'s Next for Cambodia\\'s Opposition Politics?\\nBy David Hutt\\nAfter a big week for the country\\'s opposition, a look at what may lie ahead for it as well as Cambodian politics more generally.\\nXi Jinping Warns That China\\'s Coronavirus Outbreak Must Be Taken Seriously\\nChinese authorities reported a sharp rise in the number of cases as they confirmed the disease can be spread between infected people.\\nIndia Stands Up New Su-30MKI Squadron\\nBy Franz-Stefan Gady\\nThe fighter jets of the new squadron are expected to be armed with the air-launched version of the BrahMos supersonic cruise missile.\\nJapan\\'s Leader Vows to Boost Nation\\'s Role in US Alliance\\nJapan\\'s Prime Minister Shinzo Abe pledged Sunday to bolster his country\\'s role under its security pact with the U.S. in \"outer space and cyberspace.\"\\nIndia Test Fires Intermediate-Range, Submarine-Launched Ballistic Missile\\nThe missile launch from a submerged platform off the coast of Andhra Pradesh took place on January 19.<|begin_of_text|>Report 4|60 2.19.22-2.25.22\\nXinhua published the No. 1 central document for 2022, \"Opinions of the Central Committee and State Council on Doing Key Points of Comprehensively Advancing Rural Revitalization Work Well in 2022.\" (See Senior Leaders section)\\nXi Jinping presided over a Politburo meeting on 25 February to discuss the State Council\\'s draft proposal of the \"Government Work Report\" passed by the National People\\'s Congress (NPC) and deliberated on reports on the Central Committee\\'s inspection work, particularly with regards to the financial sector. (See Senior Leaders section)\\nPeople\\'s Daily published an Editorial (社论) on the closing of the 24th Winter Olympic Games in Beijing. (See Propaganda Work section)\\nGeneral Offices of the Central Committee, State Council, and Central Military Commission Release \"Plan for Serving and Supporting Veterans [During] the \\'14th Five-Year [Plan]\\'\"\\n2.20 The General Offices of the Central Committee, State Council, and Central Military Commission (CMC) recently released a \"Plan for Serving and Supporting Veterans During the \\'14th Five-Year [Plan]\\'\" (hereafter referred to as \"the Plan\"). Referring to veterans as an \"important force in the construction of socialist modernization,\" the Plan called doing work related to veterans well as \"our Party\\'s consistent fine tradition.\" It also highlighted \"using Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era as guidance\" and \"thoroughly implementing General Secretary Xi Jinping\\'s important exposition related to veteran work\" to accomplish tasks such as \"promot[ing] the high-quality development of veteran work.\" The Plan has six goals, namely: 1. \"amply give play to the role of political guidance\"; 2. \"comprehensively raise the quality of arranging employment\"; 3. \"[have a] more robust system for the provision of pensions and preferential treatment [to deceased veterans\\' relatives]\"; 4. \"[ensure that] the legitimate rights [of veterans] receive forceful protection\"; 5. \"[realize the] clear upgrading of capabilities to serve and support [veterans]\"; and 6. \"continuously thicken the atmosphere of honor and respect.\" In addition, it listed eight \"important priorities\": 1. \"improve the management system for veteran affairs\"; 2. \"strengthen the political and ideological guidance of veterans\"; 3. \"deepen the reform of the placement system for veterans\"; 4. \"comprehensively promote employment and entrepreneurship opportunities for veterans\"; 5. \"actively upgrade the management level of military retirement service\"; 6. \"[have a] robust guarantee system for the provision of pensions and preferential treatment [to deceased veterans\\' relatives]\"; 7. \"deepen the promotion of praise and commemoration for heroes and martyrs\"; and 8. \"amply give play to the political superiority of two supports work (双拥工作).\" The Plan also called on \"all levels of party committees, governments, and relevant civilian and military departments\" to ensure the implementation of the Plan\\'s goals and tasks.\\n(Authoritative Release) \"Opinions of the Central Committee and State Council on Doing Key Points of Comprehensively Advancing Rural Revitalization Work Well in 2022\"\\n2.22 On 22 February, Xinhua released \"Opinions of the Central Committee and State Council on Doing Key Points of Comprehensively Advancing Rural Revitalization Work Well in 2022\" (hereafter referred to as the \"Opinions\"), issued on 4 January as the No. 1 central document for 2022. The Opinions noted concerns for agriculture related to the pandemic, global economic recovery, and climate change, and the Central Committee\\'s belief that rural revitalization and agricultural policies are important for \"stable and healthy socioeconomic development.\" They stated that work on the \"three rural issues\" (三农/agriculture, rural areas, and farmers) in 2022 should closely follow various aspects of ideological and policy guidance, including following Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era, implementing the spirit of the Party\\'s 19th Congress and Plenums, taking \"protecting national food security and preventing a large-scale return to poverty as the two bottom lines,\" and more. The Opinions specifically noted eight major goals of rural revitalization:\\n\"Grasp staple food production and the supply of important produce with all [our] strength\" by stabilizing year-round planting area and output of staple foods, substantially upgrading the production capacity of soybeans and oil, ensuring a stable supply of foods, ensuring that growing grains is profitable for farmers by adjusting purchasing and subsidies, and holistically regulating important agricultural products well.\\n\"Strengthen support for a modern agricultural base\" by ensuring the productive agricultural use of arable land, accomplishing staged goals for improving farmland, promoting technology for key agricultural issues, improving the development and use of agricultural equipment, developing agricultural facilities, and preventing major agricultural disasters.\\nPrevent a large-scale return to poverty by improving mechanisms to monitor aid, promoting continued increases in income for the rural population, increasing aid to key areas receiving anti-poverty aid or undergoing relocation, and promoting tangible accomplishments in anti-poverty aid.\\n\"Focus on industry to promote rural development\" by continuing to promote the integration of primary, secondary, and tertiary industry in rural areas; developing industries to enrich the people and strengthening the construction of the commerce system on the county level; promoting local employment and entrepreneurship; and promoting the green development of agriculture and rural areas.\\n\"Solidly and stably promote the construction of rural areas\" by making robust mechanisms for implementing rural construction, continuing operations for rural environmental restoration, constructing basic infrastructure in key sectors, promoting a \"digital countryside,\" and strengthening holistic planning for public services at the county level.\\nEffectively improve rural governance by strengthening the construction of grassroots Party groups, innovating \"effective platforms and media for the construction of rural spiritual civilization,\" and upholding the peace and stability of rural society.\\n\"Increase the strength of innovation for policy guarantees and systemic mechanisms\" supporting rural revitalization by expanding investment, strengthening financial services, and strengthening the construction of \"talent teams,\" as well as carrying out key rural reforms.\\n\"Persist in and strengthen the Party\\'s comprehensive leadership of \\'three rural issues\\' work\" by consolidating responsibility for rural revitalization, building strong party structures for rural work, and \"grasping points [from experience or test programs] to lead overall work in comprehensively launching rural revitalization.\"\\nWang Chen: Continuously Develop Whole-Process People\\'s Democracy and Strive to Promote the Construction of the Rule of Law in China\\n2.22 Politburo Member and China Law Society Chair Wang Chen (王晨) attended the 15th China Jurists Forum in Beijing and delivered a keynote speech. In his speech, Wang emphasized that it is necessary to \"adhere to the Party\\'s leadership, the people being the masters of their own affairs\"(当家作主), and governance based on the rule of law; \"constantly develop whole-process people\\'s democracy (全过程人民民主); ensure that the people are the masters of their own affairs by law; and strive to promote building a rule-of-law China with good laws and governance.\" He claimed that \"whole-process people\\'s democracy\" is a major achievement of the Party \"leading the people to advance democratic theoretical innovation, institutional innovation, and practical innovation,\" as well as a \"distinctive feature that distinguishes the democracy of socialism with Chinese characteristics with all kinds of bourgeois democracy (资产阶级民主) in the West.\" Wang further emphasized that the many legal practitioners in China should have a profound understanding of the major concepts of \"whole-process people\\'s democracy,\" should enhance \"historical self-confidence and institutional self-confidence,\" and \"unswervingly follow the path of socialist democratic political development with Chinese characteristics.\" He then called for \"strengthening research and propaganda related to China\\'s national system and legal system, as well as \"actively participating in the practice of socialist democratic rule of law construction.\"\\nPolitburo Discusses Government Work Report, Deliberates on \"19th Central Committee\\'s Eighth Round of Inspections Situation Summary Report,\" \"Key Work of the 2021 Central Committee Inspection Work Leading Group Situation Report,\" Xi Jinping Presides\\n2.25 Xi Jinping presided over a Politburo meeting on 25 February to discuss the State Council\\'s draft proposal of the \"Government Work Report\" passed by the National People\\'s Congress (NPC) and deliberated on a \"19th Central Committee\\'s Eighth Round of Inspections Situation Summary Report\" and \"Key Work of the 2021 Central Committee Inspection Work Leading Group Situation Report.\" The Politburo meeting discussed the achievements and challenges of 2021, and goals in preparation for the upcoming 20th Party Congress. It noted that this year, stability will be the priority of work, requiring greater implementation of macro-economic policies, deepened reform and market stimulus; implementing innovation-driven development policy, increasing domestic demand, and promoting coordinated local development, \"new-type urbanization\" (新型城镇化), agricultural production, and rural revitalization; promoting the stable development of foreign investment and trade, improving the environment and low-carbon development; reducing risks in the financial system; and improving the people\\'s livelihoods and the quality of governance. The Politburo praised the Central Committee\\'s eighth round of inspections for displaying the important function of political supervision, specifically the \"Party Central Committee with Comrade Xi Jinping as the core\" strengthening centralized, unified leadership over financial work. At the same time, the Politburo stated that the inspections uncovered the financial sector\\'s continued problems with \"implementing the Party\\'s comprehensive leadership, strengthening Party construction, [and] comprehensively and strictly [following] party governance (全面从严治党).\" The Politburo emphasized the need for the continued strengthening of Central Committee leadership over the sector and oversight to prevent risks, maintain stability, and prevent corruption. Finally, it fully approved of the Central Committee Inspection Work Leading Group\\'s 2021 work and 2022 plans.\\nPeople\\'s Daily Editorial: Jointly Play the Musical Movement of the Times of Peace, Unity, and Progress\\n2.21 People\\'s Daily published an Editorial (社论) on the closing of the 24th Winter Olympic Games in Beijing. Reviewing the Winter Olympics, the Editorial remarked that Beijing had \"again displayed the positive spirit and power of the Chinese people to the world and wrote a new saga in the Winter Olympics movement.\" Noting that successfully holding the Winter Olympics \"fulfilled China\\'s solemn promise to the world\" and \"injected faith and power into a world [grappling with] the complications of the pandemic,\" it made three observations about the Winter Olympics: First, the Winter Olympics were \"an incomparable (无与伦比) splendid extravaganza\" that saw China\\'s performance encourage the nation through winning numerous medals. Second, the Winter Olympics were \"an extraordinary appointment that was not easy to [keep].\" The Editorial noted that China holding the Winter Olympics in the midst of the global pandemic and ensuring the safety of participants \"displayed the great power of humanity triumphing over difficulties and challenges.\" Third, it stated that the Winter Olympics were an \"outstanding demonstration of the pursuit of perfection.\" The Editorial noted that elements such as venue design and technology set a \"new benchmark for the Olympics.\" Next, it noted that the Winter Olympics showed the importance of cooperation and unity in the face of challenges and stressed three aspirations for readers: 1. \"Let us keep the original aspiration of the Olympic movement firmly in mind and jointly defend world peace\"; 2. \"Let us promote the spirit of the Olympic movement and unite to respond to common challenges [facing] the international community\"; and 3. \"Let us practice the objective of the Olympic movement and continue the undertaking of promoting the progress of mankind.\" After expressing China\\'s intent to continue in endeavors such as being a \"builder of world peace, a contributor to global development, and a defender of international order,\" the Editorial concluded: \"In this season of the recovery of all living things, we are full of pride from the extravaganza of the Beijing Winter Olympics and are full of expectation for the next [Winter Olympic Games]. Let us share the great dream of the Olympics, jointly create the great glory of the Olympics, and set off together toward the more beautiful future of mankind!\"\\nZhong Sheng: [Only By] Adhering to Unity and Cooperation [Can We] Strive Toward a Bright Future\\n2.22 A Zhong Sheng (钟声) commentary focused on the 58th Munich Security Conference held from 18 to 20 February. It noted that the Conference\\'s theme of \"unlearning helplessness\" reflected the \"true social attitude of Western countries\" and was \"the embodiment of Western countries not conducting timely self-adjustment in response to changes unseen in a century (世界百年未有之大变局) due to a lack of policies to respond to global challenges.\" The commentary then gave two recommendations for \"unlearning helplessness.\" First it recommended \"establishing a correct security view that is \"shared, composite, cooperative, and sustainable\" in response to both non-traditional security issues and geopolitical tension that is increasingly global in nature and requires consultation for resolution. Second, the commentary stressed the need to \"safeguard multilateralism and the global order.\" It noted that \"individual countries\" had engaged in actions that included \"reviv[ing] Cold War thinking (冷战思维),\" \"go[ing] in big for unilateral sanctions,\" and \"esteem[ing] hegemony and bullying.\" The commentary asserted that such actions \"run counter to (背道而驰) the major trends of global multi-polarization and the democratization of international relations\" and called for countries to \"jointly construct a new type of international relations\" characterized by \"mutual respect, fairness and justice, and win-win cooperation (合作共赢)\" in addition to delivering other exhortations. Turning to the Conference\\'s special session on how to view China\\'s development, it cited examples such as China\\'s provision of COVID-19 vaccines to more than 120 countries and international organizations and the Belt and Road Initiative (BRI) to show that \"a China that has more superior development quality and stronger capability for action will inevitably offer more energy for global post-pandemic recovery and make greater contributions to international peace and stability.\" The commentary concluded by stating that \"As a permanent member state of the UN Security Council and the world\\'s second-largest economy, China will play the role and function of a responsible major country (负责任大国); continue to be a builder of world peace, contributor to global development, and a defender of the international order; and join hands with all sides to jointly create a more beautiful world in the post-pandemic era.\"\\nWang Yang Presides Over CPPCC National Chairpersons\\' Meeting\\n2.23 Politburo Standing Committee Member and Chinese People\\'s Political Consultative Conference (CPPCC) National Committee Chair Wang Yang (汪洋) presided over and delivered a speech at the 66th Chairperson\\'s meeting of the 13th CPPCC National Committee. The meeting \"conveyed the recent important instructions and spirit of General Secretary Xi Jinping on doing CPPCC work and holding the Fifth meeting of the 13th CPPCC National Committee well\" and listened to a work situation report on preparatory work for the Fifth meeting of the 13th CPPCC National Committee. In his speech, Wang highlighted the need to \"pragmatically and efficiently grasp all organization and preparatory work well [for the Fifth meeting of the 13th CPPCC National Committee]\" and \"do pandemic prevention and control work well\" in order to ensure that the meeting is a success. Turning to the convening of the 20th Party Congress later this year, he discussed conducting activities such as \"telling the stories of the Party seeking happiness for the people and national rejuvenation well and telling stories of multi-party cooperation and political consultation well, to do the work of concentrating power for the 20th Party Congress well.\" Wang also emphasized the importance of \"put[ting] forward high-quality opinions and suggestions\" and \"conducting [reviews of past work] that center around the spirit of the Central CPPCC Work Conference,\" in addition to discussing other actions. The meeting also approved the following documents: 1. \"The CPPCC National Committee 2021 democratic supervision of the implementation of 14th Five Year Plan work situation report,\" 2. \"the launching expert consultation work situation report,\" and 3. the CPPCC National Committee member independent investigation work situation report. The meeting also approved the decision to revoke the seniority of Wang Bin (王滨), Wang Pengjie (王鹏杰), Han Yi (韩沂), and Wei Yihong (魏艺红) as members of the CPPCC National Committee.\\nGeneral Office of the Central Military Commission Issues \"Opinions on Promoting the Establishment of the Base-ification and Standardization of Barracks\"\\n2.23 The General Office of the Central Military Commission (CMC) recently issued a set of Opinions on the standardization and \"base-ification\" (基地化) of barracks. Using Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era as \"guidance\" and \"revolving around constructing a modern military logistics system and a modern military property management system,\" the Opinions aim to help troops prepare for war and resolve issues in barracks construction such as a focus on ordinary life over preparing for and participating in combat. Containing six chapters and 22 articles, the Opinions focus on different types of layouts for bases and barracks. In addition, the Opinions also emphasize the use of features such as \"digital empowerment\" and low-carbon development in barracks design, as well as ways to improve the construction of barracks through methods such as \"guiding market entities to honestly participate in construction.\" The Opinions \"closely revolve around military strategy, training, and defense,\" \"suit the demands of reform and development for the military,\" and \"form methods for standardizing the entire process of barracks construction and management.\"\\n(Authoritative Release) Using the Historical Experience of the Party\\'s Hundred-Year Struggle to Promote the High-Quality Development of Disciplinary Inspection and Supervision Work and Welcome the Victorious Convening of the 20th Party Congress——Work Report at the CCP Sixth Plenum of the 19th Central Commission for Discipline Inspection\\n2.24 Xinhua published the text of Politburo Standing Committee Member and Central Commission for Discipline Inspection (CCDI) Head Zhao Leji\\'s (赵乐际) work report delivered on 18 January at the Sixth Plenum of the 19th CCDI. Reflecting on the CCDI\\'s work in 2021, Zhao highlighted several aspects of the CCDI\\'s work: 1. \"deeply studying and understanding Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era, strengthening political consciousness and the historic momentum of comprehensively and strictly [following] party governance (全面从严治党)\"; 2. \"strengthening political supervision tightly revolving around the \\'two defends\\' (两个维护) and supplying a strong guarantee for beginning the 14th Five Year Plan well\"; 3. \"promoting \\'not daring to be corrupt, being unable to engage in corruption, and not wanting to be corrupt\\' (不敢腐、不能腐、不想腐) throughout [the CCDI], obtaining more systemic results and more effective governance\"; 4. \"pushing the implementation of the spirit of the Central Eight Regulations (中央八项规定) without a moment\\'s rest\" and fighting the \"four forms\" (四风: formalism, bureaucratism, hedonism, and extravagance); 5. intensifying and making full use of inspection tours; 6. working \"according to rules, discipline, and law\" and improving upon supervision, discipline enforcement, and law enforcement; 7. making progress in \"Doing Things for the Masses\" activities and cracking down on corruption and unhealthy tendencies around the masses; and 8. strengthening \"standardization, legalization (法治化), and normalization\" and \"forging high-quality, specialized\" staff. Next, Zhao presented goals for the CCDI for 2022 and the upcoming 20th Party Congress: 1. \"deepen study and implementation of the spirit of the Party\\'s Sixth Plenum, focusing on the \\'big picture and fundamental interests of the country\\' (国之大者) to push for the normalization and concretization of political supervision\"; 2. maintain the strength and resolve of thorough anti-corruption efforts; 3. continue to reinforce the Central Eight Regulations and crackdown on corruption and unhealthy tendencies around the masses; 4. improve the quality and scope of inspection tours; 5. promote reforms to improve the integration, coordination, and effectiveness of the discipline inspection system; and 6. improve political knowledge and skills, serving as \"the Party and the people\\'s loyal guardians.\"\\n2.22 CCP International Department (CCP/ID) Deputy Head Qian Hongshan (钱洪山) held a virtual dialogue meeting with the European Parliament\\'s Party of the European Left (PEL).\\n2.23 CCP/ID Head Song Tao (宋涛) attended the inauguration of the Mwalimu Julius Nyerere Leadership School, based in Tanzania and founded by six southern African political parties, via videolink. Song read a congratulatory letter from Xi Jinping. Tanzania\\'s president Samia Suluhu Hassan and leaders of the school\\'s six founding parties spoke at the event. Congratulatory letters were sent by South Africa\\'s president Cyril Ramaphosa, Mozambique\\'s president Filipe Jacinto Nyusi, Angola\\'s president João Lourenço, Namibia\\'s president Hage Geingob, and Zimbabwe\\'s president Emmerson Mnangagwa, all leaders of their respective parties.\\n2.23 CCP/ID Deputy Head Chen Zhou (陈洲) held a video call with former Prime Minister and current chairman of the Communist Party of Nepal (Unified Socialist) Madhav Kumar Nepal.\\n2.23 CCP/ID Deputy Head Shen Beili (沈蓓莉) held a video call with Nicaragua\\'s vice-foreign minister and Sandinista National Liberation Front (FSLN) representative Arlette Cristina Marenco Meza.<|begin_of_text|>Q: RxJava 2 mock Observable doesn\\'t work I use RxJava 2 Observable to wrap barcode scanner in one of my app. This snippet show how I subscribe to Observable and listen to it\\'s events\\noverride fun start() {\\n    disposables.addAll(subscribeToBarcodeReader(), loadUser())\\n}\\n\\nprivate fun subscribeToBarcodeReader(): Disposable {\\n    return barcodeObservable\\n       .subscribeOn(bgScheduler)\\n       .observeOn(mainScheduler)\\n       .subscribeBy(\\n                onNext = { barcode -> saveBarcode(barcode) },\\n                onComplete = { Log.d(TAG, \"Barcode observable complete\") },\\n                onError = { e -> Log.d(TAG, \"Barcode observable error\", e) }\\n        )\\n}\\n\\nbarcodeObservable is object of Observable<Barcode> type. This all works fine on real device with real barcode scanner. Now I want to unit test the saveBarcode() method and try to mock the Observable<Barcode> this way\\n@RunWith(MockitoJUnitRunner::class)\\nclass OrbFoldersPresenterTests {\\n\\n    @Mock\\n    private lateinit var jobService: FolderJobService\\n    private val bgScheduler = TestScheduler()\\n    private val mainScheduler = TestScheduler()\\n    private val barcodeObservable: Observable<Barcode> = Observable.just(Barcode(\\n            \"2500020109205\", LocalDateTime.now().toString()))\\n    @Mock\\n    private lateinit var userStore: UserStore\\n    @Mock\\n    private lateinit var prefs: Preferences\\n    @Mock\\n    private lateinit var barcodeService: BarcodeReadService\\n\\n    @Test\\n    fun testBarcodeSave() {\\n        val jobId = 201804040001\\n        val disposables = CompositeDisposable()\\n\\n        whenever(userStore.authorizedUser()).thenReturn(Maybe.just(User()))\\n\\n        val presenter = OrbFoldersPresenter(jobId, jobService, disposables, bgScheduler,\\n                mainScheduler, barcodeObservable, userStore, prefs, barcodeService)\\n        presenter.start()\\n    }\\n}\\n\\nI\\'m expecting that when I call presenter.start() presenter must subscribe to barcodeObservable and receive onNext() event with object I\\'ve provided. But this isn\\'t happening. What am I doing wrong? \\n\\nA: The TestScheduler is useful if you need to test timing with your streams. Since your only concern with your implementation should be to run the stream synchronously, you should better use a Schedulers.trampoline() instead. This will then call subscription and observation without a thread change.\\n\\nA: There\\'s asynchronous processing going on because of subscribing and observing on given schedulers. onNext() does not get invoked synchronously as expected by your test code.\\nWith a TestScheduler, you can e.g. call triggerActions() or advanceTimeBy() to execute asynchronous code.\\n<|begin_of_text|>OECD Guideline 211 (Daphnia magna Reproduction Test)\\nThe substance was stored under ambient conditions.\\nThe test substance, a solid, was identified as: F-3014;\\nBatch number 290130349;\\nCAS number 158725-44-1.\\nThe test substance had an expiration date of July, 2017\\n- Sampling method: Duplicate samples were collected from each treatment and control group eight and nine days prior to the start of the test after conditioning the diluter for three and two days, respectively. Additional samples were collected from the negative and solvent control groups prior to test initiation to confirm there were not measured concentrations of test substance in the control solutions. Duplicate water samples also were collected from alternating replicate test chambers in each treatment and control group at the beginning of the test, at approximately weekly intervals during the test and at the end of the test to measure concentrations of the test substance. Samples of the stock solutions being delivered to the diluter were collected for analysis on Day 11 of the study. Additional duplicate samples of test solutions were collected on Day 14 due to a test solution delivery malfunction which impacted one replicate test chamber\\nof the 25, 50 and 100 μg/L treatment groups. All samples were collected from mid-depth. Samples to be analyzed without centrifugation were collected into glass French square bottles using glass volumetric pipettes, while samples to be analyzed after centrifugation were collected into plastic centrifuge tubesusing glass graduated cylinders.\\n- Sample storage conditions before analysis:At each sampling interval one set of samples were processed immediately for analysis and one set of samples were stored for possible future analysis.\\n- Method: Individual stock solutions were prepared for each of the five concentrations tested, and were prepared six times during the study. Test solution concentrations were not adjusted for the active ingredient of the test substance during preparation, and are based on the test substance as received. The primary stock was sonicatedfor approximately 10 or 15 minutes and appeared clear and colorless, with no visible precipitates. Four secondary stock solutions were prepared in DMF at nominal concentrations of 63, 130, 250 and 500 μg/mL by proportional dilution of the primary stock. Stock solutions were stored refrigerated in glass amber bottles with Teflon®-lined lids, and aliquots of each stock were placed in the syringe every one to four days during the study.\\nThe five test substance stock solutions were injected into the diluter mixing chambers at a rate of 10.00 μL/minute where they were mixed with dilution water delivered at a rate of 100 mL/minute to achieve the desired test concentrations.\\n- Controls: The negative control received dilution water only. The solvent control was prepared by delivering HPLC-grade DMF to the mixing chamber for the solvent control.\\n- Chemical name of vehicle (organic solvent, emulsifier or dispersant):dimethylformamide (DMF)\\n- Concentration of vehicle in test medium (stock solution and final test solution(s) or suspension(s) including control(s)):A primary stock solution was prepared by mixing a calculated amount of test substance into HPLC-grade dimethylformamide (DMF) at a nominal concentration of 1000 μg/mL. The concentration of DMF in the solvent control and all F-3014 treatment groups was 0.1 mL/L.\\n- Evidence of undissolved material (e.g. precipitate, surface film, etc.):The stock solutions were mixed by inversion, and appeared clear and colorless.\\n- Common name: Daphnia magna\\n- Strain/clone: cladoceran\\n- Justification for species other than prescribed by test guideline: no\\n- Source: cultures maintained by EAG Laboratories, Easton, Maryland\\n- Age of parental stock (mean and range, SD): Daphnid neonates used in the test were less than 24 hours old\\n- Feeding during test: yes\\n- Food type: mixture of yeast, cereal grass media, and trout chow (YCT), supplemented with a vitamin stock solution and a suspension of the freshwater green alga, Raphidocelis subcapitata.\\n- Amount:At each feeding, each test chamber was fed 0.75 mL of YCT, 1.5 mL of algae and 0.50 mL of vitamin solution. This amount of feed is equal to approximately 0.71 mg C/daphnid/day. While this amount of feed exceeds the OECD guideline recommended amount of 0.1 to 0.2 mg C/daphnid/day, an excess amount was fed in order to maintain sufficient feed in the flow-through system to support acceptable reproduction rates.\\n- Frequency: Daphnids were fed two or three times per day through Day 6 of the test and then were fed four times per day until the last day of the test.\\n- Acclimation period:\\n- Acclimation conditions (same as test or not):Adult daphnids were cultured in water from the same source and at approximately the same temperature as used during the test.\\n- Type and amount of food: as in the test\\n- Feeding frequency: as in the test\\n- Health during acclimation (any mortality observed):Adult daphnids in the culture had produced an average of at least three young per adult per day over the 7-day period prior to the test. The adults showed no signs of disease or stress and no ephippia were produced during the holding period.\\nMETHOD FOR PREPARATION AND COLLECTION OF EARLY INSTARS OR OTHER LIFE STAGES:\\nThe five adult daphnids used to supply neonates for the test were held for 24 days prior to collection of the juveniles for testing, and had each produced at least one previous brood.. To initiate the test, the juvenile daphnids were collected from the cultures and indiscriminately transferred one or two at a time to transfer chambers until each chamber contained 5 daphnids. Each group of neonates then was impartially assigned to a control or treatment group and the neonates were transferred to the test compartments to initiate the test. All transfers were made below the water surface using wide-bore pipettes.\\nflow-through\\nRemarks on exposure duration:\\n21-day exposure period under flow-through test conditions. The delivery system and the test chambers were placed in a temperature-controlled environmental chamber to maintain the target water temperature throughout the test period.\\n140-148 (mg/L as CaCO3)\\n20-21 oC\\n18.3 mg/L as sodium\\nConductivity:\\n328-382 (μS/cm)\\nTEST CONCENTRATIONS:\\nNominal Mean Measured\\nNegative Control < LOQ\\nSolvent Control < LOQ\\n6.3 µg/L 6.6 µg/L\\n13 µg/L 9.9 µg/L\\n25 µg/L 24 µg/L\\n100 µg/L 102 µg/L\\n- Test vessel: Test compartments were 300 mL glass beakers.\\n- Type (delete if not applicable): open\\n- Material, size, headspace, fill volume: Test compartments were 300 mL glass beakers, approximately 6.5 cm in diameter and 12 cm in height. Nylon mesh screens covered two holes on opposite sides of each test compartment to permit test solution to flow in and out of the compartment. The depth of the test water in a representative compartment was approximately 8 cm, while the depth of water in a representative test chamber was approximately 16 cm.\\n- Aeration: Dissolved oxygen concentrations were \\uf0b37.4 mg/L (\\uf0b382% of saturation),\\n- Type of flow-through (e.g. peristaltic or proportional diluter): proportional diluter. Test chambers were 12 L glass aquaria filled with approximately 10 L of test water. The volume in the test chambers was maintained by an overflow port on the side of the test chamber.\\n- Renewal rate of test solution (frequency/flow rate):The proportion of the test solution that was pumped into each replicate test chamber was checked prior to the test and approximately weekly during the test to ensure that flow rates varied by no more than ± 5% of the mean flow rate for the replicates. The five test substance stock solutions were injected into the diluter mixing chambers at a rate of 10.00 μL/minute where they were mixed with dilution water delivered at a rate of 100 mL/minute to achieve the desired test concentrations. The negative control received dilution water only. The solvent control was prepared by delivering HPLC-grade DMF to the mixing chamber for the solvent control. The concentration of DMF in the solvent control and all F-3014 treatment groups was 0.1 mL/L.\\n- No. of organisms per vessel: Each replicate contained two compartments with five daphnids, resulting in a total of 20 daphnids in each treatment and control group\\n- No. of vessels per vehicle control (replicates): 2\\n- Biomass loading rate:\\n- Source/preparation of dilution water:Easton Well Water\\n- Total organic carbon:< 1\\n- Particulate matter:\\n- Metals: Tables presented in \"Any other information on materials and methods\" below\\n- Pesticides:Tables presented in \"Any other information on materials and methods\" below\\n- Chlorine:4.3mg/L\\n- Alkalinity:176 – 178 mg/L as CaCO3\\n- Ca/mg ratio:\\n- Conductivity:321 – 367μS/cm\\n- Culture medium different from test medium:\\n- Intervals of water quality measurement: During the 4-Week Period Immediately Preceding the Test\\nPesticides, Organics and Metals - Analyses performed by Lancaster Laboratories on samples collected on December 7, 2015\\n- Photoperiod:16 hours of light and 8 hours of darkness. A 30-minute transition period of low light intensity was provided when lights went on and off to avoid sudden changes in lighting.\\n- Light intensity:1160 lux at the surface of the water\\n- Spacing factor for test concentrations:\\n- Justification for using less concentrations than requested by guideline:\\n- Range finding study: yes\\n- Test concentrations: 8.1, 27, 90 300, 1000 mg/L\\n- Results used to determine the conditions for the definitive study:nominal test concentrations were 6.3, 13, 25, 50 and 100 μg F-3014/L.\\nNOEC\\n102 µg/L\\nmeas. (initial)\\ntest mat.\\nLOEC\\n> 102 µg/L\\number of neonates produced per reproductive day and number of neonates produced per live adult at beginning of the test\\n- Behavioural abnormalities: Daphnids in the control and treatment groups that survived to test termination generally appeared normal throughout the test. There were a few observations of daphnids in the treatment groups that appeared pale, lethargic or were observed to be floating on the surface of the test solution. However, these observations were infrequent, comparable to observations in the control groups and did not follow a dose-response pattern. Therefore, these observations considered to be non-treatment related.\\n- Observations on body length and weight:Daphnids in the negative control group averaged 5.1 mm in length and 1.29 mg in dry weight, while daphnids in the solvent control group averaged 5.1 mm in length and 1.38 mg in dry weight. There were no significant differences in the growth parameters between the negative and solvent control groups (p > 0.05). Therefore, the control data were pooled for comparison with the treatment groups. Daphnids in the pooled control and the 6.6, 9.9, 24, 60 and 102 μg/L treatment groups had mean\\nlengths of 5.1, 5.1, 4.9, 5.0, 5.0 and 5.0 mm, respectively, and mean dry weights of 1.33, 1.19, 1.34, 1.32, 1.18 and 1.33 mg, respectively. According to Dunnett\\'s test, there were statistically significant decreases in mean length for the 9.9, 24 and 60 μg/L treatment groups in comparison to the pooled control (p ≤ 0.05). However, the differences were very slight (< 4%), did not follow a dose-response pattern and were likely due to the narrow standard deviations within each set of data. Therefore, the statistically significant decreases detected in the treatment groups were not considered to be biologically meaningful. There were no statistically significant decreases in mean dry weight for any F-3014 treatment group in comparison to the pooled control according to Dunnett\\'s test (p > 0.05). Consequently, the NOEC for growth (length and dry weight) was 102 μg/L, and the LOEC was >102 μg/L, the highest concentration tested.\\n- Other biological observations:Adult daphnids in the pooled control and the 6.6, 9.9, 24, 60 and 102 μg/L treatment groups produced an average of 229, 213, 210, 212, 264 and 195 live young per adult at the beginning of the test, respectively. Dunnett\\'s one-tailed test indicated there were no statistically significant decreases in the mean number of live young produced per adult at the beginning of the test in any F-3014 treatment group in comparison to the pooled control (p > 0.05). Consequently, based on the number of live young produced per adult at the beginning of the test, the NOEC was 102 μg/L and the LOEC was >102 μg/L, the highest concentration tested. Based on the number of live young produced per adult at the beginning of the test observed in the treatment groups, the 21-day EC10 and EC50 values were both determined to be >102 μg/L, the highest concentration tested.\\n- Mortality of control:After 21 days of exposure, survival in the negative control and solvent control groups was 90.0 and 95.0%, respectively. Since there were no statistically significant differences in survival between the negative and solvent control groups for any parameter tested (p > 0.05), the control data were pooled for comparisons to the treatment groups.\\n- Other adverse effects control:\\n- Abnormal responses:\\n- Any observations (e.g. precipitation) that might cause a difference between measured and nominal values:\\n- Effect concentrations exceeding solubility of substance in test medium: In the study concentartion exceed the water solubility of the substance (<1 μg/L) by at least two orders of magnitude using DMF as a carrier. \"When a laboratory test design has been specifically modified to accommodate the instability of test material or other factors likely to cause variability in test concentrations, and the design is judged adequate based on sufficient preliminary information, the study will not be rejected solely on the grounds that measured concentrations varied by more than 30 percent of the nominal concentration…The most important criterion is that the test levels must not experience a shift in \"order\". That is, the highest test level should remain highest, the next should remain second, etc.\" (9). There were no inversions of measured concentrations throughout the study. Therefore, the high variability in measured concentrations should not impact the interpretation of the study results.\\nThe cladoceran, Daphnia magna, was exposed to F-3014 at mean measured concentrations of 6.6 to 102 μg/L under flow-through conditions for 21 days. The substance concentartions exceed the water solubility value (<1 μg/L) by at least two orders of magnitude using DMF as a carrier. Nevertheless, there were no biologically meaningful, statistically significant treatment-related effects on survival, reproduction or growth at concentrations ≤102 μg/L. Consequently, the NOEC, was determined to be 102 μg/L. The LOEC and MATCH were both determined to be >102 μg/L, the highest concentration tested.\\nThe 21-day EC50 value for adult immobility was determined to be >102 μg/L, the highest concentration tested. Based on the number of live young produced per reproductive day, the 21-day EC10 and EC50 values were determined to be >102 μg/L. Based on the number of live young produced per adult at the beginning of the test, the 21-day EC10 and EC50 values were determined to be >102 μg/L.\\nThe cladoceran, Daphnia magna, was exposed to F-3014 at mean measured concentrations of 6.6 to 102 μg/L under flow-through conditions for 21 days. The substance concentartions exceed the water solubility value (<1 μg/L) by at least two orders of magnitude using DMF as a carrier. Nevertheless, there were no biologically meaningful, statistically significant treatment-related effects on survival, reproduction or growth at concentrations ≤102 μg/L.<|begin_of_text|>Ranton Abbey to be resurrected – or replaced?\\nWhen the historic Ranton Abbey was accidentally set alight and gutted in 1942 by the Dutch troops stationed there, it was likely that it would go the way of many other houses and simply be demolished. Yet the Earls of Lichfield, who owned the 300-acre estate, simply left it and focused on turning the land into a first-class shoot, allowing the house to slowly collapse, leaving just the ivy-clad walls visible today.\\nThe death of the 5th Earl, the famous photographer Patrick Lichfield, in 2005, prompted the family to look again at the estate. However, rather than simply sell it they decided to obtain planning permission for the building of a new house and have now put both for sale at £3.5m. Although an obvious course of action, the choices made seem a bit odd. The new house is strongly Palladian in design but the projections produced so far have it sited so close to the red-brick shell of the old house, and the grey stone of the church, that it seems to have almost landed there by accident. It certainly does not seem to appear at home in this location and appears almost arbitrary, resulting in three large architectural elements fighting for prominence in a small area.\\nAs the respected architectural writer Marcus Binney says in the \\'Bricks and Mortar\\' supplement of Friday\\'s Times newspaper, surely the better option would be to restore the original house. This would bring back the balance which existed before and remove at once the obvious difficulties of leaving the old house as a giant garden ornament to compete with the new house. Whoever buys the estate and planning permission will hopefully think again about this scheme and look seriously at restoration.\\nThis entry was posted in for sale, News and tagged architecture, country house, estate, fire, for sale, lord lichfield, marcus binney, planning permission, ranton abbey, restoration, staffordshire. Bookmark the permalink.\\n6 Responses to Ranton Abbey to be resurrected – or replaced?\\nI agree with everything you have said here.restoring the old house itself is surely more logical than the new one proposed.I have been researching the abbey for years now evr since going there as achil when I liveds in the local village. It is rich in history and to restore the old house would surely salute the past in all its glory.\\nHaving visited Ranton only a couple of weeks ago, I was struck by just how big the shell of the original house is. Why anyone would want to destroy good Regency craftsmanship and replace it with a classic \\'noveau-riche\\' Palladian building completely stumps me.\\nI have studied the Knight Frank brochure and all the pictures I can get hold of, and also bought a few lottery tickets, in the vain hope of being the lucky person that gets to restore a great house within the most wonderful parkland.<|begin_of_text|>To enable it: go to the Beta features tab of your Preferences and choose Visual editing.\\nTo choose your editing setting: go to the Editing tab, find Editing mode: and pick your favorite setting. You can choose whether you only want to see the visual editor tab, or if you prefer to get both the \"Edit source\" and the \"Edit\" tabs (the former will launch the wikitext editor; the latter will open the visual one).\\nYou can learn more about the \"single edit tab\" system at mediawiki.org. That page details how to switch between editors via the buttons on the toolbars.\\nAll edits using the visual editor will be tagged with \"Visual edit\" in recent changes, watchlists, and page histories. To access the User Guide for the visual editor, click on the \"(?)\" icon in its toolbar. If you wish to change your editing setting or to disable the visual editor, this can be done under \"Editing\" in your preferences.\\nThere is a short guide at mediawiki.org that you can follow (as if it was a \"checklist\") to learn about the community work necessary to adapt the visual editor, and its referencing system in particular, to your community\\'s needs.\\nIf you can translate from English into other languages, or know anyone who can, please follow the links below. You\\'ll help your community get the best possible experience when it comes to interface messages and documentation related to the visual editor. After you click on any links, your language should be available from the drop-down menu on the right. Once you\\'ve selected it, you\\'ll see the document in English side by side with any translation work already done in your language. You can add new translations or modify existing ones. The interface is hosted at https://translatewiki.net; you\\'ll need an account if you never translated there before. The user guide lives at MediaWiki.org, for which you can use your regular Wikipedia account. You\\'re welcome to contact a community liaison whenever you need help.\\nPlease report issues, if any, in Phabricator, the new bug tracking system or on the central feedback page (in any language) on mediawiki.org. There is also a dedicated thread on the English Wikisource. In case of emergency (like an unexpected bug causing widespread problems), please contact James Forrester, Product Manager for the visual editor, at jforrester@wikimedia.org or on IRC in the #mediawiki-visualeditor connect channel.\\nDeploying the visual editor at Wikisource has been possible thanks to recent efforts of volunteer developers Tpt and Coren, supported by Catrope, Jdlrobson and Jdforrester at the Wikimedia Hackathon 2016.<|begin_of_text|>Wine & Dine Roundup: Korean Feast!\\nKorea is a country with an amazing cuisine and history... and for this month\\'s Wine & Dine event, my friends and I celebrated Korea and their delicious eats.\\nKorean cuisine has evolved through the centuries of social and political change, through it\\'s environment and cultural trends. If you\\'ve ever dined at a Korean restaurant, one thing that you\\'ll experience is the various banchan, or small side dishes, that are served immediately while you wait for your meal to arrive. This cuisine is also known for the popular condiment, kim chi.\\nIn many ways, Korean cuisine is a combination of Japanese and Chinese cuisines, however unlike Japanese cuisine, Korean cuisine uses less fish and seafood and has more beef and pork heavy dishes... and unlike Chinese cuisine, Korean cuisine uses less oil. Korean foods also tend to be spicier than Japanese and Chinese dishes. The heat of the food usually comes from the chili that\\'s often used.\\nJust as in sake is in Japanese cuisine, soju is in Korean cuisine. For our Wine & Dine dinner, I also offered a soju tasting to pair with our Korean meal. Soju is an alcoholic drink which has a similar taste as vodka. Soju is unique in that it can be made from either rice, barley, sweet potato or a combination of these ingredients.\\nHere are the dishes that fellow food bloggers have submitted to my virtual Wine & Dine event! To check out what my friends and I feasted on for our dinner, feel free to check out our spread and recipes HERE. Thanks to all my fellow food bloggers for their submissions and I hope you give Korean cuisine a try soon!\\new\\'re starting this round up with a video by Greg! You may have remembered his previous videos for a previous Tasty Tool event featuring the food processor where he made butter. This time, he shares another video on Kim Chi! Check out his blog for the full video!\\nWhat is a Korean Feast round up without a bulgogi recipe to share?! Thankfully Renee is joining us to share this recipe for Korean bulgogi. It\\'s a delicious dish of marinated beef that involves using an Asian pear (which is a key ingredient!). Check out Renee\\'s blog for the recipe!\\nI really think rice is a magic ingredient because from it, you can get milk, flour, noodles, and these Korean Rice Pinkies. This is a type of chewy rice cake that is quite delicious! Nancy has shared this with us for the round up and it\\'s a great dish to try, especially when topped with a runny fried egg! Check out Nancy\\'s blog for the recipe!\\nI\\'m a big fan of eggplant (especially Japanese eggplant), possibly because I grew up eating it fresh from my mom\\'s garden. So it\\'s no surprise that I would be a fan of Christine\\'s entry of Gaji Namul. This eggplant recipe is made by steaming, which not only delicious but healthy too!\\nSuzanne was determined to get the perfect pajeon by testing out a few recipes and she finally got the recipe for the perfect texture she was looking for! To check out what recipe worked for her and also the announcement of some exciting news, please check her blog!\\nNing joins us from Philippines to submit this delicious Kim Chi Fried Rice. I\\'d love to know her secret for the perfect fried egg that so delicious topped her fried rice! I\\'m always looking for ways to jazz up my fried rice (as I\\'m tend to use leftovers on hand) and kim chi sounds like a wonderful way to spice up rice with a Korean twist! Check out Ning\\'s blog for the recipe!\\nChristine is definitely the life of this Korean party! She\\'s shared with us this recipe for oyster & scalion pancake. It\\'s a great dish for an appetizer as well as enough for a hearty meal. Be sure to check out Christine\\'s blog for this recipe along with the following delicious Korean dishes as well!<|begin_of_text|>Women still denied fair share of top jobs in civil service worldwide\\n28 Jan Women still denied fair share of top jobs in civil service worldwide\\nReport shows women\\'s numbers quickly drop off at senior levels – even among league leaders Canada and Australia\\nFor the 233,000 or so women employed in the UK civil service, there was some good news last week. Recent concerted efforts to increase the number of senior women in central government have paid off. Civil servants, of any gender, can be proud that they work for the organisation with the highest number of female senior officials in Europe and the fourth-highest of the G20 countries.\\nCompiled by consultants, EY, the most recent index of female officials in senior central government posts shows Canada comfortably in the lead when it comes to promoting women to its most senior posts. But the index also shows that there is not a single G20 country where 50% of top government posts are held by women.\\nRead the rest of the article by clicking here<|begin_of_text|>WCRC Legacy Scholarship\\nThe \"Western Canadian Ringette Championships Legacy Scholarship\" is awarded to a Ringette player who is a current or former resident of Calgary, is attending a Canadian post-secondary institute on a full-time basis, and who combines academic excellence with a strong commitment to the sport of Ringette.\\nApplicants are required to fill out the Application Form which includes details of their Ringette career and volunteer experience. Proof of attendance at a Canadian post-secondary institution is required.\\nTwo yearly $1000 scholarships will be awarded at the Ringette Calgary Annual General Meeting in May of each season.\\nThe applicant must be enrolled full-time and currently attending a recognized Canadian post-secondary Institution. (ie. universities, community colleges, technical institutions)\\nThe applicant must be registered to play Ringette in the current playing season.\\nApplicants must have resided and registered within Ringette Calgary Association (Zone 3) as a player for at least 5 seasons. (BV, SCalgary, NW, CalEast, AA, CORA)\\nApplicants will be scored based on their commitment to the sport of Ringette through playing, coaching, officiating and other volunteer activities as well as school and community participation and service.\\nYou may apply for the scholarship annually but are only eligible to win the scholarship one time.\\nApplications are now being accepted for the 2020-21 school year.\\nThe deadline for applications is April 20, 2021.<|begin_of_text|>The financial services industry is a hotbed of disruption but instead of viewing the entry of new players into the space as a case of \\'us\\' versus \\'them\\', the smart operators are welcoming and learning from the competition.\\nMeeting unmet needs, and the digitisation of services, are at the heart of disruption in the sector. The perfect example of these two factors coming together is Afterpay. The business, which launched in 2014, is the brainchild of 27-year-old Australian entrepreneur Nick Molnar and digitises the old-fashioned system of layby which saw shoppers pay off goods in installments.\\n\"What we\\'re really doing is replacing the bank of mum and dad, helping small businesses that would have had to go under or wouldn\\'t have been able to grow\"\\n\"They\\'ve grown their footprint quite aggressively and quickly. They\\'ve really identified an unmet customer need and it highlights how we need to do a better job of promoting what we can bring to the table in terms of our own short-term lending capabilities,\" says Newcomb.\\nAfterpay demonstrates the opportunity for new services in the lending space. Another business tapping into this is small business loan provider Prospa. The five-year-old company has recently reached the milestone of issuing 10,000 loans to small business owners to the tune of $350 million. \"We\\'re on a mission to change the way small business owners experience finance,\" says Anna Fitzgerald, senior marketing manager at Prospa.\\nWhile it may appear Prospa is playing in a space traditional banks have long owned, as Fitzgerald points out, there has long been an unserviced customer base.\\n\"There is something like 2.1 million small business in Australia and traditionally, banks have not lent to that sector because they didn\\'t have the risk appetite for it. What we\\'re really doing is replacing the bank of mum and dad, helping small businesses that would have had to go under or wouldn\\'t have been able to grow,\" says Fitzgerald.\\n\"I don\\'t think the amount of time that you\\'ve been around is necessarily going to give you an advantage – it\\'s the culture you develop and the way you innovate as an organisation.\"\\nBy tapping into a client base banks have been unable to service opens up the opportunity for a partnership between the startup and traditional financial organisations. Accordingly, Prospa has forged a partnership with Westpac.\\n\"We\\'re running a pilot program so that when they\\'re unable to help a small business customer because they don\\'t have a product that suits their requirements, they refer them to us,\" explains Fitzgerald.\\nAs Net Promoter Scores for traditional banking organisations continue to languish in the negative digits, Fitzgerald believes banks can benefit from teaming up with startups such as Prospa which is seeing NPS ranging from 30 to 70, even in instances when the loan application is not approved.\\n\"The two key things we offer are speed and simplicity,\" she says.\\nCatch more of the world\\'s brightest minds at Global Forum 2018. Get your early bird tickets now and save!<|begin_of_text|>December 16, 2019 / Ashley Miznazi / 0 Comments\\nMario Vazquez, MBA \\'21\\nMario Vazquez is a first-generation college student from El Paso, Texas, or what he likes to call, \"The West Texas Miracle.\" His journey to Texas McCombs was one of family support and inspiration.\\nHis parents grew up in Matamoros Tamaulipas, a border town in Northern Mexico. They moved to the United States after his dad was offered a job as an electrical engineer in El Paso.\\nMario was born three years later. His parents wanted him to have the best education possible, so they started researching schools and colleges when Mario was only a baby. His mother was especially dedicated to his future and went above and beyond for his education.\\n\"My parents, in their mid 20\\'s, moved to a new country with almost nothing to their name. I often think about how exciting and terrifying the move must have been. They did everything within their power to give me a chance at a better life. My mother learned of a grade school that was known for its strong academic reputation but when she inquired about enrolling me, there were only two spots left and they would be given on a first-come first-served basis at 7 a.m. the very next day. Undeterred, my mom spent the night in the parking lot of what would become my grade school. When the doors opened at 7 a.m. the next morning, she was the second parent in line and I was the last student registered.\"\\nYoung Mario with his mother\\nWhen it was time for Mario to enroll in high school, his parents weren\\'t familiar with the American high school to college pipeline. Mario and his parents researched together and discovered that Cathedral High School, a private, Catholic high school in El Paso, maintained a 100% college acceptance rate, but tuition was expensive for the family.\\n\"In El Paso and Matamoros, college is more often a dream than a possibility. My mom, with the same tenacity she showed in enrolling me for kindergarten, found every single scholarship I could apply for and by the first day of school, I was an enrolled student at Cathedral High School and on my path to college.\"\\nMario eventually enrolled at Stanford University, graduating in 2013 with a B.A. in Science, Technology, and Society. While he was there, he joined and led an organization dedicated to providing need-based scholarships to graduating high school students attending two-year or four-year institutions.\\n\"Being a first-generation, low-income student of Hispanic descent in higher education was the exception, not the norm. I looked for a community of individuals with backgrounds similar to my own, which I found in joining and leading an organization called Los Hermanos de Stanford. As a group, we fundraised annually to provide need-based scholarships to graduating high school students attending two-year colleges and universities. I felt that I was reciprocating the investment so many people had made in me over the years. At that point, I knew how I wanted to use my life– helping students from difficult circumstances earn access to life-changing opportunities.\\nMario and his family at his college graduation in 2013.\\nAfter college, Mario accepted a position with Teach for America as a 1st-grade language instructor. He loved working with students and noticed how they were impacted by family circumstances or obstacles that he could not help with through teaching alone. He realized that he wanted to scale his impact beyond the classroom. He returned home to work at his alma mater, Cathedral High School, as the Director of Admissions.\\n\"For those three years at Cathedral, I conveyed the dream of a better life to every student and parent who walked the halls of our school. Throughout my tenure at Cathedral High School, I succeeded in increasing the number of underserved students and the dollar amount of scholarships that we could provide them. On a daily basis I had the opportunity to help change the course of a young person\\'s life. Working at Cathedral was an honor, the most fun I have ever had, and will forever be one of my proudest accomplishments..\"\\nMario\\'s \"Why McCombs?\"\\nMario never imagined he would end up in business school. But while driving around El Paso, he would see a Texas McCombs MBA billboard, and it stuck in his mind.\\n\"Truth be told, I did not think I\\'d get into business school. I wasn\\'t sure if top business schools would see the value of my experience in education. I was hard on myself, thinking that perhaps I wasn\\'t good enough. But my friends and colleagues encouraged me to put forth my best effort and believe in myself– and so I did. I reminded myself that I was worthy and deserving of receiving additional education. I\\'m blessed to be surrounded by good people, and I\\'m so grateful I didn\\'t give up.\"\\nMario says what sealed his decision to come to McCombs was his experience at Discover McCombs: Diversity Weekend and the opportunity to apply to McCombs through The Consortium for Graduate Study in Management, an alliance of top business schools and companies committed to enhancing diversity and inclusion in global business education and leadership.\\n\"When I came to Austin for Diversity Weekend, I had not applied to The Consortium, an organization that provides access to MBA admissions resources for underrepresented students. Jaden Felix, my McCombs admissions officer, took note of that and vehemently encouraged me to apply. To me, someone who has always looked for a community, it was a sign that I would be cared for here at McCombs.\\nMario had seen first-hand that even a well-funded, prestigious school like Cathedral couldn\\'t circumvent every challenge that students face or provide enough aid for every student to attend. He hopes that business school can help him achieve his goal of launching and operating a school that houses an ecosystem of academic and non-academic support for its students and their families.\\n\"For every student I was able to enroll at Cathedral or secure a scholarship for, there were at least a handful more that I could not because of socioeconomic reasons, lack of school resources, etc. Cathedral does a lot of good for so many students, myself included, and all kids deserve a good school with people who genuinely care about their success. I decided to pursue an MBA because I want to dedicate my life toward scaling the impact of schools located in underrepresented and underserved communities.\"\\nMario\\'s Advice to You\\n\"The great thing about McCombs is that the people here, from the staff to students and alumni, have reiterated one common phrase: \\'Don\\'t forget why you came here.\\' To me, this phrase serves as a constant reminder to remember how I have benefited from the kindness and help of others, and my responsibility to do the same.\"\\n\"Don\\'t devalue your experiences and don\\'t worry about not having the perfect academic or professional profile. I like to think that Texas McCombs, more so than other schools, tries to find people who have made a real impact in whatever capacity they served and genuinely want to do good in the world.\"\\nStay up to date with all things McCombs by subscribing to our newsletter. Follow us on Instagram to see more about student life. If you have any questions, please reach out to MBA Admissions. Hook \\'em!<|begin_of_text|>Donald Trump said in a Monday-morning interview that he felt there was \"something going on\" with President Barack Obama\\'s response to the recent spate of attacks on law enforcement.\\n\"I watched the president, and sometimes the words are OK, but you just look at the body language — there\\'s something going on. There\\'s something going on. And the words are not often OK, by the way,\" Trump said on \"Fox & Friends.\"\\nWhen pressed to clarify what he meant, Trump said he had \"a lot of bad feeling about [Obama].\"\\nThe real-estate magnate quickly acknowledged, though, that many black Americans most likely had experiences with law-enforcement officers that many white Americans can\\'t understand.\\n\"It\\'s probably something that we really don\\'t know, and maybe we can\\'t feel it unless we\\'re black,\" Trump said. \"And it is definitely something going on there, too. And that has to do with training, and has to do with something.\\n\"But there\\'s something going on, and maybe we can\\'t recognize it unless you\\'re black.\"\\nOn Sunday, three police officers were killed in Baton Rogue, Louisiana, in what the mayor described as an ambush-style attack. Earlier this month, five officers were killed by a sniper in Dallas.\\nTrump\\'s accusation that \"something is going on\" has become a favorite refrain when questioning the motives of other high-profile figures.\\nFollowing an ISIS-inspired attack at an LGBT nightclub in Orlando earlier this year, Trump asserted that Obama may be sympathetic to the terrorist organization, claiming there was \"something going on\" with the president\\'s response to terrorist attacks.<|begin_of_text|>Start a sustainable garden with our beginner\\'s guide.\\nCreating a sustainable garden can be extremely rewarding. You can help the environment, while also saving money. Read our beginner\\'s guide to sustainable gardening and learn how to get started.\\nCheck out our blog post Top 4 Ways to Reuse Paper in Your Garden.<|begin_of_text|>2013-10-22 - ABB have released their new PCS100 Active Voltage Conditioner (AVC) series. The successful PCS100 AVC range has been upgraded with a new 400 V range. This is a fully rated product at 400 V and can be applied to 380, 400 and 415 V networks. Previously 400 VAC rated PCS100 AVCs were down rated versions of 480 VAC rated units. This provides an additional 20 percent kVA capacity at no cost.\\nThis versatile product will find acceptance in 380 V countries such as China, 400 V regions such as Europe, the majority of Asia, South America, and for a smaller number of countries using 415 V such as Malaysia. The PCS100 AVC 400 V series is compatible with both 50 and 60 Hz supplies so countries such as Japan or OEM\\'s dealing with both frequencies will find products held in stock to be readily applicable to either network.\\nThe benefits for the end user are a lower cost per kVA and a smaller footprint for a given rating. The immediate saving and reduced real estate required for new installations or the sometimes challenging retrofit applications are a \"win-win\" situation for ABB\\'s customers.\\nAll 400 V range products sold are CE certified and suitable for global markets with a range of languages available on the graphical display. As part of the modular PCS100 product portfolio, spare parts are rationalized and available on short notice with ABB\\'s back-up and support.\\nThe PCS100 AVC 400 V series is an ideal solution for demanding voltage conditioning applications providing continuous regulation and near instantaneous correction of voltage sags and surges. The improved features and performance of the 400 V PCS100 AVC will see it even more widely applied in applications as diverse as, semiconductor and industrial plant protection through to medical and data centers. Typically, wherever critical loads require continuous clean power, the PCS100 AVC 400 V series will provide continuous benefits to the end user in the commercial and industrial sectors.<|begin_of_text|>Non-localized standing waves of the hyperbolic cubic nonlinear Schrödinger equation\\nDCDS Home\\nOn the partitions with Sturmian-like refinements\\nAugust 2015, 35(8): 3503-3531. doi: 10.3934/dcds.2015.35.3503\\nBoundedness in quasilinear Keller-Segel equations with nonlinear sensitivity and logistic source\\nXie Li 1, and Zhaoyin Xiang 1,\\nSchool of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731\\nReceived November 2014 Revised December 2014 Published February 2015\\nIn this paper, we investigate the quasilinear Keller-Segel equations (q-K-S): \\\\[ \\\\left\\\\{ \\\\begin{split} &n_t=\\\\nabla\\\\cdot\\\\big(D(n)\\\\nabla n\\\\big)-\\\\nabla\\\\cdot\\\\big(\\\\chi(n)\\\\nabla c\\\\big)+\\\\mathcal{R}(n), \\\\qquad x\\\\in\\\\Omega,\\\\,t>0,\\\\\\\\ &\\\\varrho c_t=\\\\Delta c-c+n, \\\\qquad x\\\\in\\\\Omega,\\\\,t>0, \\\\end{split} \\\\right. \\\\] under homogeneous Neumann boundary conditions in a bounded domain $\\\\Omega\\\\subset\\\\mathbb{R}^N$. For both $\\\\varrho=0$ (parabolic-elliptic case) and $\\\\varrho>0$ (parabolic-parabolic case), we will show the global-in-time existence and uniform-in-time boundedness of solutions to equations (q-K-S) with both non-degenerate and degenerate diffusions on the non-convex domain $\\\\Omega$, which provide a supplement to the dichotomy boundedness vs. blow-up in parabolic-elliptic/parabolic-parabolic chemotaxis equations with degenerate diffusion, nonlinear sensitivity and logistic source. In particular, we improve the recent results obtained by Wang-Li-Mu (2014, Disc. Cont. Dyn. Syst.) and Wang-Mu-Zheng (2014, J. Differential Equations).\\nKeywords: parabolic-parabolic Keller-Segel systems., Global existence, parabolic-elliptic Keller-Segel system, boundedness.\\nMathematics Subject Classification: Primary: 35K35, 92C17; Secondary: 35K5.\\nCitation: Xie Li, Zhaoyin Xiang. Boundedness in quasilinear Keller-Segel equations with nonlinear sensitivity and logistic source. Discrete & Continuous Dynamical Systems - A, 2015, 35 (8) : 3503-3531. doi: 10.3934/dcds.2015.35.3503\\nN. D. Alikakos, $L^p$ bounds of solutions of reaction-diffusion equations,, Comm. Partial Differential Equations, 4 (1979), 827. doi: 10.1080/03605307908820113. Google Scholar\\nK. Baghaei and M. Hesaaraki, Global existence and boundedness of classical solutions for a chemotaxis model with logistic source,, C. R. Acad. Sci. Paris, 351 (2013), 585. doi: 10.1016/j.crma.2013.07.027. Google Scholar\\nJ. Burczak, T. Cieslak and C. Morales-Rodrigo, Global existence vs. blow-up in a fully parabolic quasilinear 1D Keller-Segel system,, Nonlinear Anal., 75 (2012), 5215. doi: 10.1016/j.na.2012.04.038. Google Scholar\\nX. Cao and S. Zheng, Boundedness of solutions to a quasilinear parabolic-elliptic Keller-Segel system with logistic source,, Math. Methods Appl. Sci., 37 (2014), 2326. doi: 10.1002/mma.2992. Google Scholar\\nT. Cieslak, Quasilinear nonuniformly parabolic system modelling chemotaxis,, J. Math. Anal. Appl., 326 (2007), 1410. doi: 10.1016/j.jmaa.2006.03.080. Google Scholar\\nT. Cieslak and P. Laurencot, Finite time blow-up for a one-dimensional quasilinear parabolic-parabolic chemotaxis system,, Ann. I. H. Poincaré AN, 27 (2010), 437. doi: 10.1016/j.anihpc.2009.11.016. Google Scholar\\nT. Cieslak and C. Stinner, Finite-time blow up and global-in-time unbounded solutions to a parabolic-parabolic quasilinear Keller-Segel system in higher dimensions,, J. Differential Equations, 252 (2012), 5832. doi: 10.1016/j.jde.2012.01.045. Google Scholar\\nT. Cieslak and C. Stinner, Finite-time blowup in a supercritical quasilinear parabolic-parabolic Keller-Segel system in dimension 2,, Acta Appl. Math., 129 (2014), 135. doi: 10.1007/s10440-013-9832-5. Google Scholar\\nT. Cieslak and M. Winkler, Finite-time blow-up in a quasilinear system of chemotaxis,, Nonlinearity, 21 (2008), 1057. doi: 10.1088/0951-7715/21/5/009. Google Scholar\\nA. Friedman, Partial Differential Equations,, Holt, (1969). Google Scholar\\nH. Hajaiej, L. Molinet, T. Ozawa and B. Wang, Necessary and sufficient conditions for the fractional Gagliardo-Nirenberg inequalities and applications to Navier-Stokes and generalized boson equations,, in Harmonic Analysis and Nonlinear Partial Differential Equations, 26 (2011), 159. Google Scholar\\nD. D. Haroske and H. Triebel, Distributions, Sobolev Spaces, Elliptic Equations,, European Mathematical Society, (2008). Google Scholar\\nM. A. Herrero and J. J. L. Velázquez, A blow-up mechanism for a chemotaxis model,, Ann. Scuola Norm. Sup. Pisa Cl. Sci., 24 (1997), 633. Google Scholar\\nT. Hillen and K. J. Painter, Global existence for a parabolic chemotaxis model with prevention of overcrowding,, Adv. Appl. Math., 26 (2001), 280. doi: 10.1006/aama.2001.0721. Google Scholar\\nT. Hillen and K. Painter, Volume-filling and quorum-sensing in models for chemosensitive movement,, Can. Appl. Math. Q., 10 (2002), 501. Google Scholar\\nT. Hillen and K. Painter, A user\\'s guide to PDE models for chemotaxis,, J. Math. Biol., 58 (2009), 183. doi: 10.1007/s00285-008-0201-3. Google Scholar\\nD. Horstmann and M. Winkler, Boundedness vs. blow-up in a chemotaxis system,, J. Differential Equations, 215 (2005), 52. doi: 10.1016/j.jde.2004.10.022. Google Scholar\\nD. Horstmann and G. Wang, Blow-up in a chemotaxis model without symmetry assumptions,, European J. Appl. Math., 12 (2001), 159. doi: 10.1017/S0956792501004363. Google Scholar\\nS. Ishida, T. Ono and T. Yokota, Possibility of the existence of blow-up solutions to quasilinear degenerate Keller-Segel systems of parabolic-parabolic type,, Math. Methods Appl. Sci., 36 (2013), 745. doi: 10.1002/mma.2622. Google Scholar\\nS. Ishida, K. Seki and T. Yokota, Boundedness in quasilinear Keller-Segel systems of parabolic-parabolic type on non-convex bounded domains,, J. Differential Equations, 256 (2014), 2993. doi: 10.1016/j.jde.2014.01.028. Google Scholar\\nW. Jager and S. Luckhaus, On explosions of solutions to a system of partial differential equations modeling chemotaxis,, Trans. Amer. Math. Soc., 329 (1992), 819. doi: 10.1090/S0002-9947-1992-1046835-6. Google Scholar\\nE. F. Keller and L. A. Segel, Initiation of slime mold aggregation viewed as an instability,, J. Theor. Biol., 26 (1970), 399. doi: 10.1016/0022-5193(70)90092-5. Google Scholar\\nN. Mizoguchi and P. Souplet, Nondegeneracy of blow-up points for the parabolic Keller-Segel system,, Ann. I. H. Poincaré AN, 31 (2014), 851. doi: 10.1016/j.anihpc.2013.07.007. Google Scholar\\nC. Mu, L. Wang, P. Zheng and Q. Zhang, Global existence and boundedness of classical solutions to a parabolic-parabolic chemotaxis system,, Nonlinear Anal.-Real World Appl., 14 (2013), 1634. doi: 10.1016/j.nonrwa.2012.10.022. Google Scholar\\nT. Nagai, Blow-up of radially symmetric solutions of a chemotaxis system,, Adv. Math. Sci. Appl., 5 (1995), 581. Google Scholar\\nE. Nakaguchi and K. Osaki, Global existence of solutions to a parabolic-parabolic system for chemotaxis with weak degradation,, Nonlinear Anal., 74 (2011), 286. doi: 10.1016/j.na.2010.08.044. Google Scholar\\nV. Nanjundiah, Chemotaxis, signal relaying and aggregation morphology,, J. Theoret. Biol., 42 (1973), 63. doi: 10.1016/0022-5193(73)90149-5. Google Scholar\\nL. Nirenberg, An extended interpolation inequality,, Ann. Sc. Norm. Super. Pisa Cl. Sci., 20 (1966), 733. Google Scholar\\nT. Senba, Blowup behavior of radial solutions to Jager-Luckhaus system in high dimensional domains,, Funkcialaj Ekvacioj, 48 (2005), 247. doi: 10.1619/fesi.48.247. Google Scholar\\nT. Senba and T. Suzuki, Parabolic system of chemotaxis: Blowup in a finite and the infinite time,, Methods Appl. Anal., 8 (2001), 349. Google Scholar\\nY. Tao and M. Winkler, Boundedness in a quasilinear parabolic-parabolic Keller-Segel system with subcritical sensitivity,, J. Differential Equations, 252 (2012), 692. doi: 10.1016/j.jde.2011.08.019. Google Scholar\\nY. Tao and M. Winkler, Eventual smoothness and stabilization of large-data solutions in a three-dimensional chemotaxis system with consumption of chemoattractant,, J. Differential Equations, 252 (2012), 2520. doi: 10.1016/j.jde.2011.07.010. Google Scholar\\nY. Tao and Z.A. Wang, Competing effects of attraction vs. repulsion in chemotaxis,, Math. Models Methods Appl. Sci., 23 (2013), 1. doi: 10.1142/S0218202512500443. Google Scholar\\nJ. I. Tello and M. Winkler, A chemotaxis system with logistic source,, Comm. Partial Differential Equations, 32 (2007), 849. doi: 10.1080/03605300701319003. Google Scholar\\nR. Temam, Infinite-Dimensional Dynamical Systems in Mechanics and Physics,, $2^{nd}$ edition, 68 (1997). Google Scholar\\nL. Wang, Y. Li and C. Mu, Boundedness in a parabolic-parabolic quasilinear chemotaxis system with logistic source,, Discrete and Continuous Dynamical Systems, 34 (2014), 789. doi: 10.3934/dcds.2014.34.789. Google Scholar\\nL. Wang, C. Mu and P. Zheng, On a quasilinear parabolic-elliptic chemotaxis system with logistic source,, J. Differential Equations, 256 (2014), 1847. doi: 10.1016/j.jde.2013.12.007. Google Scholar\\nZ. A. Wang and T. Hillen, Classical solutions and pattern formation for a volume filling chemotaxis model,, Chaos, 17 (2007). doi: 10.1063/1.2766864. Google Scholar\\nZ. A. Wang, On chemotaxis models with cell population interactions,, Math. Model. Nat. Phenom., 5 (2010), 173. doi: 10.1051/mmnp/20105311. Google Scholar\\nZ. A. Wang, M. Winkler and D. Wrzosek, Singularity formation in chemotaxis systems with volume-filling effect,, Nonlinearity, 24 (2011), 3279. doi: 10.1088/0951-7715/24/12/001. Google Scholar\\nZ. A. Wang, M. Winkler and D. Wrzosek, Global regularity vs. infinite-time singularity formation in a chemotaxis model with volume-filling effect and degenerate diffusion,, SIAM J. Math. Anal., 44 (2012), 3502. doi: 10.1137/110853972. Google Scholar\\nM. Winkler, Boundedness in the higher-dimensional parabolic-parabolic chemotaxis system with logistic source,, Comm. Partial Differential Equations, 35 (2010), 1516. doi: 10.1080/03605300903473426. Google Scholar\\nM. Winkler, Chemotaxis with logistic source: Very weak global solutions and their boundedness properties,, J. Math. Anal. Appl., 348 (2008), 708. doi: 10.1016/j.jmaa.2008.07.071. Google Scholar\\nM. Winkler, Finite-time blow-up in the higher-dimensional parabolic-parabolic Keller-Segel system,, J. Math. Pures Appl., 100 (2013), 748. doi: 10.1016/j.matpur.2013.01.020. Google Scholar\\nM. Winkler, Does a \\'volume-filling effect\\' always prevent chemotactic collapse?,, Math. Methods Appl. Sci., 33 (2010), 12. doi: 10.1002/mma.1146. Google Scholar\\nM. Winkler, Aggregation vs. global diffusive behavior in the higher-dimensional Keller-Segel model,, J. Differential Equations, 248 (2010), 2889. doi: 10.1016/j.jde.2010.02.008. Google Scholar\\nM. Winkler and K. C. Djie, Boundedness and finite-time collapse in a chemotaxis system with volume-filling effect,, Nonlinear Anal., 72 (2010), 1044. doi: 10.1016/j.na.2009.07.045. Google Scholar\\nD. Wrzosek, Global attractor for a chemotaxis model with prevention of over-crowding,, Nonlinear Anal., 59 (2004), 1293. doi: 10.1016/j.na.2004.08.015. Google Scholar\\nKentarou Fujie, Takasi Senba. Global existence and boundedness in a parabolic-elliptic Keller-Segel system with general sensitivity. Discrete & Continuous Dynamical Systems - B, 2016, 21 (1) : 81-102. doi: 10.3934/dcdsb.2016.21.81\\nKentarou Fujie, Chihiro Nishiyama, Tomomi Yokota. Boundedness in a quasilinear parabolic-parabolic Keller-Segel system with the sensitivity $v^{-1}S(u)$. Conference Publications, 2015, 2015 (special) : 464-472. doi: 10.3934/proc.2015.0464\\nTobias Black. Global generalized solutions to a parabolic-elliptic Keller-Segel system with singular sensitivity. Discrete & Continuous Dynamical Systems - S, 2020, 13 (2) : 119-137. doi: 10.3934/dcdss.2020007\\nPiotr Biler, Ignacio Guerra, Grzegorz Karch. Large global-in-time solutions of the parabolic-parabolic Keller-Segel system on the plane. Communications on Pure & Applied Analysis, 2015, 14 (6) : 2117-2126. doi: 10.3934/cpaa.2015.14.2117\\nMengyao Ding, Sining Zheng. $ L^γ$-measure criteria for boundedness in a quasilinear parabolic-elliptic Keller-Segel system with supercritical sensitivity. Discrete & Continuous Dynamical Systems - B, 2019, 24 (7) : 2971-2988. doi: 10.3934/dcdsb.2018295\\nHao Yu, Wei Wang, Sining Zheng. Boundedness of solutions to a fully parabolic Keller-Segel system with nonlinear sensitivity. Discrete & Continuous Dynamical Systems - B, 2017, 22 (4) : 1635-1644. doi: 10.3934/dcdsb.2017078\\nWenting Cong, Jian-Guo Liu. Uniform $L^{∞}$ boundedness for a degenerate parabolic-parabolic Keller-Segel model. Discrete & Continuous Dynamical Systems - B, 2017, 22 (2) : 307-338. doi: 10.3934/dcdsb.2017015\\nJohannes Lankeit. Infinite time blow-up of many solutions to a general quasilinear parabolic-elliptic Keller-Segel system. Discrete & Continuous Dynamical Systems - S, 2020, 13 (2) : 233-255. doi: 10.3934/dcdss.2020013\\nSachiko Ishida. $L^\\\\infty$-decay property for quasilinear degenerate parabolic-elliptic Keller-Segel systems. Conference Publications, 2013, 2013 (special) : 335-344. doi: 10.3934/proc.2013.2013.335\\nMengyao Ding, Xiangdong Zhao. $ L^\\\\sigma $-measure criteria for boundedness in a quasilinear parabolic-parabolic Keller-Segel system with supercritical sensitivity. Discrete & Continuous Dynamical Systems - B, 2019, 24 (10) : 5297-5315. doi: 10.3934/dcdsb.2019059\\nJinhuan Wang, Li Chen, Liang Hong. Parabolic elliptic type Keller-Segel system on the whole space case. Discrete & Continuous Dynamical Systems - A, 2016, 36 (2) : 1061-1084. doi: 10.3934/dcds.2016.36.1061\\nMonica Marras, Stella Vernier Piro, Giuseppe Viglialoro. Lower bounds for blow-up in a parabolic-parabolic Keller-Segel system. Conference Publications, 2015, 2015 (special) : 809-816. doi: 10.3934/proc.2015.0809\\nSachiko Ishida, Tomomi Yokota. Blow-up in finite or infinite time for quasilinear degenerate Keller-Segel systems of parabolic-parabolic type. Discrete & Continuous Dynamical Systems - B, 2013, 18 (10) : 2569-2596. doi: 10.3934/dcdsb.2013.18.2569\\nAnsgar Jüngel, Oliver Leingang. Blow-up of solutions to semi-discrete parabolic-elliptic Keller-Segel models. Discrete & Continuous Dynamical Systems - B, 2019, 24 (9) : 4755-4782. doi: 10.3934/dcdsb.2019029\\nSachiko Ishida, Tomomi Yokota. Boundedness in a quasilinear fully parabolic Keller-Segel system via maximal Sobolev regularity. Discrete & Continuous Dynamical Systems - S, 2020, 13 (2) : 211-232. doi: 10.3934/dcdss.2020012\\nMiaoqing Tian, Sining Zheng. Global boundedness versus finite-time blow-up of solutions to a quasilinear fully parabolic Keller-Segel system of two species. Communications on Pure & Applied Analysis, 2016, 15 (1) : 243-260. doi: 10.3934/cpaa.2016.15.243\\nHao Yu, Wei Wang, Sining Zheng. Global boundedness of solutions to a Keller-Segel system with nonlinear sensitivity. Discrete & Continuous Dynamical Systems - B, 2016, 21 (4) : 1317-1327. doi: 10.3934/dcdsb.2016.21.1317\\nSachiko Ishida. An iterative approach to $L^\\\\infty$-boundedness in quasilinear Keller-Segel systems. Conference Publications, 2015, 2015 (special) : 635-643. doi: 10.3934/proc.2015.0635\\nLuca Battaglia. A general existence result for stationary solutions to the Keller-Segel system. Discrete & Continuous Dynamical Systems - A, 2019, 39 (2) : 905-926. doi: 10.3934/dcds.2019038\\nHai-Yang Jin, Zhi-An Wang. Global stabilization of the full attraction-repulsion Keller-Segel system. Discrete & Continuous Dynamical Systems - A, 2019, 0 (0) : 0-0. doi: 10.3934/dcds.2020027\\nXie Li Zhaoyin Xiang<|begin_of_text|>Sex Clinic\\nAsk 9jahealth\\nHome Tags Posts tagged with \"obesity\"\\nDisease puts 1 in 5 globally at severe COVID-19 risk: study\\nby admin - Jun 16, 2020\\nAn estimated 1.7 billion people — more than 20 percent of the world\\'s population — risk becoming severely infected with COVID-19 due to underlying health problems such as obesity and heart disease, analysis showed Tuesday.\\nThe novel coronavirus, which has killed more than 420,000 people globally during the first wave of the pandemic, adversely effects patients suffering from co-morbidities.\\nA team of experts from the London School of Hygiene and Tropical Medicine analysed global data sets of illnesses including diabetes, lung disease and HIV used these to estimate how many people are at heightened risk of serious COVID-19 infection.\\nThey found that one in five people have at least one underlying health problem putting them in greater danger.\\nWhile not all of those would go on to develop severe symptoms if infected, the researchers said around 4 percent of the global population — around 350 million) would likely get sick enough to require hospital treatment.\\n\"As countries move out of lockdown, governments are looking for ways to protect the most vulnerable from a virus that is still circulating,\" said Andrew Clark, who contributed to the study.\\n\"This might involve advising people with underlying conditions to adopt social distancing measures appropriate to their level of risk.\"\\nClark said the findings could help governments make decisions on who receives a COVID-19 vaccine first when one becomes available.\\nConsistent with other studies about COVID risk, the authors found that older people are in greater danger of getting seriously unwell from the virus.\\nLess than 5 percent of people aged under 20 have an underlying risk factor, compared with two thirds of over 70s.\\nCountries with younger populations have fewer people with at least one underlying condition, but risks vary globally, according to the analysis.\\nSmall island states such as Fiji and Mauritius have among the highest rates of diabetes — a known COVID-19 risk factor — on Earth, for example.\\nAnd countries with the highest prevalence of HIV/AIDS, such as eSwatini and Lesotho, also need to be vigilant, said authors of the research published in The Lancet.\\nIn Europe, more than 30 percent of people have one or more health conditions, it showed.\\nWriting in a linked comment, Nina Schwalbe from Columbia University Mailman School of Public Health, said the study showed \"it is time to evolve from a one-size-fits-all approach to one that centres on those most at risk.\"\\nManaging fatty liver disease\\nby - Sep 25, 2017\\nNowadays, Nigerians who lead sedentary lifestyles and who have adopted irregular food habits, appear to be more prone to liver diseases than others. Fatty liver disease is the result of a build-up of fat in the liver. If the liver is healthy, there should be little or no fat in it. However, sometimes, fat molecules begin to collect in the liver cells. Small amounts of fat in the liver usually cause no problems. However, when too much fat builds in this organ, it can pose a lot of health hazards.\\nWith the exception of the brain, the liver is the most complex organ and second largest organ in the body. Its function is to process everything we eat or drink and filter harmful substances from the blood. This process is however interrupted when the liver contains too much fat. When fat accounts for more than five percent of the liver\\'s weight, the condition is described as fatty liver.\\nIt is becoming one of the most common types of liver disease and it\\'s also one of the causes of liver cancer and cirrhosis. The disease may also occur due to metabolic problems such as diabetes, obesity or Hepatitis B and C infection.\\nA diagnosis of fatty liver could raise the alarm for an impending Type 2 diabetes. Fatty liver disease can lead to an inflamed liver and scarring. This is called alcoholic hepatitis if it\\'s caused by drinking too much alcohol and non-alcoholic steatohepatitis if it\\'s not related to alcohol.\\nFrom what I have explained so far, it should be obvious that fatty liver disease is a lifestyle disease. Most people living with this disease are fat, obese and they take alcohol.\\nIt is more common in men and persons above the age of 50. Hypertensive and diabetic patients are most likely to be diagnosed with fatty liver as they are already battling with high blood sugar, glucose and cholesterol.\\nHowever, chemicals like methotrexate and tamoxifen can, but rarely cause non-alcoholic fatty liver.\\nNon-alcoholic fatty liver disease usually causes no signs and symptoms. When it does, they may include fatigue, poor appetite, pain in the upper right abdomen and weight loss.\\nIts complications include a swollen abdomen, itchy skin, vomiting of blood, confusion or poor memory, weakness and muscle wasting and jaundice.\\nFatty liver disease can sometimes be difficult to diagnose because one may not have any symptoms. There is no single test that can be used to diagnose fatty liver disease, but one may carry out some blood tests, liver biopsy, ultrasound, CT or MRI scan which help to create images of the liver. These images will show if there are any forms of fat in the liver.\\nYou may be able to prevent non-alcoholic fatty liver disease by maintaining a healthy weight for your height. Being active try to do at least 150 minutes of moderate exercise each week or 30 minutes of exercise for days.\\nThose who are obese or overweight, a gradual weight loss and regular exercise is advised. This not only helps with fatty liver but also it will help to reduce other risks of developing cardiovascular problems.\\nLimit or avoid alcoholic beverages because alcohol even in modest amounts may make fatty liver worse.\\nEating healthy foods that are low in saturated fat and reduce your sugar intake to control your blood sugar. Manage your cholesterol levels and use liver supplements.\\nAlcoholic fatty liver disease is reversible. The liver should return to normal if one stops drinking alcohol. Even if one has been a heavy drinker for many years, reducing or stopping alcohol intake will have important short and long-term benefits on the liver and one\\'s overall health.\\new send periodic newsletter to keep you well informed on current Health issues and news in Nigeria\\nTweets by @9ja_health\\n© Copyright 2015 - 9jahealth. A Cyborg Business<|begin_of_text|>2014-11-19 Assigned to MINI-LAP TECHNOLOGIES, INC. reassignment MINI-LAP TECHNOLOGIES, INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: ALWARD, ALLAN, RAVIKUMAR, SUNDARAM, DR.\\n2014-12-08 Assigned to TELEFLEX MEDICAL INCORPORATED reassignment TELEFLEX MEDICAL INCORPORATED ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: MINI-LAP TECHNOLOGIES, INC.\\nVarious surgical instruments for laparoscopic procedures are provided for aspirating and retracting a hollow organ such as a gallbladder. The surgical instruments include a needle body and an anchor coupled to the needle body. The anchor is adapted and configured for engaging and retracting the hollow organ, and can be held and deployed from within the needle body or from an outside surface of the needle body. The needle body defines an aperture for permitting aspiration of contents of the hollow organ.\\nThis application claims the benefit of priority to U.S. Patent Application Set. No. 61/291,842, filed Dec. 31, 2009 and U.S. Patent Application Set. No. 61/323,359, filed Apr. 13, 2010, which are incorporated herein by reference, in their entireties.\\nThe present invention relates to surgical procedures. Particularly, the present invention is directed to devices for laparoscopic surgical procedures, and more particularly to devices for use in single-incision laparoscopic surgical (SILS) procedures. The subject surgical devices are deployed, in accordance with one aspect, from within the lumen of a needle or from an outer surface of a needle. Such devices are sometimes termed \"needlescopic.\" U.S. Patent Publications Numbers US 2010/0016884, US 2009/0259225, US 2008/0086166, US 2007/0282170, US 2007/0250112, US 2007/0213767, US 2007/0213766, and US 2007/0213595, each of which is incorporated herein by reference, in its entirety, describe devices related to the devices described herein. The devices described therein, and aspects thereof, including configuration of control mechanisms, material selection, fabrication techniques, as well as other aspects, can be applied to the devices described herein, with advantageous effect.\\nGallbladder surgery has been revolutionized in recent years, changing from an open incisional surgery to, currently, almost a purely laparoscopic procedure, also known as a minimally invasive surgery. Conventional minimally invasive surgeries for cholecystectomy involve the use of four trocars (access devices). In general, one trocar is inserted in the umbilicus, through which an endoscope is inserted, with two trocars being inserted on the right side of the abdomen for retraction and mobilizing the gallbladder, in order to identify the important structures. The fourth trocar is typically inserted in the midline above the umbilicus.\\nThe aforementioned method has become the standard approach and has withstood twenty years of changes in surgical skill sets, in various groups of surgeons. Relatively recently, even newer and advantageous techniques for cholecystectomy have been developed that involve only a single trocar or \"port\", called SILS (single incision laparoscopic surgery). The prediction is that nearly twenty to forty percent of all gallbladder surgeries will be performed in this manner in the next five to ten years. This technology involves inserting a single port inserted through the umbilicus, with all the instruments going into the abdominal cavity through the single port. Mobilizing and retracting the gallbladder is challenging with this technology, especially if the gallbladder is distended due to inflammation.\\nThere are techniques available at present for anchoring the fundus of the gallbladder with sutures during SILS procedures, although such techniques are very cumbersome and difficult, especially with an inflamed gallbladder.\\nApplicants recognize that aspirated, emptied gallbladders are preferable if using SILS technology for cholecystectomy, thus changing what was a tense, full sac, into a malleable structure permitting instruments to grasp the wall of the gallbladder. Applicants further recognize that simply aspirating with a needle alone, and not sealing the opening caused thereby, will cause spillage of left-over materials, which is not desirable.\\nAccordingly, there remains a need in the art for devices that facilitate aspiration and retraction of gallbladder in laparoscopic procedures that prevent spillage of gallbladder contents. The present invention provides a solution for these needs.\\nIn one aspect, a surgical instrument for laparoscopic procedures is provided, which is adapted and configured to aspirate and retract a hollow organ. The surgical instrument includes a needle body, an anchor, deployable with respect to the needle body, adapted and configured for engaging and retracting the hollow organ, and an aperture provided in connection with the needle body, adapted and configured for permitting aspiration of contents of the hollow organ.\\nThe hollow organ can be a gallbladder. The anchor can be held within, and deployable from, a lumen of the needle body. The anchor can be held on, and deployable from, an outside surface of the needle body.\\nThe anchor can be a deployable cage structure. The cage structure can be spring-biased such that the cage structure is deployed by tension provided in a spring when the cage structure extends beyond the needle body by a predetermined distance. The cage structure can include one or more barbs configured to extend from the cage structure when the cage structure is in a deployed configuration. Such one or more barbs can be distally directed to facilitate reinsertion of the cage structure into the lumen of the needle body. Alternatively, such one or more barbs can be proximally directed to facilitate engagement of the barbs with the inner wall of the hollow organ. The cage can be configured so that the barbs move into a position coplanar with surrounding portions of the cage, to facilitate reinsertion of the cage into the lumen of the needle body.\\nThe cage structure can be provided with at least one fenestration to facilitate bending manipulation of the cage.\\nThe cage structure can be provided with a plurality of legs, symmetrically arranged about a longitudinal axis of the surgical instrument. The number of legs can be any or two, three, four, five, six, seven, eight or nine, for example. However, greater or fewer legs, such as one or ten and so on, can be provided.\\nThe cage structure can include a plurality of nested cages to permit flexibility of the cage while maintaining strength sufficient to reliably retract the hollow organ.\\nIn accordance with another aspect of the invention, the anchor can be a deployable wire structure.\\nAlternatively, the anchor an inflatable structure. The anchor can be adapted and configured to be inflatable by one or more of a liquid and a gas.\\nThe anchor can include a distal anchor portion and a proximal anchor portion, adapted and configured to engage inner and outer surfaces of the hollow organ, respectively. The distal anchor portion and the proximal anchor portion can be longitudinally spaced apart by a distance sufficient to permit engagement of a wall of the hollow organ. If desired, the distal anchor portion and the proximal anchor portion can be rotationally offset from one another by about 90 degrees, with respect to a longitudinal axis of the surgical instrument. Alternatively, the distal anchor portion and the proximal anchor portion can be substantially parallel with one another, with respect to a longitudinal axis of the surgical instrument.\\nThe distal anchor portion and the proximal anchor portion can be of substantially the same configuration. Alternatively, the distal anchor portion and the proximal anchor portion can be of dissimilar configurations, such as in structure, number of elements, size, material, or in other aspects thereof.\\nIn accordance with the invention, the needle body can include a sharpened distal tip. A deployable tip protector can further be provided to inhibit unintentional injury by a sharpened distal tip of the needle body. The deployable tip protector can be a translatable sheath adapted and configured to be deployed over the sharpened distal tip of the needle body. Alternatively, the deployable tip protector can be a translatable plug adapted and configured to be deployed from within a lumen of the needle body. The plug can be adapted and configured to extend distally beyond the sharpened distal tip of the needle body, to inhibit piercing of a structure by the needle body, when in a deployed position. The plug can be formed from a polymeric material.\\nIn accordance with the invention, an aperture can be provided at the distal end of the body. Alternatively, one or more apertures can be provided in a distal end portion of a sidewall of the body.\\nThe anchor can be formed at least in part from one of a shape-memory alloy and a stainless steel. Alternatively, resilient polymeric materials of sufficient strength, flexibility and durability can be used. In accordance with the invention, the anchor can be formed at least in part by laser cutting.\\nThe needle body can be any length necessary. In accordance with one aspect, the length is about 20 centimeters. An outer diameter of the needle body can be any size necessary. In accordance with one aspect, the diameter is about 2 mm.\\nThe anchor can be configured such that, in a deployed conformation, a width, measured transverse to a longitudinal axis thereof, is a maximum of about eight times that of a width in a collapsed conformation, measured transverse to the longitudinal axis thereof.\\nThe needle body can be provided with a sharpened end surface angled at about 35 degrees with respect to the longitudinal axis of the needle body.\\nA handle can be provided in connection with the subject instruments, to facilitate manipulation thereof.\\nIn accordance with a further aspect of the invention, a method of retracting a hollow organ is provided, comprising the steps of inserting a body through an abdominal wall of a patient, inserting the body through a wall of the hollow organ, aspirating contents from the hollow organ, deploying a first anchor portion within the hollow organ, to engage an inner surface of the hollow organ, and retracting the hollow organ.\\nIn accordance with the invention, the method can further include the step of deploying a second anchor portion outside the hollow organ to engage an outer surface of the hollow organ.\\nIn accordance with still another aspect of the invention, a surgical instrument for laparoscopic procedures is provided, which is adapted and configured to aspirate and retract a gallbladder, the instrument having means for aspirating contents from a gallbladder, and means for engaging and retracting the gallbladder.\\nIn accordance with still a further aspect of the invention, a surgical instrument can be manufactured by a process comprising the steps of providing a tubular needle with a lumen extending therethrough, machining a deployable anchor, and inserting the deployable anchor, in a radially collapsed conformation, into the tubular needle. The anchor can be formed from a flat stainless steel stock material. The step of machining can be performed by electrical discharge machining or laser machining, for example.\\nIt is to be understood that both the foregoing general description and the following detailed description are exemplary and are not intended to be limiting.\\nFIG. 54 is a side view of a distal end portion of the surgical aspirator-retractor of FIG. 53, having distal deployable ribbon-shaped engagement elements and proximal deployable prong-shaped engagement elements, with all elements in a deployed configuration.\\nReference will now be made in detail to the present preferred embodiments of the invention, examples of which are illustrated in the accompanying drawings.\\nIn accordance with one aspect of the invention, a surgical aspirator-retractor is provided having the capacity to aspirate and seal a hole formed thereby, as well as retract the gallbladder. In accordance with one aspect, a needle of less than 2.5 mm is introduced into the abdominal wall with a sharp tip which can pierce the skin. The same needle tip is able to pierce the fluid-filled gallbladder wall. The opposite end to the needle tip can be provided with a hub to attach a syringe or suction device to help to aspirate the contents of the gallbladder. Once the gallbladder is emptied of its contents, the surgical aspirator-retractor\\'s anchor or fixation mechanism can be deployed.\\nIn accordance with the invention, the distal anchor or fixation mechanism can include, for example, multiple curved wires coming out of the sharp end of the needle, multiple curved wires coming out of the shaft near the needle tip, an outer shaft over the needle having a shape-memory alloy wire attached to two ends and when pushed down, the wire assumes the shape of a rosette. Depending on the precise implementation, the needle tip can be split at the end and when retracted backwards can become the shape of a star. If desired, a separate instrument can be provided having a compressed hook, introduced at the proximal end of a needle body. When the separate instrument is inserted through and beyond a distal end of the needle body, it is deployed, and the hook engages the inside of the gallbladder wall.\\nDepending on the precise embodiment, once this distal anchor portion is deployed, the whole instrument is withdrawn until the sharp tip of the anchor engages and fixes to the inside of the gallbladder wall firmly. Optionally, a second anchor portion can be provided to engage the outer surface of the wall of the gallbladder to facilitate a secure grasp. The gallbladder can then be retracted or mobilized in any direction without any spillage. Once the gallbladder dissection from the liver is complete, the anchor mechanism is either retracted into the instrument or otherwise straightened, thus releasing its attachment from the gallbladder wall. The instrument will then be withdrawn from the gallbladder wall.\\nIt should be noted that although the devices of the present invention are advantageous for cholecystectomy procedures, they can advantageously be applied to aspirate, retract and/or stabilize other hollow organs, such as the stomach or urinary bladder, for example. Further, devices in accordance with the invention can be used to manipulate other tissues including organs, in addition to those that are substantially hollow.\\nDevices in accordance with the invention advantageously help empty the contents from the organ with which it is being used, such as the gallbladder, without spillage, and facilitate easy grasping of the wall of the thereof because of loss of distensability of the organ wall is reduced. The subject devices also permit easy removal of the gallbladder from the abdominal cavity through the umbilical port due to the collapsed state of the organ. Further, advantageously, the small size of the subject instruments minimize or eliminate scarring.\\nFor the purposes of explanation and illustration, and not limitation, in accordance with the invention, an exemplary embodiment of a surgical aspirator-retractor 100 is illustrated in FIGS. 1-14. In accordance with this example, the surgical aspirator-retractor includes an inner needle having a diameter, for example 1.5 mm, and a needle body 130 having diameter d1, for example about 2 mm, with a length L1, for example about 200 mm.\\nAs illustrated in FIGS. 11-14, which illustrate use of the surgical aspirator-retractor of FIG. 1, in piercing, aspirating contents of and retracting a gallbladder, respectively, the aspirator-retractor 100 can be positioned directly over the gallbladder 991 then inserted directly through the skin of the abdominal wall 990, into the gallbladder 991, by virtue of a sharpened distal tip 131. A suction source can be hooked up to a fitting 115, such as a Luer fitting provided on the body 110, and the gallbladder is aspirated of its contents 993, such as bile, from the lumen 995 thereof, via a distal end aspiration aperture 135 therein. The thumb wheel 120 can then be advanced to deploy the anchor 140, which in the illustrated embodiment is in the form of a cage with hooks or barbs 141 to engage or embed into the gallbladder 991, for retention thereof. The surgical aspirator-retractor 100 is then pulled up setting the tips of the cage into the gallbladder internally. The surgical aspirator-retractor 100 can then be pulled up and the gallbladder is raised to the desired position. The position locking mechanism 150 is placed against the skin and locked, thereby suspending the gallbladder in the body cavity allowing work to be performed on it and around it without having to reposition the gallbladder continually.\\nAs best seen in the detail views of FIGS. 4 and 5, an outer shaft 133 is provided concentrically outside of the needle body 130, and is attached to the proximal end of the anchor 140, while the distal end of the anchor 140 is attached to the needle body. Such attachment can be achieved by integral forming process, welding, crimping, mechanical fasteners, adhesives or another suitable technique, if desired.\\nFIGS. 6 and 7 are is an isometric detail views of the distal anchor portion 140 of the surgical aspirator-retractor 100, but with a solid tip 132 and apertures 137 for aspiration on a side surface thereof, shown in a collapsed condition and a deployed condition, respectively.\\nIn accordance with a further exemplary embodiment, as illustrated for example, in FIGS. 15-22, a surgical aspirator-retractor 200 is provided with a needle body 230, a distal anchor 240, a handle 210, a proximal fitting 215 and a position locking mechanism 150. The needle body 230 can have, in accordance with one example embodiment, a diameter of about 1.5 mm and a length of between about 150 mm and 200 mm.\\nAs best seen in FIGS. 19-22, which illustrate use of the surgical aspirator-retractor of FIG. 15, in piercing, aspirating contents of and retracting a gallbladder, respectively, as with the above-described embodiment, the aspirator-retractor 200 can be positioned over the gallbladder 991, and then inserted directly through the abdominal wall 990, into the lumen 995 of the gallbladder 991. Suction can then be hooked up to the luer fitting 215 on the end thereof, and the gallbladder 991 is aspirated of its contents 993, such as bile. Suction can then be turned off and the anchor 240 advanced, as shown in FIG. 21, to expose a single or multiple needle tips (e.g., similar to a grappling hook). As shown in FIG. 22, the surgical aspirator-retractor 200 is then pulled up setting the needles into the inner surface of the wall of the gallbladder 991. Then, the surgical aspirator-retractor 200 is pulled up and the gallbladder is raised to the desired position. The position locking mechanism 150 is placed against the skin and locked, thereby suspending the gallbladder in the body cavity allowing work to be performed on it and around it without having to continually reposition the gallbladder 991.\\nFIGS. 23-31 show various views an additional embodiment of a surgical aspirator-retractor in accordance with the present invention, having a deployable cage-shaped anchor 340.\\nBy way of example, the needle body 130 is provided as a hollow needle. In accordance with one aspect, the diameter of the needle body 130 can be about 2.1 mm. In use, the needle body is inserted through the abdomen under internal observation. The needle body 130 is inserted into the gallbladder 991 and fluids are aspirated through the needle body 130. A shaft 340, which may be formed from a tubular material, and being internal to the needle body 130, is advanced distally to deploy the expandable cage-shaped anchor 340, which is affixed to the front of the tube 338. A shaft 343 runs through a lumen of the tube 338, and is attached to the distal portion of the anchor cage 340. As best seen in FIG. 27, a spring 345 is provided and is secured to the shaft 343, thus spring loading the anchor cage 340, under tension applied thereto. When the anchor cage 340 is advanced beyond the needle body 130, the tension of the spring 345 causes the cage to expand up to a stop. Bending of the anchor cage 340 exposes grip fingers or barbs 341 that secure the inside of the gall bladder 991.\\nIn use, the internal components are typically recessed inside the 2.1 mm hollow needle body 130. The needle body 130 is then inserted through the abdomen and then into the gallbladder 991. Fenestrations 349 facilitate achieving the desired structural properties of the anchor cage 340, and also permit fluids to be aspirated past the distal tip of the anchor cage 340. Once the gallbladder 991 is aspirated, the anchor cage 340 is advanced through the needle body 130, and into the lumen 995 of the gallbladder 991. In accordance with one aspect, the anchor cage 340 expands outwardly, to a maximum width of about 16 mm. In the illustrated embodiment, the barbs 341 face distally, so that there are no edges to catch on the needle body 130, when the cage 340 is drawn back into the needle body 130.\\nAfter insertion within the lumen 995 of the gallbladder 991 and deployment of the anchor 340, the aspirator-retractor can be manipulated such as by rotation or axial translation, to facilitate access to the gallbladder 991. Once removed, the gallbladder 991 is placed in a bag, for example, and the anchor cage 340 is retracted to release the gallbladder 991 from the aspirator-retractor, which is then removed from the patient.\\nTo retract the anchor cage 340, the inner drive tube 338 is retracted. The gallbladder is then stripped from the aspirator-retractor. The anchor cage 340 is then returned to its original position and the needle body 130 is removed from the abdomen.\\nIn accordance with the invention, the anchor cage 340 is assembled by any suitable technique, to the inner tube 338, such as by welding, soldering or crimping. In accordance with the invention, the shaft 343 can be connected to the anchor cage 340 by a threaded connection, or other suitable technique.\\nDue to the high amount of flex and associated strain placed on the cage, material must be selected accordingly. Shape memory alloys or any suitable materials can be used. In accordance with one aspect, a high strength stainless steel alloy is used in cased of thin cross-sections, to maintain stresses below their tensile limits. In accordance with the invention, 17-7PH Condition C stainless steel with a post forming heat-treatment to condition CH900 can be utilized for this application. In accordance with the invention, such a material can have a tensile strength of approximately 250,000 psi and elongation of 3% expected, with minimal part distortion during heat-treatment. If desired, a flash electropolish and subsequent low temperature bake to prevent Hydrogen embrittlement can be used to remove heat tint during 900 degree F. open air precipitation age hardening.\\nFIG. 30 is an isometric view of a distal anchor 340 of a surgical aspirator-retractor having a deployable cage configuration, which is similar in many respects to the embodiment illustrated in FIG. 23. The anchor cage 440 differs there from in that it includes a plurality of nested layers 440 a, 440 b, and additional fenestrations 449, to promote strength while facilitate a reliable change in conformation thereof in use. FIG. 31 is a detail isometric view of the distal anchor portion 440 of the surgical aspirator-retractor of FIG. 30. In accordance with one aspect of the invention, the anchor cage 340 and/or the anchor cage portions 440 a, 440 b can be formed from a stainless steel material having about a 0.002 inch stock thickness.\\nWith reference to FIGS. 32-34, still another embodiment of a surgical aspirator-retractor in accordance with the present invention is illustrated, having a distal anchor 540 in a variation of the above-described deployable cage structures. The distal anchor 540 includes outwardly expanding ribbons of material 540 a, 540 b. A main needle body 530 is provided, axially inner to other components. A deployable tip protector 537 is also provided. As illustrated in FIG. 32, the tip protector 537 is here illustrated as a sheath which can be deployed by manipulating respective concentric tube(s), such as one provided radially outward from the main needle body 530. As best seen in FIG. 34, when a compressive force is applied distally on the ribbons 540 a, 540 b, they expand radially outwardly, as with other embodiments described herein, due to the configuration thereof and material selection therefore.\\nFIGS. 35-36 illustrate a further embodiment of a surgical aspirator-retractor in accordance with the present invention having a distal deployable anchor 640 as a deployable cage, formed by axially offset pairs of outwardly expanding anchor portions 640 a, 640 b, which are generally ribbon-shaped in configuration.\\nIn accordance with the invention, the needle body 630 can be configured as desired. In accordance with one aspect of the invention, the needle body 630 has about a 2.1 mm outer diameter and 225 mm length. A safety plug 639 can be provided for the same reason as the sheath 537 of the above-described embodiment, namely to inhibit unintentional trauma to the patient when the needle body 130 is not intentionally and actively being inserted through anatomy. In the safe position illustrated in FIG. 35, a sharp tip of the needle body 630 is shielded by the plug 639, which extends distally past the tip thereof.\\nConversely, to pierce a structure, the plug 639 is retracted by withdrawing the cage 640 proximally. Suction applied to a central lumen allows for aspiration of contents through the lumen, around the plug 639. Alternatively or additionally, fluid can be aspirated through the (four) fenestrations in the needle body 630 provided for the expanding anchor portions 640 a, 640 b. Aspirated contents can be carried through an inner tube and to the connected suction system.\\nLater, for deployment of the anchor portions 640 a, 640 b, the cage 640 is urged distally, which also results in the plug 639 being placed in the safety position. In the illustrated embodiment, tabs formed by on respective legs of the cage 640 engage respective slots in a pushing element, or expander 642 and a pusher tip 644. The expander 642 and pusher tip 644 can be welded to respective inner and outer tubes, such as actuator 646, that can be move axially relative to one another, to enable control of deployment of the cage 640.\\nIn use, an inner tube (not illustrated) connected to the expander 642, can be advanced distally to deploy the distal grasper portions 640 b, within the gallbladder. The whole aspirator-retractor can then be retracted proximally until the set of distal anchor portions 640 b are engaged with an inner surface of the gallbladder wall. The outer tube 646, connected to the pusher 644 can then be advanced to open the proximal grasper portions 640 a, to expand on the outside of the gallbladder, sandwiching the wall of the gallbladder therebetween.\\nThus, the aspirated gallbladder is securely held by the aspirator-retractor and is able to be manipulated by the surgeon while it is dissected from connecting vessels and tissues. In accordance with one aspect, the gallbladder can then be placed in an endoscopic collection bag and both inner and outer tubes can be retracted to pull the anchor portions 640 a, 640 b inside of the needle body 630, to release the gallbladder. Subsequently, the aspirator-retractor can then be removed from the abdomen and discarded.\\nAs with other embodiments set forth herein, the illustrated configuration of an aspirator-retractor can be integrated with handles described herein.\\nAs with other embodiments described herein, the anchor portions 640 a, 640 b extend through respective apertures, which are formed, in this case, in the needle body 630 by a suitable technique, such as by laser cutting.\\nIn accordance with one aspect, the anchor cage portions 640 a, 640 b can be formed of a 0.005 inch-thick, full hard stainless steel, or another suitable material. The Anchor cage 640 can be formed from a single or a plurality of nested layers.\\nVarious additional alternative embodiments of aspirator-retractors in accordance with the invention are provided, as follows.\\nFIG. 37 is an isometric view of a distal end portion of a further embodiment of a surgical aspirator-retractor 700 in accordance with the invention having deployable ribbon elements 740 a, 740 b with barbs formed thereon to facilitate engagement with a hollow structure. Construction and operation of the aspirator-retractor 700 is in keeping with other embodiments described herein, such as with the embodiment of FIGS. 35 and 36.\\nFIG. 38 is an isometric view of a distal end portion of still a further embodiment of a surgical aspirator-retractor in accordance with the invention having a distal anchor element 840 formed by deployable ribbon elements 840 a for deploying respective elongated barbs 840 b.\\nFIG. 39 is an isometric view of a distal end portion of still a further embodiment of a surgical aspirator-retractor in accordance with the invention, having an axial, radially deployable wire anchor 940, deployable from the needle body 930 thereof. Deployment of the anchor 940 can be effected by providing distally-directed force to an actuating rod, connected to a proximal end of the wire anchor 940, and concentrically disposed within the lumen of the needle body 930.\\nFIG. 40 is an isometric view of a distal end portion of another embodiment of a surgical aspirator-retractor in accordance with the invention, having a helical, radially deployable wire anchor 1040. A distal portion of the helical wire anchor 1040 is secured to a main needle body 1030, while a proximal end portion of the helical wire anchor 1040 is secured to a concentrically outer actuating tube 1033. Therefore, relative movement between the main needle body 1030 and the outer tube 1033, including rotation and/or translation, can effect deployment of the anchor 1040. The distal end 1032 can be solid, or open, or can include apertures for aspiration on side surfaces thereof.\\nFIG. 41 is an isometric view of a distal end portion of another embodiment of a surgical aspirator-retractor in accordance with the invention, having a single inflatable distal anchor element 1140 carried by a needle body 1130. The inflatable distal anchor element 1140 can be inflated via one or more channels formed within the needle body 1130, and configured and adapted to be insufflated by a liquid, such as saline, or a gas, such as compressed air or carbon dioxide. As with any of the embodiments described herein, the distal end 1032 can be solid, or open, or can include apertures for aspiration on side surfaces thereof.\\nFIG. 42 is an isometric view of a distal end portion of a further embodiment of a surgical aspirator-retractor in accordance with the invention, having a plurality of inflatable distal anchor elements 1240 a, 1240 b, provided on a needle body 1230, for respectively engaging inner and outer surfaces of a hollow organ, such as a the gallbladder. The inflatable anchor elements 1240 can be inflated via one or more channels formed within the needle body 1230, and configured and adapted to be insufflated by a liquid, such as saline, or a gas, such as compressed air or carbon dioxide. As with any of the embodiments described herein, the distal end 1032 can be solid, or open, or can include apertures for aspiration on side surfaces thereof.\\nFIGS. 43-48 illustrate various views of still a further embodiment of a surgical aspirator-retractor in accordance with the present invention having a distal anchor 1340 with axially offset pairs of outwardly expanding anchor portions 1340 a, 1340 b, formed of ribbons of material, for engaging inner and outer wall surfaces of a hollow organ, respectively, as described above in connection with other embodiments. In accordance with this embodiment, a moveable inner shaft 1331 is provided over the needle body 1330, over which a stationary intermediate shaft 1333 is provided, over which a moveable outer shaft 1337 is provided. Each of the moveable shafts is controllable, with respect to the stationary main needle body 1330 and intermediate shaft 1333. In accordance with the invention, distally-directed compressive forces result in radial outward expansion of the respective anchor portions 1340 a, 1340 b. As with any of the embodiments described herein, apertures 1337 for aspiration can be provided on side surfaces of the needle body 1330.\\nFIG. 49 is a side view of a distal end portion 1440 a of still a further embodiment of a surgical aspirator-retractor in accordance with the invention, having an expandable mesh distal anchor elements.\\nFIG. 49 is a side view of a distal end portion of still a further embodiment of a surgical aspirator-retractor in accordance with the invention, having two expandable mesh distal anchor elements 1440 a, 1440 b, with the distalmost anchor 1440 a in a deployed, expanded conformation. FIG. 50 is a side view of the surgical aspirator of FIG. 49, with both anchor elements deployed, sandwiching a wall of the gallbladder therebetween. As with other embodiments, the mesh distal anchor elements 1440 a, 1440 b are connected to coaxial elements to permit manipulation thereof.\\nFIG. 51 is a side view of a distal end portion of the surgical aspirator-retractor having proximal and distal prong-shaped anchor elements 1540 a, 1540 b, with only distal anchor elements 1540 a deployed. FIG. 52 is a side view of the surgical aspirator-retractor of FIG. 51 with both inner (distal) 1540 a and outer (proximal) 1540 b anchor elements deployed. An outer sheath 1537 is provided to facilitate stowing of the anchor elements when retraction is completed.\\nFIG. 53 is a side view of a distal end portion of an additional embodiment of a surgical aspirator-retractor in accordance with the invention, having distal deployable ribbon-shaped engagement elements 1640 a, and proximal deployable prong-shaped engagement elements 1640 b, adapted and configured for deployable from common slots provided in the needle body 1630. FIG. 54 is a side view illustrating all anchor elements in a deployed configuration, thereby sandwiching the wall of the gallbladder 991 therebetween.\\nIt will be apparent to those skilled in the art that various modifications and variations can be made in the device and method of the present invention without departing from the spirit or scope of the invention. It is particularly conceived that elements of one embodiment described herein can advantageously be applied to any embodiment of devices in accordance with the invention, even if such features are not explicitly described in connection therewith, unless such feature should be mutually exclusive or otherwise incompatible with other features of such embodiment. Thus, it is intended that the present invention include modifications and variations that are within the scope of the appended claims and their equivalents.\\nwherein the distal end of the anchor is attached to an outer surface of the needle body such that the sharpened distal tip extends beyond the distal end of the anchor in both the collapsed and the expanded deployed configurations.\\n2. The surgical instrument of claim 1, wherein the aperture in the needle body is operatively disposed between the proximal and distal ends of the anchor in both the collapsed and expanded deployed configurations.\\n3. The surgical instrument of claim 1, wherein the distal end of the anchor is longitudinally fixed relative to an outside surface of the needle body.\\n4. The surgical instrument of claim 1, wherein the anchor is a deployable cage structure.\\n5. The surgical instrument of claim 4, wherein the cage structure is spring-biased such that the cage structure is deployed by tension provided in a spring when the cage structure extends beyond the needle body by a predetermined distance.\\n6. The surgical instrument of claim 4, wherein the cage structure includes at least one barb configured to extend from the cage structure when the cage structure is in the deployed configuration.\\n7. The surgical instrument of claim 6, wherein barb is distally directed to facilitate reinsertion of the cage structure into a lumen of the needle body.\\n8. The surgical instrument of claim 6, wherein the at least one barb is proximally directed to facilitate engagement thereof with an inner wall of the hollow organ.\\n9. The surgical instrument of claim 8, wherein the cage is configured so that the at least one barb is substantially parallel to the needle body and surrounding portions of the cage in the collapsed configuration.\\n10. The surgical instrument of claim 4, wherein the cage structure is provided with at least one fenestration to facilitate bending manipulation of the cage.\\n11. The surgical instrument of claim 4, wherein the cage structure is provided with a plurality of legs, symmetrically arranged about a longitudinal axis of the surgical instrument.\\n12. The surgical instrument of claim 4, wherein the cage structure includes a plurality of nested cages to permit flexibility of the cage.\\n13. The surgical instrument of claim 1, wherein the anchor is a deployable wire structure.\\n14. The surgical instrument of claim 1, wherein the anchor includes a distal anchor portion and a proximal anchor portion adapted and configured to engage inner and outer surfaces of the hollow organ, respectively.\\n15. The surgical instrument of claim 14, wherein the distal anchor portion and the proximal anchor portion are longitudinally spaced apart by a distance sufficient to permit engagement of a wall of the hollow organ.\\n16. The surgical instrument of claim 14, wherein the distal anchor portion and a proximal anchor portion are rotationally offset from one another by about 90 degrees, with respect to a longitudinal axis of the surgical instrument.\\n17. The surgical instrument of claim 14, wherein the distal anchor portion and the proximal anchor portion are of substantially the same configuration.\\n18. The surgical instrument of claim 1, further comprising a deployable tip protector to inhibit unintentional injury by the sharpened distal tip of the needle body.\\n19. The surgical instrument of claim 18, wherein the deployable tip protector is a translatable sheath adapted and configured to be deployed over the sharpened distal tip of the needle body.\\n20. The surgical instrument of claim 18, wherein the deployable tip protector is a translatable plug adapted and configured to be deployed from within a lumen of the needle body.\\n21. The surgical instrument of claim 20, wherein the plug is adapted and configured to extend distally beyond the sharpened distal tip of the needle body, to inhibit piercing of a structure by the needle body, when in a deployed position.\\n22. The surgical instrument of claim 1, wherein the aperture is provided at the distal end of the body.\\n23. The surgical instrument of claim 1, wherein the aperture is provided in a distal end portion of a sidewall of the body.\\n24. The surgical instrument of claim 1, wherein the anchor is formed at least in part from one of a shape-memory alloy and a stainless steel.\\n25. The surgical instrument of claim 1, when in the anchor is formed at least in part by laser cutting.\\n26. The surgical instrument of claim 1, wherein an outer diameter of the needle body is about 2 mm.\\n27. The surgical instrument of claim 1, wherein the anchor is configured such that, in the deployed configuration, a width, measured transverse to a longitudinal axis thereof, is a maximum of about eight times that of a width in the collapsed configuration, measured transverse to the longitudinal axis thereof.\\n28. The surgical instrument of claim 1, wherein the needle body is provided with a sharpened end surface angled at about 15 degrees with respect to a longitudinal axis of the needle body.\\n29. The surgical instrument of claim 1, further comprising a handle in connection therewith, to facilitate manipulation of the surgical instrument.\\n30. The surgical instrument of claim 1, wherein the needle body includes a side surface having a plurality of apertures for aspiration.\\n32. The method of claim 31, further comprising the step of: deploying a second anchor portion of the surgical instrument outside the hollow organ to engage an outer surface of the hollow organ.\\nwherein the distal end of the anchor is attached to an outer surface of the needle such that the sharpened distal tip extends beyond the distal end of the anchor in both the collapsed and the expanded deployed configurations.\\nwherein the mounting the deployable anchor includes attaching a distal end of the anchor to an outer surface of the needle such that the sharpened distal tip extends beyond the distal end of the anchor in both the radially collapsed and the expanded deployed configurations.\\nCauterization, Wikipedia entry, Apr. 5, 2011 (3 pages) http://en.wikipedia.org/wiki/Cauterization.\\nInternational Search Report and Written Opinion for PCT/US2010/053707 issued May 9, 2011.\\nInternational Search Report for PCT/US07/63883.\\nInternational Search Report for PCT/US07/80938.\\nNeedlescopic Cholecystectomy, Procedure Profile, California Pacific Medical Center.\\nES2376660T3 (en) 2012-03-15 endoscopic organ retraction system and method of use thereof.<|begin_of_text|>That\\'s what we\\'re up against, that it\\'s perceived as at triumph that you can get strawberries in January as opposed to a catastrophe. Not all choice is good. Even if the January strawberry tastes OK, even if you have a really good strawberry that\\'s organic, I still know you turned down other things for that to happen.\\nThat\\'s something I can do is try to make the menu, as much as I can, reflect a lot of the natural rhythms of this part of the world and reflect used to be the way you would eat before you could cheat.\\nAnd guess what? That\\'s what culinary tradition is, making the harvest season last all year long. My God, the most unique holiday we have is Thanksgiving, it should be something that if you really ponder what Thanksgiving is all about, you would really understand food. But people think it\\'s about gluttony, as opposed to truly revering this your great harvest celebration, and now put stuff up so you don\\'t starve over the winter. But people don\\'t think about it that way—here, it\\'s the beginning of the eating season.\\nVery interesting…I do agree that having all foods available all the time can make eating less pleasurable. For example, I never eat fresh apples out of hand…except for every fall, when I pounce on the Honeycrisps from Door County.\\nStill, I wonder about the practicality of eating seasonally and putting food up for winter. With a full time position in academia, a working spouse, and a toddler, I think I\\'m doing well to get anything homemade on the table most days. Would I love to can and preserve and put up those tomatoes from my garden, so that I have homemade sauces and local veggies all winter? Absolutely…and maybe someday I\\'ll get there. But in the meantime, I can\\'t promise that I\\'ll limit myself to root vegetables until next May in the name of eating locally.\\nI\\'m not saying this to argue Rodgers\\'s point, because I strongly believe in supporting the local farmer. I\\'d love to, however, tap the knowledge resources of everyone here–how DO we live sustainably in a time-crunched world?\\nI was just talking about this today on another board. I think so many people think of healthy eating as an \"all or nothing\" approach, and I think it\\'s not being \"sold\" the right way to the public. They hear \"This is bad for you, that is bad for you,\" they think \"There\\'s nothing left to eat! So they throw up their hands and grab whatever they see that looks and sounds good and is quick and easy (and cheap) or they drive through wherever is closest.\\nI think we have gotten so far off the path of what we are supposed to be eating as human beings that it\\'s just going to take gradual tweaking and tweaking and doing your best to make the right choices when and where you can. It\\'s not about being perfect and starting to can your own veggies or make your own jams as that\\'s not feasible for many of us (including apartment dwellers like me). However, my grocery cart in the checkout line today is nowhere near what it was 5 years ago, and is on a completely different planet from 10 years ago, but I know I\\'m still \"not there\" and I continue to tweak when and where I can. And I *enjoy* it. I don\\'t feel like it\\'s a chore. I like finding out that this product is better than that one or that I prefer this one to that one because their company or farm does things I approve of and the competitor product does not. It has made shopping enjoyable for me again instead of a chore.\\nThere\\'s a big misconception about scratch cooking=TIME and though I find her irritating, Rachael Ray is doing a great job of smashing that barrier for the \"average American\" (whatever that is). I think at the same time, despite the hard work of many like Ms. Rodgers, the whole \"seasonal\" thing is not being explained well or pushed out to the masses the right way. I keep thinking if we had someone like Rachael Ray who could show QUICK and SIMPLE and TASTY and INEXPENSIVE as well as SEASONAL, seasonal shoppers would help drive LOCAL by virtue of demand, instead of putting out the local produce (which I see even in the big chain groceries now, albeit in limited quantity/variety) and them buying what they\\'re used to buying because they always buy it and they don\\'t know what to do with radishes or parsnips or why tomatoes from less than 20 miles away are better and fresher than those trucked in from the other side of the country.\\nMaybe you can only make one thing and put it away for winter right now, and it\\'s a fun, family project that you do for Thanksgiving instead of everyone gorging as Rodgers points out, and then you enjoy it when those dark and cold days come in January and February and it feels like the winter will never end. And it makes you smile. And that\\'s what it\\'s about.\\nI have recently had a great deal of interest in learning to braise food. I am mastering that skill now, and I think I have done it well.At the same time I am learning what to do with celery root. It is amazing how many different types of food we see through the seasons that are maybe out of our normal paradigm of what we may or may not eat. This summer I learned how to grow and harvest fennel. Of course I can say that much of my interest in these things comes from the vast amount of reading I do. Whether it be on egullet, Food and Wine, Gourmet or a blog, a great deal of interest in food comes from what is out there in the media.\\nFind a reason to eat in season.\\nA lot of eating seasonally definitely revolves around techniques for cooking food that\\'s available at the time.\\nFall and Winter foods are certainly harder to cook, since you typically have to do something involved to the ingredients to make their flavors come out. This is a decidedly different approach to cooking than most Spring and Summer food, where you\\'re likely to get the best results by staying hands off and letting the ingredients speak for themselves.\\nAlso, I think there\\'s certainly a distinction between eating Chilean blueberries in February and eating commercially preserved blueberries (assuming they\\'re done in a way that\\'s reasonably healthy and natural). Nobody says you have to do all of the preservation work yourself.<|begin_of_text|>Lingual retainer\\nThe invention relates to a lingual retainer which can be connected at both ends to the teeth of a patient by means of an adhesive connection in order to maintain the position of the corrected teeth of the patient in said corrected position. The retainer avoids known problems encountered with conventional material and also exhibits good flexibility as well as good biocompatibility and a high patient comfort. It can also be used over a long period of time (in extreme cases, for a lifetime) without any detrimental effects on health. The retainer is made of one material which is either titanium or a titanium alloy.\\nSernetz, Friedrich (Pforzheim, DE)\\nDentaurum J. P. Winkelstroeter KG (Ispringen, DE)\\nA61C5/00; A61C7/00; A61C13/225; (IPC1-7): A61C13/225\\n20050196723 Assortment of teeth and method for preparing teeth September, 2005 Monkmeyer\\n20080293016 TRY-IN IMPLANT WITH HANDLE November, 2008 Lussi et al.\\n20040137405 Method for preparing a full denture device July, 2004 Fang\\n20080070195 Energetically activated biomedical nanotheurapeutics integrating dental and medical treatments and procedures March, 2008 Divito et al.\\n20100047734 PERIODONTAL LASER TREATMENT AND LASER APPLICATOR February, 2010 Harris et al.\\n20090162808 Apparatus in Dental Environment and Method for Controlling a Device Belonging to the Same June, 2009 Nyholm\\n20090269718 Oral implant placement system October, 2009 Duncan\\n20090104582 Male threaded implant drill April, 2009 Duncan\\n20070275351 Healing Abutment and Dental Implant Having the Same November, 2007 Park et al.\\n20040241607 Incisal guiding table for dental articulators or the like December, 2004 Slavicek\\n20080166677 Light directing and amplifying device July, 2008 Graham\\nEIDE, HEIDI MARIE\\nLEYDIG VOIT & MAYER, LTD (Alexandria, VA, US)\\n1. An orthodontic appliance in the form of a lingual retainer comprising a bow having two ends, wherein the retainer is fabricated from only one material selected from the group consisting of titanium and titanium alloys, the bow having a bonding region having a surface at each of its two ends, and wherein the bonding regions are roughened on the surfaces thereof to be bonded.\\n2. The appliance as defined in claim 1, wherein the bow and the bonding regions are fabricated as a unitary structure.\\n3. The appliance as defined in claim 1, wherein the bow has substantially the same thickness as the bonding regions and the bow is connected to each of the bonding regions by a substantially flush joint.\\n4. The appliance as defined in claim 2, wherein the bow is fabricated from a sheet metal material.\\n5. The appliance as defined in claim 1, wherein the bow is fabricated from a multistrand wire.\\n6. The appliance as defined in claim 1, wherein the roughening of the bonding surface of the bonding regions is produced by sandblasting, etching or laser structuring.\\n7. The appliance as defined in claim 1, wherein the bow is a profiled bow.\\n8. The appliance as defined in claim 1, wherein the bow has surface regions at and/or between its ends on that side of its surface which will face the teeth of a patient, which surface regions are roughened for the accommodation of a bonding agent.\\n9. The appliance of claim 7, wherein the bow exhibits a profile of half-round cross section.\\n10. The appliance of claim 7, wherein the bow exhibits a profile of half-oval cross section.\\n11. The appliance as defined in claim 2, wherein the bow has substantially the same thickness as the bonding regions and the bow is connected to each of the bonding regions by a substantially flush joint.\\n12. The appliance as defined in claim 3, wherein the bow is fabricated from a sheet metal material.\\n13. The appliance as defined in claim 2, wherein the bow has surface regions at and/or between its ends on that side of its surface which will face the teeth of a patient, which surface regions are roughened for the accommodation of a bonding agent.\\n19. The appliance as defined in claim 10, wherein the bow has surface regions at and/or between its ends on that side of its surface which will face the teeth of a patient, which surface regions are roughened for the accommodation of a bonding agent.\\nThis application is a continuation of International Application No. PCT/EP03/10478, filed Sep. 19, 2003, which is incorporated herein by reference.\\nThe invention relates to an orthodontic appliance in the form of a lingual retainer comprising a bow that can be attached at both ends to the teeth of a patient by means of a cement bond, in order to keep the patient\\'s teeth in position following corrective treatment.\\nThe purpose of lingual retainers is to keep teeth in a new, corrected position following orthodontic treatment and to stabilize this position. Lingual retainers are usually bonded to the teeth on the non-visible (lingual) surface thereof.\\nPrior art lingual retainers consist, for example, of a bow made of, say, a non-annealed Co/Cr alloy, as this alloy ensures that the brace is sufficiently pliable to enable the bonding regions to be positioned to fit well against the surface of the teeth. The bonding regions are produced by soldering so-called metal mesh pads of, e.g., stainless steel to the ends of the bow.\\nThe main disadvantages of this kind of lingual retainer comprise the use of different metals or alloys and the fact that the metal mesh pad is joined to the bow by soldering, as a result of which the resistance to corrosion or the biocompatibility of the retainer is substantially reduced. Furthermore, the bonding regions increase the overall thickness and reduce patient comfort.\\nIt is an object of the present invention to provide a lingual retainer showing good pliability and biocompatibility while avoiding the aforementioned material-dependent problems and affording enhanced patient comfort, thereby allowing it to be worn for prolonged periods (in extreme cases for a lifetime) without causing health-related side effects.\\nThis object is achieved, according to the invention, by fabricating a lingual retainer of the type defined above from a single material selected from the group consisting of titanium and titanium alloys.\\nRetainers of the present invention made from titanium or titanium alloys are highly biocompatible and can thus be used for very long periods of time without causing any adverse health-related side effects.\\nFurthermore, titanium or titanium alloys are materials that are of low rigidity (low modulus of elasticity), are pliable, having a low elastic limit, and can be readily bonded to teeth.\\nIn a variant of the retainer of the invention, the bow has a bonding region at each end thereof, by means of which it can be bonded in a simple and accurate manner to the patient\\'s teeth.\\nAlternatively, simple retainers can be used, these being composed of a bow only and often consisting of a (frequently multistrand) wire, the elastic limit of which is so low that it is pliable. These simple bows not equipped with bonding regions are bonded as such to the lingual surface of the teeth to be stabilized.\\nWithin the scope of the present invention, bonding is understood to mean any kind of connection that adhesively joins materials together. Specifically, a bond can be created using any of the standard cements employed in dentistry, particular examples of which for use in the present context are glasionomer cements.\\nThese retainers can also be specially prepared for bonding by providing them with specially prepared surface regions at the sites where they are to be bonded to the patient\\'s teeth. In the simplest case, these would be surface regions located at each end of the bow. This bow more preferably has on its side designed to face the surface of the teeth one or more additional surface regions prepared for bonding to teeth.\\nThe preparation of the surface region for bonding purposes may consist of roughening, for example. Roughening can be accomplished by etching, sandblasting, laser machining, or by mechanical machining, such as embossing or metal cutting.\\nThe retainer is preferably produced with its bow and the two bonding regions forming a unitary structure. If desired, the bonding regions may be adapted to provide an enlarged surface area for bonding the retainer to the teeth.\\nThe bow more preferably has substantially the same thickness as the bonding regions, and the transition between the bow and the bonding regions is such that the bow substantially merges with the bonding region or is attached thereto in flushed relationship. In this way the bonding regions do not increase the overall thickness, and patient comfort is enhanced.\\nWith respect to this requirement as well as to the need for the simplest possible manufacturing process, the retainer is preferably made from sheet metal, e.g., by stamping.\\nThe entire retainer, that is, the bow including the bonding regions at its ends, is thus stamped from the sheet metal, or else fabricated there from in some other way, so that the retainer has consistent thickness. The necessary residual rigidity is set by the occlusal-gingival dimension of the bow.\\nIn another preferred embodiment, the bow of the retainer is made from multi-strand wire. In this case, a plurality of wire filaments is stranded to form a wire. The individual filaments may be of the same or different types. Thus it will be a very simple matter for the person skilled in the art to produce retainers having the desired mechanical properties mentioned above, not only by varying the number of filaments used, but also by selecting them according to their mechanical strength values. In this regard, not only the diameter of the individual filaments, but also their composition, can be varied so that, for example, a number of filaments of various similar titanium alloys can be used. This meets the demand for biocompatibility forming one of the objectives of the invention.\\nAdvantageous retainers can be produced from half-round or half-oval profiled materials, and the surface regions required for bonding purposes can be formed on the flat side of the bow.\\nThis avoids the presence of projections and depressions on the retainer, which are detrimental to oral hygiene, and result, inter alia, in improved patient comfort, because the tongue, which can detect very small uneven regions, will only come into contact with a material that is substantially uniformly thick and thus smooth.\\nThe bonding regions are preferably roughened on the surface to be bonded.\\nVarious methods are recommended for roughening the relevant surfaces of the bonding regions, such as sandblasting, chemical etching or, in particular, laser structuring, that is, machining with a laser ray, as disclosed in EP 0 841 877 B1.\\nThe titanium or titanium alloy lingual retainers of the invention can be fabricated in particular as a unitary structure without involving soldering or the use of additional metal mesh pads or other supplementary materials, so that the high degree of biocompatibility of titanium and titanium alloys can by fully exploited.\\nAn advantage of titanium and titanium alloys is that they have a low modulus of elasticity, so that the lingual retainer itself will react with only a low restoring force to any possible deflection thereof by the tooth to be held in place. This is assisted by the pliability, i.e., the low elastic limit, of titanium and titanium alloys, which makes the shape of the bow readily adaptable to the topology of a patient\\'s mouth.\\nThe flat form, which is preferred, is easy to produce by manufacturing the lingual retainer from a titanium or titanium alloy sheet metal, e.g., by stamping or cutting.\\nIn the latter case especially, the bonding region is formed flush with the bow and is thus not made thicker by any soldered-on metal mesh pad.\\nThe previously mentioned method of laser structuring (EP 0 841 877 B1) creates an adequate number of retention sites, which is conducive to a lifelong, durable adhesive bond.\\nThese and other advantages of the invention are explained in greater detail below with reference to the drawings, in which:\\nFIG. 1: shows an initially unbent embodiment of a lingual retainer of the invention;\\nFIG. 2: shows another variant of the lingual retainer of the invention;\\nFIG. 3: is a diagrammatic representation of a lingual retainer of the invention attached to the lower jaw of a patient; and\\nFIG. 4: shows another embodiment of the lingual retainer of the invention.\\nFIG. 1 illustrates a lingual retainer made of, e.g., a titanium alloy, designated as a whole by the reference number 10. Lingual retainer 10 consists of a profiled bow 12 and two bonding regions 14, 16 formed one at each end thereof.\\nLingual retainer 10 illustrated in FIG. 1 is stamped from a titanium alloy sheet as a unitary structure, i.e., bonding regions 14 and 16 are integral with bow 12. Furthermore, lingual retainer 10 is of consistent thickness over its entire length, and this promotes oral hygiene and, since there are no recesses or protuberances which could disturb the tongue, enhances the patient comfort.\\nBonding regions 14 and 16 are roughened on their surfaces 18 and 20 respectively in preparation for bonding the same to a patient\\'s tooth, said roughening being in the form of a grid-like laser structure. It is therefore not necessary to solder on a metal mesh pad, as otherwise necessary, which is not only an advantage with regard to the biocompatibility of the lingual retainer of the invention, but also reduces the number of production steps, since laser structuring is much easier to accomplish and is more economical. Furthermore, corrosion problems are avoided, since the incorporation of additional materials other than titanium or titanium alloys is no longer necessary due to the type of bonding surface 18 or 20 used.\\nAlternatively, bonding surfaces 18, 20 may be sandblasted or chemically etched, in which case it is only necessary to ensure that the surface is adequately roughened with, in particular, undercutting thereof, which will ensure secure anchorage of the cement to the bonding regions 18 and 20.\\nFIG. 2 illustrates another variant of a lingual retainer 30 of the invention, which is composed of a bow 32 and two bonding regions 34, 36. In this embodiment, the bow 32 is welded to the separately manufactured bonding regions, e.g., by laser welding.\\nBow 32 is anatomically pre-formed so that the dentist merely has to make slight additional corrections to the shape of the bent bow 32 before placing it in the mouth of a patient and cementing it to the patient\\'s teeth.\\nThe bonding regions 34, 36 have a bonding surface 38 and 40 respectively, which is again laser structured, as described above in connection with FIG. 1.\\nFIG. 3 is a diagrammatic illustration of a typical attachment situation involving a lingual retainer, for example a lingual retainer 50 comprising a bow 54 and bonding regions 56, 58 formed thereon.\\nBonding regions 56, 58 are bonded to the lingual side of, say, the cuspids of the lower jaw 52 of a patient by a cement bond and they maintain said cuspids, as well as the incisors located between them, in the position attained by previous corrective treatment using some other orthodontic device.\\nFIG. 4 illustrates an alternative embodiment of a retainer 60 of the invention made from a profiled titanium material having a half-round cross section. Unlike the retainers illustrated in FIGS. 1 to 3, the lingual retainer 60 has no enlarged region on the ends 62, 63 of its brace 64 for bonding to the surfaces of the teeth, but instead the surface regions 66, 67 are confined to the flat surface of the half-round profile.\\nFIG. 4 further illustrates that the lingual retainers of the invention may also preferably have surface regions 68 along their bow at intervals corresponding to the positions of the teeth, which surface regions supplement the surface regions 66 and 67, so that this lingual retainer 60 can, if required, be adhesively attached to each of the teeth supported by bow 64.\\nPrevious Patent: Dental implant system and method for effecting a dental restoration using the same\\nNext Patent: System and method for detecting dental caries<|begin_of_text|>Seats and Chairs\\n6029 Luce Ave SE 49302 Alto, Michigan\\nHome About Us Contact Us Wish List (0) My Account Checkout\\nSeatsAndChairs.com | Where Your Home Theater Begins! | 1-800-632-7657\\nNew Movie Theater Chairs\\nUsed Movie Theater Chairs\\nCommercial Grade Power Movie Theater Recliner\\nLeather Seating (3)\\nClassic Theater Seating (3)\\nStackable Chairs\\nInstallation & Removal Services\\nRefurbishing Services\\new Buy Chairs\\nHome Theater Resources\\nSeats and Chairs Videos\\nSeats and Chairs Return Policy\\nTypical Shipping Costs\\nHome » News/Blog Headlines » Seven of the Best Movie Theaters in the World\\nSeven of the Best Movie Theaters in the World\\nIf you\\'re like us, you probably enjoy most of your movies at home. But sometimes; there are movies that are so good, so awe-inspiring, and so epic that you want to enjoy them where they\\'re supposed to be watched: in the cold, dark confines of a movie theater with a giant tub of popcorn in hand, and a jumbo-sized drink in your seat\\'s cup holder. Some movies are just worth getting in the car to drive to the theater, and stand in line to buy a ticket just to see it once. Or twice. Or seven times.\\nTo be fair, it\\'s not always the movie. The movie theaters themselves can be so awesome and so epic as to be worth the hassle just to get there, no matter what movie they\\'re playing. And no, we\\'re not talking about 4D or other newfangled types of sound and picture processing technology. We\\'re talking about an incredible theater experience that will make you feel like coming back for more. Here is our list of seven of the best movie theaters ever:\\nThe Alamo Drafthouse in Austin, Texas – First opened in 1997, the Alamo Drafthouse can now be found in 22 different locations in the US. It is famous for being among the first theaters to adopt a more classy movie-watching experience by offering comfortable seating, drinks, and food that you might find in an upscale, fine dining restaurant.\\nThe Cine-de Chef in Kathmandu, Nepal – This theater\\'s claim to fame is its level of luxury, with its expensive ticket prices, plush leather chairs, and gourmet food prepared by a chef. Cine-de Chef also boasts of having another branch in Seoul, South Korea.\\nThe Nitehawk Cinema in Brooklyn, New York – Williamsburg in Brooklyn is where you\\'ll need to go to find this unique venue with three screens where; aside from a movie, you can partake of a global menu and craft cocktails that are served straight to your luxury seat.\\nThe Electric Cinema in London, England – To say that this movie theater; found in London\\'s Notting Hill Area, is quite posh is an understatement. Watch a movie while relaxing in large, comfy seats with footstools and cashmere blankets; or on beds (yes, beds) located at the front of the screen. Enjoy a bottle of wine, or have some Camden Ale while munching on Carrot Cake, Nachos, or a big portion of Chicken Bites. You can also have drinks at the full bar; and have an after-movie meal at its Electric Diner. Posh, indeed.\\nThe Cinémathèque Française in Paris – When is a movie theater more than just a place to watch films? When it\\'s also a museum (partially, anyway)!The museum part of the theater boasts an impressive collection of film memorabilia: from historical items such as camera obscura, magic lanterns, and optic boxes from the past; as well as posters, costumes, and props such as the classic female robot used in Fritz Lang\\'s film Metropolis. Designed by architect Franck Gehry, the theater shows films from all over the world, and sometimes screens classic films of cinematic legends.\\nThe Raj Mandir Cinema in Jaipur, India – This movie theater gets special mention for its grand interiors and palatial design: balcony viewing areas, impressive high ceiling decked with chandeliers, carpets, and elaborate carvings make this venue feel more like a tourist spot than a theater. The Raj Mandir is one of the oldest movie theaters is India, having been built in 1976, and is a popular site for movie premieres of Hindi films. Watch the movie on an extra-large screen while enjoying Samosas, and bask in the theater\\'s incredible history.\\nThe TCL Chinese Theatre in Los Angeles, California – No discussion of movie theaters would be complete without including the TCL Chinese Theatre. Known to people by its more popular names; as the Grauman\\'s Chinese Theatre, and then as the Mann\\'s Chinese Theatre, the TCL Chinese Theatre is an important part of movie history. Famous for its Hollywood Walk of Fame where you can find the foot and hand prints of your favorite stars; the TLC Chinese Theatre also features a guided tour, or you can just take in a movie showing on the theater\\'s massive screen.\\nCreate your own unforgettable movie experience by watching films in your very own Home Theater. Seats and Chairs.com can provide used and new movie theater seats to give your movie room that authentic theater feel. We supply homes and commercial establishments with used and new theater seats; as well as Stackable Chairs and Home Theater Accessories. We also install, remove, rent out, and refurbish movie seats for you.. Give us a call at (800) 632-7657, or contact us online for all of your movie theater seat inquiries and for more information.\\nNew Savoy Movie Theater Rocker - Home Theater Seating\\nThe Home Theater Checklist\\nInstallation Projects\\nNew Theater Chairs\\nUsed Theater Seating\\nAccessories And Audio\\nSeats And Chairs. com\\nReal theater seats offer real comfort and durability. Since 2002, home owners, theaters, and businesses have turned to us to provide them with high-quality theater seats and chairs, accessories, and audio at affordable prices.\\nWhen the lights dim and the show begins, the audience quiets and settles into authentic theater seats, designed to be comfortable and long-lasting.\\n2017 © SeatsandChairs.com<|begin_of_text|>Roe v. Wade / Casey OVERTURNED. What\\'s the Effect on Employers and Health Plans?\\nLisa Nelson June 24, 2022, 8:25 am August 1, 2022 Comments Off on Roe v. Wade / Casey OVERTURNED. What\\'s the Effect on Employers and Health Plans?\\nUpdate June 24, 2022\\nThis morning, the Supreme Court of the United States (SCOTUS) found in favor of the state of Mississippi in the Dobbs case (cited in detail below). In doing so, SCOTUS also overturned prior SCOTUS decisions in Roe (1973) and Casey (1992), effectively banning abortive care in states where there exists pre-Roe and \"trigger\" bans of abortion. Trigger bans are where state law already bans access, in some degree, to abortive care should Roe be overturned. Since Roe was overturned in the Dobbs decision, it is up to each state to determine access to abortive care in their state. To-date, states with such bans potentially effective upon the overturning of Roe based on pre-Roe laws or pre-decision state action include: AL, AZ, AK, GA, ID, IA, KY, LA, MI, MS, MO, ND, OH, OK, SC, SD, TN, TX, UT, WV, WI and WY. Of which OK, NE, SD, TX and LA are immediate and others within 30 days or upon state decision on how to handle pre-Roe laws still on the books that ban abortive care. Four other states have indicated they too will impose restrictions to abortive care access in some form, including: FL, IN, MT and NE. Conversely, the following states have or plan to take action to ensure continued access to abortive care: CA, CO, CT, DE. HA, IL, ME, MD, MA, NV, NJ, NY, OR, RI, VT, WA and the District of Columbia.\\nThe specific questions posed to SCOTUS in the Dobbs case were:\\n1. Whether all pre-viability prohibitions on elective abortions are unconstitutional.\\n2. Whether the validity of a pre-viability law that protects women\\'s health, the dignity of unborn children, and the integrity of the medical profession and society should be analyzed under Casey\\'s \"undue burden\" standard or Hellerstedt\\'s balancing of benefits and burdens.\\n3. Whether abortion providers have third-party standing to invalidate a law that protects women\\'s health from the dangers of late-term abortions.\\nJustice Alito drafted the 6-3 opinion (which was virtually identical to the leaked draft opinion in May), with Chief Justice agreeing with the decision in favor of Mississippi but not that the decision needed to overturn Roe / Casey. Breyer, Sotomayer and Kagan dissented. Justice Thomas stated that this decision could be broader than the abortion issue, whereas Alito stated this decision should only apply to the issue of abortion. Ultimately, the Court found that abortion is not protected as a \"liberty\" under the Fourteenth Amendment equal protection clause since it is not steeped in the traditions and history of this nation. You may view the decision by the Court – 19-1392 Dobbs v. Jackson Women\\'s Health Organization (06/24/2022) (supremecourt.gov)\\nHeld: The Constitution does not confer a right to abortion; Roe and Casey are overruled; and the authority to regulate abortion is returned to the people and their elected representatives. Pp. 8–79.\\nEmployers and health plan sponsors wishing to take action following this decision are encouraged to speak with their legal or compliance professional before taking any action to ensure compliance with applicable law. It is also important to avoid potentially harmful communications with employees who maintain opinions vastly different than the organization\\'s.\\nLeavitt Group has been on top of this issue for our clients and can offer support regardless of the position they may have on the issue, including analyzing the compliance challenges that may come with adopting certain policies or plan designs in response to the Dobbs decision. Be sure to contact your Leavitt Group representative. See below for full details on the cases cited herein and the impact of the decision on employers and health plans, including important questions to ask and considerations to think about.\\nOriginal article published May 9, 2022, after the leak of the draft opinion for the Dobbs Supreme Court of the United States (SCOTUS) case. See below for full details on this case and it\\'s impact on employers and health plans.\\n\"May Day\" brought more than the start of a new month. News source Politico published a bombshell report that the Supreme Court of the United States (SCOTUS) draft decision (titled \"1st Draft\" of the \"Opinion of the Court\") in the Mississippi (MS) case (Dobbs v. Jackson Women\\'s Health Organization) challenging the legality of a ban on abortions after 15 weeks of pregnancy. [SCOTUS Oral Arguments 12/1/21 Audio/Transcript.] In Dobbs, MS asked SCOTUS to overturn both Roe v. Wade (1973) and Planned Parenthood v. Casey (1992), to eliminate the federal right to abortion, and in Casey, the right to be free from undue burden in exercising the right to abortion before fetal viability. [See for other unrelated laws overturned in recent years, indicating that this SCOTUS bench has a panache for doing so.]\\n\"First, picking up [where]… you just left off, Justice Barrett, on safe haven laws, the Respondents in this case, [I]… believe, as Your Honor pointed out, have emphasized parenting burdens being a lead or the lead reason that women seek abortions. I would emphasize safe haven laws, as best I\\'ve been able to find, first came into existence in 1999 in Texas. They\\'re now ubiquitous, and you\\'re correct, Justice Barrett, that they relieve that huge burden. I would also add that as to — as to burdens during pregnancy, I would emphasize that contraception is more accessible and affordable and available than it was at the time of Roe or Casey. It serves the same goal of allowing women to decide if, when, and how many children to have.\" – Oral Arguments in favor of MS for overturning Roe and Casey.\\nCourt Reasoning\\nJustice Alito (appointed by W. Bush) writes the opinion of the court, which indicates it may be a decision leaning in favor of MS. With the majority of the bench appointed by Republican Presidents, and both assumed and witnessed in prior decisions, generally, to lean conservative and pro-life, the 6-3 draft decision shows all of those Republican-appointed Justices deciding to overturn Roe and Casey, with Breyer, Sotomayor, and Kegan the dissents (notably, Democrat-appointed Justices). The shift from more liberal to \"conservative\" (a comment generally used but not accurate, conservatives can also be pro-choice, etc.) is noticeable and remarked upon by Justice Sotomayor – \"The newest ban that Mississippi has put in place, the six-week ban, the Senate sponsors said we\\'re doing it [challenging Roe & Casey now] because we have new justices on the Supreme Court.\"\\n\"Roe was egregiously wrong from the start,\" the draft opinion states.\\nOf course, a document labeled a \"1st Draft\" means this opinion and, hence, the decision itself, could change between now and the anticipated release date of the actual decision. Expected in June. Likely June 27th, the last day of the term usually reserved for the most controversial case decisions.\\nAlito\\'s draft decision of the court argues that rights protected by the Constitution, but not explicitly mentioned in it (unenumerated rights) must be strongly rooted in U.S. history and tradition.\\n\"I think that that is part of it, yes. And I think, for many women, that is an incredibly difficult choice, but it\\'s one that this Court for 50 years has recognized must be left up to them based on their beliefs and their conscience and their determination about what is best for the course of their lives.\" – Oral Arguments for in favor of the Plaintiff seeking to overturn restrictive Mississippi abortion law.\\nImpact of Overturning of Roe & Casey on Insurance Landscape\\nInsured health plans would be subject to state mandates, while self-funded plans are exempt from most state insurance mandates per ERISA. (See Guttmacher Institute research on state laws related to reproductive health). The insurance landscape is already inconsistent, and that is with Roe & Casey intact. Insurance coverage of abortive care is mandated in only six states (CA, NY, IL, ME, OR, WA). The number of other states with some level of abortive care restrictions ranges from 22 to 26 and growing. (See Guttmacher Institute State Policy Research). If the SCOTUS decision indeed overturns Roe and Casey, those states will have restrictions or bans in force immediately.\\nEffect on Health Plans\\nInsured plans will be subject to a state law banning coverage, performing and being a patient to an abortion. In states with bans or restriction on abortive care, some employers are considering policies and programs to assist in facilitation and paying for abortive care in a state where abortions are legal.\\nSelf-funded plans are not affected by state laws (they are regulated by ERISA, a federal law the preempt state law and permits, mostly, large employers to set their own policies) banning abortive coverage, with the exception of states that criminalize facilitating abortive care. Even then, some states are trying to get ahead of that threat by enacting their own laws protecting those from abortion facilitation liabilities. The outcome of battling the state laws will no doubt end up in court.\\n\\u200bPaying for Abortive Care\\nEmployer Considerations for Funding Abortive Care Through Health Plans or Otherwise\\nMulti-state employers will have to analyze their plans\\' rights and obligations by considering the following:\\nIs the plan self-funded (or level) or fully insured?\\nSelf/level-funded plans will generally not be subject to the ban and can offer health plan coverage or reimbursement for travel to a state that provides abortive care.\\nThis is presumptuous. The IRS may remove the tax write off for travel for abortive purposes. A tax write-off may still be available for health coverage.\\nWould out-of-state abortion for a self-funded plan in a different state be out-of-network? How will it be billed? Will state taxation apply in the state banning abortions? All these questions will need answering and cannot be know at this stage.\\nWhich state is your business situs?\\n16 states and the D.C., have laws that protect access to abortive care, with CO, NJ and WA joining the list just this year.\\nA response to overturning Roe could equally affect red states that are, generally, passing legislation to ban or restrict abortion, and blue states passing similar laws as the 16 above (as of May 3, 2022) to protect the right to abortion and freedom from undue burden in exercising the Roe right pre-viability.\\nDoes your state prohibit facilitation of abortive care, like Texas?\\nDo you have employees on TRICARE or Medicaid?\\nHyde Amendment would result in these employees not having access to abortive care, like self-funded plan members or insured plan members in states protecting the right to abortive care.\\nConsider whether to offer an option for those employees via one of the methods discussed below.\\nSome states will use state funded Medicaid to finance abortive care for those without access (CA, HA, IL, ME, MD, NY, OR, & WA).\\nDo you have employees on the Affordable Care Act\\'s state Exchange Marketplace (e.g., Covered California)?\\n25 states restrict insurance coverage even in private insurance plans, including those through the Exchange.\\nConsider if you would want a policy to address the need for these employees.\\nAre you a public employer?\\n22 states restrict coverage for public employees.\\nExchange Marketplace, TRICARE, Medicare & Medicaid Funding of Abortive Care is Prohibited\\nThe Hyde Amendment prohibits use of federal funds for abortion regardless of the status of Roe, Casey & state law (exceptions for rape, incest, and endangerment of mother\\'s health). The issue of who will pay for abortions will become more complex should SCOTUS overturn Roe, sending the decision as to legality of abortion each state. (Roe became law in 1972 intending to remove the states\\' patchwork of rights to abortive care and privacy in reproductive health and birth control.)\\nPaying for Travel for Abortive Care\\nMany large employers have expressed their intention (or already have installed such policy in response to the Texas law enacted in 2021) to reimburse U.S. employees (and eligible dependents in some cases) up to $4,000 in travel expenses (e.g., Match, Salesforce, Uber/Lyft, Amazon, Google, Levi Strauss, Bumble, Citigroup, and Yelp to name a few). Per the Internal Revenue Code section 213, travel and lodging are reimbursable medical expenses. The IRC is ruled by the federal government. Whether the feds will allow reimbursement of such travel expenses to receive what a state may deem illegal could have unintended consequences for which it is too soon to identify and speculate.\\nFor example – The IRS does not permit tax-free coverage of state-registered domestic partners mandated to be offered employer-sponsored health coverage the same as a spouse. While the state will not tax that coverage, the IRS does! Will the IRS do the same with IRC 213? Prohibit tax-free travel for what is deemed illegal in the resident state? Or, will only state taxation be impacted? Federal law will not define \"medical expenses\" to consider state law legal medical procedures? Only time will tell. Be sure you are signed up for the Leavitt Group news alerts so that you will be informed of changes in the law affecting your health plans and eligibility for tax free travel expenses for purposes of abortive care.\\nEmployer Options for Self-funded Plan Coverage of Out-of-State Abortive Care Travel\\nPathways and considerations that complicate a policy of offering financial and/or facilitation costs for abortive care include:\\nGross-up salary to avoid all health plan or medical expense rules.\\nThis option would tax the employee and is complicated by issues related to accruing other benefits related to income and inconsistent application of policies that could appear discriminatory.\\nProvide a reimbursement through a Health Reimbursement Arrangement or other self-funded plan.\\nNondiscrimination testing would still apply.\\nIf the IRS redefines medical expense for purposes of tax-free IRC 213 reimbursements to consider legality of the procedure, this may complicate this option.\\nOne-time bonus for the travel and cost of procedure in a state permitting abortive care.\\nThis option will result in a higher taxation that a gross up and could present the same appearance of inconsistency or discrimination.\\nIf the self-funded plan decides to run all procedure and travel costs through the plan, as any other medical expenses, they will still need to define the benefit.\\nQuestions to answer when defining an abortive care benefit include:\\nWhat are the limits, terms, etc.?\\nIf using an HRA model, what would reimbursement look like?\\nAre you setting up an entire new HRA just for these purposes?\\nWill it be integrated with an ACA-compliant health plan?\\nAre plan documents and other health plan compliance measures considered?\\nWill COBRA need to be offered?\\nRecent State Actions Related to Abortive Care\\nRecently, the Missouri legislature and the 2021 Texas law made it a civil crime for any person assisting the pregnant woman with travel to receive an abortion. This means, employers could potentially face liability for facilitating travel to another state via providing the travel funds or health plan coverage to provide abortive care. But states are in a battle to either protect your rights one way or another, depending on which side you lean.\\nIn response to restrictive state laws in Texas, Missouri, and Mississippi and in response to the Dobbs, some states are taking action to make their statement as to the legality of abortion in that state if Roe and Casey were to be overturned. In California, SB 1142 (which will be addressed in the appropriations committee on May 9) is a measure that would provide funding for out-of-state residents who may travel there for abortive care. Additionally, California legislature is working on a bill that would protect those who facilitate travel to the state for such care. How the courts will handle the imminent legal challenges is impossible to know while all these measures are still being considered. (Connecticut has a similar law to California also working its way through legislature.)\\nMeanwhile, in Florida, the No Tax Breaks for Radical Corporate Activism Act will prohibit employers from reimbursing or paying directly for travel expenses to go out-of-state to receive abortive care.\\n\"Will this institution survive the stench that this creates in the public perception that the Constitution and its reading are just political acts?\" – Justice Sotomayor\\nEverything is speculative until the decision is formally released. Any forecasting of laws to come, effects of current, often-times antiquated laws, and even the outcome of the SCOTUS decision in Mississippi, is speculative. Overturning Roe and Casey will undoubtedly have earthquake effects across many components of our lives, including employer policy, taxation, health care, mother and infant mortality, economics of many women and social dialogue.\\nRegardless, compliance on. Regardless of which position an employer will take, it is important to consider the many compliance laws that will come into play when putting in place any benefits or tax-benefited programs. Communication with your employees and doing so with sensitivity cannot be overdone. It can save a lot of headaches. Many laws will include a notice provision!\\nConsider communicating with sensitivity. When discussing a sensitive topic like abortion, there is indeed the likelihood someone could get offended or have strong opinions. Try to be matter of fact rather than having an opinion or making a prediction as if it is a known thing. For example, instead of saying \"The injustice of Roe will be overturned.\" Consider \"SCOTUS draft opinion/opinion overturned Roe.\" Or, \"To afford employees continued access to abortive care, XYZ is available.\" Not, \"To allow employees to exercise their right to abortions….\" It may be worth getting ahead of the conversation with your employee population if you have a demographic where this may cause some rumblings in the workforce. This is early yet. There is a lot to be known and decisions yet to be made. Patience while preparing is always a sound approach. Let us know how we can help!\\nNeed help? Employers should consult a tax and employment attorney to analyze their obligations and rights. For all your insurance questions, Leavitt Group is your trusted advisor and here to help you strategize how to best utilize available resources and benefits. Need a tax or employment attorney? Let us know! We have preferred partnerships with top-notch nationwide attorneys.\\nabortion rightsabortive carehealth plan abortion coverageroe v wadeSCOTUS<|begin_of_text|>Items placed on Reserve in the Music Library circulate for 2 hours and may not leave the library. Exception: Faculty may check out their own reserve materials or another\\'s by special permission. Please refer to the Reserve Request Form for procedural information.\\nThe Reserve Collection resides behind the service desk in call number order. Patrons are asked to request reserve items for check out by call number (which may be found by clicking on the \"Search course reserves\" link in GIL, the CSU Libraries catalog).<|begin_of_text|>KASHMIR, POLITICS\\nDivision of Jammu & Kashmir: Integration or Alienation?\\nDate: August 7, 2019Author: Atul Depak 37 Comments\\nImage: Associated Press\\nBJP led government of India on Monday scrapped the special status of its only Muslim majority province Jammu and Kashmir through series of presidential orders and bifurcated the state into two union territories after ensuring complete lockdown in the valley by sending thousands of troops, imposing curfews, arresting civil and political leaders, suspending all modes of communications and by creating an atmosphere of unprecedented fear, chaos and confusion firmly indicating that the consent of the governed is missing in this brazen exercise. While many mainstream Indian leaders hailed the decision as historic for the territorial integrity of India but many Kashmiri Muslims feel betrayed and cheated and are wondering if they made a historic blunder by rejecting the two-nation theory. It is unfortunate that a nation that once fought so vigorously against British attempt to divide its provinces such as Bengal on religious lines is playing the same evil game with its own people who have allegedly lost faith in it due to incessant betrayals ranging from deliberate rigging of elections to toppling of democratically elected governments. In the words of an eminent academician PB Mehta– \"Even if Article 370 were to be scrapped, the proposal to alter Jammu and Kashmir\\'s status to Union Territory, even if temporarily, is designed to humiliate an already subjugated population. How dare a Muslim dominated state exists in India? Kashmir can now not even be trusted to be a state. The optics of this measure is not integration, it is humiliation, of a piece with subtle and unsubtle reminders to minorities of their place in India.\"\\nSince the authorities at whose behest all this was done constitute the government of India, they have done not only an irreparable damage to the honor of this republic but have also portrayed it as a nation that relishes in breaking promises made to its own people. All this should not come as a surprise given that the people who took this drastic decision come from a class of Hindu Upper Castes who have been historically adept at taking decisions ill-intentioned at best and inegalitarian at worst. Though these bloodline based cliche castes constitute only 10-15% of the Indian population but have been dominating and exploiting the riches of the sub-continent since long by manipulating public opinion using vicious tactics of communal hatred, Islamophobia, jingoism, etc and through their cowardly hate speeches bring shame and disrepute to the whole nation. If one were to analyse the forces behind all controversial, insensitive and communal decisions taken in India over the last two centuries, almost all would invariably come out to have been taken or engineered by someone from this rigidly over-pampered and notorious tiny class. (to have a better understanding of their historic injustices, one is advised to read the writings of Dr. Bhimrao Ambedkar). And now they have wreaked havoc on Kashmir. They seem to forget that while governments come and go but certain injustices have tendencies to torn apart nations.\\nThe genesis of the Kashmir Dispute-\\nIndia got independence from British rule in 1947 but unfortunately was partitioned into two nations namely India and Pakistan. Under the partition plan, Hindu majority areas of British India were to constitute India and the Muslim majority areas were to constitute Pakistan. Hundreds of princely states of the subcontinent were given the choice of either acceding to any of these two dominions or remain independent but were advised to keep in mind their people\\'s wishes and geographical circumstances. Kashmir was a Muslim majority state, (as per 1941 census) but it had a Hindu Upper Caste Maharaja who initially wanted to remain independent. But sensing a pro-India tilt in the ruler\\'s attitude, Pakistan allegedly staged an invasion by tribal militias who soon captured vast territories which are now termed as Pakistan occupied Kashmir. The panic-stricken King asked for India\\'s help which assured him of military help but on the condition that he accede to the Indian dominion. After he agreed, Indian troops were hurriedly air-lifted to the province and the fall of the capital Srinagar was prevented but skirmishes between Indian forces and Pakistan backed militias continued for few months until India sought the intervention of United Nations.\\nA resolution (47) dated 21 April 1948 passed by UN Commission for India and Pakistan called for immediate ceasefire and demilitarization of the province so that a plebiscite might take place to determine the will of Kashmiri people. The withdrawal of the forces by both sides however never happened and nor the plebiscite because India wanted an asymmetric withdrawal of forces under which Pakistan had to withdraw first on the reason that it was an aggressor. Pakistan did not agree to this and demanded a parity in treatment which of course was rejected by India.\\nSince then various proposals by subsequent UN supervisors including those by McNaughton and Dixon have been rejected by India and Pakistan under various excuses. Quite ironically India also abhors proposals of arbitration and mediation in this dispute even though it endorses arbitration as a method for settlement of all international disputes in its constitution (Article 51). After imprisoning Sheikh Abdullah (the Prime Minister of Kashmir) in 1953, Indian government fortified the Kashmir Valley to an extent that today it has become the most militarized zone in the world with its streets being under the constant vigil of the armed forces. India Government also equipped its armed forces with such vast and draconian powers (under different legislations like AFSPA etc) not exercised even by the British Army stationed in India during the colonial rule. There have also been allegations by Kashmiri watchdogs that India has deliberately rigged elections in Kashmir and by doing so has denied Kashmiris their democratic rights.\\nOfficial flag of the erstwhile State of Jammu & Kashmir under India\\nThough Kashmir was allowed until now to have its own constitution and flag but the constant intervention by the Central government in the legislative affairs of Jammu and Kashmir is no hidden fact. Time and again State governments in Kashmir have been dismissed at whims and fancies of the central government under varied excuses. Re-elections for the dissolved assemblies have also been delayed for a prolonged time. And now it has been made a Union Territory and will be governed directly by the central government in which Kashmiris will have little say if no say. One should wonder if such a system is unable to work in NCT of Delhi (where there is a face-off between the legislature and Central Government almost on a daily basis) then how it will work in Kashmir where public opinion is already beset with disaffection.\\nWhether there exists demand of self-determination in Kashmir?\\nThere is no doubt that since 1947, Kashmir has been embroiled in a great unrest with hundreds of civilians and insurgents getting killed annually during face-off with the armed forces stationed there. Separatist movements have also been active in the Kashmir Valley since long and as per official estimates, violence emanating from these movements has killed thousands of individuals. The recent suicide attack in Pulwama which killed over 50 military personals was one amongst series of other such events showing that all is not well in Kashmir as has been claimed by successive governments. Many popular Indian leaders like Jaiprakash Narayan have openly acknowledged the Valley\\'s disaffection towards India. In the words of Jaiprakash Narayan–\\n\"From all the information I have, 95 percent of Kashmir Muslims do not wish to be or remain Indian citizens. I doubt therefore the wisdom of trying to keep people by force where they do not wish to stay. This cannot but have serious long-term political consequences, though immediately it may suit policy and please public opinion.\"\\nQuite recently even the Indian Governor of Kashmir Satyapal Malik acknowledged that Kashmiris have lost faith in the democratic process as elections in Kashmir have been rigged. Apart from this, various reports of the UN and Human Rights Commissions on forced disappearances, mass executions, rapes and abuses in Kashmir lay bare the claims of normalcy. All these facts strengthen the argument that there is a demand for self-determination in Kashmir through its intensity and scope cannot be ascertained in absence of wider polls to that effect. Moreover, Kashmir has been promised plebiscite by none other than the United Nations.\\nWhether Kashmir satisfies the parameters of self-determination under International Law?\\nSelf-determination under International law has become a contentious issue these days with great difference between the written law and the practices of the states. Whereas various international agreements and conventions including UN Charter, ICCPR and ICESCR recognise the right to self determination as an invaluable right but in practice states have rarely honoured this commitment on their sweet will and generally frown upon any attempt of self-determination especially external self-determination (also known as extreme/violent self-determination) by any entity under their effective control and dominance. Various international charters and conventions talk about the right of self-determination and recognized it as a customary norm like right erga omnes (right owed to all). Article 1 of the UN Charter envisages Self-Determination as an objective of the United Nations for the strengthening World Peace. Several resolutions of UN including Resolution 1514 of 1960 and Friendly Relations Declarations of 1970 uphold the right of self-determination of people. Friendly Relations Declaration has by far been the most comprehensive articulation of the concept of Self-Determination and casts a positive obligation on every state to promote the principle of self-determination of people. It also casts a negative obligation on every state to refrain from those actions which deprive the people of their right to Self-Determination and freedom. Similarly, two other important international conventions namely ICCPR and ICESCR also talk about this right and provide that all people have the right to self-determination and states which are parties to the covenant have a duty to promote it. Though India is a party to these covenants, it made certain reservations and upheld self-determination only in the decolonization paradigm and also declared that it supports the self-determination of only those people who are under foreign domination and not of a section of people living under sovereign independent states. It is believed that India made these reservations keeping in mind the various secessionist movements on its own soil and especially with regards to the Kashmir issue.\\nSubjective and Objective analysis- This provides that a group to constitute people must subjectively feel that it is different from the rest of the inhabitants of the mother state and it should also satisfy the objective criteria of uniqueness in terms of its territory, ethnicity, language, culture, language, religion, etc. As is evident from various reports and studies, majority of Kashmiris do feel subjectively different from the rest of India and uniqueness of Kashmir has been recognized officially by the Indian government so much so that Kashmir was allowed until now to have a separate constitution and flag and given greater autonomy than other Indian states. Objectively also the uniqueness of Kashmir in terms of its territory (mountainous terrain), ethnicity (Kashmiri), language (Kashmiri), culture (Kashmiri), religion (pre-dominantly Muslim) is not a disputed fact. Therefore Kashmiris can be said to be fulfilling the subjective and objective criterion of people who can exercise the right to self-determination.\\nDecolonization Perspective– Under International law demand of self-determination is justified only in the case of decolonization paradigm and in some cases delayed decolonization paradigm. To prove that India is a colonizing power in Kashmir is a difficult task and more so when Kashmiris enjoy same rights and liabilities as rest of the Indians under the law of the land notwithstanding ground realities. Though it is widely believed that Kashmiris don\\'t want to remain in India or that they want to join Pakistan but in absence of any polling, plebiscite or referendum to that effect it is difficult to ascertain the opinion of the majority. However, there is no denying that many Kashmiris regard India as an occupying force and same can be witnesses in the daily strikes, hartals, bundhs, anti-India sloganeering and stone-pelting on Indian forces stationed in Kashmir all of which has become a routine affair now. Another important fact that raises eyebrows is the deployment of over 600000 Indian Military personals in Kashmir with vast draconian powers. Had public opinion in Kashmir been affectionate towards India, it would not have resorted to these extreme steps and excessive measures.\\nTerritorial Integrity- Uti Possidetis is a Just Cozens norm in International law and countries value their territorial integrity more than anything else but the moot question here is can a country make the argument of territorial integrity regarding a internationally disputed territory. Can all questions regarding the other most important Just Cozens norms like Human rights, civil and political liberty be shunted off by the mere claim of Uti-Possidetis? This certainly is not in tune with the spirit of United Nations and various International covenants including ICCPR and ICESCR that majestically uphold the cherished principles of Universal civil and political rights in accordance with the principles of Human Rights and the will of the people. Kashmir is undoubtedly a disputed territory under the annuls of International law and neither India nor Pakistan can ward off the question of its self-determination by the arguments of Uti-Possidetis or territorial integrity. Also, it seems too farcical to claim in this modern liberal and post-modern world that Uti-Possidetis is above Human Rights.\\nWhether there exists any possibility of the exercise of the right of self-determination in Kashmir?\\nNow with the abrogation of the special status and internal autonomy of India held Kashmir, there is little hope of anything of that sort happening in the current scenario given that India has time and again refused to budge on its stand that Kashmir is its integral part. And its a ravishing truth of the world history that smaller and weaker political entities under a more powerful and colossal polity have been rarely allowed to secede or broke away from the latter unilaterally even if the latter has been established to be an occupying force. It has also been observed that in many such scenarios, International law fails and hardcore realism takes over the mantle of the International Order as has been seen in the secessionist movements in powerful nations like Russia and China where they have been brutally suppressed and the world community could do little except raising eyebrows. India is also a growing economic and military power with a majoritarian government whose realist and jingoist tendencies are on ascendance and in such scenario there is little hope that it will deal benevolently with those Kashmiris who are disaffectionate towards it. Therefore any attempt by Kashmiris which is perceived hostile by the ruling dispensation would necessarily be rendered futile unless there is a drastic change in the sociopolitical structure of the sub-continent or of Kashmir.\\nUndoubtedly, it is one of the biggest ironies and hypocrisies of the 20th century that some people who had fought for their freedom with so much fanfare and dramebaazi spared no time in playing with Kashmir\\'s freedom, unity and dignity once they had purchased their own from their colonial masters. Kashmir deserves better and not just Kashmir, the whole subcontinent needs freedom from rampant socio-economic injustice, subordination, discrimination, exploitation, and corruption and slavery of a few elite castes and classes who have since long held hostage its resources and have mercilessly trampled upon the rights and dignity of others. But given that external self-determination is rarely successful in international arena and almost impossible without the consent of the mother entity that is powerful and brutal, Kashmiris should rather try to secure an effective internal self-determination within the current constitutional framework that benefits all other stakeholders of this dispute rather than making it a zero-sum game. Fragmentation or Balkanisation of this majestic sub-continent will only lead to interference from other foreign powers who can prove more pernicious and hostile as can be witnessed in Afghanistan and the Middle East. They should keep in mind that historically the Indian sub-continent has always clamoured for consolidation under one powerful entity for stability, power, fame, and prosperity. Whenever there has been division, disunity, and discord, it has plunged into deep crisis and a third power has taken the advantage and given nightmares to everyone as was the case during the British occupation. Hence Kashmir or any other entity of the subcontinent with secessionist ambitions should reflect deeply on the totality of circumstances and their viability as an independent nation before taking any extreme step. They should rather try to secure their rights and dignity within the current constitutional dynamics of the sub-continent by collaborating and cooperating with other affected groups and by collectively asserting control over the central authority in case they dislike the ruling dispensation. And in a vast subcontinent like this which is full of great diversity, they would definitely find a lot of sympathisers and hoards of people on their sides if they honestly try and persevere to march together for collective justice and not for fulfillment of narrow self-interests. And this would be much easier for them than seeking clandestine ways to secede and run away from positions of power and responsibility and then plunge into chaos and perpetual conflict. By choosing the narrower approach, they would be achieving no independence but on the contrary inviting other pernicious powers to interfere and meddle into the sub-continental affairs and squeeze its riches, honor, and dignity. And this a time tested old saying that \"United we stand and divided we fall.\"\\nAs for those who are mad under the inebriating influence of stately/regal power, they should know that this world is but an illusion and is ephemeral as is evident in the demise of one of their own former minister who was so desperate to see this Kashmir moment. And that they shall be held accountable for whatever they do either in this world or in the hereafter or in both- God knows the best. And that there is a difference between the justice of fallible man and that of the infallible Almighty who is all knowing, ever watchful and swift in reckoning.\\nBlameworthy are those who oppress people and tyrannize upon the land without right. They will have a painful punishment.\\nAl-Quran 42:42\\nPeace!🌹\\nNOTE:- Dear all, before commenting on this issue and other posts, please read our Disclaimer, Community Engagement Terms & Comment Guidelines to avoid any confusion or misunderstanding.\\nLIKE THIS? SHARE IT\\nINDO-PAK DISPUTESJUSTICEKASHMIRSELF-DETERMINATION & AUTONOMY\\nPublished by Atul Depak\\nAtul Depak is a law student from New Delhi, India.\\tView all posts by Atul Depak\\nPrevious Previous post: The concept of Zakat-the Mandatory Charity\\nNext Next post: Is Islamophobia a Bourgeois Conspiracy?\\n37 thoughts on \"Division of Jammu & Kashmir: Integration or Alienation?\"\\nSaba,NiazSiddique says:\\nHats off to you Mustafa!\\nLiving in such society where freedom itself a joke you have done an incredible job 👍\\nI don\\'t have words but you\\'ve told that you are neither a blind nor dumb.\\nMy blessings are always with you.\\nAtul Depak says:\\nThank you Saba for your insight and praise Alhamdulillah. Well if you start counting, you will discover that peace-seekers and rights upholders in India are greater than war-mongers but unfortunately the latter wield greater power and authority these days and are also more visible and vocal than the former. And if you observe editorials of some prominent newspapers, you will find many terming the government\\'s move as arbitrary, unreasonable and unconstitutional. Ya unfortunately Freedom has been reduced to joke for some classes and sections in many nations of the world. Jazakallah for the blessings! May the almighty bless and guide you!\\nYour posts are always so well researched and balanced Depak. I was very upset and disturbed after the news and to find even educated people getting caught in this distorted social media hype.\\nBut just when I was feeling very low I got a Whatsapp post on a saying of Paramahansa Yogananda, where he is telling his disciples that this world is a Joke and an Illusion. That gave me peace. And Karma is supreme. We can\\'t run away from our individual or collective karma!\\nI too had written a few posts on this life being a dream and a reality show. I do believe in that! Let us hope and pray that good sense prevails and that we have more dreams of peace and love than hatred!\\nDelhi has been a state for some years but yes, there remains a big conflict between State and center. While Chandigarh has been a UT for ages and that was the best thing that happened to it. If it had gone to any state it would have been a disaster for the residents.\\nPeace unto all 🙏\\nThank you sir for reading this write-up and providing such a detailed analysis and candid insight of yours on this issue. The message that this world is an illusion is there almost in every civilization including ours yet many seem to forget this and take this illusion as reality and also for granted. Ya we should pray that good sense prevails as well as peace in the sub-continent. I have corrected the part where I mistakenly referred Delhi as UT. Thanks for highlighting that issue. Peace be upon you too. Wa alaykum!\\nMy pleasure Depak. Sleep well.\\nAre you a historian?\\nNo. I am a law student currently in my fourth year. 😊\\nLooked like that to me: History or Law 😊\\nYou are very bright Depak. All the best\\nAlhamdulillah. May the almighty bestow everyone with it if its a virtue. You are very kind. Warm regards!\\nRosaliene Bacchus says:\\nTragic to see that your part of the world also continues to reap the divisive seeds of colonization.\\nYa. its unfortunate but true that they inherited some of the wrong legacies. Thank you for your remarks and insight. 🙂\\nThis was a very interesting and informative post. Thank you for sharing this.\\nThank you for your feedback! 🌷🌷🌷\\nVery well portrayed and courageous step to reveal the truth in current scenario of India. It\\'s very informative post. Thanks. Best Wishes\\nThank you so much for the kind remarks. 😊\\nKashmir will now remain an integral part of India. Article 370 & 35 A is in the dustbin. It\\'s not coming back now!\\nFaisal Farooq says:\\nKashmir Bleeds and Ummah Sleeps\\nPingback: Special Blogger Award – Saba Niaz siddique\\nInteresting, as always! This world is sure a complicated place — no matter where one lives!\\nThanks for your visit and insight Nora. 🌹🌹🌹\\nSameera says:\\nHow brainwashed India is.😑\\nMariam Naveed says:\\nTruth described so effortlessly. Hope our words work for the freedom of kashmiris.\\nInshallah☝️thanks for the visit and insight. Jazakallah Khair!\\nsandomina says:\\nDear Atul Depak, thank you for your perspective.\\nJ&K could be a very detailed debate and a few lines or words would not suffice. First and foremost India came into the present form or rather in the larger form many times in its very long history. J&K was part of that ancient India many times. After independence, many of the states of present-day India had to be brought in the union against the will of Rajas/Nawabs. J&K, on the other hand, came willingly and peacefully, till self-proclaimed leader of Muslims, Pakistan intruded and brought catastrophe to the region. Giving J&K a religious color is absurd. From that logic, Kashmiris have been Shaivites all their life barring last thousand years or so. In fact, that is one reason their demeanor has always been very different from the rest of the Muslim world. Indian central leadership has done many mistakes in the past but J&K leadership is equally responsible for the present-day status. No one has till to date asked Yasin Malik that how does his wife live such a lavish life when he has no declared source of income.\\nI think this is the best chance populace of J&K got in the last 72 years to bring the state to normalcy rather than getting hoodwinked by Pak Army, who would be struggling to maintain their livelihood if Kashmir cause dies down. Time has come for Pakistani populace to stand up against Paki Army, which has brought the country at the brink of bankruptcy and international isolation.\\nThis my point of view and I believe in inclusive politics rather than absolutism.\\ninsightful.co.in\\nFirst of all thanks for giving such a detailed insight of yours on this contentious issue. brother i respect your views but we can differ. Probably you didn\\'t read the conclusion part of this post. have highlighted it for your convenience. Best wishes!\\nI had not only read your conclusion but other reader\\'s comments too. The reply was not entirely to you but to many readers too, who visit your popular blog.\\nPray for peace.❤️\\n🌹🌹🌹\\nA well researched and balanced approach to write on a highly sensitive and divisive issue. Why can\\'t the mainstream media in India take a pragmatic role in projecting the true nature of a problem that has started eroding the very fabric of the whole society. India can\\'t afford to be relegated to a status other than a secular, democratic and progressive state.\\nThanks for the visit and insight. It\\'s unfortunate but true that pragmatism is losing to realism and rhetoric these days. No country can afford to take a regressive stand for long. Best wishes!\\nVishal Gaur says:\\nRear and support\\nhttps://indiangoggle.wordpress.com/2019/09/23/learningkashmir/\\nStandPoint says:\\nWelcome to my blog http://www.standpointe.wordpress.com Machiavellianism and Kashmir\\nAkash MP says:\\nVisit http://www.fromthestandpointe.wordpress.com Machiavellianism and Kashmir\\nI read your page. May god give you guidance and peace. You have got good writing skills, utilise it for the right cause. don\\'t advocate injustice by endorsing Machiavelli. His ways have been tried and tested before. They proved disastrous for the world. They might prove disastrous for you too, here as well as in the hereafter. You will be judged on the basis of your deeds and not on the basis of how many nations you conquered or subdued.\\nRead Quran, you will come to better conclusions which will be beneficial to them and to you.\\nAl-Quran 5.8- \"O ye who believe! stand out firmly for Allah, as witnesses to fair dealing, and let not the hatred of others to you make you swerve to wrong and depart from justice. Be just: that is next to piety: and fear Allah. For Allah is well-acquainted with all that ye do.\"\\nTruly, injustices tear apart families, societies and nations.\\nBest wishes! 🌹🌹🌹\\nSaaib Ahmed says:\\nSerious Questions Emerging Post Revocation of Article 370 https://ssaaib.wordpress.com/2019/10/25/serious-questions-emerging-post-revocation-of-article-370/\\nthanks for sharing. have read and given my insights. Best wishes!\\nDear all, before commenting on this issue and other posts, please read the Disclaimer and our community engagement and comment guidelines (https://atuldepak.com/about/disclaimer/) to avoid any confusion or misunderstanding.<|begin_of_text|>[Javier de Blas in Abrantes, Portugal] Eduardo Salavisa is organizing for the first year Cadernos de Viagem de Abrantes (Abrantes Travel Sketchbooks ). I have been invited, in this edition, to draw the city for a week.\\nAnother thing I learn from my \"conversations at the restaurant\" with Miguel Real is that postmodernism is characterized by having more of concept rather than location, taking profit, many times, of old buildings to adaptate to contemporary circumstances. I draw the municipal library Antonio Botto, which was rebuilt from an old Romanesque convent. I am also attracted by the many Art Deco buildings of the city, designed by leading European architects. The one I draw is not the most interesting, but it is a good example of the dialogue that the postmodernist building next, is generating with it.\\nFinally I observe the municipal market, which is great for the purity of its lines and volumes and I go to speak to one of the fishmongers, who tells me how he travels every week to the Azores for supplies.<|begin_of_text|>module FFaker\\n  module Food\\n    extend ModuleUtils\\n    extend self\\n\\n    def ingredient\\n      self.send( %w(vegetable fruit meat herb_or_spice)[rand 4] )\\n    end\\n\\n    def vegetable\\n      VEGETABLE.sample\\n    end\\n\\n    def fruit\\n      FRUIT.sample\\n    end\\n\\n    def meat\\n      MEAT.sample\\n    end\\n\\n    def herb_or_spice\\n      HERB_SPICE.sample\\n    end\\n\\n  end\\nend\\n<|begin_of_text|>This summer sees the launch of a brand new epic music festival Cool Britannia, celebrating all things Britpop at Knebworth Park, the stately home of rock.\\nFeaturing some of the heavyweights of the 90s, the three-day festival (Friday 31st - Sunday 2nd September) will play host to the likes of the Happy Mondays, Ocean Colour Scene, Feeder, The Lightning Seeds, Peter Hook & The Light, Heather Small, Cast and Embrace.\\nThe festival, taking place at the iconic Hertfordshire venue, will also see the debut of \\'Britpop Classical\\', a full orchestra together with rock band and guest soloists performing unique versions of Britpop classics.\\nCool Britannia have also teamed up with legendary dance institution Ministry of Sound. Housed in the Big Top, they will feature some of the best club DJs of the era, including: Todd Terry, Brandon Block, Jazzie B and Alfredo.\\nListen to XS Manchester during XS Festival Week 11 - 15 June for your chance to be at Cool Britannia festival this summer!<|begin_of_text|>Based on an investigation by José Argüelles of the mathematics of the unique Mayan calendrical system, The Law of Time establishes that time is the universal factor of synchronization. This radically new perception of time accounts for the harmony inherent in the natural order.\\nA corollary to this perception of time is that the velocity of time is instantaneously infinite. Traveling faster than the speed of light, telepathy is thus inseparable from time understood as the experience of synchronicity.\\nIn light of the current planetary crisis and the need for humanity to return to the natural timing frequency, the 13 Moon calendar has been presented by the Foundation for the Law of Time as a first step toward reestablishing world harmony and universal peace. Through the Foundation\\'s auspices, the Planet Art Network, a global peace movement to change to the Thirteen Moon/28-day calendar has now spread to more than 90 countries.\\nThe Foundation sees the calendar change as a necessary means of reformulating how humans think at the most basic level – their daily timing program. This fundamental change in thinking – foreseen by Einstein as the most necessary step for humans to take if they are to avoid a world catastrophe – is also in advance of a new stage of global evolution, the noosphere.<|begin_of_text|>I recently purchased this piece and am enjoying it immensely. It\\'s beautiful and haunting. The tremolo section is a good challenge for me. I describe myself as an advanced intermediate player, at a point where I find myself eager to work on techniques that help me move to a higher level. This piece seems good for that.<|begin_of_text|>This article is about the character in Super Smash Bros. Brawl. For other uses of \"Trainer\", see Trainer.\\nThe Pokémon Trainer releases a random Pokémon from a Poké Ball.\\nThe Pokémon Trainer is a playable character in the game Super Smash Bros. Brawl. He is represented by Red, the main male character of Pokémon Red Version and Pokémon Green Version, Pokémon Blue Version, Pokémon Yellow Version, and their remakes, using the design of the character first seen in Pokémon FireRed and LeafGreen Versions.\\nPokémon Trainer artwork from Super Smash Bros. Brawl.\\nThe Pokémon Trainer is the first playable Pokémon representative in the Super Smash Bros. series who is not an actual Pokémon. Though a selectable character, he is not an actual fighter, instead commanding any of his three Pokémon in the background of the stage, his team consisting of Squirtle, Ivysaur, and Charizard. The only move the trainer performs is Pokémon Change, which allows the player to switch out his three Pokémon at will throughout the battle. He also automatically switches Pokémon whenever one is KO\\'d. The Pokémon also run on a stamina system that weakens them, as their stamina decreases the longer they are out on the field. Their Final Smash is Triple Finish, which has the trainer send out all three Pokémon at once to attack. The Pokémon Trainer is voiced by Michele Knotz.\\nThe Pokémon Trainer in the Subspace Emissary.\\nIn the Subspace Emissary, he allies with Lucas who helps him find his Charizard and Ivysaur. The two also encounter Wario and a large Subspace Army robot, Galleom. They are saved from the robot\\'s detonation by Meta Knight, and they team with him, Marth and Ike afterwards. When encountering a huge Subspace Army group on the foothills of a mountain (Meta Knight has left to retake the Halberd), they are saved by Mario and his team (Link, Yoshi, Pit, and Kirby).\\nIn Super Smash Bros. for Nintendo 3DS and Super Smash Bros. for Wii U, transforming during battle is omitted, so Charizard was made into a separate character, while the Pokémon Trainer, Squirtle, and Ivysaur are no longer playable. He, Squirtle, and Ivysaur appear as collectable trophies, however.\\nThe male Pokémon Trainer in Super Smash Bros. Ultimate.\\nThe female Pokémon Trainer in Super Smash Bros. Ultimate.\\nPokémon Trainer returns as a playable character in Super Smash Bros. Ultimate. With the removal of the stamina system, one can play as Squirtle, Ivysaur, or Charizard for an extended period of time with no penalty. A female Pokémon Trainer variant can also be used, and is statistically identical to the male one. She is represented by Leaf, the main female character of Pokémon FireRed Version and Pokémon LeafGreen Version. Kate Bristol voices the female Pokémon Trainer, while Billy Bob Thompson voices the male. A majority of the male Pokémon Trainer\\'s quotes are also different from Super Smash Bros. Brawl as well.\\nPokémon Trainer (opposite gender) The Battle at the Summit!\\nPokémon Change is the Pokémon Trainer\\'s down special move, and by extension the down special move of Charizard, Squirtle, and Ivysaur. The move is based on the ability for players to switch out their Pokémon mid-battle in the Pokémon series, allowing players to switch between using Squirtle, Ivysaur, and Charizard in that order. Pokémon Change is also automatically used whenever one of the Pokémon\\'s stamina is depleted or whenever one is KO\\'d. This move cannot be used immediately after respawning, or at all in midair. Status effects are also not carried over between Pokémon, though damage percentages are, and a Pokémon\\'s stamina recharges while it is not in use.\\nIn Super Smash Bros. Ultimate, the move is much faster, and the stamina mechanic is removed. It can also be done in midair.\\nTriple Finish is the Pokémon Trainer\\'s Final Smash. The trainer sends out all three of his Pokémon to attack at the same time. Ivysaur hits with SolarBeam, a narrow beam of light that fires across the screen; Charizard with Fire Blast, a flame projectile that travels across the screen; and Squirtle with Hydro Pump, a water attack that sprays in multiple directions at close range, all of which deal continuous damage before opponents are knocked back by the final Fire Blast. If a player is too close to the team while they are attacking, they are knocked into the air rather than into the attack.\\nThroughout the entire attack, a text box designed after the ones in Pokémon Diamond and Pearl appears on the bottom of the screen, saying, \"Take that, Triple Finish!\" If the attack hits, the dialogue changes to say, \"It\\'s super effective!\", referencing the type effectiveness mechanic of the Pokémon series.\\nSince Charizard is the only Pokémon of the three to return in Super Smash Bros. for Nintendo 3DS and Super Smash Bros. for Wii U, its Final Smash has been changed to its Mega Evolution.\\nPokémon Trainer A person who raises Pokémon and trains them as partners in battle. In battle, a Trainer gives orders to the Pokémon and uses items. It\\'s not an exaggeration to say battles can be won or lost on a Trainer\\'s single strategic move. Trainers pour their hearts into their Pokémon and share anger, sadness, and joy as they adventure in hopes of becoming Pokémon Masters.\\nSnake: Pokémon Trainer... That\\'s the guy giving orders behind a Pokémon, right?\\nColonel: Right, and this Pokémon Trainer is controlling Squirtle, Ivysaur, and Charizard. They represent water, grass, and fire, and they\\'re all powerful.\\nSnake: So he makes his Pokémon fight while he sits back and watches. Sounds like a good deal if you ask me.\\nColonel: It\\'s not like that, Snake. Those Pokémon wouldn\\'t know what to do if the Pokémon Trainer wasn\\'t there giving orders. In every battle, there\\'s a soldier doing the fighting, and a commander telling him what to do. By working together as a team, they accomplish much more than either could on their own. So let\\'s do this together, partner.\\nSnake:...Yeah... Whatever you say, Colonel.\\nGBA Pokémon FireRed & Pokémon LeafGreen (09/2004) NA: Pop quiz! What do Misty, Brock, Cynthia, Iris, and Ash all have in common? That\\'s right - they\\'re all Pokémon Trainers! This Pokémon Master in the making is the same. Back in Super Smash Bros. Brawl, he fought to be the very best; like no one ever was. To smash them was his real test; to launch them was his cause!\\nPAL: Quiz time! What do Misty, Brock, Cynthia, Iris and Ash all have in common? That\\'s right - they\\'re all Pokémon Trainers! This Pokémon Master in the making is just the same. He fought to be the very best; like no one ever was - back in Super Smash Bros. Brawl. To smash them was his real test; to launch them was his cause.\\nPokémon Trainer is one of the few fighters to only get five alternate costumes in Super Smash Bros. Brawl, instead of the usual six. This is also shared with Lucario, Jigglypuff, and Sonic.\\nOne of Pokémon Trainer\\'s alternative costumes has the same colors as another Pokémon Trainer; Brendan\\'s outfit from Pokémon Emerald.\\nThis page was last edited on April 22, 2019, at 19:59.<|begin_of_text|>You are here: Home / Uncategorized / Acts (Part 3-Chapters 5-7)\\nActs (Part 3-Chapters 5-7)\\nApril 9, 2015 By bcoadmin Leave a Comment\\nby Gary T. Panell\\n(1-11) This account of Ananias and Sapphira is a sad one for sure. We wish these things would not happen in the Church, but they do. The very fact that Christians still have a free will, even after they are saved, makes it possible for sin to be in the Church. As hard as this reality is to accept, it is true. \"Luke does not try to gloss over the situation but relates the event with black colors.\\n\"1, 2. Sapphira in the Aramaic tongue means beautiful. Like Barnabas, she and her husband sold a piece of property. Ananias, with his wife\\'s knowledge, determined upon the plan of bringing only part of the money to the apostles, but pretending that they were giving all. 3.We are not told how Peter recognized this deception; it was probably by divine illumination. Peter charged Ananias not with deceiving him but with attempting to deceive the Holy Spirit. The Holy Spirit is obviously a person, and verse 4 shows that the Holy Spirit is also God.\\n[\"In Acts 5:3, Peter said that Ananias had lied to the Holy Ghost: in Acts 5:4, he said that Ananias had lied to God. Thus, God and the Holy Ghost are used synonymously, showing clearly that the Holy Spirit is God.\" (The Defender\\'s Bible)]\\n\"4. The program of sharing wealth in the early church was a purely voluntary one and not compulsory. While the land remained in Ananias\\' possession, it was his alone to dispose of as he chose; and even after he had sold it, the money was his to do with as he pleased. Ananias\\' sin did not consist in his keeping back the money, but in his pretending a complete consecration to God while deliberately keeping back part of the money.\\n\".The same fate that struck Ananias overtook Sapphira, and she fell down and expired. There is no reason to believe that Ananias and Sapphira were not saved persons. Their physical death was a divine judgment upon them which did not involve the question of their salvation. The very fact that they were believers determined the enormity of their sin. They were pretending to \"surrender all\" but were deliberately holding back from God. This is a sin that can be committed only by a Christian.\" (The Wycliffe Bible Commentary)\\nIt is possible for Christians to sin, even a sin unto death: \"If anyone sees his brother sinning a sin which does notlead to death, he will ask, and He will give him life for those who commit sin not leading to death. There is sin leading to death. I do not say that he should pray about that. All unrighteousness is sin, and there is sin not leading to death.\" (1 John 5:16-17) We should not take lightly these warnings for Christians. I know of Christians, I believe, who went to heaven before they should have, as a result of their willful sin. Now the passage goes on to say, \"We know that whoever is born of God does not sin [practice sin]; but he who has been born of God keeps himself, and the wicked one does not touch him.\" (1 John 5:18)\\new believe that Christians are to live a victorious Christian life; that does not mean that they never sin, but that they don\\'t want to sin (Look at our Romans 7-8 study). However, they do sin and that is why we need these verses: \"If we say that we have no sin, we deceive ourselves, and the truth is not in us. If we confess our sins, He is faithful and just to forgive us our sins and to cleanse us from all unrighteousness. If we say that we have not sinned, we make Him a liar, and His word is not in us.\" (1 John 1:8-10)\\nI have met people on both sides of the spectrum concerning the sin issue. Some Christians claim that they never sin, and others are afraid that they have committed the unpardonable sin. First, if you say that you have no sin and are perfect, you are lying because God says no one is perfect, not even Christians. Usually these people redefine sin as the \"big ones\" they think, like murder, adultery, and so on, but God does not make these distinctions in His word.\\nThe problem with this theory, that we can be perfect before we get to heaven, is that it just is not true, even though we are to be perfect as He is perfect; this is a goal that we will not totally reach until we get to heaven. That is why we need 1 John 1:9, because we do have a need, as Christians, to confess our sins. Peter gave Ananias and his wife Sapphira an opportunity to repent, but they didn\\'t take it, so they died for their unconfessed sin.\\nThe other case, where a Christian thinks he or she has committed the unpardonable sin, they have not, because they are under conviction of sin. If they had committed the unpardonable sin, they would not even be concerned about it, they would be so hardened. The mere fact that they are being convicted by the Holy Spirit shows that they can still be forgiven. The unpardonable sin is actually rejecting the Holy Spirit\\'s convicting of a person of their need of salvation. Once a person has died it is too late to repent and receive Christ\\'s pardon for salvation.\\nI believe, though, that we will see Ananias and Sapphira in heaven. You see, God has forgiven us in Christ, but we will have to give an account of our lives when we stand before Him. Many Christians in the Church have sinned like these two did, and many of these Christians have not died immediately. Why is this? It is because these two were used as examples of what God feels about us thinking that we can deceive Him. He knows everything we do, say, and think, so we need to be careful of our motives!\\nBefore we take the Holy Communion we need to examine ourselves, St. Paul says. \"Therefore whoever eats this bread or drinks this cup of the Lord in an unworthy manner will be guilty of the body and blood of the Lord. But let a man examine himself, and so let him eat of the bread and drink of the cup. For he who eats and drinks in an unworthy manner eats and drinks judgment to himself, not discerning the Lord\\'s body. For this reason many are weak and sick among you, and many sleep [have died]. For if we would judge ourselves [1 John 1:9], we would not be judged. But when we are judged, we are chastened by the Lord, that we may not be condemned with the world.\" (1 Corinthians 11:27-32)\\n(11) God is a holy God, someone has noted that the angels in Isaiah 6 are not saying \"love,\" \"love,\" \"love,\" when they are worshipping before God, but are saying, \"Holy,\" \"Holy,\" \"Holy!\" God wants us to live holy lives for our own well being and for His name\\'s sake, because that is whose we are; we are His name\\'s sake. \"He leads me in the paths of righteousness for His name\\'s sake.\" (Psalm 23:3b)\\n\"This event brought great awe and fear of God into the church and exercised a purifying influence. Here for the first time in Acts the word for church, ekklēsia, appears. It means, called out, and refers to the calling out of Greek citizens from their homes to the public assembly for civic purposes. The word is taken over by the Greek OT and used of Israel as the people of God. Its use in the NT therefore indicates that the Church is the new people of God. This word is never used of a building. It designates both the church at large (5:11; 9:31; 20:28) and local congregations of believers (11:26; 13:1).\\n(12) \"The early Christians did not have their own building for worship but met in Solomon\\'s Porch, which bordered the east side of the vast temple area.\" (The Wycliffe Bible Commentary) Usually they met in homes or rented buildings as we will see in other parts of Acts.\\n\"Sings and wonders characterized the ministry of the early Church and are equally intended to be expected in and through the Church today. [1 Corinthians 12: 1-31, we have a study on this in our Corinthians commentary.]\\n\"One Heart and One Soul, POWER OF UNITY. The early church grew rapidly as \\'the Lord added to the church daily those who were being saved\\' (Acts 2:27). In 4:32, 33, it is reported that the growing multitude of believers were experiencing a profound dimension of spiritual unity. First, they were \\'of one heart,\\' which is a description in the original Greek, meaning \\'in tune\\' or \\'in sync\\' with one another. To put it another way, they were all going the same way, spiritually together. Second, they were of \\'one soul\\' (sometimes translated as \\'one mind\\'). This has a wonderfully deep meaning in the original Greek. It literally means \\'to breathe\\' or \\'to breathe spiritually together.\\' The results of this quality of spiritual unity were both powerful and practical.\" (New Spirit Filled Life Bible)\\n\"The tragic and terrible weakness of the contemporary church is that its people are not rock solid in their faith in the living Lord Jesus Christ. Their leaders are so eager to pack their sanctuaries with happy people, so keen to come to an easy accommodation with the world, so willing to be soft on sin and tolerant of almost any lifestyle, that the church has almost no impact on our culture.\\n\"If we are going to shape our society to serve God and honor Him, it will not be at the ballot box or through the political powers per se. It will be by the relentless power of God\\'s own gracious Spirit becoming supremely in control of individual believers who are firm in their devotion to Christ. People, plain people who stand on their faith in our Father, will shape society and change our civilization for good more than will ten thousand, big-time TV campaigns with all their glitz and glamour.\\n\"God is not looking for smooth, slick communicators. He is looking for a few noble souls who will stand firm for Him, who will not flinch before their foes, who will not fear no matter how much others may rant and rave in rage. Let me name but a few of these dauntless ones:\\nJoseph in Egypt,\\nDaniel in Babylon,\\nPaul in Greece and Italy,\\nAugustine in Africa,\\nFlorence Nightingale in the Crimea,\\nWilberforce in Britain,\\nAbraham Lincoln in North America.\\nIt takes courage to be firm and fearless.\\nIt means a man or woman must be bold for God and His Word.\\nIt demands that we be different from the crowd.\\nBut our Father honors those who honor Him!\"\\n(What Makes LIFE Worth Livingby the author of A Shepherd Looks at Psalm 23, W. Phillip Keller)\\n(13) The unsaved are watching us all the time to see if our salvation is real. Sometimes they may say things like, \"Oh, it is just a phase they are going through, they will get over it.\" Also, even though they may respect us they are afraid of what others will think of them if they get saved, or they are afraid of the persecution it will bring. Don\\'t give up, it may take years, but if we keep praying for them and keep living for the Lord they, in many cases, will come to know Christ as their personal Lord and Savior.\\nHere is a true account of this very same thing happening recently in India: \"The 105-year-old man stood before his fellow villagers. The people respected the elderly man and stood at rapt attention, waiting to hear what he had to say. As the words began to tumble out of his mouth, the people knew something was drastically different.\\n\"\\'My dear friends and villagers, so many years I misunderstood Christianity and I persecuted the Christians a lot,\\' he began. \\'But all these years I had no peace in my heart. Then I realized my sins and I came to know that only Jesus Christ could forgive my sins, and give me peace of mind. So whether you kill me or not, I am going to take baptism.\\'\\n\"The people were stunned at his bold confession of faith. They still could hardly believe their eyes when the centenarian and his family chose to be baptized and became active members of the local Gospel for Asia Believers Church.\\n\"GFA leaders in Tripura, where this man lives, were not surprised at the turn of events. They had been fasting and praying that God would remove the veil of opposition from the man\\'s eyes.Whether old or young, former persecutors of Christians are today embracing the faith they once resisted-thanks to the prayers of God\\'s people.\" (Gospel for Asia News Update December 2006)\\n(14) Now at this point in history so many were getting saved that the Apostles lost track of how many there were. \"Estimates of the size of the Church by 250 [AD] vary between five and twelve percent of the population of the [Roman] Empire.\" (Christianity Through The Centuries)\\n(15-16) \".so that they brought the sick out into the streets and laid them on beds and couches, that at least the shadow of Peter passing by might fall on some of them. Also a multitude gathered from the surrounding cities to Jerusalem, bringing sick people and those who were tormented by unclean spirits, and they were all healed.\" (Notice Peter didn\\'t take up an offering here, or even say anything about money!)\\nGod used special miracles to confirm His message to the people of that time at the beginning of the Church Age, but that is not to say that God cannot or will not do this type of thing again. The book of Acts is the blue-print for the Church, but we also need to understand that the foundation was laid by Jesus and the Twelve Apostles along with St. Paul. So you don\\'t lay down another foundation after the building is going.\\n\"For we are God\\'s fellow workers; you are God\\'s field, you are God\\'s building. According to the grace of God which was given to me, as a wise master builder I have laid the foundation, and another builds on it. But let each one take heed how he builds on it. For no other foundation can anyone lay than that which is laid, which is Jesus Christ.\" (1 Corinthians 3:9-11)\\n\"\\'Therefore, of these men who have accompanied us all the time that the Lord Jesus went in and out among us, beginning from the baptism of John to that day when He was taken up from us, one of these must become a witness with us of His resurrection.\\'. And they prayed and said, \\'You, O Lord, who know the hearts of all, show which of these two You have chosen to take part in this ministry and apostleship from which Judas by transgression fell, that he might go to his own place.\\' And they cast their lots, and the lot fell on Matthias. And he was numbered with the eleven apostles.\" (Acts 1: 21-26) So today we do not have an apostleship as it was in the early Church, but there are apostles in the sense of missionaries, look at our Ephesians 4 study.\\n\"The shadow of Peter was not magic nor was it intended to provide a formula. Sometimes God uses physical objects as a point at which our faith may make a kind of link between the seen and the unseen (see 19:12). The bread and cup of Communion, the water of baptism, and the anointing oil (James 5:14) are some examples.\" (New Spirit Filled Life Bible)\\nThat being said, some today are making money out of sending pieces of cloth that have been prayed over, and they add, healing will follow if you send us money, but (they imply) \"no money, no healing.\" How far from the truth, and how perverted are such people who would teach and preach such things! All I can say is that they will be judged for such a perversion of the precious, glorious Gospel of our Lord Jesus Christ! Salvation is a free gift, and healing is also a free gift!\\nIn the Old Testament there is an example of someone making profit out of healing and what happened to him:\\nNow Naaman, commander of the army of the king of Syria, was a great and honorable man in the eyes of his master, because by him the LORD had given victory to Syria. He was also a mighty man of valor, but a leper.Then Naaman went with his horses and chariot, and he stood at the door of Elisha\\'s house. And Elisha sent a messenger to him.So he [Naaman].went down and dipped seven times in the Jordan, according to the saying of the man of God; and his flesh was restored like the flesh of a little child, and he was clean.\\nAnd he returned to the man of God, he and all his aides, and came and stood before him; and he said, \\'Indeed, now I know that there is no God in all the earth, except in Israel; now therefore, please take a gift from your servant.\\' But he said, \\'As the LORD lives, before whom I stand, I will receive nothing.\\' And he urged him to take it, but he refused.Then he said to him, \\'Go in peace.\\' So he departed from him a short distance.\\nBut Gehazi, the servant of Elisha the man of God, said, \\'Look, my master has spared Naaman this Syrian, while not receiving from his hands what he brought; but as the LORD lives, I will run after him and take something from him.\\nSo Naaman said, \\'Please, take two talents.\\' And he urged him, and bound two changes of garments, and handed them to two of his servants; and they carried them on ahead of him. When he came to the citadel, he took them from their hand, and stored them away in the house; then he let the men go, and they departed.\\nNow he went in and stood before his master. Elisha said to him, \\'Where did you go, Gehazi? And he said, \\'Your servant did not go anywhere.\\' Then he said to him, \\'Did not my heart gowith you when the man turned back from his chariot to meet you? Is it time to receive money and to receive clothing, olive groves and vineyard, sheep and oxen, male and female servants? Therefore the leprosy of Naaman shall cling to you and your descendants forever.\\' And he went out from his presence leprous, as white as snow.\" (2 Kings 5: 1-27)\\nHere is but one example of the perversion from our day of what God intended for healing gifts, and how they should be used: \"—— [Name of a person] then promised that anyone suffering from an extreme financial crisis need only carry the prayer cloth in a purse, wallet, or checkbook to receive a financial breakthrough. There was one small catch: Before the cloth could work, it had to be sent back to ——. The prayer cloth, according to ——, presently \\'does not carry or contain any special anointing or qualities. It is just a simple piece of plain cloth.but in a few days (if you act in faith RIGHT NOW) it can become a MIRACLE PRAYER CLOTH.\\' But —— had one more suggestion: When you return the cloth, be sure to send money. As —— puts it, \\'Receiving follows giving.\\'\" (Christianity in Crisis)\\nThe Church has not seen the likes of such teaching since Martin Luther confronted John Tetzel for the selling of indulgences. Look what was happening in Luther\\'s time: \"The prior of the Dominican convent at Leipzig, John Tetzel, was selling these indulgences. When he entered Juterbog where Luther\\'s people went to see and hear him, he had the papal bull, announcing the indulgence, carried on velvet cloth at the head of a procession.\\n\"With great pomp and ceremony he marched through the streets of the town to the place of preaching. There, in unbelievable boldness, he promised to the Saxons that they could buy release from all punishment imposed by church law; they also could buy release from the penances they must do in purgatory for their sins.\\n\"With mock pathos and brutal hypocrisy, he painted for the benefit of his hearers the sufferings of their dead relatives in purgatory and told them point-blank that they could release their loved ones from suffering by paying a little money. Duped by these promises, the unlettered Germans whom Luther looked upon as his sheep, believed the great reward of character thus could be bought.\" (Heroes of the Faith, Martin Luther, Edwin P. Booth)\\nSo it is today, some are preaching another gospel, and some are \"selling the gospel.\" Healing comes all of \"faith\" and faith in God\\'s power, not faith in faith! Nor does God charge for salvation or healing! \"And the Spirit and the bride say, \\'Come!\" And let him who hears say, \\'Come!\\' And let him who thirsts come. Whoever desires, let him take the water of life freely.\" (Revelation 22:17)\\n(17-18) Tertullian said, \"The blood of the martyr is often the seed of the Church.\" \"Such rapid growth was not without much opposition on the part of the Jews. Quickly the ecclesiastical authorities realized that Christianity offered a threat to their prerogatives as interpreters and priests of the law, and they rallied their forces to combat Christianity. Persecution came first from a politico-ecclesiastical body, the Sanhedrin, which, with Roman permission, supervised the civil and religious life of the state. Peter and John were hailed before that august body at least twice and forbidden to preach the Gospel, but they refused to accede to the request.\" (Christianity Through the Centuries, Cairns)\\n(19-21) Men of this world and enemies of the cross think they can physically stop the spread of the Gospel into the entire world. Whatever they do will only \\'backfire\\' in their faces, here they think by locking up some of the apostles they will stop the spread of the good news of Christ\\'s resurrection. This only makes Christ\\'s disciples more determined than ever that they are walking in the truth and light, while the Sadducees \"are sad you see\" because they are walking in darkness.\\n\"5:17 Sadducees. Strangely, the chief priests were all members of the Sadducees, the religious party which (like the pagan nations around them denied the doctrine of resurrection. Therefore, they were increasingly furious at the effectiveness of the powerful preaching of the resurrection by the apostles (Acts 4:33; 6:7). 5:20 Go, stand. Regardless of opposition or difficulties the Lord expects His people to stand-that is, to take a stand, once and for all (Ephesians 6:13, 14)-and to speak-to speak all the words of this life, just as the apostles\\'spake the word of God with boldness\\' (Acts 4:31)\" (The Defender\\'s Study Bible)\\nIn this case the apostles were not in common prison long because an angel took them out. They didn\\'t let fear take hold of them, but they went right back to work preaching the gospel in the temple. The high priest, after having breakfast decided to have the apostles for lunch, but he was to have a big surprise instead!\\nAngels are spoken of throughout the Bible; actually there are more references to angels in the New Testament than in the Old. They are always helping believers. They were with Christ at His birth, resurrection, and ascension. Now we see them at work in the ministry of the early Church. Do you suppose they have stopped ministering to the saints? No, I don\\'t think so, they are always doing their job, even though we don\\'t see them, at least we don\\'t think we see them. \"Do not forget to entertain strangers, for by so doing some have unwittingly entertained angels.\" (Hebrews 13:2)\\nGod delivers some, and others He allows to stay in jail. John Bunyan spent something like twelve years in an English jail, however, as a result of that time he wrote Pilgrim\\'s Progress, which has brought multitudes to the saving grace of Christ. Paul himself spent many years in jail, \"We need to bloom where we are planted,\" as someone has said.\\nAt that time, at the inception of the Church, there were just a few suffering for the Lord Jesus Christ; today many around the world suffer in prisons and in many other horrible ways. There is probably more persecution today than at any other time in Church history. One reason for so many being persecuted is because there are more Christians than there has ever been before.\\nHere are just a few of the countries where Christians are put in prison and tortured for their faith:\\nChina, Belarus, Uzbekistan, Turkmenistan, Tajikistan, Iraq, Iran, Afghanistan, Pakistan, North Korea, Laos, Vietnam, Myanmar (Burma), Brunei and Malaysia, Indonesia, Saudi Arabia, Egypt, Northern Sudan, Libya, Tunisia, Morocco, Algeria, Libya, Mauritania, Northern Nigeria, Cuba, Kuwait, Qatar, Oman, Yemen, Eritrea, Somalia, Lebanon, Syria, Gaza Strip, Chiapas (Mexico), Colombia, Turkey, Ethiopia, Kyrgyzstan, parts of India, Nepal, Bhutan, Bangladesh, Sri Lanka, Maldives, Mindanao (Philippines), Comoro Islands.\\n\"Richard Wurmbrand learned firsthand that although you can imprison the body, no one can bind the soul. He later learned his solitary cell was adjacent to the toilet (if you could call it that) where prisoners would line up each morning. He began to shout through the wall. \"God is good.\" \"Jesus died for your sins.\" \"Believe in Jesus.\" \"He is your only hope.\" \"Hallelujah!\"\\nRichard became know as the \"Hallelujah Pastor\" and his reputation spread throughout the prisons in Romania-an unseen and unnamed pastor who shouted through concrete walls to bring hope to others.\\nRichard spent a total of 14 years in prison, three of those years in solitary confinement. After being freed and coming to the West, he started The Voice of the Martyrs (see our web sites) in October of 1967. This year (2007) marks [their] 40th anniversary.\" (The Voice of the Martyrs January 2007) If you do not get their magazine I highly recommend it, so you can keep in touch with what God is doing around the world through Christians who are suffering greatly for their faith.\\n\"Doing the work of God is dangerous-not doing it is more dangerous.\" (Sabina Wurmbrand) To view a video reenactment by Richard Wurmbrand in his prison cell, visit www.persecution.com. Go to media rooms and enter the passcode \"Wurmbrand\" for more on Richard Wurmbrand\\'s life.\\n(26) These religious leaders should have feared the Lord instead of the people!\\n(27-28) You will remember that the Jews cried out, \"His blood be on us and on our children.\" when they wanted Jesus crucified. Now they seem to have forgotten what they had said earlier or maybe they were bothered by it. At any rate, they are still responsible for Jesus death, along with all the rest of the world, since we are all sinners, and He died for our sins! However, the Jewish nation does have the blood of Jesus on their hands, and until they ask God the Father\\'s forgiveness for this they will not have God\\'s protection or blessing as they had before. Once they do ask God the Father to forgive them, and ask Jesus to save them, He will. He will forgive and save them as individuals and as a nation. Then He will bless them, beyond what the world could ever fathom!\\n(29) \"5:29 ought to obey God. Christians are commanded to \\'be subject unto higher powers\\' (Romans 13:1) and to\\'submit yourselves to every ordinance of man for the Lord\\'s sake\\' (1 Peter 2:13), with this one exception. They had been commanded not to \\'teach in this name\\' (Acts 5:28), but God had said: \\'Stand and speak\\' (Acts 5:20). God\\'s commands take priority, but they should be His commands, not our extensions of those commands.\" (The Defender\\'s Study Bible)\\n(30) The disciples did not mince any words when they said to the false religious leaders, \"The God of our fathers raised up Jesus whom you murdered by hanging on a tree.\"\\n(31-32) \"The gift of the Holy Spirit, whom Luke notes is given to all believers at the time of salvation, bears witness to the reality of the exaltation of Jesus.\"\\n(33-42) Gamaliel, Paul\\'s former teacher (22:3), did not see Jesus as the Messiah, but his counsel to the Sanhedrin was certainly influenced by divine providence. Luke\\'s more subtle message is that even the highest levels of Jewish leadership had to admit that they had no valid reason for resisting the early church.\" (New Spirit Filled Life Bible)\\n\"Compare Acts 2:37. The Gospel, when preached in the power of the Holy Spirit, often convicts or enrages.\" (New Scofield Reference Edition)\\n\"5:34 Gamaliel, a Pharisee rather than a Sadducee like the chief priests and well instructed in the Scriptures, had been the teacher of young Paul before the latter became a Christian (Acts 22:3)\\n\"5:39 ye cannot overthrow it. Gamaliel may well have known Nicodemus, who was also a member of the council, a Pharisee, and a respected teacher (John 3:1,10). He must have been profoundly impressed by the conversion and devotion of Nicodemus to Jesus, and then by the empty tomb and the reports of Christ\\'s resurrection. He had good reason to fear that suppression of the Christians might indeed be fighting against God.\" (The Defender\\'s Study Bible)\\n\"In the above incident, Dr. Griffith-Thomas notices three representative forces-the spirit of error (the Sadducees); the spirit of compromise (Gamaliel); the spirit of truth (Peter).\" (Myer Pearlman)\\n\"38,39 Gamaliel counseled the Sanhedrin to trust God\\'s providence. If God was in the movement, it would prosper; otherwise it would fail.\"\\n\"40. Gamaliel\\'s influence was so great that he carried the decision of the Sanhedrin. A minor punishment of beating was inflicted, probably with thirty-nine blows (2 Cor. 11:24), for disobeying the Sanhedrin\\'s earlier command.\\n\"41,42. The apostles were by no means discouraged, for they considered it an honor to suffer for the name of Jesus. They continued their activities of teaching and preaching of Jesus as the Messiah, both publicly in the Court of the Gentiles in the temple and in their Christian gatherings in their private homes.\" (The Wycliffe Bible Commentary)\\n\"Both public services in the temple and small group meetings in private homes were employed for the nurturing of believers. Luke establishes both types of meetings as a paradigm, vital to the life of any local congregation (2:46).\" (New Spirit Filled Life Bible)\\n(1) \"Up to this point, the apostles had given no evidence of a purpose to carry the Gospel into all the world but had stayed in Jerusalem witnessing to the Jews. Luke now relates the beginnings of expansion of the church throughout Judea and Samaria, which was occasioned by the persecution that arose around Stephen. This expansion was accomplished not by the vision and purpose of the church but by the providential act of God in scattering the believers. To explain this persecution, Luke first relates how Stephen came into a position of prominence as one of the seven.\\n\"Choice of the Seven. 6:1-7. The church in its earliest days had no formal organization and no officials or leaders except the apostles. The numerical growth of the church and the rise of problems in its internal organization and the choice of additional leaders or ministers.\\n\"Jews who were natives of Palestine spoke primarily Aramaic; but Jews who had lived in the Mediterranean world outside of Palestine spoke Greek and often did not know Aramaic. Many of these Diaspora Jews returned to Jerusalem to live, and some of them were converted and came into the church.\\n\"A contention now arose between the Greek-speaking Christians (Grecians) [Hellenists] and the Aramaic-speaking Christians (Hebrews) because it appeared that favoritism for the latter was being shown in the distribution of food to the widows. Widows were persons without any means of support, who were provided with the bare necessities of life by the Christian community.\\n(2) \"The twelve apostles called together the entire church and pointed out that this responsibility for the care of the poor had become such a burden that they found themselves devoting most of their time to this material ministry and neglecting the ministry of the Word. Such neglect was not right. [\"The words\\'ministration\\' and\\'serve\\' are cognates in the Greek to the word which later became rendered as \\'deacon.\\'\" (The Defender\\'s Study Bible)]\\n(3-4) \"They recommended that the distribution of food be placed under the direction of seven Spirit-filled men of good reputation. [The Apostles were looking for three things in leadership: 1. Men of good reputation 2. Full of the Holy Spirit 3. Wisdom] The apostles would then be free to devote themselves to the ministry of prayer and of preaching and teaching the Word.\\n(5) \"Stephen was among the seven men chosen. All seven had Greek names and apparently were drawn from the Greek wing of the church. [\"The murmuring had come from the Greek-speaking segment of the church; so those elected to care for the work came from their number so as to represent their interests fairly.\\nOnly Stephen and Philip of the seven receive further notice (Stephen, 6:8-7:60; Philip, 8:5-40; 21:8-9). From Antioch, a convert to Judaism. It is significant that a proselyte was included in the number and that Luke points out his place of origin as Antioch, the city to which the gospel was soon to be taken and which was to become the \\'headquarters\" for the forthcoming Gentile missionary effort. (The NIV Study Bible)]\\n(6) \"The church at large selected these seven men, but the apostles approved the selection and appointed them to their office. The seven were then ordained to their office by the imposition of the apostles\\' hands. This laying on of hands was an OT custom (Gen. 48:13 ff.; Lev. 1:4; Num. 27:23), which was also practiced by the Jews when men were admitted to the Sanhedrin.\\n\"It was taken over by the early church for the ordination of these leaders. A preliminary qualification, however, was that the seven be filled with the Holy Spirit. Aside from the apostles, these seven were the first officials in the church. By tradition they have been designated deacons; but they are not so designated in the text.\\n\"The solution of this problem added to the effectiveness of the Christian testimony, and even many priests believed.\" (The Wycliffe Bible Commentary)\\n\"The laying on of hands sometimes accompanied prayer (Mt. 19:13,15) and was also used as a sign of healing (Mk. 5:23: 6:5, etc.), a symbol for the impartation of the Holy Spirit (Acts 8:17,19; 9:17; 19:6), and a token of ordination for special service (Acts 6:6; 13:3; 1 Tim. 4:14, etc.).\" (New Scofield Reference Edition)\\n(7) The Lord showed He was pleased with the resolution of the problem by adding to the Church new believers. I have known of churches that grew very quickly through evangelism or other forms of church growth, but then they just collapsed because they were not organized, nor did they have trained people to teach the new converts. So here again we see the blueprint for the Church.\\n\"One of a series of progress reports given periodically throughout the book of Acts (1:15; 2:41; 4:4; 5:14; 6:7; 9:31; 12:24; 16:5; 19:20; 28:31). A large number of priests. Though involved by lineage and life service in the priestly observances of the old covenant, they accepted the preaching of the apostles, which proclaimed a sacrifice that made the old sacrifices unnecessary (Heb 8:13; 10:1-4, 11-14) became obedient to the faith. Responded to the commands of the gospel. To believe is to obey God. Faith itself is obedience, but faith also produces obedience (Ro 1:1:5; Eph 2:8-10; Jas 2:14-26).\" (The NIV Study Bible)\\n(8) Notice also that miracles were the norm in the early Church. Are they the norm today or the exception? If they are the exception what has happened? Has God changed? Or is it that we have changed?!\\n(9) \"[Stephen] was bearing witness to the Messiahship of Jesus in the Jewish synagogues in Jerusalem, particularly in one that was attended by Freedmen\\n(RSV; Libertines, AV) who had formerly lived in the four places named. A\\nsynagogue was composed of ten or more Jews who met together for the reading and interpretation of the Scriptures. An exaggerated tradition says there were 480 synagogues in Jerusalem.\" (The Wycliffe Bible Commentary).\\n\"The \\'Libertines\\' [Freedmen] were freedmen, formerly slaves. All of these groups were Jewish immigrants to Jerusalem from other lands, who had evidently formed their own synagogue. As such, they were quite legalistic and very zealous of the Mosaic traditions, especially the temple worship. They may well have immigrated to Jerusalem for this very reason.\" (The Defender\\'s Study Bible)\\n\"Freedmen. Persons who had been freed from slavery. [But not from the slavery of sin!] They came from different Hellenistic areas. Cyrene. The chief city in Libya and north Africa.halfway between Alexandria and Carthage. One of its population groups was Jewish. Alexandria. Capital of Egypt and second only to Rome in the empire. Two out of five districts in Alexandria were Jewish.\\n\"Cilicia. A Roman province in the southeast corner of Asia Minor adjoining Syria. Tarsus, the birthplace of Paul, was one of its principal towns. Asia. A Roman province in the western part of Asia Minor. Ephesus, where Paul later ministered for a few years, was its capital. These men began to argue. Since Saul was from Tarsus, this may have been the synagogue he attended, and he may have been among those who argued with Stephen.\" (The NIV Study Bible)\\n(10) When a Christian is testifying for the Lord this is called witnessing. It will involve a spiritual warfare! Every time we tell others that Jesus is the only way to heaven we will suffer persecution.\\nAll of this was prophesied by Jesus that it would happen. \"But before all these things, they will lay their hands on you and persecute you, delivering you up to the synagogues and prisons. You will be brought before kings and rulers for My name\\'s sake. But it will turn out for you as an occasion for testimony. Therefore settle it in your hearts not to meditate beforehand on what you will answer; for I will give you a mouth and wisdom which all your adversaries will not be able to contradict or resist.\" (Luke 21:12-15)\\n(11-14) \"blasphemy against Moses and against God. Since Stephen declared that the worship of God was no longer to be restricted to the temple (7:48-49), his opponents twisted these words to trump up an accusation that Stephen was attacking the temple, the law, Moses and, ultimately, God.\" (The NIV Study Bible)\\n\"6:13 false witnesses. Stephen had been accused of blasphemy against the temple and the law, but even though the false witnesses had distorted his message, Stephen did not attempt to defend himself. Instead he probably presented the same type of message to the council as he had been preaching in the synagogue, stressing that the principles of God\\'s plan for Israel had been established long before the temple system, and that the Abrahamic Covenant centered in the promised Messiah, as did the preaching of the prophets. But Israel had rejected God\\'s Word at every stage, had killed the prophets, corrupted the law and finally murdered the Messiah when He came.\" (The Defender\\'s Study Bible)\\n\"The same argument had been leveled at Jesus (Matt. 26:60, 61). Actually, the coming of Christ meant the end of the temple order, which was the foundation and centerpiece of Judaism.\" (New Spirit Filled Life Bible)\\n(15) \"And all who sat in the council, looking steadfastly at him, saw his face as the face of an angel.\" (NKJV) God was preparing Stephen for a grand entrance into his heavenly home, as He does for all His Christian martyrs! \"Others were tortured, not accepting deliverance, that they might obtain a better resurrection. Still others had trial of mockings and scourgings, yes, and of chains and imprisonment.\\nThey were stoned, they were sawn in two, were tempted, were slain with the sword. They wandered about in sheepskins and goatskins, being destitute, afflicted, tormented-\\nOf whom the world was not worthy. They wandered in deserts and mountains. In dens and caves of the earth. And all these, having obtained a good testimony through faith.\" (Hebrews 11:35b-40)\\nI have had Christians tell me that if Stephen had had enough faith he would not have had to suffer stoning. This could not be further from the truth, just the opposite is true, Hebrews 11: 35b says, \"Others were tortured, not accepting deliverance, that they might obtain a better resurrection.\"\\nNot only that, we see the heavens opened, ready to receive Stephen with open arms! No, there is no lack of faith here. \"But he, being full of the Holy Spirit, gazed into heaven and saw the glory of God, and Jesus standing at the right hand of God, and said, \\'Look! I see the heavens opened and the Son of Man standing at the right hand of God!\" (Acts 7:55-56)\\nDon\\'t believe for a minute, this foolish teaching that Christians don\\'t have to suffer if they have enough faith! What does Holy Scripture say? \"Beloved, do not think it strange concerning the fiery trial which is to try you, as though some strange thing happened to you; but rejoice to the extent that you partake of Christ\\'s sufferings, that when His glory is revealed, you may also be glad with exceeding joy. If you are reproached for the name of Christ, blessed are you, for the Spirit of glory and of God rests upon you. On their part He is blasphemed, but on your part He is glorified.\" (1 Peter 4:12-14) (NKJV)\\n(1-59) \"Stephen\\'s lengthy address is more than a rebuttal of the charges against him. Rather than defending himself, he brought an indictment against his accusers. Instead of manifesting a true zeal for the temple and the Law in their opposition to the gospel, the Jews were displaying the same rebellious spirit of unbelief that characterized their forebears who resisted the purposes of God. In a skillful review of Israel\\'s history, he also concludes that God\\'s presence is not limited to a geographical place nor to a particular people.\" (New Spirit Filled Life Bible)\\n\"Running through his discourse are the following thoughts:\\n\"1. Divine revelation is progressive. Stephen had been accused of preaching that the Law of Moses would pass away (6:14). Though his words had been misquoted and their meaning perverted, Stephen had evidently been preaching the passing of the age of law, and the ushering in of the age of grace. So he shows that God has always been giving new revelations of Himself.\\n\"First He revealed Himself to Abraham, through the institution of the altar; to Moses in the burning bush and on Mount Sinai; then to Israel, through the tabernacle, and finally through the temple. Stephen shows that God\\'s dwelling in the tabernacle and temple was only symbolical (vv. 48, 49). God now dwells in and reveals Himself in reality through a new institution-the Church.\\n\"2. He had been accused of declaring that the temple would be destroyed (6:14). He shows that the temple is not the only holy place, but that God reveals Himself anywhere He finds an open heart. He revealed Himself to Abraham in Mesopotamia (v.2); to Joseph in Egypt (vv. 9-12); to Moses in Egypt (v. 25), and in the wilderness (vv. 30-33, 38).\\n\"3. Israel has always rejected God\\'s first offer of mercy, suffered for it, and then has accepted it the second time. They rejected Joseph and Moses the first time, but accepted them the second time (vv. 9-13, 24-35). In like manner they have rejected Jesus but after they have suffered, they will accept His second offer.\" (Through the Bible Book by Book by Myer Pearlman)\\nStephen concluded this with these two charges: \"You stiff-necked and uncircumcised in heart and ears! You always resist the Holy Spirit; as your fathers did, so do you. Which of the prophets did your fathers not persecute? And they killed those who foretold the coming of the Just One, of whom you now have become the betrayers and murderers.\" (7:51-52 NKJV)\\n\"And the LORD God of their fathers sent warnings to them by His messengers, rising up early and sending them, because He had compassion on His people and on His dwelling place. But they mocked the messengers of God, despised His words, and scoffed at His prophets, until the wrath of the LORD arose against His people, tillthere was no remedy.\" (2 Chronicles 15-16 NKJV)\\n\"Yet for many years You had patience with them, and testified against them by Your Spirit in Your prophets. Yet they would not listen; therefore You gave them into the hand of the peoples of the lands.\" (Nehemiah 9:30 NKJV)\\nJust like Jesus, Stephen, with his last breath forgave those who sinned against him. \"Then Jesus said, \\'Father, forgive them, for they do not know what they do.\\'\" (Luke 23:34) \"And they stoned Stephen as he was calling on\\nGod and saying, \\'Lord Jesus, receive my spirit.\\' Then he knelt down and cried out with a loud voice, \\'Lord, do not charge them with this sin.\\' And when he had said this he fell asleep.\" (7:59-60 NKJV) Sleep is a metaphor for death.\\nStephen\\'s prayer was answered in Saul. \".and they cast him out of the city and stoned him. And the witnesses laid down their clothes at the feet of a young man named Saul.\" (7:58) \".although I was formerly a blasphemer, a persecutor, and an insolent man; but I obtained mercy because I did it ignorantly in unbelief. And the grace of our Lord was exceedingly abundant, with faith and love which are in Christ Jesus.\" (1 Timothy 1:13-14)\\nStephen was the first in the Church to be martyred, but since him millions upon millions of Christians have suffered for their precious Lord Jesus Christ.\\n\"Do not think that I came to bring peace on earth. I did not come to bring peace but a sword. For I have come to\\'set a man against his father, a daughter against her mother, and a daughter-in-law against her mother-in-law\" and a man\\'s enemies will be those of his own household.\\' He who loves father or mother more than Me is not worthy of Me. And he who loves son or daughter more than Me is not worthy of Me. And he who does not take his cross and follow after Me is not worthy of Me. He who finds his life will lose it, and he who loses his life for My sake will find it.\" (Matthew 10:34-39)\\nDownload a PDF version of this article:Acts3_English<|begin_of_text|>Snøffeltøffs\\nYou want some garage, but nothing too garage (you still know all the lyrics to \\'Spice Up Your Life\\'). You want something pop, but you bought that Velvet Underground t-shirt from H&M and you don\\'t want people to think you\\'re frontin\\'. Entré Snøffeltøffs: Berlin\\'s pop-meets-garage sonic brawl of jangling, danceable indie tunes. They talk to us about terrible tour luck, pasta with ketchup, and they teach us an important lesson about proof-reading questions before sending them.\\nTHE LO DOWN\\nBangOn Team: Tell us a little about your band/project. What\\'s your sound?\\new\\'re Snøffeltøffs from Berlin. A project started by Florian and Julian about 5 years ago. We\\'ve known each other for fifteen years now and decided to work together after we played in several other more-or-less successful bands. It\\'s a project and not a band because it involves more people than just the band members. In 2016 Meghan from Cape Town joined to play drums. We used to describe our sound as \\'Hi-Fi, Lo-Fi, Shit-Fi\\' when we were a two piece. Now it\\'s \\'Lo-Fi Garage for Pop Lovers. Lo-Fi Pop for Garage Lovers.\\'\\nBOT: How do you go about songwriting?\\nJulian: It\\'s a pretty spontaneous process.\\nFlorian: Usually, someone comes up with a great idea and then we try to completely destroy it in the rehearsal room. People have called us unapproachable before, but critics said the same about The Velvet Underground, so I guess that\\'s okay. It\\'s the only way we can work really.\\nMeghan: The guys connect musically automatically and it takes them like five seconds to come up with a new song idea. Then I \\'beautiful mind\\' it and make tons of diagrams and notes to work out a structure for myself, then they make me throw away the papers, and then I have a meltdown, then we have beers and talk about turtles and seagulls, usually, and then the song is born. I had a lot of fun learning the songs from their first album, Hokus Pokus (which I think is great) and the songs we worked on together for the new album coming out later this year.\\nJ: We\\'re not meeting up and say, \\'Okay, we gotta come up with a song now, any ideas?\\'\\nBOT: Who are your biggest influences?\\nJ: Everyday life.\\nM: Ringo Starr and Phil Rudd when it comes to drummers.\\nF: Weird people we randomly meet.\\nBOT: What\\'s been your lowest and highest point as a band/project?\\nF: Coming back from an ill-fated Europe tour completely broke, owing the bank €2000\\nand having to live off about a Euro a day for the next couple of months– not being able to buy even remotely appropriate christmas presents for the parents. Yeah, that was pretty bad. Or opening for Eagles Of Death Metal and having to get off stage fifteen minutes into the show because of technical problems. That was pretty bad too. At least we got good money for the EODM show, which was kind of a high point… Oh no, wait, we lost all that money two weeks later because of a car crash in Prague. Or spending a lot of money on an album that was never released (great songs, though!). I guess the highest point was when we realized that, despite having had so much bad luck, we\\'re still doing this when other bands probably would have broken up a long time ago. That\\'s something we\\'re really proud of. Proves that friendship is stronger than band politics.\\nJ: Yes! Florian just summed up the highs of all low points in the past five years. Another low point we just talked about last week is an interview we did right in the beginning where we got quoted completely wrong, then sounded like rich arrogant musicians and had to explain ourselves for two years because people kept on asking what we meant.\\nBut even this all sounds pretty bad to others, we never ever even thought about splitting up. Friendship and music is stronger than cancelled bank accounts and pasta with ketchup.\\nBOT: What\\'s your ultimate aim?\\nJ: Make more albums, go on tour and make music great again.\\nF: Not having to play Squier guitars anymore.\\nM: To be able to continue playing more shows and always become a better player.\\nBOT: You have the chance to play one song for a legend of your choice. What do you play?\\nM: I\\'d like to play \\'Bitch Don\\'t Kill My Vibe\\' by Kendrick Lamar for Ginger Spice.\\nF: I\\'d like to play \\'Safety Dance\\' by Men Without Hats for Stefani Germanotta, because I read she likes it too and I think she\\'s pretty kewl.\\nJ: \\'Linus & Lucy (Snoopy Theme)\\' to Elton John.\\nYour friends don\\'t dance. But ours do.\\nBOT: What does Berlin do for you musically? What do we have to look forward to in the coming months from you?\\nF: You get the chance to see and meet a different band at a different venue basically every single day of the week, which is more than any musician could ever ask for.\\nJ: Which can also be pretty tiring to be honest because it\\'s just too much. It\\'s like the best town to make music; you just gotta find the right people or have to grow up with them. Apart from that we\\'re about to finish our second album which took some time and we want to extend the band with more members.\\nM: For me Berlin has always been very inspiring. I come from Cape Town: a beautiful city, but it\\'s also very laid back and super chill. I love the way it feels like anything is possible here, that sounds really lame, but i really do feel that way.\\nChoose one random question of your choice. (Editor\\'s note: We never expected such a direct and Snøffeltøffsish interpretation of this question! And as you\\'ll see from the [sic] below, even a typo of ours was Snøffeltøffsilised!)\\nJ: What\\'s your favourite cheese?\\nM: What is the Human Caterpillar?\\nF: How was dating Bruce Jenner?\\nBOT: Which member of your band would you put in the Human Caterpillar [sic]?\\nM: Do you mean the movie where the scientist kidnaps three tourists, keeps them in cages and then and joins them surgically mouth to a**? Okay... Wait that\\'s the Human Centipede. I don\\'t know what a human caterpillar is but I\\'m gonna say... Julian because he is a turtle.\\nF: No one, that\\'s just mean.\\nJ: Yes, why?\\nBOT: Which muppet would you take in a fist fight?\\nM: Florian the Muppet Sloth\\nF: I couldn\\'t. They\\'re all my friends.\\nBOT: Donald Trump has invited you to play a private party for him. He\\'ll pay you $1,000,000. Nobody ever has to know. Do you play?\\nM: I would take any opportunity I could get to get close enough to Donald Trump to give him a massive wedgie.\\nF: Sure, and then I would donate the money to organisations he opposes.\\nJ: …\\nCatch Snøffeltøffs on April 7th at Bang On\\'s (iron) maiden show, Clash Symbols #1 with Voodoo Beach and Paper Spook<|begin_of_text|>Jacques d\\'Armagnac (4 August 1477), duke of Nemours, was the son of Bernard d\\'Armagnac, count of Pardiac, and Eleanor of Bourbon-La Marche.\\n\\nAs the Count of Castres, Jacques served under Charles VII of France in Normandy in 1449 and 1450, and afterwards in Guienne. Louis XI awarded him with honours. In 1462, Jacques succeeded his father, and Louis XI married him to his god-daughter, Louise of Anjou, daughter of Charles of Le Maine. Louis XI also recognized his title to the duchy of Nemours, which he had disputed with the King of Navarre.\\n\\nSent by Louis to pacify Roussillon, Nemours felt that he had been insufficiently rewarded for the rapid success of this expedition, and joined the League of the Public Weal in 1465. Subsequently, he reconciled with Louis, but soon resumed his intrigues. After twice pardoning him, the king\\'s patience became exhausted, and he besieged the duke\\'s chateau at Carlat and imprisoned him. Nemours was treated with the utmost rigour, being shut up in a cage. He was finally condemned to death and beheaded, 4 Aug 1477.\\n\\nJacques and Louise had:\\n Jacques (d. young)\\n Jean d\\'Armagnac, Duke of Nemours (1467–1500)\\n Louis d\\'Armagnac, Duke of Nemours (1500–1503)\\n Marguerite d\\'Armagnac, Duchess of Nemours (d. 1503), married Peter de Rohan (d.1514)\\n Catherine d\\'Armagnac (d. 1487), married John II, Duke of Bourbon in 1484\\n Charlotte d\\'Armagnac, Duchess of Nemours (d. 1504), married Charles de Rohan (d.1504)\\n\\nReferences\\n\\nSources\\n\\n|-\\n\\n1430s births\\n1477 deaths\\n\\nYear of birth uncertain\\n\\nArmagnac, Jacques of\\n\\nCounts of Castres\\nArmagnac, Jacques of\\nArmagnac, Jacques of\\nPeople executed by France by decapitation\\nExecuted French people\\nPeople executed by the Ancien Régime in France\\n15th-century peers of France\\nPrisoners of the Bastille\\n15th-century executions by France<|begin_of_text|>Deciding on buying a Whole Life Insurance Policy is extremely complicated.\\nThe Complex world of Whole Life Insurance requires hard work.\\nYou won\\'t learn what you need to by just trusting one insurance agent.\\nThe Boat Anchor that could be Whole Life.\\nThe Numbers are Just Half the Story.\\nHow One Affluent Family did a Full Self Analysis.\\nMeet Jenny and Tom Wang an affluent and successful couple residing in a wealthy Southern California neighborhood. Jenny is a prominent lawyer and is a partner with her firm. Tom is a semi famous physician who owns his own practice and can be heard on the local radio station as a guest star dispensing medical advice. Jenny has just gone back to work after having given birth to their second daughter. The say this family is well off would be an understatement. To say this family is not well financially organized would be laughable. But even the classic well off family struggles with the possibility of buying whole life insurance.\\nBoth Jenny and Tom have multiple insurance policies. Jenny has a group life policy at her firm and a small $500K 25 year term policy that she purchased when you she first got pregnant with her oldest daughter. Tom owns a small key man life insurance policy through work, which is used for business purposes. He also has a small 20 year policy of $600K for his personal use.\\nWhen Jenny and Tom first purchased their new house 8 years ago, they found their old insurance company was unable to write the insurance due to the value of the home and the proximity to a wildfire area. The home is currently insured with one of the higher cost affluent insurance companies. Their three autos are also covered by the same insurer. We will refer to this company as PRP Home and Auto insurance. When they met their Property and Causality insurance agent he quickly assesses that they had a real need for purchasing and maintaining an Umbrella policy. The Umbrella Insurance policy sits over their main home, second vacation/rental home in Colorado, and three cars. It is written in the amount of $3 Million US Dollars with an additional $1 Million US Dollars in excess uninsured motorist coverage.\\nBoth Jenny and Tom maintain Professional Liability Insurance due to the nature of their licenses and work. Both of their businesses are fully insured.\\nThe Wangs are financial savers… They met at local investor conference and with the suggestion of a friend, Tom initially asked out Jenny. After the fourth date they quickly became inseparable and married a year or so later. Both Jenny and Tom love investing and saving money. Tom is more interested in risky investments and Jenny is more interested paying off every debt they have. However both of them agree in living well below their means. Because they both save so much, there biggest financial problem is deciding where to invest or save their extra dollars.\\nBecause the couple saves upwords of 20% of their pretax take home pay, the couple has amassed quite an array of savings. Their home, purchased just eight years ago was originally purchased for $1.2 Million Dollars, but has risen in value to something in the nature of $1.5 Million Dollars. Because they make at least one, if not two, extra mortgage payments per year and because they put so much down when they bought it, their mortgage sits at around $635,000. They have a very competitive mortgage rate.\\nTheir second home, is mostly rented out during the year and is located in a ski town in Colorado. It is a condo, which is valued at about $515,000 and they carry a $310,000 mortgage on it. Since it is mostly rented out, the Wangs CPA has advised them that they are getting a small tax advantage from owning it.\\nOther than their two homes, the couple has numerous other assets, including two 401Ks for Jenny valued at about $612,000 and a Roth IRA of $75,000. Tom has one 401K in the amount of $105,000, SEP IRA valued at $367,000 and an old Roth IRA in the amount of $34,000.\\nAs impressive as that all sounds the couple also has ample non retirement savings as well: An online savings account with 162,000 and a local joint saving account held at the local bank with $23,500. They have a investment account held with a national investment company that is mostly invested in passive ETFs and municipal bond funds in the amount of $459,000. They have various other small investments totaling about $45,000.\\nTheir oldest daughter has a 529 account that lists her as a beneficiary with about $51,000 and the youngest daughter has a brand new 529 with her listed as the beneficiary. This account has only $10,000. Both 529 accounts receive automatic monthly deposits of $1,000 per month. The couple is confident that between the current balance and future monthly deposits will be able to cover most of their children\\'s undergraduate costs.\\nBoth of their daughters also have less than $10K (8K, 2K) set aside for them in California UTMA accounts through their national broker. Whenever Jenny receives gifts for her two girls she immediately deposits the money into the accounts.\\nOther than the two mortgage listed above, the only debt that the couple has is a small residual amount of medical school debt in the amount of $45,000. Jenny was lucky in having saved enough and was helped by her parents to pay off law school long ago. But her husbands medical school debt is a source of anxiety for her. Both Tom and her argue about it often. Tom thinks that they should just allow it to be paid off on time, while Jenny would like to write a check and be done with it.\\nThe Wangs are cash flow positive, meaning they are easily taking in more money than they are spending. They drive nice autos, but plan to drive them until they are at least ten years old. They have few things that they consider luxuries and do not enjoy the expensive lifestyle of many of their children\\'s parents friends, preferring to spend time with extended family.\\nThe take in excess at least $550,000 per year and sometimes up to $650,000 per year.\\nIncluding their homes, 529s, children\\'s UTMA accounts, they have total assets of about $2,678,500 not including the increased value of their primary home of about $300,000. This net worth does not take into account numerous things including, but not limited to: Their Autos, There general possessions, Their small art collection, nor the potential use of social security at retirement. It also completely excludes Tom\\'s Physicians practice and Jenny\\'s Law partnership as these businesses are extremely hard to value. However, they do have value.\\nEven with this amazing amount of savings Jenny does not feel secure. She worrys constantly about Tom getting sued for the medical advice he shares on the radio as well as his practice Being a lawyer herself, she knows that the barrier in the United States to merely begin legal proceedings against someone is rather low. And although Tom carrys Malpractice insurance, she worrys that it may not be enough.\\nTom is not worried about this too much and claims that getting sued is part of being a business owner. He is however, slightly concerned about the stock market and is constantly looking for investments outside of stocks. He believes that between their investment accounts and retirement accounts, they are over placed into the market as a whole.\\nBoth Tom and Jenny save the maximum allowable amount into their Work Retirement plans. About $16,000 plus an employer contribution of $5K for Jenny and Tom with a SEP IRA contribution of somewhere between $18K to $35K per year. Jenny also puts money into a non deductible IRA yearly and converts it to a Roth IRA. They squirrel away about $24K per year into the kids 529 plans, make extra mortgage payments, and are fully insured. They add at least $30K to $35K per year to their online saving bank and deposit the rest of their savings joint the National Investment Company buying up Muni ETFs and Passive Stock ETFs. Soon they worry that their oldest child\\'s 529 will have all it needs and then what should they do? But what else to do with their money?\\nTom reads some stories and meets a pushy insurance agent at a golf outing who has been trying to convince him that a whole life insurance policy is the best thing since the sucher. This Life Insurance agent sponsors events and specializes in Life Insurance policies for wealthy doctors. All the doctors joke about him, when he not around. However, one of the wealthiest older docs in the group, tells the group that his ideas are not entirely wrong.\\nNot wanting to approach the life insurance agent, Tom does some research online and finds general condemnation for whole life insurance and its ugly cousins Universal and Variable Life. However in his reading he does see claims that Whole Life Insurance can serve as a form of asset protection and this appeals to him. More Life Insurance is probably a good thing, thinks Tom. After reading this he calls and schedules a quick meeting in his office with his golfing insurance agent. One of the things that immediately bothers Tom about the insurance agent is the lack of needs based questioning that the insurance agent has with him. The insurance agent is adamant that whole life insurance is the best thing in the world for most families and that term life insurance will run out, leaving the Wangs \"life insurance less.\" Tom immediately thinks this is funny because the insurance agent has no idea what his net worth is, nor their need for life insurance after their term policies end. He wants to end the meeting right then and there, but gets diverted by an incoming emergency phone call. After the phone call he allows the patient salesmen to continue.\\nThe conversation continues with the insurance agent reviewing some key reasons that doctors really should consider a whole life policy, including possible asset protection and a small interest rate paid through dividends in the participating whole life policy. Caught off guard, not knowing what dividends are in relationship to life insurance, Dr Tom, immediately starts taking notes. The insurance agent brags that his A+ carrier has paid out dividends for decades. After learning about the dividends, Tom Wang learns that this insurance agent has only one insurance company that he sells for. Tom is slightly concerned about this and decides its time to read up and speak with more people.\\nTom, discusses the presentation with his wife who in intrigued with the concept of a contract based saving plan but is confused by the combination with an insurance product. She suggest that Tom reach out to the their P&C Insurance Agent Bobby. Bobby is more than happy to discuss Permanent Life Insurance options, mostly offered by PRP Insurance Holdings and after a medium length needs based discussion, zones in an Indexed Universal Life Insurance policy insisting that it is all the rage these days. Tom is a bit put off by this as in their original phone discussion he had mentioned wanting a non stock market savings plan and the Indexed Universal Life insurance policy is somewhat tied to market performance. Also when asked about how it was linked, Bobby the P&C agent explained it, but not well. The whole thing seemed too confusing to Tom and he was not comfortable with the agents level of knowledge on the situation.\\nTom then reaches out to a former Wealth Manager that had long ago drawn up a fee for service financial plan for Tom, back when he was single. Tom\\'s recollection was that her work was terrific, but that the Wealth Manager wanted him to let her manage his assets. Not wanting to pay 1.1% per year for this service Tom demurred. With a renewed interest from an old Client, Sally the Wealth Manager quickly surveyed the landscape and did hint that a Whole Life Insurance plan could… be useful to someone in their financial situation. They discussed Indexed Universal Life plans, but she suggested that these life insurance policies were laden with high fees and confusing calculations of investment limitations and caps. Sally hinted that Participating Whole Life, if nothing else, was less complex than Indexed Universal and was indeed less market sensitive. Although she did bring up her belief that although Participating Whole Life Insurance companies were not stocks and did not usually own too many in their portfolio, they were at risk of bond performance since they usually had many in their portfolios.\\nIn the end the Wealth Manager really thought a better move was one of investing in new markets for the couple. She suggested a portfolio of Emerging Markets, and High Yield debt, feeling that the Wangs did not hold these types of investments currently.\\nFrustrated, now Tom does not know what to do. He was not going to hire a Wealth Manager and was certainly not going to be pushed into an Indexed Universal policy. He still felt his best option lay with the Golfing Insurance Agent, but wanted someone to review his needs from multiple companies. Tom tables the discussion with his wife and faisl to decide what to do.\\nA year goes by and Jenny no longer wants to put any more money into their oldest daughters 529 plan as she calculates that it is probably enough for their daughters future education in about 13 years. She doubles up on the contributions to her youngest daughters 529 plan from $1,000 to $2,000 per month. Both children are invested in the age (graduation) based portfolios so they are essentially on autopilot. Jenny is concerned that they now really have more money to invest than they know what to do with. A good problem to have, but it keeps her up at night.\\nJenny starts a small project of looking at the Alternative World of Investments that they can make with their small pile of money. She considers purchasing a $100K rental property near where her parents live in Arizona. Buying into a Hedge Fund. Investing in a small local restaurant through a friend. All of the options scare her though. When Jenny and Tom discuss the subject its clear that she is the safe investor and Tom likes to push the risk meter. Jenny brings up the whole life option again to Tom.\\nAlthough by this time Tom has been referred to multiple other insurance agents, he fails to find one that really knows his stuff and is able to work with multiple carriers. Tom finally, via the internet, discovers an Insurance Agency licensed in multiple states, including California, that really seems able to review their situation.\\nThe very first thing that the Insurance Agent, Eon from the Internet firm, asks after carefully reviewing their case is: Are either of their Term Life Insurance policies convertible? Tom has no idea what he is asking and asks him to repeat the question and then explain. Impressed they end their discussion, with Tom going out to explore if indeed either of their term life policies have this option.\\nTom calls Eon the life agent back to tell him that none of their term life policies are convertible. Eon assures him, that its OK, that he can get either or both of them – a small whole life policy with an A rated participating carrier. Tom inquires about the value of the credit rating and Eon insists that its more important with whole life than it is with term life. Tom then stops Eon to tell him that he would like a large whole life policy, something in excess of One Million US Dollars. Eon, states that he will happily show him the numbers for a range of options, but suggests that they look at smaller options as well.\\nThe internet insurance agent also spends a few minutes to politely educate Tom in his ideas of asset protection which was one of the original fundamental reasons that Tom had sought out Whole Life. Eon, the internet agent shares with him that asset protection is \"extremely state specific\" and that California does not have terrific bankruptcy asset protection. He suggests that he engage an attorney in a detailed discussion, but emails him a website that lists some basics about California whole life \"cash value\" creditor protection.\\nNext Eon and Tom discuss Tom\\'s health, his activities, profession, and numerous other underwriting criteria. With the phone call getting to be over an hour long they stop short of reviewing Jenny\\'s health and underwriting information. Tom later regrets this.\\nEon, presents to both Tom and Jenny various whole life insurance options with A and A+ rated participating whole life carriers. He insists that they both understand the difference between the guaranteed and assumed value charts. The assumed value chart use numbers that are less than the past dividend rates.\\nHe thoroughly explains why clients of his pretty much only purchase whole life insurance, in this type situation, with participating carriers. How participating carriers are owned by their insureds and the use of the dividends. Tom is now fully at home with all of the reading and speaking about whole life and assists in explaining some of the finer points to Jenny.\\nEon, also brings up a \"Waiver of Premium Rider\" and explains its value if the insured is unable to work. Being a doctor, Tom immediately smiles and is turned off by the idea not liking insurance companies definition of disability. Eon, the internet agent engages Tom, the Doctor and assures him that there are many definitions used for disability and that he might be able to find a definition that he can live with.\\nThe presentation goes pretty well, but the cost of the Two Million and even One Million dollars plans shock Jenny and slightly surprise Tom. Both of them, were surprised how much more it costs than level term life insurance. Tom, quickly remember that the internet insurance agent had suggested the $500K option as a \"smaller plan\" and is glad that his proposal include this option. Eon has proposals for both of them and he states that since they have not had the opportunity to discuss Jenny\\'s underwriting the price estimates are really not that accurate.\\nThat being said, Jenny\\'s yearly costs seem lower, partially based on the fact that she is a woman (generally women live longer), and and possibly based on the lack of negative information about her health history since they have not discussed it. The presentation ends on a high note, with both Tom and Jenny feeling confident in having found a knowledgeable agent that has conducted a full needs based analysis on their situation.\\nJenny first remarks to Tom, that she thinks its too expensive and that she doesn\\'t understand why they would want insurance once the kids are out of the house and they retire. Tom, who is usually not the safe investor in the house knows that Jenny loves safe investments so he uses this persuasively in his argument about the ability to put a small amount of money in a whole life policy that will easily be affordable for them, even during retirement. Jenny, not fully agreeing, at least agrees that $500K is the most she is interested in. They both wonder about the suitability to insure Tom vs Jenny vs both of them. Jenny is appalled about the thought of both of them buying a whole life policy. For internal political reasons, Tom thinks they he will press forward with the smaller whole life policy for just himself. Jenny thinks they should invest more in the market in safe mutual funds and stocks such as some of the options she saw last night on CNBC, such as Utility stocks which tend to pay out safe dividends.\\nAlthough the girls are getting older, in a couple of years the younger daughter will be done with preschool and be enrolled at the local elementary school cutting their costs a bit. They still have about, on average $35K per year in excess investment money in which to use. On occasional years it can balloon depending on bonuses of the two workers to something much higher. When they are done fully investing in their youngest daughters 529 plan though it will mean a possible additional $24K per year needing an investment home. After speaking with Jenny he is concerned about one of the objections she brought up and that this only makes sense if they are both able to keep working and continue to make the same amount of money. If one of them were to lose their jobs or their businesses became unprofitable the whole life option might weight on them like an unwelcome anchor.\\nTom thinks long and hard about what a non working situation could look like. He is not alarmed by it, but it is concerning. Perhaps he should just drop this.\\nNot liking computers Tom, sits down with Pen and Paper to review his options with the proposed whole life policy. At $7K per year it would be one of their biggest yearly expenses after property taxes on two properties and mortgage payments. Perhaps he can abandon his term life policy? No, that does not make sense. At $7K per year, 30 years of payments will amount of $210K in total. Not the end of the policy but a good chunk of it. And he already has more than $210K set aside, so even if he losses his job…somehow, he could still afford to make the life insurance premium payment, right? Wait, how would he make the mortgage payment? The Property Tax payment? The last think in the world he is going to want to do with his money is pay for a forced savings plan. But wait, his wife works.\\nIt would really only be a major issue if they BOTH lost their jobs, at the same time. She is a partner at a law firm and he owns his own business, is this possible? Tom gets up from his self discussion convinced that it would require a black swan event to make this a reality and he believes these types of swans can not be prepared for.\\nHe does get a chuckle out of imagining buying this product on a much lower income as a few of his younger and less successful neighbors have done. He wonders how they really pull it off. Do they ignore their 401K? Not make extra mortgage payments? Skip the college savings plan? Seven Thousand Dollars per year, for life, for whole life insurance! Wow that just sounds like a lot he thinks.\\nTom knows that Jenny keeps accurate spreadsheets for her assets, so he sits down to do what she would do. He creates columns, adds rows and numerically himself researches how this policy would look with the help of the whole life guaranteed and assumed value charts. He compares returns both taxable and untaxable in his spreadsheet with those of the life insurance companies.\\nAfter Jenny returns from a business trip and over wine they sit down during the fifteen minutes they have free to review what Tom wants to do. Jenny says that she is OK with him moving forward on the $500K front but is just too financially concerned abut anything larger than this. She also admits that if were not for his dogged determination, she probably would never have followed through with the purchase. Tom tells Jenny his concerns about lower earning people buying whole life and Jenny remarks that that is a really good point. \"I don\\'t know how others do it\" She says. Tom chuckles knowing his wife knows the finances better than he does and if she is OK with it, than it probably is the best decision.\\nJenny and Tom obviously have their financial act together. They do not represent the average American family. Yet even in their situation the decision to purchase and fund for the rest of their lives a whole life insurance policy is really not easy.\\nAdd in an excess of $100,000 per year, each and every year, to new savings.\\nBoth of them work. Both working could serve as an odd form of disability self insurance for each other.\\nThey keep spreadsheets and records.\\nThey talk about the finances.\\nThey are paying down their homes with extra payments, adding to retirement and college saving plans.\\nThey do a lot of homework, meet with numerous experts to find just the right product.\\nThey have spent dozens of hours, maybe fifty hours researching Whole Life and its Options.\\nAre the Wangs correct to assume that their proposed whole life insurance policy might protect their assets in the case of something happening with their business? Perhaps, asset protection and bankruptcy laws are very state specific, these clients happen to live in California. And According to California law Whole Life Insurance Asset protection is somewhat limited. Clients are advised to always speak with a lawyer in their state when considering this.\\nThe point to all of this is that these make believe people, The Wangs, are NOT average Americans. They make a ton of money! They have save like the Millionaires Next Door. They are not middle class workers. They took years to carefully make their decision. For most people that do not fit this profile… Term Life Insurance is more than likely the way to go. Yes, there are some exceptions to that rule, for example families that need a Special Needs Trust, but in general Term is the best Option.\\nShould you have questions or not understand something, please feel free to contact us directly at sales@marindependent.com. Whereas Term Life Insurance is simple and inexpensive, Whole Life is complex and complicated. It is really in your best interest to do your own homework on the subject of life insurance. Please see our disclosures. Thank you for reading An Affluent Family Considers Whole Life Insurance.\\nThe above example about an Affluent Family Considers Whole Life Insurance is fiction. Any similarities between actual people is purely confidential. Names and Insurance Company names are fictional. Why is it fiction? Well, first off, it would be very hard to get clients to allow an insurance agency to use their exact financial information. Second, its not practical. Third, I wanted to illustrate a potential client that I believe, barely qualifies to make a whole life policy make sense.\\nThis entry was posted in Life Insurance Story, Whole Life Insurance. Bookmark the permalink.\\nWow, thanks for the story. Long – but well Worth it.\\new'"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "llama3_tokenizer.decode(line['input_ids'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "128001"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(line['input_ids'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/draft.ipynb b/draft.ipynb
new file mode 100644
index 00000000..d4530e8b
--- /dev/null
+++ b/draft.ipynb
@@ -0,0 +1,79 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/admin/home/phuc_nguyen/miniconda3/envs/nanotron-dev/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datasets import load_from_disk"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_disk = load_from_disk(\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/needle_eval_datasets/needle_eval_ctx_len_32768_and_depth_100_and_id_17\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................... The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\\nThe. The pass key is 1995242. Remember it. 1995242 is the pass key. . \\n\\nWhat is the pass key? The pass key is \""
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_disk[1][\"prompt\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/infinite-context-length/configs/280m_llama_1024_ctx_infini.yaml b/examples/infinite-context-length/configs/280m_llama_1024_ctx_infini.yaml
new file mode 100644
index 00000000..34816aa3
--- /dev/null
+++ b/examples/infinite-context-length/configs/280m_llama_1024_ctx_infini.yaml
@@ -0,0 +1,108 @@
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: debug
+  run: tiny_llama_%date_%jobid
+  seed: 42
+  step: null
+infini_attention:
+  segment_length: 256
+  turn_on_memory: false
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    hidden_size: 128
+    initializer_range: 0.02
+    intermediate_size: 256
+    is_llama_config: true
+    max_position_embeddings: 1024
+    num_attention_heads: 8
+    num_hidden_layers: 1
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015
+    lr_decay_starting_step: null
+    lr_decay_steps: 2860
+    lr_decay_style: cosine
+    lr_warmup_steps: 715 # 20% of the total steps
+    lr_warmup_style: linear
+    min_decay_lr: 0.00001
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+parallelism:
+  # dp: 1
+  # tp: 8
+
+  dp: 1
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+data_stages:
+  - name: Stable Training Stage
+    start_training_step: 1
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: roneneldan/TinyStories
+        hf_dataset_splits: train
+        text_column_name: text
+      num_loading_workers: 1
+      seed: 42
+lighteval: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: gpt2
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1
+  limit_test_batches: 0
+  limit_val_batches: 0
+  # micro_batch_size: 256
+  # sequence_length: 1024
+  # train_steps: 1787
+  micro_batch_size: 32
+  sequence_length: 1024
+  # train_steps: 3575
+  train_steps: 1
+  val_check_interval: -1
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: null
+  save_initial_state: false
+profiler: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
diff --git a/examples/infinite-context-length/configs/exp10/exp10_8b_llama3_32k_ctx_and_4m_bs.yaml b/examples/infinite-context-length/configs/exp10/exp10_8b_llama3_32k_ctx_and_4m_bs.yaml
new file mode 100644
index 00000000..70595f2c
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp10/exp10_8b_llama3_32k_ctx_and_4m_bs.yaml
@@ -0,0 +1,198 @@
+checkpoints:
+  checkpoint_interval: 250
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp10_8b_llama3_32k_ctx_and_4m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/projects/infini-attention/llama3-ckps/8b/nanotron_ckp_tp_agnostic
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp10_8b_llama3_32k_ctx_and_4m_bs_and_lr_1.0e-6
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.015625
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 1.0e-6
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 4000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-7
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 8
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: meta-llama/Meta-Llama-3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 8 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 1 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  # sequence_length: 40960 # 8192 * 32 = 40960
+  # sequence_length: 73728 # 8192 * 9 = 73728
+  # sequence_length: 73728 # 8192 * 7 = 57344
+  # sequence_length: 65536 # 8192 * 8 = 65536
+  # sequence_length: 57344 # 8192 * 7 = 57344
+  # sequence_length: 49152 # 8192 * 6 = 57344
+  sequence_length: 32768 # 8192 * 4 = 32768
+  train_steps: 20_000
+  val_check_interval: -1
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    # dataset_weights:
+    # - 0.3
+    # - 0.3
+    # - 0.15
+    # - 0.15
+    # - 0.08
+    # - 0.02
+    datasets:
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp10_8b_llama3_32k_ctx_and_4m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp11/exp11_8b_llama3_32k_ctx_and_4m_bs.yaml b/examples/infinite-context-length/configs/exp11/exp11_8b_llama3_32k_ctx_and_4m_bs.yaml
new file mode 100644
index 00000000..03bb94d9
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp11/exp11_8b_llama3_32k_ctx_and_4m_bs.yaml
@@ -0,0 +1,198 @@
+checkpoints:
+  checkpoint_interval: 250
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp11_8b_llama3_32k_ctx_and_4m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/projects/infini-attention/llama3-ckps/8b/nanotron_ckp_tp_agnostic
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp11_8b_llama3_32k_ctx_and_4m_bs_and_lr_1.0e-6
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.015625
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 1.0e-6
+    lr_decay_starting_step: null
+    lr_decay_steps: 80000
+    lr_decay_style: cosine
+    lr_warmup_steps: 2000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-7
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 8
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: meta-llama/Meta-Llama-3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 8 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 1 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  # sequence_length: 40960 # 8192 * 32 = 40960
+  # sequence_length: 73728 # 8192 * 9 = 73728
+  # sequence_length: 73728 # 8192 * 7 = 57344
+  # sequence_length: 65536 # 8192 * 8 = 65536
+  # sequence_length: 57344 # 8192 * 7 = 57344
+  # sequence_length: 49152 # 8192 * 6 = 57344
+  sequence_length: 8192 # 8192 * 4 = 32768
+  train_steps: 20_000
+  val_check_interval: -1
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    # dataset_weights:
+    # - 0.3
+    # - 0.3
+    # - 0.15
+    # - 0.15
+    # - 0.08
+    # - 0.02
+    datasets:
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp11_8b_llama3_32k_ctx_and_4m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp12/exp12_8b_llama3_8k_ctx_and_4m_bs.yaml b/examples/infinite-context-length/configs/exp12/exp12_8b_llama3_8k_ctx_and_4m_bs.yaml
new file mode 100644
index 00000000..9b7b3965
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp12/exp12_8b_llama3_8k_ctx_and_4m_bs.yaml
@@ -0,0 +1,186 @@
+checkpoints:
+  checkpoint_interval: 250
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp12_8b_llama3_8k_ctx_and_4m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp12_8b_llama3_8k_ctx_and_4m_bs_lr_2.0e-5
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.015625
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 2.0e-5
+    lr_decay_starting_step: null
+    lr_decay_steps: 98_000
+    lr_decay_style: cosine
+    lr_warmup_steps: 2000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 2.0e-6
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 8
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: meta-llama/Meta-Llama-3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 8 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 8 * 1 * 8192 * 16 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  # sequence_length: 40960 # 8192 * 32 = 40960
+  # sequence_length: 73728 # 8192 * 9 = 73728
+  # sequence_length: 73728 # 8192 * 7 = 57344
+  # sequence_length: 65536 # 8192 * 8 = 65536
+  # sequence_length: 57344 # 8192 * 7 = 57344
+  # sequence_length: 49152 # 8192 * 6 = 57344
+  sequence_length: 8192 # 8192 * 4 = 32768
+  train_steps: 100_000
+  val_check_interval: -1
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    # dataset_weights:
+    # - 0.3
+    # - 0.3
+    # - 0.15
+    # - 0.15
+    # - 0.08
+    # - 0.02
+    datasets:
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp12_8b_llama3_8k_ctx_and_4m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp13/exp13_8b_llama3_8k_ctx_and_4m_bs.yaml b/examples/infinite-context-length/configs/exp13/exp13_8b_llama3_8k_ctx_and_4m_bs.yaml
new file mode 100644
index 00000000..e0a676d6
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp13/exp13_8b_llama3_8k_ctx_and_4m_bs.yaml
@@ -0,0 +1,186 @@
+checkpoints:
+  checkpoint_interval: 250
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp13_8b_llama3_8k_ctx_and_4m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp13_8b_llama3_8k_ctx_and_4m_bs_lr_2.0e-5
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.015625
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 1.0e-7
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 20_000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-8
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 8
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: meta-llama/Meta-Llama-3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 16 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 8 * 1 * 8192 * 16 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  # sequence_length: 40960 # 8192 * 32 = 40960
+  # sequence_length: 73728 # 8192 * 9 = 73728
+  # sequence_length: 73728 # 8192 * 7 = 57344
+  # sequence_length: 65536 # 8192 * 8 = 65536
+  # sequence_length: 57344 # 8192 * 7 = 57344
+  # sequence_length: 49152 # 8192 * 6 = 57344
+  sequence_length: 8192 # 8192 * 4 = 32768
+  train_steps: 100_000
+  val_check_interval: -1
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    # - 0.3
+    - 0.3
+    - 0.45
+    - 0.15
+    - 0.08
+    - 0.02
+    datasets:
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp13_8b_llama3_8k_ctx_and_4m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp14/exp14_8b_llama3_8k_ctx_length_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp14/exp14_8b_llama3_8k_ctx_length_and_2m_bs.yaml
new file mode 100644
index 00000000..cc3abc70
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp14/exp14_8b_llama3_8k_ctx_length_and_2m_bs.yaml
@@ -0,0 +1,198 @@
+checkpoints:
+  checkpoint_interval: 250
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp14_8b_llama3_8k_ctx_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp14_8b_llama3_8k_ctx_length_and_2m_bs_and_lr_1.0e-6
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.015625
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 1.0e-6
+    lr_decay_starting_step: null
+    lr_decay_steps: 16000
+    lr_decay_style: cosine
+    lr_warmup_steps: 4000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-7
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 8
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: meta-llama/Meta-Llama-3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 8 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 1 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  # sequence_length: 40960 # 8192 * 32 = 40960
+  # sequence_length: 73728 # 8192 * 9 = 73728
+  # sequence_length: 73728 # 8192 * 7 = 57344
+  # sequence_length: 65536 # 8192 * 8 = 65536
+  # sequence_length: 57344 # 8192 * 7 = 57344
+  # sequence_length: 49152 # 8192 * 6 = 57344
+  sequence_length: 8192 # 8192 * 4 = 32768
+  train_steps: 20_000
+  val_check_interval: -1
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    # dataset_weights:
+    # - 0.3
+    # - 0.3
+    # - 0.15
+    # - 0.15
+    # - 0.08
+    # - 0.02
+    datasets:
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp14_8b_llama3_8k_ctx_length_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp15/exp15_8b_llama3_1k_ctx_length_and_1m_bs.yaml b/examples/infinite-context-length/configs/exp15/exp15_8b_llama3_1k_ctx_length_and_1m_bs.yaml
new file mode 100644
index 00000000..28a90e71
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp15/exp15_8b_llama3_1k_ctx_length_and_1m_bs.yaml
@@ -0,0 +1,198 @@
+checkpoints:
+  checkpoint_interval: 250
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp15_8b_llama3_1k_ctx_length_and_1m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp15_8b_llama3_1k_ctx_length_and_1m_bs_and_lr_1.0e-6
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.015625
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 1.0e-6
+    lr_decay_starting_step: null
+    lr_decay_steps: 16000
+    lr_decay_style: cosine
+    lr_warmup_steps: 4000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-7
+  torch_adam_is_fused: true
+  weight_decay: 0.01
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 8
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: meta-llama/Meta-Llama-3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 16 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 1 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 4
+  # sequence_length: 40960 # 8192 * 32 = 40960
+  # sequence_length: 73728 # 8192 * 9 = 73728
+  # sequence_length: 73728 # 8192 * 7 = 57344
+  # sequence_length: 65536 # 8192 * 8 = 65536
+  # sequence_length: 57344 # 8192 * 7 = 57344
+  # sequence_length: 49152 # 8192 * 6 = 57344
+  sequence_length: 1024 # 8192 * 4 = 32768
+  train_steps: 20_000
+  val_check_interval: -1
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    # dataset_weights:
+    # - 0.3
+    # - 0.3
+    # - 0.15
+    # - 0.15
+    # - 0.08
+    # - 0.02
+    datasets:
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp15_8b_llama3_1k_ctx_length_and_1m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp16/exp16_8b_llama3_4k_ctx_length_and_1m_bs.yaml b/examples/infinite-context-length/configs/exp16/exp16_8b_llama3_4k_ctx_length_and_1m_bs.yaml
new file mode 100644
index 00000000..6c1ceaf9
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp16/exp16_8b_llama3_4k_ctx_length_and_1m_bs.yaml
@@ -0,0 +1,213 @@
+checkpoints:
+  checkpoint_interval: 250
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp16_8b_llama3_4k_ctx_length_and_1m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp16_8b_llama3_4k_ctx_length_and_1m_bs_and_lr_1.0e-6
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.015625
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 1.0e-6
+    lr_decay_starting_step: null
+    lr_decay_steps: 16000
+    lr_decay_style: cosine
+    lr_warmup_steps: 4000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-7
+  torch_adam_is_fused: true
+  weight_decay: 0.01
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 8
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: meta-llama/Meta-Llama-3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 16 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 1 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  # sequence_length: 40960 # 8192 * 32 = 40960
+  # sequence_length: 73728 # 8192 * 9 = 73728
+  # sequence_length: 73728 # 8192 * 7 = 57344
+  # sequence_length: 65536 # 8192 * 8 = 65536
+  # sequence_length: 57344 # 8192 * 7 = 57344
+  # sequence_length: 49152 # 8192 * 6 = 57344
+  sequence_length: 4096 # 8192 * 4 = 32768
+  train_steps: 20_000
+  val_check_interval: -1
+
+
+data_stages:
+- name: Stable Training Stage
+  start_training_step: 1
+  data:
+    dataset:
+      dataset_overwrite_cache: false
+      dataset_processing_num_proc_per_process: 1
+      hf_dataset_config_name: null
+      hf_dataset_or_datasets: JeanKaddour/minipile
+      hf_dataset_splits: train
+      text_column_name: text
+    num_loading_workers: 1
+    seed: 42
+
+# data:
+#   dataset:
+#     dataloader_type: single
+#     dataset_max_tokens: null
+#     # dataset_weights:
+#     # - 0.3
+#     # - 0.3
+#     # - 0.15
+#     # - 0.15
+#     # - 0.08
+#     # - 0.02
+#     datasets:
+#     # - filename_pattern: .*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+#     #   dtype: uint32
+#     #   skip_tokens: 0
+#     # - filename_pattern: .*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+#     #   dtype: uint32
+#     #   skip_tokens: 0
+#     # - filename_pattern: .*.ds
+#     #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+#     #   dtype: uint32
+#     #   skip_tokens: 0
+#     # - filename_pattern: .*.ds
+#     #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+#     #   dtype: uint32
+#     #   skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+#       dtype: uint32
+#       skip_tokens: 0
+#     pad_samples_to_global_batch_size: false
+#     skip_in_stream: true
+#   num_loading_workers: 0
+#   seed: 42
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+# s3_upload:
+#   remove_after_upload: true
+#   s5cmd_concurrency: 5
+#   s5cmd_numworkers: 16
+#   upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp16_8b_llama3_4k_ctx_length_and_1m_bs/
+
+# experiment_logger:
+#   tensorboard_logger:
+#     flush_secs: 30
+#     tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+#   wandb_logger:
+#     wandb_entity: null
+#     wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp17/exp17_8b_llama3_8k_ctx_length.yaml b/examples/infinite-context-length/configs/exp17/exp17_8b_llama3_8k_ctx_length.yaml
new file mode 100644
index 00000000..f1f16f99
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp17/exp17_8b_llama3_8k_ctx_length.yaml
@@ -0,0 +1,197 @@
+checkpoints:
+  checkpoint_interval: 250
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp17_8b_llama3_8k_ctx_length/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp17_8b_llama3_8k_ctx_length_and_lr_1.0e-6
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.015625
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 1.0e-6
+    lr_decay_starting_step: null
+    lr_decay_steps: 16000
+    lr_decay_style: cosine
+    lr_warmup_steps: 4000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-7
+  torch_adam_is_fused: true
+  weight_decay: 0.01
+  zero_stage: 0
+
+parallelism:
+  dp: 1
+  tp: 8
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: meta-llama/Meta-Llama-3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 16 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 1 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  # sequence_length: 40960 # 8192 * 32 = 40960
+  # sequence_length: 73728 # 8192 * 9 = 73728
+  # sequence_length: 73728 # 8192 * 7 = 57344
+  # sequence_length: 65536 # 8192 * 8 = 65536
+  # sequence_length: 57344 # 8192 * 7 = 57344
+  # sequence_length: 49152 # 8192 * 6 = 57344
+  sequence_length: 8192 # 8192 * 4 = 32768
+  train_steps: 20_000
+  val_check_interval: -1
+
+
+# data:
+#   dataset:
+#     dataloader_type: cyclic
+#     dataset_max_tokens: null
+#     datasets:
+#     # - filename_pattern: .*.ds
+#     #   folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+#     #   dtype: uint32
+#     #   skip_tokens: 0
+#     # NOTE: the dataset has filename_pattern 86564408 bytes
+#     # so it has 86564408 // 4 = 21641102 tokens
+#     # 100 samples = 100 * 8192 = 819200 tokens
+#     # so we skip 21641102 - 819200 = 20821902 tokens
+#     - file_path: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3/00000_00000_shuffled.ds
+#       dtype: uint32
+#       skip_tokens: 20821902
+#     pad_samples_to_global_batch_size: false
+#     skip_in_stream: true
+#   num_loading_workers: 0
+#   seed: 42
+
+data:
+  dataset:
+    dataloader_type: cyclic
+    dataset_max_tokens:
+    - 819200
+    datasets:
+    # NOTE: the dataset has filename_pattern 86564408 bytes
+    # so it has 86564408 // 4 = 21641102 tokens
+    # 100 samples = 100 * 8192 = 819200 tokens
+    # so we skip 21641102 - 819200 = 20821902 tokens
+    - filepath: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3/00000_00000_shuffled.ds
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp17_8b_llama3_8k_ctx_length/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp18/exp18_1b_llama2_100k_ctx_length_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp18/exp18_1b_llama2_100k_ctx_length_and_2m_bs.yaml
new file mode 100644
index 00000000..4a4dbd8d
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp18/exp18_1b_llama2_100k_ctx_length_and_2m_bs.yaml
@@ -0,0 +1,245 @@
+checkpoints:
+  checkpoint_interval: 5000
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp18_1b_llama2_100k_ctx_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  # resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp18_1b_llama2_100k_ctx_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp18_8b_llama3_8k_ctx_length_and_lr_1.0e-6
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.03125 # 1/sqrt(1024)=0.03125
+    std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 2048
+    intermediate_size: 8192
+    num_hidden_layers: 14
+
+    is_llama_config: true
+    max_position_embeddings: 32768
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 600 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 8
+  tp: 4
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 4 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 16 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 2
+  # n_segments = 20
+  # 2048 * 20 = 40960
+  # 8192*14
+  # # 1024*100 = 102400
+  # 8192 * 14 = 114688
+  # 4096 * 16 = 65536
+  # 2048*16 = 32768
+  sequence_length: 32768
+  train_steps: 30_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp18_1b_llama2_100k_ctx_length_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp18/exp18_1b_llama2_finetune_needle.yaml b/examples/infinite-context-length/configs/exp18/exp18_1b_llama2_finetune_needle.yaml
new file mode 100644
index 00000000..daeacce9
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp18/exp18_1b_llama2_finetune_needle.yaml
@@ -0,0 +1,257 @@
+checkpoints:
+  checkpoint_interval: 240
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp18_1b_llama2_100k_ctx_length_and_2m_bs/checkpoints/finetune_needle_checkpoints_with_needle_in_prediction
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp18_1b_llama2_100k_ctx_length_and_2m_bs/checkpoints/30000
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp18_8b_llama3_8k_ctx_length_and_lr_1.0e-6
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.03125 # 1/sqrt(1024)=0.03125
+    std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 2048
+    intermediate_size: 8192
+    num_hidden_layers: 14
+
+    is_llama_config: true
+    max_position_embeddings: 32768
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00005 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: linear
+    lr_warmup_steps: 40 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-06
+  torch_adam_is_fused: true
+  weight_decay: 0.01
+  zero_stage: 0
+
+parallelism:
+  dp: 2
+  tp: 4
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 16 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  # n_segments = 20
+  # 2048 * 20 = 40960
+  # 8192*14
+  # # 1024*100 = 102400
+  # 8192 * 14 = 114688
+  # 4096 * 16 = 65536
+  # 2048*16 = 32768
+  sequence_length: 32768
+  train_steps: 484
+  val_check_interval: -1
+
+
+# data:
+#   dataset:
+#     dataloader_type: single
+#     dataset_max_tokens: null
+#     dataset_weights:
+#     - 0.6
+#     - 0.2
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     datasets:
+#     - filename_pattern: .*/tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/fineweb/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack_full/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/c4/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/arxiv/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/synthetic-data/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-pull-requests/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/open-web-math/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-issues/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stackoverflow/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/wikipedia/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/project-gutenberg/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/deepmind-math/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-documentation/
+#       skip_tokens: 0
+#     pad_samples_to_global_batch_size: false
+#     skip_in_stream: true
+#   num_loading_workers: 0
+#   seed: 42
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+data_stages:
+  - name: Finetune Needle
+    start_training_step: 1
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: nanotron/needle_in_a_hay_stack_finetune_dataset
+        hf_dataset_splits: train
+        text_column_name: prompt
+      num_loading_workers: 1
+      seed: 42
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+# s3_upload:
+#   remove_after_upload: true
+#   s5cmd_concurrency: 5
+#   s5cmd_numworkers: 16
+#   upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp18_1b_llama2_100k_ctx_length_and_2m_bs/
+
+# experiment_logger:
+#   tensorboard_logger:
+#     flush_secs: 30
+#     tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+#   wandb_logger:
+#     wandb_entity: null
+#     wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp19/exp19_1b_llama2_32k_ctx_length_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp19/exp19_1b_llama2_32k_ctx_length_and_2m_bs.yaml
new file mode 100644
index 00000000..dad21eb5
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp19/exp19_1b_llama2_32k_ctx_length_and_2m_bs.yaml
@@ -0,0 +1,245 @@
+checkpoints:
+  checkpoint_interval: 5000
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp19_1b_llama2_32k_ctx_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  # resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp19_1b_llama2_32k_ctx_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp19_8b_llama3_32k_ctx_length_and_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.03125 # 1/sqrt(1024)=0.03125
+    std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 2048
+    intermediate_size: 8192
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 2048
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 18000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 4
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 2 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 16 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 2
+  # n_segments = 20
+  # 2048 * 20 = 40960
+  # 8192*14
+  # # 1024*100 = 102400
+  # 8192 * 14 = 114688
+  # 4096 * 16 = 65536
+  # 2048*16 = 32768
+  sequence_length: 32768
+  train_steps: 90_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp19_1b_llama2_32k_ctx_length_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp19/exp19_finetuning.yaml b/examples/infinite-context-length/configs/exp19/exp19_finetuning.yaml
new file mode 100644
index 00000000..ed4555b5
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp19/exp19_finetuning.yaml
@@ -0,0 +1,228 @@
+checkpoints:
+  checkpoint_interval: 100
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp19_1b_llama2_32k_ctx_length_and_2m_bs/checkpoints/finetune_needle
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp19_finetuning/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  # resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp19_1b_llama2_32k_ctx_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp19_finetuning
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.03125 # 1/sqrt(1024)=0.03125
+    std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 2048
+    intermediate_size: 8192
+    num_hidden_layers: 14
+
+    is_llama_config: true
+    max_position_embeddings: 2048
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.000075 # note: 1/2 of the original learning rate
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 96 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 1
+  tp: 4
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  # batch_accumulation_per_replica: 16 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 16 = 655,360
+  # limit_test_batches: 0
+  # limit_val_batches: 0
+  # micro_batch_size: 2
+  # train_steps: 484
+
+  # NOTE: if dp=2, then batch_accumulation_per_replica=15
+  batch_accumulation_per_replica: 30 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 16 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 2
+  train_steps: 589
+
+  sequence_length: 32768
+  val_check_interval: -1
+
+
+# data:
+#   dataset:
+#     dataloader_type: single
+#     dataset_max_tokens: null
+#     dataset_weights:
+#     - 0.3
+#     - 0.3
+#     - 0.15
+#     - 0.15
+#     - 0.08
+#     - 0.02
+#     datasets:
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+#       dtype: uint32
+#       skip_tokens: 0
+#     pad_samples_to_global_batch_size: false
+#     skip_in_stream: true
+#   num_loading_workers: 0
+#   seed: 42
+
+data_stages:
+  - name: Finetune Needle
+    start_training_step: 1
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        # hf_dataset_or_datasets: nanotron/needle_in_a_hay_stack_finetune_dataset
+        hf_dataset_or_datasets: nanotron/needle_32k_finetuning_dataset
+        hf_dataset_splits: train
+        text_column_name: prompt
+      num_loading_workers: 1
+      seed: 42
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+# s3_upload:
+#   remove_after_upload: true
+#   s5cmd_concurrency: 5
+#   s5cmd_numworkers: 16
+#   upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp19_1b_llama2_32k_ctx_length_finetune_needle/
+
+# experiment_logger:
+#   tensorboard_logger:
+#     flush_secs: 30
+#     tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+#   wandb_logger:
+#     wandb_entity: null
+#     wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp20/exp20_1b_llama2_32k_ctx_length_and_2k_seglen_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp20/exp20_1b_llama2_32k_ctx_length_and_2k_seglen_and_2m_bs.yaml
new file mode 100644
index 00000000..0e63dd91
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp20/exp20_1b_llama2_32k_ctx_length_and_2k_seglen_and_2m_bs.yaml
@@ -0,0 +1,245 @@
+checkpoints:
+  checkpoint_interval: 5000
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp20_1b_llama2_32k_ctx_length_and_2k_seglen_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  # resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp20_1b_llama2_32k_ctx_length_and_2k_seglen_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp20_1b_llama2_32k_ctx_length_and_2k_seglen_and_2m_bs_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.03125 # 1/sqrt(1024)=0.03125
+    std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 2048
+    intermediate_size: 8192
+    num_hidden_layers: 4
+
+    is_llama_config: true
+    max_position_embeddings: 2048
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 18000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 4
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 2 * 4 * 32768 * 8 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 4
+  # n_segments = 20
+  # 2048 * 20 = 40960
+  # 8192*14
+  # # 1024*100 = 102400
+  # 8192 * 14 = 114688
+  # 4096 * 16 = 65536
+  # 2048*16 = 32768
+  sequence_length: 32768
+  train_steps: 90_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp20_1b_llama2_32k_ctx_length_and_2k_seglen_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp20/exp20_1b_llama2_32k_ctx_length_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp20/exp20_1b_llama2_32k_ctx_length_and_2m_bs.yaml
new file mode 100644
index 00000000..88e5d507
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp20/exp20_1b_llama2_32k_ctx_length_and_2m_bs.yaml
@@ -0,0 +1,268 @@
+checkpoints:
+  checkpoint_interval: 5000
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp20_1b_llama2_32k_ctx_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  # resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  # resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp20_1b_llama2_32k_ctx_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp20_1b_llama2_32k_ctx_length_and_2m_bs
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.03125 # 1/sqrt(1024)=0.03125
+    std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 2048
+    intermediate_size: 8192
+    # num_hidden_layers: 14
+    num_hidden_layers: 4
+
+    is_llama_config: true
+    max_position_embeddings: 2048
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.000015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 18000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  # dp: 16
+  dp: 1
+  tp: 4
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  # NOTE: this is for big dp
+  # batch_accumulation_per_replica: 2 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 16 = 655,360
+
+  # NOTE: not megatron sp
+  batch_accumulation_per_replica: 8 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 16 = 655,360
+  micro_batch_size: 4
+  sequence_length: 32768
+  train_steps: 170
+
+  # batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 16 = 655,360
+  # micro_batch_size: 16 # 16
+  # sequence_length: 1024
+  # # train_steps: 447
+  # train_steps: 10_000
+
+
+  limit_test_batches: 0
+  limit_val_batches: 0
+  val_check_interval: -1
+
+
+data_stages:
+  - name: Stable Training Stage
+    start_training_step: 1
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: roneneldan/TinyStories
+        hf_dataset_splits: train
+        text_column_name: text
+      num_loading_workers: 1
+      seed: 42
+
+# data:
+#   dataset:
+#     dataloader_type: single
+#     dataset_max_tokens: null
+#     # dataset_weights:
+#     # - 0.6
+#     # - 0.2
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     datasets:
+#     # - filename_pattern: .*/tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/fineweb/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack_full/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/c4/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/arxiv/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/synthetic-data/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack-pull-requests/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/open-web-math/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack-issues/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stackoverflow/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/wikipedia/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/project-gutenberg/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/deepmind-math/
+#     #   skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-documentation/
+#       skip_tokens: 0
+#     pad_samples_to_global_batch_size: false
+#     skip_in_stream: true
+#   num_loading_workers: 0
+#   seed: 42
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+# s3_upload:
+#   remove_after_upload: true
+#   s5cmd_concurrency: 5
+#   s5cmd_numworkers: 16
+#   upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp20_1b_llama2_32k_ctx_length_and_2m_bs/
+
+# experiment_logger:
+#   tensorboard_logger:
+#     flush_secs: 30
+#     tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+#   wandb_logger:
+#     wandb_entity: null
+#     wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp20/exp20_32k_context_and_2k_segment_length_and_finetune.yaml b/examples/infinite-context-length/configs/exp20/exp20_32k_context_and_2k_segment_length_and_finetune.yaml
new file mode 100644
index 00000000..77eae9c4
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp20/exp20_32k_context_and_2k_segment_length_and_finetune.yaml
@@ -0,0 +1,184 @@
+checkpoints:
+  checkpoint_interval: 275
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp20_32k_context_and_2k_segment_length_and_finetune/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp20_1b_llama2_32k_ctx_length_and_2k_seglen_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp20_32k_context_and_2k_segment_length_and_finetune
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.03125 # 1/sqrt(1024)=0.03125
+    std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 2048
+    intermediate_size: 8192
+    num_hidden_layers: 4
+
+    is_llama_config: true
+    max_position_embeddings: 2048
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.0001 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 110 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-06
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 4
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 2 * 4 * 32768 * 8 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 4
+  # n_segments = 20
+  # 2048 * 20 = 40960
+  # 8192*14
+  # # 1024*100 = 102400
+  # 8192 * 14 = 114688
+  # 4096 * 16 = 65536
+  # 2048*16 = 32768
+  sequence_length: 32768
+  train_steps: 550 # 34428 / 8 = 4300
+  # train_steps: 100 # 34428 / 8 = 4300
+  val_check_interval: -1
+
+data_stages:
+  - name: Finetune Needle
+    start_training_step: 1
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: nanotron/needle_32k_finetuning_dataset
+        hf_dataset_splits: train
+        text_column_name: prompt
+      num_loading_workers: 1
+      seed: 42
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+# s3_upload:
+#   remove_after_upload: true
+#   s5cmd_concurrency: 5
+#   s5cmd_numworkers: 16
+#   upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp20_1b_llama2_32k_ctx_length_and_2k_seglen_and_2m_bs/
+
+# experiment_logger:
+#   tensorboard_logger:
+#     flush_secs: 30
+#     tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+#   wandb_logger:
+#     wandb_entity: null
+#     wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp20/test_train.yaml b/examples/infinite-context-length/configs/exp20/test_train.yaml
new file mode 100644
index 00000000..6148e9c5
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp20/test_train.yaml
@@ -0,0 +1,258 @@
+checkpoints:
+  checkpoint_interval: 5000
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp20_1b_llama2_32k_ctx_length_and_2k_seglen_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  # resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  # resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp20_1b_llama2_32k_ctx_length_and_2k_seglen_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp20_1b_llama2_32k_ctx_length_and_2k_seglen_and_2m_bs_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.03125 # 1/sqrt(1024)=0.03125
+    std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 2048
+    intermediate_size: 8192
+    num_hidden_layers: 4
+
+    is_llama_config: true
+    max_position_embeddings: 1024
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 18000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 1
+  tp: 2
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 16 * 4096 * 32 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 16
+  # n_segments = 20
+  # 2048 * 20 = 40960
+  # 8192*14
+  # # 1024*100 = 102400
+  # 8192 * 14 = 114688
+  # 4096 * 16 = 65536
+  # 2048*16 = 32768
+  sequence_length: 4096
+  train_steps: 100
+  val_check_interval: -1
+
+
+# data:
+#   dataset:
+#     dataloader_type: single
+#     dataset_max_tokens: null
+#     dataset_weights:
+#     - 0.6
+#     - 0.2
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     datasets:
+#     - filename_pattern: .*/tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/fineweb/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack_full/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/c4/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/arxiv/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/synthetic-data/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-pull-requests/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/open-web-math/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-issues/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stackoverflow/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/wikipedia/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/project-gutenberg/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/deepmind-math/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-documentation/
+#       skip_tokens: 0
+#     pad_samples_to_global_batch_size: false
+#     skip_in_stream: true
+#   num_loading_workers: 0
+#   seed: 42
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+data_stages:
+  - name: Stable Training Stage
+    start_training_step: 1
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: roneneldan/TinyStories
+        hf_dataset_splits: train
+        text_column_name: text
+      num_loading_workers: 1
+      seed: 42
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+# s3_upload:
+#   remove_after_upload: true
+#   s5cmd_concurrency: 5
+#   s5cmd_numworkers: 16
+#   upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp20_1b_llama2_32k_ctx_length_and_2k_seglen_and_2m_bs/
+
+# experiment_logger:
+#   tensorboard_logger:
+#     flush_secs: 30
+#     tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+#   wandb_logger:
+#     wandb_entity: null
+#     wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp21/exp21_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp21/exp21_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs.yaml
new file mode 100644
index 00000000..e5aa8225
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp21/exp21_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs.yaml
@@ -0,0 +1,227 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp21_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp21_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp21_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs_and_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.03125 # 1/sqrt(1024)=0.03125
+    std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 2048
+    intermediate_size: 8192
+    num_hidden_layers: 4
+
+    is_llama_config: true
+    max_position_embeddings: 1024
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 18000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 32
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 16 * 4096 * 32 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 16
+  sequence_length: 4096
+  train_steps: 90_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp21_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp22/exp22_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp22/exp22_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs.yaml
new file mode 100644
index 00000000..f749fd33
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp22/exp22_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs.yaml
@@ -0,0 +1,227 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp22_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp22_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp22_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs_and_lr_0.00010
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.03125 # 1/sqrt(1024)=0.03125
+    std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 2048
+    intermediate_size: 8192
+    num_hidden_layers: 14
+
+    is_llama_config: true
+    max_position_embeddings: 1024
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00010 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 18000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 32
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 14 * 4096 * 32 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 14
+  sequence_length: 4096
+  train_steps: 90_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp22_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp23/exp23_200m_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp23/exp23_200m_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs.yaml
new file mode 100644
index 00000000..245e63d1
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp23/exp23_200m_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs.yaml
@@ -0,0 +1,227 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp23_200m_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp23_200m_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp23_200m_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs_and_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.03125 # 1/sqrt(1024)=0.03125
+    std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 2048
+    intermediate_size: 8192
+    num_hidden_layers: 8
+
+    is_llama_config: true
+    max_position_embeddings: 1024
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00010 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 18000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 2
+  tp: 1
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 14 * 4096 * 32 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 14
+  sequence_length: 4096
+  train_steps: 90_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp23_200m_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp24/exp24_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs_and_orig_doremi_lr.yaml b/examples/infinite-context-length/configs/exp24/exp24_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs_and_orig_doremi_lr.yaml
new file mode 100644
index 00000000..540aee89
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp24/exp24_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs_and_orig_doremi_lr.yaml
@@ -0,0 +1,227 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp24_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs_and_orig_doremi_lr/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp24_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs_and_orig_doremi_lr/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp24_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs_and_orig_doremi_lr
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.03125 # 1/sqrt(1024)=0.03125
+    std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 2048
+    intermediate_size: 8192
+    num_hidden_layers: 14
+
+    is_llama_config: true
+    max_position_embeddings: 1024
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 18000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 32
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 14 * 4096 * 32 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 14
+  sequence_length: 4096
+  train_steps: 90_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp24_1b_llama2_4k_ctx_length_and_1k_seglen_and_2m_bs_and_orig_doremi_lr/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp25/config.yaml b/examples/infinite-context-length/configs/exp25/config.yaml
new file mode 100644
index 00000000..4a4dbd8d
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp25/config.yaml
@@ -0,0 +1,245 @@
+checkpoints:
+  checkpoint_interval: 5000
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp18_1b_llama2_100k_ctx_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  # resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp18_1b_llama2_100k_ctx_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp18_8b_llama3_8k_ctx_length_and_lr_1.0e-6
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.03125 # 1/sqrt(1024)=0.03125
+    std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 2048
+    intermediate_size: 8192
+    num_hidden_layers: 14
+
+    is_llama_config: true
+    max_position_embeddings: 32768
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 600 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 8
+  tp: 4
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 4 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 16 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 2
+  # n_segments = 20
+  # 2048 * 20 = 40960
+  # 8192*14
+  # # 1024*100 = 102400
+  # 8192 * 14 = 114688
+  # 4096 * 16 = 65536
+  # 2048*16 = 32768
+  sequence_length: 32768
+  train_steps: 30_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp18_1b_llama2_100k_ctx_length_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp26/exp26_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp26/exp26_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs.yaml
new file mode 100644
index 00000000..874d6210
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp26/exp26_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs.yaml
@@ -0,0 +1,230 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp26_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp26_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp26_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs_and_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+infini_attention:
+  segment_length: 256
+  turn_on_memory: false
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 1024
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 14000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 128
+  sequence_length: 1024
+  train_steps: 70_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp26_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp27/exp27_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp27/exp27_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs.yaml
new file mode 100644
index 00000000..785c56d3
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp27/exp27_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs.yaml
@@ -0,0 +1,230 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp27_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp27_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp27_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs_and_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+infini_attention:
+  segment_length: 256
+  turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 1024
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 14000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 128
+  sequence_length: 1024
+  train_steps: 70_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp27_200m_llama2_1k_ctx_length_and_256_seglen_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp28/exp28_ref_200m_llama2_256_ctx_length_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp28/exp28_ref_200m_llama2_256_ctx_length_and_2m_bs.yaml
new file mode 100644
index 00000000..54593b01
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp28/exp28_ref_200m_llama2_256_ctx_length_and_2m_bs.yaml
@@ -0,0 +1,236 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp28_ref_200m_llama2_256_ctx_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp28_ref_200m_llama2_256_ctx_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp28_ref_200m_llama2_256_ctx_length_and_2m_bs_and_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 256
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 14000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 512
+  sequence_length: 256
+  train_steps: 10_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp28_ref_200m_llama2_256_ctx_length_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp29/exp29_200m_llama2_256_ctx_length_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp29/exp29_200m_llama2_256_ctx_length_and_2m_bs.yaml
new file mode 100644
index 00000000..1e05d90f
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp29/exp29_200m_llama2_256_ctx_length_and_2m_bs.yaml
@@ -0,0 +1,240 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp29_200m_llama2_256_ctx_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp29_200m_llama2_256_ctx_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp29_200m_llama2_256_ctx_length_and_2m_bs_and_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 256
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 14000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 512
+  sequence_length: 256
+  train_steps: 10_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp29_200m_llama2_256_ctx_length_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 256
+  turn_on_memory: false
diff --git a/examples/infinite-context-length/configs/exp29/main.yaml b/examples/infinite-context-length/configs/exp29/main.yaml
new file mode 100644
index 00000000..70b4e9f5
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp29/main.yaml
@@ -0,0 +1,219 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp29_200m_llama2_256_ctx_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp29_200m_llama2_256_ctx_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp29_200m_llama2_256_ctx_length_and_2m_bs_and_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 256
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 14000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  # dp: 20
+  dp: 1
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  # micro_batch_size: 512
+  micro_batch_size: 2
+  sequence_length: 256
+  # train_steps: 10_000
+  train_steps: 1
+  val_check_interval: -1
+
+
+# data:
+#   dataset:
+#     dataloader_type: single
+#     dataset_max_tokens: null
+#     # dataset_weights:
+#     # - 0.6
+#     # - 0.2
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     datasets:
+#     # - filename_pattern: .*/tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/fineweb/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack_full/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/c4/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/arxiv/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/synthetic-data/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack-pull-requests/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/open-web-math/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack-issues/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stackoverflow/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/wikipedia/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/project-gutenberg/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/deepmind-math/
+#     #   skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-documentation/
+#       skip_tokens: 0
+#     pad_samples_to_global_batch_size: false
+#     skip_in_stream: true
+#   num_loading_workers: 0
+#   seed: 42
+
+data_stages:
+  - name: Stable Training Stage
+    start_training_step: 1
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: roneneldan/TinyStories
+        hf_dataset_splits: train
+        text_column_name: text
+      num_loading_workers: 1
+      seed: 42
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+# s3_upload:
+#   remove_after_upload: true
+#   s5cmd_concurrency: 5
+#   s5cmd_numworkers: 16
+#   upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp29_200m_llama2_256_ctx_length_and_2m_bs/
+
+# experiment_logger:
+#   tensorboard_logger:
+#     flush_secs: 30
+#     tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+#   wandb_logger:
+#     wandb_entity: null
+#     wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 256
+  turn_on_memory: false
diff --git a/examples/infinite-context-length/configs/exp29/ref.yaml b/examples/infinite-context-length/configs/exp29/ref.yaml
new file mode 100644
index 00000000..ab6ef7e8
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp29/ref.yaml
@@ -0,0 +1,219 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp29_200m_llama2_256_ctx_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  # resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp29_200m_llama2_256_ctx_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp29_200m_llama2_256_ctx_length_and_2m_bs_and_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 256
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 14000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  # dp: 20
+  dp: 1
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  # micro_batch_size: 512
+  micro_batch_size: 2
+  sequence_length: 256
+  # train_steps: 10_000
+  train_steps: 1
+  val_check_interval: -1
+
+
+# data:
+#   dataset:
+#     dataloader_type: single
+#     dataset_max_tokens: null
+#     # dataset_weights:
+#     # - 0.6
+#     # - 0.2
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     # - 0.1
+#     datasets:
+#     # - filename_pattern: .*/tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/fineweb/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack_full/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/c4/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/arxiv/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/synthetic-data/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack-pull-requests/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/open-web-math/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stack-issues/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/stackoverflow/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/wikipedia/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/project-gutenberg/
+#     #   skip_tokens: 0
+#     # - filename_pattern: tokenized-v1/standard/.*.ds
+#     #   folder: s3://huggingface-llm-datasets/deepmind-math/
+#     #   skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-documentation/
+#       skip_tokens: 0
+#     pad_samples_to_global_batch_size: false
+#     skip_in_stream: true
+#   num_loading_workers: 0
+#   seed: 42
+
+data_stages:
+  - name: Stable Training Stage
+    start_training_step: 1
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: roneneldan/TinyStories
+        hf_dataset_splits: train
+        text_column_name: text
+      num_loading_workers: 1
+      seed: 42
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+# s3_upload:
+#   remove_after_upload: true
+#   s5cmd_concurrency: 5
+#   s5cmd_numworkers: 16
+#   upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp29_200m_llama2_256_ctx_length_and_2m_bs/
+
+# experiment_logger:
+#   tensorboard_logger:
+#     flush_secs: 30
+#     tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+#   wandb_logger:
+#     wandb_entity: null
+#     wandb_project: infini_attention_8b_llama
+
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: false
diff --git a/examples/infinite-context-length/configs/exp30/exp30_ref_200m_llama2_256_ctx_length_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp30/exp30_ref_200m_llama2_256_ctx_length_and_2m_bs.yaml
new file mode 100644
index 00000000..c84bd38b
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp30/exp30_ref_200m_llama2_256_ctx_length_and_2m_bs.yaml
@@ -0,0 +1,236 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp30_ref_200m_llama2_256_ctx_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp30_ref_200m_llama2_256_ctx_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp30_ref_200m_llama2_256_ctx_length_and_2m_bs_and_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 256
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 14000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 512
+  sequence_length: 256
+  train_steps: 10_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp30_ref_200m_llama2_256_ctx_length_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp31/exp31_200m_llama2_256_ctx_length_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp31/exp31_200m_llama2_256_ctx_length_and_2m_bs.yaml
new file mode 100644
index 00000000..114b6e08
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp31/exp31_200m_llama2_256_ctx_length_and_2m_bs.yaml
@@ -0,0 +1,240 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp31_200m_llama2_256_ctx_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp31_200m_llama2_256_ctx_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp31_200m_llama2_256_ctx_length_and_2m_bs_and_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 256
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 14000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 512
+  sequence_length: 256
+  train_steps: 10_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp31_200m_llama2_256_ctx_length_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 256
+  turn_on_memory: false
diff --git a/examples/infinite-context-length/configs/exp32/exp32_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp32/exp32_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs.yaml
new file mode 100644
index 00000000..e2427c41
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp32/exp32_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs.yaml
@@ -0,0 +1,240 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp32_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp32_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp32_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 256
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 14000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 512
+  sequence_length: 256
+  train_steps: 35000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp32_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
diff --git a/examples/infinite-context-length/configs/exp33/debug_config.yaml b/examples/infinite-context-length/configs/exp33/debug_config.yaml
new file mode 100644
index 00000000..93d015e7
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp33/debug_config.yaml
@@ -0,0 +1,265 @@
+checkpoints:
+  checkpoint_interval: 10
+  # checkpoints_path: /fsx/phuc/projects/nanotron/checkpoints/exp33_debug_amplify_gradient_and_lr_0.00015
+  checkpoints_path: /fsx/phuc/projects/nanotron/checkpoints/exp33_debug_ref_200m_and_lr_0.00015_and_warmup_50_steps
+  checkpoints_path_is_shared_file_system: false
+  # resume_checkpoint_path: /fsx/phuc/projects/nanotron/checkpoints/exp33_debug
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp33_debug_ref_200m_and_lr_0.00015_and_warmup_50_steps
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.25 # 1/sqrt(16)=0.25
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 10
+
+    # hidden_size: 16
+    # intermediate_size: 64
+    # num_hidden_layers: 2
+
+    is_llama_config: true
+    max_position_embeddings: 16
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 50 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+
+  # adam_beta1: 0.9
+  # adam_beta2: 0.95
+  # adam_eps: 1.0e-08
+  # torch_adam_is_fused: true
+
+  optimizer_factory:
+    adam_beta1: 0.9
+    adam_beta2: 0.95
+    adam_eps: 1.0e-08
+    name: adamW
+    torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 1
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 4
+  sequence_length: 16
+  train_steps: 3000
+  val_check_interval: -1
+
+
+data_stages:
+  - name: Needle Finetuning, Epoch 1
+    start_training_step: 1
+    data:
+      # dataset:
+      #   dataset_overwrite_cache: false
+      #   dataset_processing_num_proc_per_process: 1
+      #   hf_dataset_config_name: null
+      #   hf_dataset_or_datasets: nanotron/llama3-16k-passkey-retrieval-finetuning
+      #   hf_dataset_splits: train
+      #   text_column_name: prompt
+      # num_loading_workers: 1
+      # seed: 42
+
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: stas/openwebtext-10k
+        hf_dataset_splits: train
+        text_column_name: text
+      num_loading_workers: 1
+      seed: 42
+
+# data:
+#   dataset:
+#     dataloader_type: single
+#     dataset_max_tokens: null
+#     dataset_weights:
+#     - 0.6
+#     - 0.2
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     datasets:
+#     - filename_pattern: .*/tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/fineweb/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack_full/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/c4/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/arxiv/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/synthetic-data/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-pull-requests/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/open-web-math/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-issues/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stackoverflow/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/wikipedia/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/project-gutenberg/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/deepmind-math/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-documentation/
+#       skip_tokens: 0
+#     pad_samples_to_global_batch_size: false
+#     skip_in_stream: true
+#   num_loading_workers: 0
+#   seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+# s3_upload:
+#   remove_after_upload: true
+#   s5cmd_concurrency: 5
+#   s5cmd_numworkers: 16
+#   upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp33_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/
+
+# experiment_logger:
+#   tensorboard_logger:
+#     flush_secs: 30
+#     tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+#   wandb_logger:
+#     wandb_entity: null
+#     wandb_project: infini_attention_8b_llama
+
+# infini_attention:
+#   segment_length: 4
+#   turn_on_memory: true
diff --git a/examples/infinite-context-length/configs/exp33/exp33_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp33/exp33_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs.yaml
new file mode 100644
index 00000000..a8c36b1c
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp33/exp33_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs.yaml
@@ -0,0 +1,240 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp33_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp33_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp33_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 256
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 14000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 512
+  sequence_length: 256
+  train_steps: 35000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp33_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
diff --git a/examples/infinite-context-length/configs/exp33/exp33_debug_with_no_warmup.yaml b/examples/infinite-context-length/configs/exp33/exp33_debug_with_no_warmup.yaml
new file mode 100644
index 00000000..13d6c718
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp33/exp33_debug_with_no_warmup.yaml
@@ -0,0 +1,265 @@
+checkpoints:
+  checkpoint_interval: 10000
+  # checkpoints_path: /fsx/phuc/projects/nanotron/checkpoints/exp33_debug_amplify_gradient_and_lr_0.00015
+  checkpoints_path: /fsx/phuc/projects/nanotron/checkpoints/exp33_debug_ref_200m_and_lr_0.00015_and_warmup_50_steps
+  checkpoints_path_is_shared_file_system: false
+  # resume_checkpoint_path: /fsx/phuc/projects/nanotron/checkpoints/exp33_debug
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp33_debug_original_sigmoid_and_lr_0.00015_and_no_warmup
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.25 # 1/sqrt(16)=0.25
+    # std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 16
+    intermediate_size: 64
+    num_hidden_layers: 2
+
+    is_llama_config: true
+    max_position_embeddings: 16
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 50 # 10% warm up of total training steps
+    lr_warmup_style: constant
+    min_decay_lr: 1.0e-05
+
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 1
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 4
+  sequence_length: 16
+  train_steps: 3000
+  val_check_interval: -1
+
+
+data_stages:
+  - name: Needle Finetuning, Epoch 1
+    start_training_step: 1
+    data:
+      # dataset:
+      #   dataset_overwrite_cache: false
+      #   dataset_processing_num_proc_per_process: 1
+      #   hf_dataset_config_name: null
+      #   hf_dataset_or_datasets: nanotron/llama3-16k-passkey-retrieval-finetuning
+      #   hf_dataset_splits: train
+      #   text_column_name: prompt
+      # num_loading_workers: 1
+      # seed: 42
+
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: stas/openwebtext-10k
+        hf_dataset_splits: train
+        text_column_name: text
+      num_loading_workers: 1
+      seed: 42
+
+# data:
+#   dataset:
+#     dataloader_type: single
+#     dataset_max_tokens: null
+#     dataset_weights:
+#     - 0.6
+#     - 0.2
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     datasets:
+#     - filename_pattern: .*/tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/fineweb/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack_full/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/c4/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/arxiv/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/synthetic-data/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-pull-requests/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/open-web-math/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-issues/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stackoverflow/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/wikipedia/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/project-gutenberg/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/deepmind-math/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-documentation/
+#       skip_tokens: 0
+#     pad_samples_to_global_batch_size: false
+#     skip_in_stream: true
+#   num_loading_workers: 0
+#   seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+# s3_upload:
+#   remove_after_upload: true
+#   s5cmd_concurrency: 5
+#   s5cmd_numworkers: 16
+#   upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp33_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/
+
+# experiment_logger:
+#   tensorboard_logger:
+#     flush_secs: 30
+#     tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+#   wandb_logger:
+#     wandb_entity: null
+#     wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 4
+  turn_on_memory: true
diff --git a/examples/infinite-context-length/configs/exp34/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp34/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs.yaml
new file mode 100644
index 00000000..930ab625
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp34/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs.yaml
@@ -0,0 +1,171 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: true
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_lr_2.0e-5
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    path: /fsx/phuc/projects/infini-attention/llama3-ckps/haojun-8b-llama-nanotron-ckp/NanotronLlama3-8B
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_interleaved: false
+    rope_scaling: null
+    rope_theta: 500000.0
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+
+  # NOTE: old
+  # learning_rate_scheduler:
+  #   learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+  #   lr_decay_starting_step: null
+  #   lr_decay_steps: null
+  #   lr_decay_style: cosine
+  #   lr_warmup_steps: 14000 # 10% warm up of total training steps
+  #   lr_warmup_style: linear
+  #   min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+
+  learning_rate_scheduler:
+    learning_rate: 1.0e-5
+    lr_decay_starting_step: null
+    lr_decay_steps: 16000
+    lr_decay_style: cosine
+    lr_warmup_steps: 4000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-6
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 4
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: /fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 8 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 8 * 1 * 16384 * 16 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  # sequence_length: 32768
+  sequence_length: 16384 # 8192 x 2 = 16384
+  train_steps: 20_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.3
+    - 0.3
+    - 0.45
+    - 0.15
+    - 0.08
+    - 0.02
+    datasets:
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 8192
+  turn_on_memory: true
diff --git a/examples/infinite-context-length/configs/exp34/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_SlimPajama_per_source_upsampling_long_samples.yaml b/examples/infinite-context-length/configs/exp34/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_SlimPajama_per_source_upsampling_long_samples.yaml
new file mode 100644
index 00000000..2a4ece60
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp34/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_SlimPajama_per_source_upsampling_long_samples.yaml
@@ -0,0 +1,187 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_SlimPajama_per_source_upsampling_long_samples/checkpoints
+  checkpoints_path_is_shared_file_system: true
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_SlimPajama_per_source_upsampling_long_samples/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_SlimPajama_per_source_upsampling_long_samples_and_lr_1.0e-5
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    path: /fsx/phuc/projects/infini-attention/llama3-ckps/haojun-8b-llama-nanotron-ckp/NanotronLlama3-8B
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_interleaved: false
+    rope_scaling: null
+    rope_theta: 500000.0
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+
+  # NOTE: old
+  # learning_rate_scheduler:
+  #   learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+  #   lr_decay_starting_step: null
+  #   lr_decay_steps: null
+  #   lr_decay_style: cosine
+  #   lr_warmup_steps: 14000 # 10% warm up of total training steps
+  #   lr_warmup_style: linear
+  #   min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+
+  learning_rate_scheduler:
+    learning_rate: 1.0e-5
+    lr_decay_starting_step: null
+    lr_decay_steps: 16000
+    lr_decay_style: cosine
+    lr_warmup_steps: 4000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-6
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  # dp: 16
+  dp: 1
+  tp: 4
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: /fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 8 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 8 * 1 * 16384 * 16 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  # sequence_length: 32768
+  sequence_length: 16384 # 8192 x 2 = 16384
+  train_steps: 222
+  val_check_interval: -1
+
+data:
+  dataset:
+    dataloader_type: cyclic
+    dataset_max_tokens: null
+    dataset_weights: null
+    datasets:
+    - filename_pattern: '.*\.ds'
+      folder: /fsx/haojun/datasets/tokenized_bytes_4B_tokens
+      # seed: null
+      # shuffle: false
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+# data:
+#   dataset:
+#     dataloader_type: single
+#     dataset_max_tokens: null
+#     dataset_weights:
+#     - 0.3
+#     - 0.3
+#     - 0.45
+#     - 0.15
+#     - 0.08
+#     - 0.02
+#     datasets:
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+#       dtype: uint32
+#       skip_tokens: 0
+#     pad_samples_to_global_batch_size: false
+#     skip_in_stream: true
+#   num_loading_workers: 0
+#   seed: 42
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_SlimPajama_per_source_upsampling_long_samples/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 8192
+  turn_on_memory: true
diff --git a/examples/infinite-context-length/configs/exp34/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_needle_task.yaml b/examples/infinite-context-length/configs/exp34/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_needle_task.yaml
new file mode 100644
index 00000000..b1af67a6
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp34/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_needle_task.yaml
@@ -0,0 +1,171 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_needle_task/checkpoints
+  checkpoints_path_is_shared_file_system: true
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_needle_task/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_finetuning_needle_task_and_lr_2.0e-5
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    path: /fsx/phuc/projects/infini-attention/llama3-ckps/haojun-8b-llama-nanotron-ckp/NanotronLlama3-8B
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_interleaved: false
+    rope_scaling: null
+    rope_theta: 500000.0
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+
+  # NOTE: old
+  # learning_rate_scheduler:
+  #   learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+  #   lr_decay_starting_step: null
+  #   lr_decay_steps: null
+  #   lr_decay_style: cosine
+  #   lr_warmup_steps: 14000 # 10% warm up of total training steps
+  #   lr_warmup_style: linear
+  #   min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+
+  learning_rate_scheduler:
+    learning_rate: 1.0e-5
+    lr_decay_starting_step: null
+    lr_decay_steps: 16000
+    lr_decay_style: cosine
+    lr_warmup_steps: 4000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-6
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 4
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: /fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 8 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 8 * 1 * 16384 * 16 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  # sequence_length: 32768
+  sequence_length: 16384 # 8192 x 2 = 16384
+  train_steps: 20_000
+  val_check_interval: -1
+
+
+# data:
+#   dataset:
+#     dataloader_type: single
+#     dataset_max_tokens: null
+#     dataset_weights:
+#     - 0.3
+#     - 0.3
+#     - 0.45
+#     - 0.15
+#     - 0.08
+#     - 0.02
+#     datasets:
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+#       dtype: uint32
+#       skip_tokens: 0
+#     pad_samples_to_global_batch_size: false
+#     skip_in_stream: true
+#   num_loading_workers: 0
+#   seed: 42
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+# s3_upload:
+#   remove_after_upload: true
+#   s5cmd_concurrency: 5
+#   s5cmd_numworkers: 16
+#   upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp34_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs/
+
+# experiment_logger:
+#   tensorboard_logger:
+#     flush_secs: 30
+#     tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+#   wandb_logger:
+#     wandb_entity: null
+#     wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 8192
+  turn_on_memory: true
diff --git a/examples/infinite-context-length/configs/exp35/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp35/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs.yaml
new file mode 100644
index 00000000..7cfc5270
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp35/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs.yaml
@@ -0,0 +1,170 @@
+checkpoints:
+  checkpoint_interval: 1500
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: true
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_lr_2.0e-5
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    path: /fsx/phuc/projects/infini-attention/llama3-ckps/haojun-8b-llama-nanotron-ckp/NanotronLlama3-8B
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_interleaved: false
+    rope_scaling: null
+    rope_theta: 500000.0
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+
+  # NOTE: old
+  # learning_rate_scheduler:
+  #   learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+  #   lr_decay_starting_step: null
+  #   lr_decay_steps: null
+  #   lr_decay_style: cosine
+  #   lr_warmup_steps: 14000 # 10% warm up of total training steps
+  #   lr_warmup_style: linear
+  #   min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+
+  learning_rate_scheduler:
+    learning_rate: 1.0e-5
+    lr_decay_starting_step: null
+    lr_decay_steps: 16000
+    lr_decay_style: cosine
+    lr_warmup_steps: 4000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-6
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 32
+  tp: 4
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: /fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 4 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 8 * 1 * 16384 * 16 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  sequence_length: 16384 # 8192 x 2 = 16384
+  train_steps: 20_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.3
+    - 0.3
+    - 0.45
+    - 0.15
+    - 0.08
+    - 0.02
+    datasets:
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 8192
+  turn_on_memory: true
diff --git a/examples/infinite-context-length/configs/exp35/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_needle_finetuning.yaml b/examples/infinite-context-length/configs/exp35/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_needle_finetuning.yaml
new file mode 100644
index 00000000..d12a9765
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp35/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_needle_finetuning.yaml
@@ -0,0 +1,209 @@
+checkpoints:
+  checkpoint_interval: 663
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_needle_finetuning/checkpoints
+  checkpoints_path_is_shared_file_system: true
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_needle_finetuning/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_needle_finetuning_and_lr_1.0e-5
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    # path: /fsx/phuc/projects/infini-attention/llama3-ckps/haojun-8b-llama-nanotron-ckp/NanotronLlama3-8B
+    path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs/checkpoints/19500
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_interleaved: false
+    rope_scaling: null
+    rope_theta: 500000.0
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+
+  # NOTE: old
+  # learning_rate_scheduler:
+  #   learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+  #   lr_decay_starting_step: null
+  #   lr_decay_steps: null
+  #   lr_decay_style: cosine
+  #   lr_warmup_steps: 14000 # 10% warm up of total training steps
+  #   lr_warmup_style: linear
+  #   min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+
+  learning_rate_scheduler:
+    learning_rate: 1.0e-5
+    lr_decay_starting_step: null
+    lr_decay_steps: 3976
+    lr_decay_style: cosine
+    lr_warmup_steps: 1994 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-6
+  weight_decay: 0.01
+  zero_stage: 0
+
+parallelism:
+  dp: 4
+  tp: 4
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: /fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 4 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 8 * 1 * 16384 * 4 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  sequence_length: 16384 # 8192 x 2 = 16384
+  train_steps: 5970 # 1990 per epoch, 1990*3=5970
+  val_check_interval: -1
+
+
+# data:
+#   dataset:
+#     dataloader_type: single
+#     dataset_max_tokens: null
+#     dataset_weights:
+#     - 0.3
+#     - 0.3
+#     - 0.45
+#     - 0.15
+#     - 0.08
+#     - 0.02
+#     datasets:
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+#       dtype: uint32
+#       skip_tokens: 0
+#     - filename_pattern: .*.ds
+#       folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+#       dtype: uint32
+#       skip_tokens: 0
+#     pad_samples_to_global_batch_size: false
+#     skip_in_stream: true
+#   num_loading_workers: 0
+#   seed: 42
+
+data_stages:
+  - name: Needle Finetuning, Epoch 1
+    start_training_step: 1
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: nanotron/llama3-16k-passkey-retrieval-finetuning
+        hf_dataset_splits: train
+        text_column_name: prompt
+      num_loading_workers: 1
+      seed: 42
+  - name: Needle Finetuning, Epoch 2
+    start_training_step: 1991
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: nanotron/llama3-16k-passkey-retrieval-finetuning
+        hf_dataset_splits: train
+        text_column_name: prompt
+      num_loading_workers: 1
+      seed: 42
+  - name: Needle Finetuning, Epoch 3
+    start_training_step: 3981
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: nanotron/llama3-16k-passkey-retrieval-finetuning
+        hf_dataset_splits: train
+        text_column_name: prompt
+      num_loading_workers: 1
+      seed: 42
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+# s3_upload:
+#   remove_after_upload: true
+#   s5cmd_concurrency: 5
+#   s5cmd_numworkers: 16
+#   upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs/
+
+# experiment_logger:
+#   tensorboard_logger:
+#     flush_secs: 30
+#     tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+#   wandb_logger:
+#     wandb_entity: null
+#     wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 8192
+  turn_on_memory: true
diff --git a/examples/infinite-context-length/configs/exp36/exp36_200m_infini_gqa_llama2_256_ctx_length_and_64_segment_length_and_2m_bs.yaml b/examples/infinite-context-length/configs/exp36/exp36_200m_infini_gqa_llama2_256_ctx_length_and_64_segment_length_and_2m_bs.yaml
new file mode 100644
index 00000000..5d059d6d
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp36/exp36_200m_infini_gqa_llama2_256_ctx_length_and_64_segment_length_and_2m_bs.yaml
@@ -0,0 +1,192 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp36_200m_infini_gqa_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp36_200m_infini_gqa_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp36_200m_infini_gqa_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 256
+    num_attention_heads: 8
+    num_key_value_heads: 4
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 14000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 512
+  sequence_length: 256
+  train_steps: 35000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    # dataset_weights:
+    # - 0.6
+    # - 0.2
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    datasets:
+    # - filename_pattern: .*/tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/c4/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/arxiv/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/synthetic-data/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/stack-pull-requests/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/open-web-math/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/stack-issues/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/stackoverflow/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/wikipedia/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/project-gutenberg/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/deepmind-math/
+    #   skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp36_200m_infini_gqa_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
diff --git a/examples/infinite-context-length/configs/exp37/exp37_debug_200b_llama_and_256_ctx_length_and_64_segment_length_and_constant_lr.yaml b/examples/infinite-context-length/configs/exp37/exp37_debug_200b_llama_and_256_ctx_length_and_64_segment_length_and_constant_lr.yaml
new file mode 100644
index 00000000..adfb4825
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp37/exp37_debug_200b_llama_and_256_ctx_length_and_64_segment_length_and_constant_lr.yaml
@@ -0,0 +1,267 @@
+checkpoints:
+  checkpoint_interval: 10000
+  # checkpoints_path: /fsx/phuc/projects/nanotron/checkpoints/exp33_debug_amplify_gradient_and_lr_0.00015
+  checkpoints_path: /fsx/phuc/projects/nanotron/checkpoints/exp33_debug_ref_200m_and_lr_0.00015_and_warmup_50_steps
+  checkpoints_path_is_shared_file_system: false
+  # resume_checkpoint_path: /fsx/phuc/projects/nanotron/checkpoints/exp33_debug
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp37_debug_200b_llama_and_256_ctx_length_and_64_segment_length_and_constant_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    # std: 0.25 # 1/sqrt(16)=0.25
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 10
+
+    # hidden_size: 16
+    # intermediate_size: 64
+    # num_hidden_layers: 2
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    # lr_decay_style: cosine
+    lr_decay_style: linear
+    lr_warmup_steps: 50 # 10% warm up of total training steps
+    lr_warmup_style: constant
+    min_decay_lr: 1.0e-05
+
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 4
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 4
+  sequence_length: 256
+  train_steps: 3000
+  val_check_interval: -1
+
+
+data_stages:
+  - name: Needle Finetuning, Epoch 1
+    start_training_step: 1
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: nanotron/llama3-16k-passkey-retrieval-finetuning
+        hf_dataset_splits: train
+        text_column_name: prompt
+      num_loading_workers: 1
+      seed: 42
+
+      # dataset:
+      #   dataset_overwrite_cache: false
+      #   dataset_processing_num_proc_per_process: 1
+      #   hf_dataset_config_name: null
+      #   hf_dataset_or_datasets: stas/openwebtext-10k
+      #   hf_dataset_splits: train
+      #   text_column_name: text
+      # num_loading_workers: 1
+      # seed: 42
+
+# data:
+#   dataset:
+#     dataloader_type: single
+#     dataset_max_tokens: null
+#     dataset_weights:
+#     - 0.6
+#     - 0.2
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     - 0.1
+#     datasets:
+#     - filename_pattern: .*/tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/fineweb/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack_full/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/c4/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/arxiv/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/synthetic-data/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-pull-requests/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/open-web-math/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-issues/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stackoverflow/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/wikipedia/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/project-gutenberg/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/deepmind-math/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+#       skip_tokens: 0
+#     - filename_pattern: tokenized-v1/standard/.*.ds
+#       folder: s3://huggingface-llm-datasets/stack-documentation/
+#       skip_tokens: 0
+#     pad_samples_to_global_batch_size: false
+#     skip_in_stream: true
+#   num_loading_workers: 0
+#   seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+# s3_upload:
+#   remove_after_upload: true
+#   s5cmd_concurrency: 5
+#   s5cmd_numworkers: 16
+#   upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp33_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/
+
+# experiment_logger:
+#   tensorboard_logger:
+#     flush_secs: 30
+#     tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+#   wandb_logger:
+#     wandb_entity: null
+#     wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.001
diff --git a/examples/infinite-context-length/configs/exp38/exp38_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.001_for_balance_factors.yaml b/examples/infinite-context-length/configs/exp38/exp38_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.001_for_balance_factors.yaml
new file mode 100644
index 00000000..edd155dc
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp38/exp38_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.001_for_balance_factors.yaml
@@ -0,0 +1,241 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp38_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.001_for_balance_factors/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp38_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.001_for_balance_factors/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp38_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.001_for_balance_factors
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 5000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp38_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.001_for_balance_factors/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.001
diff --git a/examples/infinite-context-length/configs/exp38/exp38_debug.yaml b/examples/infinite-context-length/configs/exp38/exp38_debug.yaml
new file mode 100644
index 00000000..969f2e8f
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp38/exp38_debug.yaml
@@ -0,0 +1,241 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp38_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.001_for_balance_factors/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp38_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.001_for_balance_factors/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp38_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.001_for_balance_factors
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 5000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 4
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    # dataset_weights:
+    # - 0.6
+    # - 0.2
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    # - 0.1
+    datasets:
+    # - filename_pattern: .*/tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/c4/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/arxiv/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/synthetic-data/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/stack-pull-requests/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/open-web-math/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/stack-issues/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/stackoverflow/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/wikipedia/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/project-gutenberg/
+    #   skip_tokens: 0
+    # - filename_pattern: tokenized-v1/standard/.*.ds
+    #   folder: s3://huggingface-llm-datasets/deepmind-math/
+    #   skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp38_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.001_for_balance_factors/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.001
diff --git a/examples/infinite-context-length/configs/exp39/exp39_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.002_for_balance_factors.yaml b/examples/infinite-context-length/configs/exp39/exp39_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.002_for_balance_factors.yaml
new file mode 100644
index 00000000..bddd60e1
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp39/exp39_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.002_for_balance_factors.yaml
@@ -0,0 +1,241 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp39_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.002_for_balance_factors/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp39_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.002_for_balance_factors/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp39_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.002_for_balance_factors
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 5000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp39_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.002_for_balance_factors/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.002
diff --git a/examples/infinite-context-length/configs/exp40/exp40_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.0005_for_balance_factors.yaml b/examples/infinite-context-length/configs/exp40/exp40_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.0005_for_balance_factors.yaml
new file mode 100644
index 00000000..760d9bf1
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp40/exp40_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.0005_for_balance_factors.yaml
@@ -0,0 +1,241 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp40_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.0005_for_balance_factors/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp40_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.0005_for_balance_factors/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp40_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.0005_for_balance_factors
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 5000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp40_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.0005_for_balance_factors/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.0005
diff --git a/examples/infinite-context-length/configs/exp41/exp41_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.00025_for_balance_factors.yaml b/examples/infinite-context-length/configs/exp41/exp41_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.00025_for_balance_factors.yaml
new file mode 100644
index 00000000..47f660ca
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp41/exp41_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.00025_for_balance_factors.yaml
@@ -0,0 +1,241 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp41_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.00025_for_balance_factors/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp41_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.00025_for_balance_factors/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp41_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.00025_for_balance_factors
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 5000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp41_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_custom_lr_0.00025_for_balance_factors/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.00025
diff --git a/examples/infinite-context-length/configs/exp43/exp43_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015.yaml b/examples/infinite-context-length/configs/exp43/exp43_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015.yaml
new file mode 100644
index 00000000..8ac3b95d
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp43/exp43_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015.yaml
@@ -0,0 +1,241 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp43_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp43_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp43_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 5000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp43_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.00015
diff --git a/examples/infinite-context-length/configs/exp44/exp44_200m_ref_llama2_256_ctx_length_and_global_lr_0.00015.yaml b/examples/infinite-context-length/configs/exp44/exp44_200m_ref_llama2_256_ctx_length_and_global_lr_0.00015.yaml
new file mode 100644
index 00000000..fb6f06b4
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp44/exp44_200m_ref_llama2_256_ctx_length_and_global_lr_0.00015.yaml
@@ -0,0 +1,236 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp44_200m_ref_llama2_256_ctx_length_and_global_lr_0.00015/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp44_200m_ref_llama2_256_ctx_length_and_global_lr_0.00015/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp44_200m_ref_llama2_256_ctx_length_and_global_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 5000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp44_200m_ref_llama2_256_ctx_length_and_global_lr_0.00015/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp45/exp45_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000075.yaml b/examples/infinite-context-length/configs/exp45/exp45_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000075.yaml
new file mode 100644
index 00000000..a1f13e76
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp45/exp45_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000075.yaml
@@ -0,0 +1,241 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp45_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000075/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp45_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000075/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp45_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000075
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.000075 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 5000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 0.0000075
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp45_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000075/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.000075
diff --git a/examples/infinite-context-length/configs/exp46/exp46_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015_and_10k_warmup.yaml b/examples/infinite-context-length/configs/exp46/exp46_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015_and_10k_warmup.yaml
new file mode 100644
index 00000000..c72a1d48
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp46/exp46_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015_and_10k_warmup.yaml
@@ -0,0 +1,241 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp46_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015_and_10k_warmup/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp46_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015_and_10k_warmup/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp46_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015_and_10k_warmup
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 10000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp46_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00015_and_10k_warmup/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.00015
diff --git a/examples/infinite-context-length/configs/exp48/exp48_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00001875.yaml b/examples/infinite-context-length/configs/exp48/exp48_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00001875.yaml
new file mode 100644
index 00000000..f6248c6f
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp48/exp48_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00001875.yaml
@@ -0,0 +1,241 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp48_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00001875/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp48_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00001875/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp48_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00001875
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00001875 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 5000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 0.000001875
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp48_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.00001875/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.00001875
diff --git a/examples/infinite-context-length/configs/exp49/exp49_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000009375.yaml b/examples/infinite-context-length/configs/exp49/exp49_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000009375.yaml
new file mode 100644
index 00000000..0cf4d5b1
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp49/exp49_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000009375.yaml
@@ -0,0 +1,241 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp49_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000009375/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp49_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000009375/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp49_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000009375
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.000009375 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 5000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 0.0000009375
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp49_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.000009375/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.000009375
diff --git a/examples/infinite-context-length/configs/exp5/exp5_8b_llama3_original_config.yaml b/examples/infinite-context-length/configs/exp5/exp5_8b_llama3_original_config.yaml
new file mode 100644
index 00000000..30de8894
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp5/exp5_8b_llama3_original_config.yaml
@@ -0,0 +1,179 @@
+checkpoints:
+  checkpoint_interval: 250
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp5_8b_llama3_original_config/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/projects/infini-attention/llama3-ckps/8b/nanotron_ckp_tp_agnostic
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp5_8b_llama3_original_config
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.015625
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 1.0e-6
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 4000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-7
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 8
+  tp: 4
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: meta-llama/Meta-Llama-3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 16 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 1 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 2
+  sequence_length: 8192
+  train_steps: 20_000
+  val_check_interval: -1
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    # dataset_weights:
+    # - 0.3
+    # - 0.3
+    # - 0.15
+    # - 0.15
+    # - 0.08
+    # - 0.02
+    datasets:
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+lighteval:
+  batch_size: 16
+  checkpoints_path: null
+  generation: null
+  logging:
+    hub_repo_details: null
+    hub_repo_results: null
+    hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+    local_output_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp5_8b_llama3_original_config//logs
+    push_details_to_hub: null
+    push_results_to_hub: null
+    push_results_to_tensorboard: true
+    tensorboard_metric_prefix: e
+  parallelism:
+    dp: 8
+    pp: 1
+    pp_engine: 1f1b
+    tp: 1
+    tp_linear_async_communication: false
+    tp_mode: ALL_REDUCE
+  slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp5_8b_llama3_original_config/lighteval/slurm_scripts
+  slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp5_8b_llama3_original_config/run_eval.slurm.jinja
+  tasks:
+    custom_tasks: brrr.lighteval.evaluation_tasks
+    dataset_loading_processes: 8
+    max_samples: 1000
+    multichoice_continuations_start_space: null
+    no_multichoice_continuations_start_space: null
+    num_fewshot_seeds: null
+    tasks: early-signal
+  wandb:
+    wandb_project: infini_attention_8b_llama
+    wandb_entity: null
+    wandb_run_name: exp5_8b_llama3_original_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp5_8b_llama3_original_config/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp50/exp50_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00001875.yaml b/examples/infinite-context-length/configs/exp50/exp50_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00001875.yaml
new file mode 100644
index 00000000..9391b3cb
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp50/exp50_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00001875.yaml
@@ -0,0 +1,241 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp50_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00001875/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp50_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00001875/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp50_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00001875
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.0000375 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 5000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 0.00000375
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp50_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00001875/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.00001875
diff --git a/examples/infinite-context-length/configs/exp51/exp51_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00015.yaml b/examples/infinite-context-length/configs/exp51/exp51_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00015.yaml
new file mode 100644
index 00000000..7dd5696e
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp51/exp51_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00015.yaml
@@ -0,0 +1,241 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp51_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00015/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp51_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00015/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp51_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.0000375 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 5000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 0.00000375
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp51_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00015/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.00015
diff --git a/examples/infinite-context-length/configs/exp52/exp52_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_orig_tanh_act_and_randn_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015.yaml b/examples/infinite-context-length/configs/exp52/exp52_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_orig_tanh_act_and_randn_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015.yaml
new file mode 100644
index 00000000..56ec7345
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp52/exp52_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_orig_tanh_act_and_randn_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015.yaml
@@ -0,0 +1,247 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp52_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_orig_tanh_act_and_randn_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp52_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_orig_tanh_act_and_randn_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp52_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_orig_tanh_act_and_randn_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.0000375 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 5000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 0.00000375
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp52_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_orig_tanh_act_and_randn_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.00015
+  balance_act_type: orig_tanh
+  balance_init_type: randn
+  logging: true
+  logging_interval: 2000
+  log_grad: false
+  log_segment_acts: false
diff --git a/examples/infinite-context-length/configs/exp53/exp53_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_hard_sigmoid_act_and_zeros_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015.yaml b/examples/infinite-context-length/configs/exp53/exp53_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_hard_sigmoid_act_and_zeros_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015.yaml
new file mode 100644
index 00000000..e57cc21e
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp53/exp53_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_hard_sigmoid_act_and_zeros_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015.yaml
@@ -0,0 +1,247 @@
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp53_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_hard_sigmoid_act_and_zeros_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp53_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_hard_sigmoid_act_and_zeros_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp53_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_hard_sigmoid_act_and_zeros_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: true
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+    # std: 0.022097086912079608 # 1/sqrt(2048)=0.022097086912079608
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    initializer_range: 0.02
+
+    # NOTE: 250m
+    # hidden_size: 1024
+    # intermediate_size: 4096
+    # num_hidden_layers: 10
+
+    hidden_size: 1024
+    intermediate_size: 4096
+    num_hidden_layers: 6
+
+    is_llama_config: true
+    max_position_embeddings: 64
+    num_attention_heads: 8
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.0000375 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 5000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 0.00000375
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: lvwerra/the-tokenizer-v1
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 128 * 1024 * 20 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 448
+  sequence_length: 256
+  train_steps: 50000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.6
+    - 0.2
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    - 0.1
+    datasets:
+    - filename_pattern: .*/tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/fineweb/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack_full/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/c4/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/arxiv/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/synthetic-data/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-pull-requests/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-jupyter-structured/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/open-web-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-issues/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stackoverflow/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/wikipedia/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/deepmind-math/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-kaggle-scripts/
+      skip_tokens: 0
+    - filename_pattern: tokenized-v1/standard/.*.ds
+      folder: s3://huggingface-llm-datasets/stack-documentation/
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp53_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_hard_sigmoid_act_and_zeros_init_and_global_lr_0.0000375_and_balance_factor_lr_0.00015/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64
+  turn_on_memory: true
+  balance_factor_lr: 0.00015
+  balance_act_type: hard_sigmoid
+  balance_init_type: zeros
+  logging: true
+  logging_interval: 2000
+  log_grad: false
+  log_segment_acts: false
diff --git a/examples/infinite-context-length/configs/exp54/exp54_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.00015.yaml b/examples/infinite-context-length/configs/exp54/exp54_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.00015.yaml
new file mode 100644
index 00000000..e7198925
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp54/exp54_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.00015.yaml
@@ -0,0 +1,176 @@
+checkpoints:
+  checkpoint_interval: 1000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp54_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.00015/checkpoints
+  checkpoints_path_is_shared_file_system: true
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp54_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.00015/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp54_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.00015
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    path: /fsx/phuc/projects/infini-attention/llama3-ckps/haojun-8b-llama-nanotron-ckp/NanotronLlama3-8B
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_interleaved: false
+    rope_scaling: null
+    rope_theta: 500000.0
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+
+  # NOTE: old
+  # learning_rate_scheduler:
+  #   learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+  #   lr_decay_starting_step: null
+  #   lr_decay_steps: null
+  #   lr_decay_style: cosine
+  #   lr_warmup_steps: 14000 # 10% warm up of total training steps
+  #   lr_warmup_style: linear
+  #   min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+
+  learning_rate_scheduler:
+    learning_rate: 1.0e-5
+    lr_decay_starting_step: null
+    lr_decay_steps: 23500
+    lr_decay_style: cosine
+    lr_warmup_steps: 1500 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-6
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 32
+  tp: 4
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: /fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 4 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 8 * 1 * 16384 * 16 = 2m
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  sequence_length: 16384 # 8192 x 2 = 16384
+  train_steps: 25_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.3
+    - 0.3
+    - 0.45
+    - 0.15
+    - 0.08
+    - 0.02
+    datasets:
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp54_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.00015/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 8192
+  turn_on_memory: true
+  balance_factor_lr: 0.00015
+  balance_act_type: orig_sigmoid
+  balance_init_type: zeros
+  logging: true
+  logging_interval: 500
+  log_grad: false
+  log_segment_acts: false
+  # log_balance_factor: true
+  # log_other_weight: false
diff --git a/examples/infinite-context-length/configs/exp55/exp55_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.001.yaml b/examples/infinite-context-length/configs/exp55/exp55_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.001.yaml
new file mode 100644
index 00000000..e8c0afd1
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp55/exp55_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.001.yaml
@@ -0,0 +1,176 @@
+checkpoints:
+  checkpoint_interval: 1000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp55_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.001/checkpoints
+  checkpoints_path_is_shared_file_system: true
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp55_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.001/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp55_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.001
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    path: /fsx/phuc/projects/infini-attention/llama3-ckps/haojun-8b-llama-nanotron-ckp/NanotronLlama3-8B
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_interleaved: false
+    rope_scaling: null
+    rope_theta: 500000.0
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+
+  # NOTE: old
+  # learning_rate_scheduler:
+  #   learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+  #   lr_decay_starting_step: null
+  #   lr_decay_steps: null
+  #   lr_decay_style: cosine
+  #   lr_warmup_steps: 14000 # 10% warm up of total training steps
+  #   lr_warmup_style: linear
+  #   min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+
+  learning_rate_scheduler:
+    learning_rate: 1.0e-5
+    lr_decay_starting_step: null
+    lr_decay_steps: 23500
+    lr_decay_style: cosine
+    lr_warmup_steps: 1500 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-6
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 4
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: /fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 4 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 1 * 16384 * 20 = 1m3
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  sequence_length: 16384 # 8192 x 2 = 16384
+  train_steps: 25_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.3
+    - 0.3
+    - 0.45
+    - 0.15
+    - 0.08
+    - 0.02
+    datasets:
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp55_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.001/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 8192
+  turn_on_memory: true
+  balance_factor_lr: 0.001
+  balance_act_type: orig_sigmoid
+  balance_init_type: zeros
+  logging: true
+  logging_interval: 500
+  log_grad: false
+  log_segment_acts: false
+  # log_balance_factor: true
+  # log_other_weight: false
diff --git a/examples/infinite-context-length/configs/exp56/exp56_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.0025.yaml b/examples/infinite-context-length/configs/exp56/exp56_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.0025.yaml
new file mode 100644
index 00000000..0a55c92a
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp56/exp56_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.0025.yaml
@@ -0,0 +1,176 @@
+checkpoints:
+  checkpoint_interval: 1000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp56_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.0025/checkpoints
+  checkpoints_path_is_shared_file_system: true
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp56_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.0025/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp56_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.0025
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    path: /fsx/phuc/projects/infini-attention/llama3-ckps/haojun-8b-llama-nanotron-ckp/NanotronLlama3-8B
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_interleaved: false
+    rope_scaling: null
+    rope_theta: 500000.0
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+
+  # NOTE: old
+  # learning_rate_scheduler:
+  #   learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+  #   lr_decay_starting_step: null
+  #   lr_decay_steps: null
+  #   lr_decay_style: cosine
+  #   lr_warmup_steps: 14000 # 10% warm up of total training steps
+  #   lr_warmup_style: linear
+  #   min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+
+  learning_rate_scheduler:
+    learning_rate: 1.0e-5
+    lr_decay_starting_step: null
+    lr_decay_steps: 23500
+    lr_decay_style: cosine
+    lr_warmup_steps: 1500 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-6
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 20
+  tp: 4
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: /fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 4 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 1 * 16384 * 20 = 1m3
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  sequence_length: 16384 # 8192 x 2 = 16384
+  train_steps: 25_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.3
+    - 0.3
+    - 0.45
+    - 0.15
+    - 0.08
+    - 0.02
+    datasets:
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp56_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.0025/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 8192
+  turn_on_memory: true
+  balance_factor_lr: 0.0025
+  balance_act_type: orig_sigmoid
+  balance_init_type: zeros
+  logging: true
+  logging_interval: 500
+  log_grad: false
+  log_segment_acts: false
+  # log_balance_factor: true
+  # log_other_weight: false
diff --git a/examples/infinite-context-length/configs/exp57/exp57_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.01_and_balance_factor_0_weight_decay.yaml b/examples/infinite-context-length/configs/exp57/exp57_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.01_and_balance_factor_0_weight_decay.yaml
new file mode 100644
index 00000000..bf00ebcb
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp57/exp57_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.01_and_balance_factor_0_weight_decay.yaml
@@ -0,0 +1,179 @@
+checkpoints:
+  checkpoint_interval: 1000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/exp57_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.01_and_balance_factor_0_weight_decay/checkpoints
+  checkpoints_path_is_shared_file_system: true
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp57_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.01_and_balance_factor_0_weight_decay/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp57_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.01_and_balance_factor_0_weight_decay
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    path: /fsx/phuc/projects/infini-attention/llama3-ckps/haojun-8b-llama-nanotron-ckp/NanotronLlama3-8B
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_interleaved: false
+    rope_scaling: null
+    rope_theta: 500000.0
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+
+  # NOTE: old
+  # learning_rate_scheduler:
+  #   learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+  #   lr_decay_starting_step: null
+  #   lr_decay_steps: null
+  #   lr_decay_style: cosine
+  #   lr_warmup_steps: 14000 # 10% warm up of total training steps
+  #   lr_warmup_style: linear
+  #   min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+
+  learning_rate_scheduler:
+    learning_rate: 1.0e-5
+    lr_decay_starting_step: null
+    lr_decay_steps: 23500
+    lr_decay_style: cosine
+    lr_warmup_steps: 1500 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-6
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 6
+  tp: 4
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: /fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 1 * 16384 * 3 = 49k
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 16
+  sequence_length: 1024 # 8192 x 2 = 16384
+  train_steps: 25_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.3
+    - 0.3
+    - 0.45
+    - 0.15
+    - 0.08
+    - 0.02
+    datasets:
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp57_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.01_and_balance_factor_0_weight_decay/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64 # 64 * 16 rollouts = 1024
+  turn_on_memory: true
+  balance_factor_lr: 0.01
+  balance_act_type: orig_sigmoid
+  balance_init_type: zeros
+  logging: true
+  # logging_interval: 250
+  logging_interval: 250
+  log_grad: false
+  log_segment_acts: false
+  balance_factor_weight_decay: 0.
+  # log_balance_factor: true
+  # log_other_weight: false
diff --git a/examples/infinite-context-length/configs/exp58/exp58_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.005_and_balance_factor_0_weight_decay.yaml b/examples/infinite-context-length/configs/exp58/exp58_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.005_and_balance_factor_0_weight_decay.yaml
new file mode 100644
index 00000000..efb59169
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp58/exp58_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.005_and_balance_factor_0_weight_decay.yaml
@@ -0,0 +1,179 @@
+checkpoints:
+  checkpoint_interval: 1000
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/exp58_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.005_and_balance_factor_0_weight_decay/checkpoints
+  checkpoints_path_is_shared_file_system: true
+  resume_checkpoint_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp58_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.005_and_balance_factor_0_weight_decay/checkpoints
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp58_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.005_and_balance_factor_0_weight_decay
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    path: /fsx/phuc/projects/infini-attention/llama3-ckps/haojun-8b-llama-nanotron-ckp/NanotronLlama3-8B
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_interleaved: false
+    rope_scaling: null
+    rope_theta: 500000.0
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  torch_adam_is_fused: true
+  clip_grad: 1.0
+
+  # NOTE: old
+  # learning_rate_scheduler:
+  #   learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+  #   lr_decay_starting_step: null
+  #   lr_decay_steps: null
+  #   lr_decay_style: cosine
+  #   lr_warmup_steps: 14000 # 10% warm up of total training steps
+  #   lr_warmup_style: linear
+  #   min_decay_lr: 1.0e-05
+  # optimizer_factory:
+  #   adam_beta1: 0.9
+  #   adam_beta2: 0.95
+  #   adam_eps: 1.0e-08
+  #   name: adamW
+  #   torch_adam_is_fused: true
+
+  learning_rate_scheduler:
+    learning_rate: 1.0e-5
+    lr_decay_starting_step: null
+    lr_decay_steps: 23500
+    lr_decay_style: cosine
+    lr_warmup_steps: 1500 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-6
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 6
+  tp: 4
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: false
+  tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: /fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 1 * 1 * 16384 * 3 = 49k
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 16
+  sequence_length: 1024 # 8192 x 2 = 16384
+  train_steps: 25_000
+  val_check_interval: -1
+
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    - 0.3
+    - 0.3
+    - 0.45
+    - 0.15
+    - 0.08
+    - 0.02
+    datasets:
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp58_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.005_and_balance_factor_0_weight_decay/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
+
+infini_attention:
+  segment_length: 64 # 64 * 16 rollouts = 1024
+  turn_on_memory: true
+  balance_factor_lr: 0.05
+  balance_act_type: orig_sigmoid
+  balance_init_type: zeros
+  logging: true
+  # logging_interval: 250
+  logging_interval: 250
+  log_grad: false
+  log_segment_acts: false
+  balance_factor_weight_decay: 0.
+  # log_balance_factor: true
+  # log_other_weight: false
diff --git a/examples/infinite-context-length/configs/exp6/exp6_llama3_8b_config.yaml b/examples/infinite-context-length/configs/exp6/exp6_llama3_8b_config.yaml
new file mode 100644
index 00000000..3c946d74
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp6/exp6_llama3_8b_config.yaml
@@ -0,0 +1,198 @@
+checkpoints:
+  checkpoint_interval: 250
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/projects/infini-attention/llama3-ckps/8b/nanotron_ckp_tp_agnostic
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp6_8b_llama3_32k_ctx_and_2m_bs
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.015625
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 1.0e-5
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 4000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 3.0e-06
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 8
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: meta-llama/Meta-Llama-3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 8 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 1 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  # sequence_length: 40960 # 8192 * 32 = 40960
+  # sequence_length: 73728 # 8192 * 9 = 73728
+  # sequence_length: 73728 # 8192 * 7 = 57344
+  # sequence_length: 65536 # 8192 * 8 = 65536
+  # sequence_length: 57344 # 8192 * 7 = 57344
+  # sequence_length: 49152 # 8192 * 6 = 57344
+  sequence_length: 32768 # 8192 * 4 = 32768
+  train_steps: 20_000
+  val_check_interval: -1
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    # dataset_weights:
+    # - 0.3
+    # - 0.3
+    # - 0.15
+    # - 0.15
+    # - 0.08
+    # - 0.02
+    datasets:
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+lighteval:
+  batch_size: 16
+  checkpoints_path: null
+  generation: null
+  logging:
+    hub_repo_details: null
+    hub_repo_results: null
+    hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+    local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+    push_details_to_hub: null
+    push_results_to_hub: null
+    push_results_to_tensorboard: true
+    tensorboard_metric_prefix: e
+  parallelism:
+    dp: 8
+    pp: 1
+    pp_engine: 1f1b
+    tp: 1
+    tp_linear_async_communication: false
+    tp_mode: ALL_REDUCE
+  slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+  slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+  tasks:
+    custom_tasks:
+    dataset_loading_processes: 8
+    max_samples: 1000
+    multichoice_continuations_start_space: null
+    no_multichoice_continuations_start_space: null
+    num_fewshot_seeds: null
+    tasks: early-signal
+  wandb:
+    wandb_project: infini_attention_8b_llama
+    wandb_entity: null
+    wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp3_llama3_8b_config/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp7/exp7_llama3_8b_config.yaml b/examples/infinite-context-length/configs/exp7/exp7_llama3_8b_config.yaml
new file mode 100644
index 00000000..bb4c311a
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp7/exp7_llama3_8b_config.yaml
@@ -0,0 +1,198 @@
+checkpoints:
+  checkpoint_interval: 250
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp7_llama3_8b_config/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/projects/infini-attention/llama3-ckps/8b/nanotron_ckp_tp_agnostic
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp7_8b_llama3_32k_ctx_and_4m_bs_and_lr_3.0e-6
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.015625
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 3.0e-6
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 4000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 3.0e-07
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 8
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: meta-llama/Meta-Llama-3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 8 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 1 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  # sequence_length: 40960 # 8192 * 32 = 40960
+  # sequence_length: 73728 # 8192 * 9 = 73728
+  # sequence_length: 73728 # 8192 * 7 = 57344
+  # sequence_length: 65536 # 8192 * 8 = 65536
+  # sequence_length: 57344 # 8192 * 7 = 57344
+  # sequence_length: 49152 # 8192 * 6 = 57344
+  sequence_length: 32768 # 8192 * 4 = 32768
+  train_steps: 20_000
+  val_check_interval: -1
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    dataset_weights:
+    # - 0.3
+    # - 0.3
+    - 0.15
+    - 0.15
+    - 0.08
+    - 0.02
+    datasets:
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+lighteval:
+  batch_size: 16
+  checkpoints_path: null
+  generation: null
+  logging:
+    hub_repo_details: null
+    hub_repo_results: null
+    hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+    local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+    push_details_to_hub: null
+    push_results_to_hub: null
+    push_results_to_tensorboard: true
+    tensorboard_metric_prefix: e
+  parallelism:
+    dp: 8
+    pp: 1
+    pp_engine: 1f1b
+    tp: 1
+    tp_linear_async_communication: false
+    tp_mode: ALL_REDUCE
+  slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp7_llama3_8b_config/lighteval/slurm_scripts
+  slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp7_llama3_8b_config/run_eval.slurm.jinja
+  tasks:
+    custom_tasks:
+    dataset_loading_processes: 8
+    max_samples: 1000
+    multichoice_continuations_start_space: null
+    no_multichoice_continuations_start_space: null
+    num_fewshot_seeds: null
+    tasks: early-signal
+  wandb:
+    wandb_project: infini_attention_8b_llama
+    wandb_entity: null
+    wandb_run_name: exp7_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp3_llama3_8b_config/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/exp8/exp8_llama3_8b_infini_config.yaml b/examples/infinite-context-length/configs/exp8/exp8_llama3_8b_infini_config.yaml
new file mode 100644
index 00000000..0ffdd1d4
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp8/exp8_llama3_8b_infini_config.yaml
@@ -0,0 +1,99 @@
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention
+  run: exp8_llama3_8b_infini_config
+  seed: 42
+  step: null
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    hidden_size: 1024
+    initializer_range: 0.02
+    intermediate_size: 4096
+    is_llama_config: true
+    max_position_embeddings: 1024
+    num_attention_heads: 8
+    num_hidden_layers: 10
+    num_key_value_heads: 4
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 715 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 1
+parallelism:
+  dp: 4
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp: 2
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+
+data_stages:
+  - name: Stable Training Stage
+    start_training_step: 1
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: roneneldan/TinyStories
+        hf_dataset_splits: train
+        text_column_name: text
+      num_loading_workers: 1
+      seed: 42
+
+lighteval: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: gpt2
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 5
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  sequence_length: 1024
+  train_steps: 3575
+  val_check_interval: -1
+checkpoints:
+  checkpoint_interval: 1000
+  checkpoints_path: checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: null
+  save_initial_state: false
+profiler: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
diff --git a/examples/infinite-context-length/configs/exp9/exp9_llama3_8b_config.yaml b/examples/infinite-context-length/configs/exp9/exp9_llama3_8b_config.yaml
new file mode 100644
index 00000000..4d127068
--- /dev/null
+++ b/examples/infinite-context-length/configs/exp9/exp9_llama3_8b_config.yaml
@@ -0,0 +1,198 @@
+checkpoints:
+  checkpoint_interval: 250
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp9_llama3_8b_config/checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /fsx/phuc/projects/infini-attention/llama3-ckps/8b/nanotron_ckp_tp_agnostic
+  save_initial_state: false
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: infini_attention_8b_llama
+  run: exp9_8b_llama3_32k_ctx_and_2m_bs
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.015625
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 3.0e-5
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 4000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 3.0e-06
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+
+parallelism:
+  dp: 16
+  tp: 8
+
+  # dp: 1
+  # tp: 2
+
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: meta-llama/Meta-Llama-3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 8 # batch_accumulation_per_replica * micro_batch_size * sequence_length * dp = 4 * 4 * 40960 * 1 = 655,360
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  # sequence_length: 40960 # 8192 * 32 = 40960
+  # sequence_length: 73728 # 8192 * 9 = 73728
+  # sequence_length: 73728 # 8192 * 7 = 57344
+  # sequence_length: 65536 # 8192 * 8 = 65536
+  # sequence_length: 57344 # 8192 * 7 = 57344
+  # sequence_length: 49152 # 8192 * 6 = 57344
+  sequence_length: 32768 # 8192 * 4 = 32768
+  train_steps: 20_000
+  val_check_interval: -1
+
+data:
+  dataset:
+    dataloader_type: single
+    dataset_max_tokens: null
+    # dataset_weights:
+    # - 0.3
+    # - 0.3
+    # - 0.15
+    # - 0.15
+    # - 0.08
+    # - 0.02
+    datasets:
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    # - filename_pattern: .*.ds
+    #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+    #   dtype: uint32
+    #   skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+      dtype: uint32
+      skip_tokens: 0
+    - filename_pattern: .*.ds
+      folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+      dtype: uint32
+      skip_tokens: 0
+    pad_samples_to_global_batch_size: false
+    skip_in_stream: true
+  num_loading_workers: 0
+  seed: 42
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp6_llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks:
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: infini_attention_8b_llama
+#     wandb_entity: null
+#     wandb_run_name: exp6_llama3_8b_config
+
+
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+
+s3_upload:
+  remove_after_upload: true
+  s5cmd_concurrency: 5
+  s5cmd_numworkers: 16
+  upload_s3_path: s3://phuc-experiments/infini-attention/8b-llama/exp9_llama3_8b_config/
+
+experiment_logger:
+  tensorboard_logger:
+    flush_secs: 30
+    tensorboard_dir: /fsx/phuc/project_data/infini_attention/tb_logs
+  wandb_logger:
+    wandb_entity: null
+    wandb_project: infini_attention_8b_llama
diff --git a/examples/infinite-context-length/configs/nouamane_config.yaml b/examples/infinite-context-length/configs/nouamane_config.yaml
new file mode 100644
index 00000000..34e647ce
--- /dev/null
+++ b/examples/infinite-context-length/configs/nouamane_config.yaml
@@ -0,0 +1,122 @@
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: debug
+  run: tiny_llama_%date_%jobid
+  seed: 42
+  step: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: meta-llama/Meta-Llama-3-8B
+  tokenizer_revision: null
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.2
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: false
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015 # note: 1/2 of pythia use this for a 400m model
+    lr_decay_starting_step: null
+    lr_decay_steps: null
+    lr_decay_style: cosine
+    lr_warmup_steps: 715 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 1.0e-05
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 1
+parallelism:
+  dp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp: 2
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+data_stages:
+  # - name: Stable Training Stage
+  #   start_training_step: 1
+  #   data:
+  #     dataset:
+  #       dataset_overwrite_cache: false
+  #       dataset_processing_num_proc_per_process: 1
+  #       hf_dataset_config_name: null
+  #       hf_dataset_or_datasets: HuggingFaceH4/testing_alpaca_small
+  #       hf_dataset_splits: train
+  #       text_column_name: completion
+  #     num_loading_workers: 1
+  #     seed: 42
+  # - name: Annealing Phase
+  #   start_training_step: 10
+  #   data:
+  #     dataset:
+  #       dataset_overwrite_cache: false
+  #       dataset_processing_num_proc_per_process: 1
+  #       hf_dataset_config_name: null
+  #       hf_dataset_or_datasets: HuggingFaceH4/testing_alpaca_small
+  #       hf_dataset_splits: train
+  #       text_column_name: completion
+  #     num_loading_workers: 1
+  #     seed: 42
+
+  - name: Stable Training Stage
+    start_training_step: 1
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: roneneldan/TinyStories
+        hf_dataset_splits: train
+        text_column_name: text
+      num_loading_workers: 1
+      seed: 42
+
+lighteval: null
+tokens:
+  batch_accumulation_per_replica: 1
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  sequence_length: 2048
+  train_steps: 10
+  val_check_interval: -1
+checkpoints:
+  checkpoint_interval: 10000
+  checkpoints_path: checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: /scratch/nouamane/projects/nanotron/pretrained/llama3-8B-interleave
+  save_initial_state: false
+profiler: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
diff --git a/examples/infinite-context-length/configs/ref_280m_1024_ctx.yaml b/examples/infinite-context-length/configs/ref_280m_1024_ctx.yaml
new file mode 100644
index 00000000..53467ad3
--- /dev/null
+++ b/examples/infinite-context-length/configs/ref_280m_1024_ctx.yaml
@@ -0,0 +1,107 @@
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: true
+  project: debug
+  run: tiny_llama_%date_%jobid
+  seed: 42
+  step: null
+# infini_attention:
+#   segment_length: 256
+#   turn_on_memory: false
+model:
+  ddp_bucket_cap_mb: 120
+  dtype: bfloat16
+  init_method:
+    # std: 0.025 # original
+    std: 0.03125 # 1/sqrt(1024)=0.03125
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    hidden_size: 128
+    initializer_range: 0.02
+    intermediate_size: 256
+    is_llama_config: true
+    max_position_embeddings: 1024
+    num_attention_heads: 8
+    num_hidden_layers: 1
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    # tie_word_embeddings: true
+    tie_word_embeddings: false # original use true
+    use_cache: true
+    vocab_size: 49152
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.00015
+    lr_decay_starting_step: null
+    lr_decay_steps: 2860
+    lr_decay_style: cosine
+    lr_warmup_steps: 715 # 20% of the total steps
+    lr_warmup_style: linear
+    min_decay_lr: 0.00001
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 0
+parallelism:
+  # dp: 1
+  # tp: 8
+
+  dp: 1
+  tp: 2
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+data_stages:
+  - name: Stable Training Stage
+    start_training_step: 1
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: roneneldan/TinyStories
+        hf_dataset_splits: train
+        text_column_name: text
+      num_loading_workers: 1
+      seed: 42
+lighteval: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: gpt2
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 1
+  limit_test_batches: 0
+  limit_val_batches: 0
+  # micro_batch_size: 256
+  # sequence_length: 1024
+  # train_steps: 1787
+  micro_batch_size: 32
+  sequence_length: 1024
+  train_steps: 1
+  val_check_interval: -1
+checkpoints:
+  checkpoint_interval: 5000
+  checkpoints_path: checkpoints
+  checkpoints_path_is_shared_file_system: false
+  resume_checkpoint_path: null
+  save_initial_state: false
+profiler: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
diff --git a/examples/infinite-context-length/configs/ref_llama3_8b_config.yaml b/examples/infinite-context-length/configs/ref_llama3_8b_config.yaml
new file mode 100644
index 00000000..ba54cb5e
--- /dev/null
+++ b/examples/infinite-context-length/configs/ref_llama3_8b_config.yaml
@@ -0,0 +1,214 @@
+checkpoints:
+  checkpoint_interval: 1000000
+  # checkpoints_path: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/checkpoints
+  checkpoints_path: /fsx/phuc/projects/infini-attention/llama3-ckps/8b/nanotron_ckp_initial_state
+  checkpoints_path_is_shared_file_system: false
+  # resume_checkpoint_path: /fsx/phuc/projects/infini-attention/llama3-ckps/8b/nanotron_ckp_tp_agnostic
+  resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  # resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr
+  # resume_checkpoint_path: /fsx/phuc/projects/nanotron/llama3_8b_generated_from_brrr_with_pp_4/
+  # resume_checkpoint_path: /fsx/haojun/lighteval_evaluation_model/llama3-8b-hf
+  save_initial_state: true
+general:
+  benchmark_csv_path: null
+  consumed_train_samples: null
+  ignore_sanity_checks: false
+  project: test
+  run: llama
+  seed: 42
+  step: null
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.2
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 128000
+    eos_token_id: 128001
+    hidden_act: silu
+    hidden_size: 4096
+    initializer_range: 0.02
+    intermediate_size: 14336
+    is_llama_config: true
+    max_position_embeddings: 8192
+    num_attention_heads: 32
+    num_hidden_layers: 32
+    num_key_value_heads: 8
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    tie_word_embeddings: false
+    use_cache: true
+    vocab_size: 128256
+
+optimizer:
+  accumulate_grad_in_fp32: true
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_eps: 1.0e-08
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 2.0e-5
+    lr_decay_starting_step: null
+    lr_decay_steps: 98_000
+    lr_decay_style: cosine
+    lr_warmup_steps: 2000 # 10% warm up of total training steps
+    lr_warmup_style: linear
+    min_decay_lr: 2.0e-6
+  torch_adam_is_fused: true
+  weight_decay: 0.1
+  zero_stage: 1
+parallelism:
+  dp: 1
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp: 8
+  tp_linear_async_communication: true
+  tp_mode: REDUCE_SCATTER
+# parallelism:
+#   dp: 1
+#   expert_parallel_size: 1
+#   pp: 1
+#   pp_engine: afab
+#   tp: 1
+#   tp_linear_async_communication: false
+#   tp_mode: ALL_REDUCE
+profiler: null
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: meta-llama/Meta-Llama-3-8B
+  tokenizer_revision: null
+tokens:
+  batch_accumulation_per_replica: 32 # accum * bs * seq_len * dp = 32 * 1 * 32768 * 1
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 1
+  sequence_length: 32768
+  # sequence_length: 8192
+  train_steps: 100_000
+  val_check_interval: -1
+
+data_stages:
+  # - name: Stable Training Stage
+  #   start_training_step: 1
+  #   data:
+  #     dataset:
+  #       dataset_overwrite_cache: false
+  #       dataset_processing_num_proc_per_process: 1
+  #       hf_dataset_config_name: null
+  #       hf_dataset_or_datasets: HuggingFaceH4/testing_alpaca_small
+  #       hf_dataset_splits: train
+  #       text_column_name: completion
+  #     num_loading_workers: 1
+  #     seed: 42
+  # - name: Stable Training Stage
+  #   start_training_step: 1
+  #   data:
+  #     dataset:
+  #       dataset_overwrite_cache: false
+  #       dataset_processing_num_proc_per_process: 1
+  #       hf_dataset_config_name: null
+  #       hf_dataset_or_datasets: JeanKaddour/minipile
+  #       hf_dataset_splits: train
+  #       text_column_name: text
+  #     num_loading_workers: 1
+  #     seed: 42
+
+  - name: Stable Training Stage
+    start_training_step: 1
+    data:
+      dataset:
+        dataset_overwrite_cache: false
+        dataset_processing_num_proc_per_process: 1
+        hf_dataset_config_name: null
+        hf_dataset_or_datasets: roneneldan/TinyStories
+        hf_dataset_splits: train
+        text_column_name: text
+      num_loading_workers: 1
+      seed: 42
+
+# data_stages:
+# - name: Stable Training Stage
+#   start_training_step: 1
+#   data:
+#     dataset:
+#       dataloader_type: single
+#       dataset_max_tokens: null
+#       # dataset_weights:
+#       # - 0.3
+#       # - 0.3
+#       # - 0.15
+#       # - 0.15
+#       # - 0.08
+#       # - 0.02
+#       datasets:
+#       # - filename_pattern: .*.ds
+#       #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/long/
+#       #   dtype: uint32
+#       #   skip_tokens: 0
+#       # - filename_pattern: .*.ds
+#       #   folder: s3://huggingface-llm-datasets/stack_full_v21-8k/tokenized-llama3/short/
+#       #   dtype: uint32
+#       #   skip_tokens: 0
+#       # - filename_pattern: .*.ds
+#       #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/long/CC-MAIN-2024-10
+#       #   dtype: uint32
+#       #   skip_tokens: 0
+#       # - filename_pattern: .*.ds
+#       #   folder: s3://huggingface-llm-datasets/fineweb-v1-8k/tokenized-llama3/short/CC-MAIN-2024-10
+#       #   dtype: uint32
+#       #   skip_tokens: 0
+#       - filename_pattern: .*.ds
+#         folder: s3://huggingface-llm-datasets/project-gutenberg/tokenized-llama3/
+#         dtype: uint32
+#         skip_tokens: 0
+#       - filename_pattern: .*.ds
+#         folder: s3://huggingface-llm-datasets/OpenHermes-2-5/tokenized-llama3
+#         dtype: uint32
+#         skip_tokens: 0
+#       pad_samples_to_global_batch_size: false
+#       skip_in_stream: true
+#     num_loading_workers: 0
+#     seed: 42
+
+# lighteval:
+#   batch_size: 16
+#   checkpoints_path: null
+#   generation: null
+#   logging:
+#     hub_repo_details: null
+#     hub_repo_results: null
+#     hub_repo_tensorboard: HuggingFaceBR4/8b_llama3_evals
+#     local_output_path: /fsx/phuc/new_workspace/experiments/8b_llama3/evals_of_the_released_ckp/logs
+#     push_details_to_hub: null
+#     push_results_to_hub: null
+#     push_results_to_tensorboard: true
+#     tensorboard_metric_prefix: e
+#   parallelism:
+#     dp: 8
+#     pp: 1
+#     pp_engine: 1f1b
+#     tp: 1
+#     tp_linear_async_communication: false
+#     tp_mode: ALL_REDUCE
+#   slurm_script_dir: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/lighteval/slurm_scripts
+#   slurm_template: /fsx/phuc/new_workspace/experiments/8b_llama3/llama3_8b_config/run_eval.slurm.jinja
+#   tasks:
+#     custom_tasks: brrr.lighteval.evaluation_tasks
+#     dataset_loading_processes: 8
+#     max_samples: 1000
+#     multichoice_continuations_start_space: null
+#     no_multichoice_continuations_start_space: null
+#     num_fewshot_seeds: null
+#     tasks: early-signal
+#   wandb:
+#     wandb_project: 8b_llama3
+#     wandb_entity: null
+#     wandb_run_name: llama3_8b_config
diff --git a/examples/infinite-context-length/data/exp34/debug_amount_of_change_in_weight.ipynb b/examples/infinite-context-length/data/exp34/debug_amount_of_change_in_weight.ipynb
new file mode 100644
index 00000000..d80d2439
--- /dev/null
+++ b/examples/infinite-context-length/data/exp34/debug_amount_of_change_in_weight.ipynb
@@ -0,0 +1,1119 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch.nn.functional as F\n",
+    "import torch\n",
+    "\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "from nanotron.helpers import _get_lr_lambda_in_training\n",
+    "from nanotron.config import LRSchedulerArgs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_changes(changes):\n",
+    "    import matplotlib.pyplot as plt\n",
+    "    # Plotting the changes\n",
+    "    plt.figure(figsize=(10, 6))\n",
+    "    plt.plot(range(1, len(changes) + 1), changes)\n",
+    "    plt.title('Absolute Weight Changes per Step')\n",
+    "    plt.xlabel('Step')\n",
+    "    plt.ylabel('Absolute Weight Change')\n",
+    "    plt.grid(True)\n",
+    "    plt.show()\n",
+    "\n",
+    "def plot_accumulated_changes(changes):\n",
+    "    import matplotlib.pyplot as plt\n",
+    "    import numpy as np\n",
+    "    \n",
+    "    # Calculate accumulated changes\n",
+    "    accumulated_changes = np.cumsum(changes)\n",
+    "    \n",
+    "    # Plotting the accumulated changes\n",
+    "    plt.figure(figsize=(10, 6))\n",
+    "    plt.plot(range(1, len(accumulated_changes) + 1), accumulated_changes)\n",
+    "    plt.title('Accumulated Weight Changes per Step')\n",
+    "    plt.xlabel('Step')\n",
+    "    plt.ylabel('Accumulated Weight Change')\n",
+    "    plt.grid(True)\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import math\n",
+    "import numpy as np\n",
+    "\n",
+    "def simulate_adam_update(lr_scheduler_args, total_steps, l2_norm_gradient, beta1=0.9, beta2=0.95, epsilon=1.0e-08):\n",
+    "    m = 0  # First moment vector\n",
+    "    v = 0  # Second moment vector\n",
+    "    t = 0  # Timestep\n",
+    "\n",
+    "    total_weight_change = 0\n",
+    "    changes = []\n",
+    "    gradients = []\n",
+    "\n",
+    "    for step in range(1, total_steps + 1):\n",
+    "        t += 1\n",
+    "        lr = _get_lr_lambda_in_training(\n",
+    "            current_step=t,\n",
+    "            initial_lr=lr_scheduler_args.learning_rate,\n",
+    "            total_training_steps=total_steps,\n",
+    "            lr_scheduler_args=lr_scheduler_args\n",
+    "        ) * lr_scheduler_args.learning_rate\n",
+    "\n",
+    "        # Simulate gradient\n",
+    "        # gradient = abs(np.random.randn() * l2_norm_gradient / math.sqrt(1))\n",
+    "        gradient = l2_norm_gradient\n",
+    "\n",
+    "        m = beta1 * m + (1 - beta1) * gradient\n",
+    "        v = beta2 * v + (1 - beta2) * (gradient**2)\n",
+    "        m_hat = m / (1 - beta1**t)\n",
+    "        v_hat = v / (1 - beta2**t)\n",
+    "\n",
+    "        # Compute update\n",
+    "        update = lr * m_hat / (math.sqrt(v_hat) + epsilon)\n",
+    "        \n",
+    "        total_weight_change += abs(update)\n",
+    "        changes.append(abs(update))\n",
+    "        gradients.append(abs(gradient))\n",
+    "\n",
+    "    return total_weight_change, changes, gradients"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "debug_total_changes, changes, _ = simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.001,\n",
+    "    lr_warmup_steps=50,\n",
+    "    lr_warmup_style=\"constant\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), 3000, l2_norm_gradient=0.00001)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_accumulated_changes(changes)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "5.074930069930068"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.0005,\n",
+    "    lr_warmup_steps=4000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=16000,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), 20000, l2_norm_gradient=0.00001)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.8450041549958394"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.00015/2,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=20000, l2_norm_gradient=0.01)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.0950039049960907"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.0001,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=20000, l2_norm_gradient=0.01)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.5950034049965929"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.00015,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=20000, l2_norm_gradient=0.01)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.5900034099965823"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.00015,\n",
+    "    lr_warmup_steps=2000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=20000, l2_norm_gradient=0.01)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.5800034199965796"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.00015,\n",
+    "    lr_warmup_steps=4000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=20000, l2_norm_gradient=0.01)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.095001904998105"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.0003,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=20000, l2_norm_gradient=0.01)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([0.7493, 0.8313, 0.8292, 0.9164, 0.9567])"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "torch.sigmoid(torch.tensor([1.0950039049960907, 1.5950034049965929, 1.5800034199965796, 2.3950026049973743, 3.095001904998105]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.00,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=20000, l2_norm_gradient=0.01)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plot_accumulated_changes(simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.0000375,\n",
+    "    lr_warmup_steps=5000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=0.000015\n",
+    "), total_steps=50000, l2_norm_gradient=0.1)[1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_accumulated_changes(simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate= 0.00015,\n",
+    "    lr_warmup_steps=5000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=0.000015\n",
+    "), total_steps=50000, l2_norm_gradient=0.1)[1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor(0.4013)"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F.sigmoid(torch.tensor(-0.4))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Exp 32"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "exp32_total_change, exp32_changes, _ = simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.00015,\n",
+    "    lr_warmup_steps=14000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=35000, l2_norm_gradient=0.01)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "17.604987395012746"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "exp32_total_change"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2gAAAIjCAYAAAB2/jgmAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8g+/7EAAAACXBIWXMAAA9hAAAPYQGoP6dpAACp/UlEQVR4nOzdd1yV5f/H8ddhD5kOEPfGBa4kR1mKo8zUHGl9G1ZqlmWZWpZpjoampanfzPbQr+bITE3DVamkuXBv3IIDEQGZ5/79QZ5fJCoYeB/g/Xw8eJT3fZ1zv8+5OMqH+3Nft8UwDAMRERERERExnYPZAURERERERCSLCjQRERERERE7oQJNRERERETETqhAExERERERsRMq0EREREREROyECjQRERERERE7oQJNRERERETETqhAExERERERsRMq0EREREREROyECjQRkQJw9OhRLBYLEydOvK3HffLJJ6lcufJtPaa9uOeee7jnnntu+bH16tXL30C3wGKxMHDgQLNjiIiIiVSgiYjcgv/+979YLBbCwsLMjpJvli1bxltvvZWvzzlhwgQsFgvbtm3Ltt0wDPz8/LBYLERHR2fbl5KSgqurK4888ki+ZskPp0+f5q233mL79u15etzhw4fp378/VatWxc3NDW9vb1q0aMGUKVO4cuVKwYSVf+XcuXMMGjSI4OBg3N3dKVOmDE2bNuXVV18lMTHRNm727NlMnjzZvKAiUuQ4mR1ARKQwmjVrFpUrV2bTpk0cOnSI6tWrmx3pX1u2bBnTp0/P1yKtZcuWAKxbt46GDRvatu/evZv4+HicnJxYv349VapUse37888/SUtLsz02t3755Zf8CX0Dp0+fZvTo0VSuXJkGDRrk6jFLly6lR48euLq68vjjj1OvXj3S0tJYt24dQ4cOZffu3cycObNgg0uexMXF0aRJExISEnjqqacIDg7mwoUL7Nixg48//pgBAwZQokQJIKtA27VrFy+99JK5oUWkyFCBJiKSR9HR0WzYsIGFCxfSv39/Zs2axahRo8yOZZeaNGmCm5sb69at44UXXrBtX79+PSVLlqRJkyasW7eO//znP7Z969atA8hzgebi4pI/ofNRdHQ0vXr1olKlSqxevZqyZcva9j3//PMcOnSIpUuXmpiw+EpKSsLT0zPHfZ9//jnHjx9n/fr1NG/ePNu+hIQEu/xeE5GiQy2OIiJ5NGvWLPz8/OjYsSPdu3dn1qxZNxz/4YcfUqlSJdzd3WnVqhW7du3Ktj8mJoY+ffpQvnx5XF1dKVu2LJ07d+bo0aPZxv33v/+lbt26uLq6EhQUxPPPP098fPwNj7127VosFgtr167Ntv3qNXJfffUVkHXt2vTp04Gs66Cufl1ltVqZPHkydevWxc3NjYCAAPr378/FixdveHwXFxfuuOMO1q9fn237+vXradasGS1atMhxn6+vr+2asNweO6dr0I4dO8aDDz6Ip6cnZcqU4eWXX2bFihU5vicAe/bs4d5778XDw4Ny5coxYcKEbO/lHXfcAUCfPn1s79HV9zAnEyZMIDExkc8//zxbcXZV9erVGTRo0DXbFy1aRL169XB1daVu3bosX778mtf13HPPUatWLdzd3SlZsiQ9evS45nvmq6++wmKxsH79egYPHkzp0qXx9PSka9eunDt3LttYq9XKW2+9RVBQEB4eHtx7773s2bOHypUr8+STT2YbGx8fz0svvUSFChVwdXWlevXqjB8/HqvVmm3cnDlzaNy4MV5eXnh7e1O/fn2mTJly3fcLsl+/ebPPDsC+ffvo3r07/v7+uLm50aRJExYvXpzj+/Drr7/y3HPPUaZMGcqXL3/dDIcPH8bR0ZE777zzmn3e3t64ubkBWd9zS5cu5dixY7bvh79fA5qamsqoUaOoXr06rq6uVKhQgWHDhpGamprtOa9eezhr1ixq1aqFm5sbjRs35rfffrvheyUiRZPOoImI5NGsWbN46KGHcHFxoXfv3nz88cf8+eefth/e/+6bb77h8uXLPP/886SkpDBlyhRat27Nzp07CQgIAKBbt27s3r2bF154gcqVK3P27FkiIiI4fvy47Ye9t956i9GjRxMeHs6AAQPYv3+/7bjr16/H2dn5X72m/v37c/r0aSIiIvj2229z3P/VV1/Rp08fXnzxRaKjo5k2bRrbtm276fFbtmzJ77//ztGjR22vZ/369TzzzDM0bdqUUaNGER8fj6+vL4ZhsGHDBpo1a4aDg8O/OnZSUhKtW7fmzJkzDBo0iMDAQGbPns2aNWtyHH/x4kU6dOjAQw89RM+ePZk/fz6vvvoq9evX57777qN27dqMGTOGkSNH0q9fP+666y6Aa86w/N1PP/1E1apVbzjmn9atW8fChQt57rnn8PLy4qOPPqJbt24cP36ckiVLAlltoBs2bKBXr16UL1+eo0eP8vHHH3PPPfewZ88ePDw8sj3nCy+8gJ+fH6NGjeLo0aNMnjyZgQMHMnfuXNuY4cOHM2HCBDp16kT79u2Jioqiffv2pKSkZHuu5ORkWrVqxalTp+jfvz8VK1Zkw4YNDB8+nDNnztiux4qIiKB37960adOG8ePHA7B3717Wr1+fY1H6T7n57OzevZsWLVpQrlw5XnvtNTw9Pfn+++/p0qULCxYsoGvXrtme87nnnqN06dKMHDmSpKSk6x67UqVKZGZm8u233/LEE09cd9wbb7zBpUuXOHnyJB9++CGArfXRarXy4IMPsm7dOvr160ft2rXZuXMnH374IQcOHGDRokXZnuvXX39l7ty5vPjii7i6uvLf//6XDh06sGnTJrtYwEZEbiNDRERybfPmzQZgREREGIZhGFar1ShfvrwxaNCgbOOio6MNwHB3dzdOnjxp275x40YDMF5++WXDMAzj4sWLBmC8//771z3m2bNnDRcXF6Ndu3ZGZmambfu0adMMwPjiiy9s25544gmjUqVKtj+vWbPGAIw1a9bkmO/LL7+0bXv++eeNnP5Z+P333w3AmDVrVrbty5cvz3H7Py1dutQAjG+//dYwDMM4c+aMARi//vqrcfnyZcPR0dFYunSpYRiGsWvXLgMw3n777Twfu1WrVkarVq1sf540aZIBGIsWLbJtu3LlihEcHHzNe9KqVSsDML755hvbttTUVCMwMNDo1q2bbduff/55zft2PZcuXTIAo3PnzjcdexVguLi4GIcOHbJti4qKMgBj6tSptm3JycnXPDYyMvKa1/Dll18agBEeHm5YrVbb9pdfftlwdHQ04uPjDcMwjJiYGMPJycno0qVLtud86623DMB44oknbNvGjh1reHp6GgcOHMg29rXXXjMcHR2N48ePG4ZhGIMGDTK8vb2NjIyMXL9+w8j9Z8cwDKNNmzZG/fr1jZSUFNs2q9VqNG/e3KhRo8Y170PLli1zlScmJsYoXbq0ARjBwcHGs88+a8yePdv2fv1dx44ds33mrvr2228NBwcH4/fff8+2fcaMGQZgrF+/3rYNMABj8+bNtm3Hjh0z3NzcjK5du940r4gULWpxFBHJg1mzZhEQEMC9994LZLUmPfzww8yZM4fMzMxrxnfp0oVy5crZ/ty0aVPCwsJYtmwZAO7u7ri4uLB27drrtguuXLmStLQ0XnrpJdtZJYC+ffvi7e1d4NcwzZs3Dx8fH9q2bcv58+dtX40bN6ZEiRLXPSN1VfPmzXFwcLBdW3b1rNcdd9xBiRIlCAkJsbU5Xv3v1evP/s2xly9fTrly5XjwwQdt29zc3Ojbt2+O40uUKJHtWjgXFxeaNm3KkSNHcvEuXSshIQEALy+vPD0uPDycatWq2f4cEhKCt7d3thzu7u62/09PT+fChQtUr14dX19ftm7des1z9uvXL1vL6l133UVmZibHjh0DYNWqVWRkZPDcc89le9zfrxu8at68edx11134+fllm5Pw8HAyMzNtbXm+vr4kJSURERGRp9d/1c0+O3FxcaxevZqePXty+fJlW44LFy7Qvn17Dh48yKlTp7I9Z9++fXF0dLzpsQMCAoiKiuLZZ5/l4sWLzJgxg0ceeYQyZcowduxYDMO46XPMmzeP2rVrExwcnO19at26NcA137vNmjWjcePGtj9XrFiRzp07s2LFihz/bhGRoksFmohILmVmZjJnzhzuvfdeoqOjOXToEIcOHSIsLIzY2FhWrVp1zWNq1KhxzbaaNWvarhVydXVl/Pjx/PzzzwQEBHD33XczYcIEYmJibOOv/hBdq1atbM/j4uJC1apVbfsLysGDB7l06RJlypShdOnS2b4SExM5e/bsDR/v6+tL3bp1sxVhDRs2tBUZzZs3z7bvamH0b4997NgxqlWrlq0wAa674mb58uWvGevn53fT6+yux9vbG4DLly/n6XEVK1a8Zts/c1y5coWRI0fargErVaoUpUuXJj4+nkuXLt30Of38/ABsz3n1e+if742/v79t7FUHDx5k+fLl18xHeHg4gG1OnnvuOWrWrMl9991H+fLleeqpp665lu5GbvbZOXToEIZh8Oabb16T5eqiPf/8/vj7aqE3U7ZsWT7++GPOnDnD/v37+eijj2ztkZ9//vlNH3/w4EF27959TbaaNWvmmO16rzc5Ofma6wVFpGjTNWgiIrm0evVqzpw5w5w5c5gzZ841+2fNmkW7du3y/LwvvfQSnTp1YtGiRaxYsYI333yTd999l9WrV2dbmv5W/LPguCovv5G3Wq2UKVPmuouhlC5d+qbP0bJlS2bMmEF8fPw1K+M1b96cL774gvT0dNatW0fjxo1tizDkx7Fz63pnVnJztiQn3t7eBAUF5biwxb/N8cILL/Dll1/y0ksv0axZM3x8fLBYLPTq1euahTpy+5y5ZbVaadu2LcOGDctx/9UCpEyZMmzfvp0VK1bw888/8/PPP/Pll1/y+OOP8/XXX+f5uDnlABgyZAjt27fPccw/C86/n3nMLYvFQs2aNalZsyYdO3akRo0azJo1i2eeeeam+erXr88HH3yQ4/4KFSrkOYuIFA8q0EREcmnWrFmUKVPGttrh3y1cuJAffviBGTNmZPsh8ODBg9eMPXDgQLaV3gCqVavGK6+8wiuvvMLBgwdp0KABkyZN4rvvvqNSpUoA7N+/n6pVq9oek5aWRnR0tO3MRU6unv3452qPOZ11u14xV61aNVauXEmLFi1u6QdcyCrQPv74Y1auXMm2bdsYOnSobV/z5s25cuUKS5cu5ciRI3Tr1i1fjl2pUiX27NmDYRjZXtuhQ4du6TXA9d+j63nggQeYOXMmkZGRNGvW7JaP+0/z58/niSeeYNKkSbZtKSkpN13V83qufo8dOnQo21mmCxcuXHMGsVq1aiQmJt7w++4qFxcXOnXqRKdOnbBarTz33HN88sknvPnmmze9d+DNPjtXPwvOzs65ypIfqlatip+fH2fOnLFtu9HnJioqijZt2uTq++Z6r9fDwyNffxEhIvZPLY4iIrlw5coVFi5cyAMPPED37t2v+Ro4cCCXL1++ZnnvRYsWZbsOZtOmTWzcuJH77rsPyFoR75+r5FWrVg0vLy/bUtzh4eG4uLjw0UcfZTvj8fnnn3Pp0iU6dux43dyVKlXC0dHxmuW6//vf/14z9uo9of75Q37Pnj3JzMxk7Nix1zwmIyMjV0XB1WvKPvjgA9LT07OdQatcuTJly5a1LWn/9/uf/Ztjt2/fnlOnTmWbk5SUFD799NOb5r2e671H1zNs2DA8PT155plniI2NvWb/4cOHb7rsfE4cHR2vOfs1derUW75WqU2bNjg5OfHxxx9n2z5t2rRrxvbs2ZPIyEhWrFhxzb74+HgyMjKArOLu7xwcHAgJCQG4Zpn5nNzss1OmTBnuuecePvnkk2wF01X/pi1w48aNOa7yuGnTJi5cuJCt3djT0zPHttKePXty6tSpHL/frly5cs3zR0ZGZrt+8MSJE/z444+0a9cuV9fNiUjRoTNoIiK5sHjxYi5fvpxtwYm/u/POOyldujSzZs3i4Ycftm2vXr06LVu2ZMCAAaSmpjJ58mRKlixpaw87cOAAbdq0oWfPntSpUwcnJyd++OEHYmNj6dWrF5DVxjd8+HBGjx5Nhw4dePDBB9m/fz///e9/ueOOO7ItbPFPPj4+9OjRg6lTp2KxWKhWrRpLlizJ8dqtqwsUvPjii7Rv3x5HR0d69epFq1at6N+/P++++y7bt2+nXbt2ODs7c/DgQebNm8eUKVPo3r37Dd+/ihUrUqFCBSIjI6lcuTJBQUHZ9jdv3pwFCxZgsVho0aKFbfu/OXb//v2ZNm0avXv3ZtCgQZQtW5ZZs2bZ2ifzejYMsopnX19fZsyYgZeXF56enoSFhV332qZq1aoxe/ZsHn74YWrXrs3jjz9OvXr1SEtLY8OGDcybN++ae4zlxgMPPMC3336Lj48PderUITIykpUrV9qW4c+rgIAABg0axKRJk3jwwQfp0KEDUVFR/Pzzz5QqVSrbezV06FAWL17MAw88wJNPPknjxo1JSkpi586dzJ8/n6NHj1KqVCmeeeYZ4uLiaN26NeXLl+fYsWNMnTqVBg0aULt27ZtmutlnB2D69Om0bNmS+vXr07dvX6pWrUpsbCyRkZGcPHmSqKioW3o/vv32W2bNmkXXrl1p3LgxLi4u7N27ly+++AI3Nzdef/1129jGjRszd+5cBg8ebFv4plOnTjz22GN8//33PPvss6xZs4YWLVqQmZnJvn37+P7771mxYgVNmjSxPU+9evVo3759tmX2AUaPHn1Lr0FECjHzFpAUESk8OnXqZLi5uRlJSUnXHfPkk08azs7Oxvnz521Lhb///vvGpEmTjAoVKhiurq7GXXfdZURFRdkec/78eeP55583goODDU9PT8PHx8cICwszvv/++2uef9q0aUZwcLDh7OxsBAQEGAMGDDAuXryYbcw/l9k3DMM4d+6c0a1bN8PDw8Pw8/Mz+vfvb1vO/u/LxWdkZBgvvPCCUbp0acNisVyz5P7MmTONxo0bG+7u7oaXl5dRv359Y9iwYcbp06dz9R727t3bAIxHHnnkmn0ffPCBARi1a9fO8bG5OfY/l9k3DMM4cuSI0bFjR8Pd3d0oXbq08corrxgLFiwwAOOPP/7I9ti6detec9yc3s8ff/zRqFOnjuHk5JTrJfcPHDhg9O3b16hcubLh4uJieHl5GS1atDCmTp2abYl4wHj++eeveXylSpWyLXV/8eJFo0+fPkapUqWMEiVKGO3btzf27dt3zbiry8v/+eef2Z4vp9svZGRkGG+++aYRGBhouLu7G61btzb27t1rlCxZ0nj22WezPf7y5cvG8OHDjerVqxsuLi5GqVKljObNmxsTJ0400tLSDMMwjPnz5xvt2rUzypQpY7i4uBgVK1Y0+vfvb5w5c+aG71VuPztXHT582Hj88ceNwMBAw9nZ2ShXrpzxwAMPGPPnz7/p+3A9O3bsMIYOHWo0atTI8Pf3N5ycnIyyZcsaPXr0MLZu3ZptbGJiovHII48Yvr6+BpDt+yUtLc0YP368UbduXcPV1dXw8/MzGjdubIwePdq4dOmSbdzVef/uu++MGjVqGK6urkbDhg2vuT2GiBQPFsO4xaufRURECqHJkyfz8ssvc/LkyWzLuMu14uPj8fPzY9y4cbzxxhu35ZhHjx6lSpUqvP/++wwZMuS2HNNsFouF559/PseWUhEpfnQNmoiIFFlXrlzJ9ueUlBQ++eQTatSooeLsH/75XkFWMQtwzz333N4wIiLFmK5BExGRIuuhhx6iYsWKNGjQgEuXLvHdd9+xb9++6y7bX5zNnTuXr776ivvvv58SJUqwbt06/ve//9GuXbts1wWKiEjBUoEmIiJFVvv27fnss8+YNWsWmZmZ1KlThzlz5mRbyEWyhISE4OTkxIQJE0hISLAtHDJu3Dizo4mIFCu6Bk1ERERERMRO6Bo0ERERERERO6ECTURERERExE7oGrQCZLVaOX36NF5eXrd0Q1QRERERESkaDMPg8uXLBAUF4eBw/fNkKtAK0OnTp6lQoYLZMURERERExE6cOHGC8uXLX3e/CrQC5OXlBWRNgre3t6lZ0tPT+eWXX2jXrh3Ozs6mZhHNhz3SnNgfzYl90XzYH82J/dGc2Bd7m4+EhAQqVKhgqxGuRwVaAbra1ujt7W0XBZqHhwfe3t528Q1a3Gk+7I/mxP5oTuyL5sP+aE7sj+bEvtjrfNzs0ictEiIiIiIiImInVKCJiIiIiIjYCRVoIiIiIiIidkIFmoiIiIiIiJ1QgSYiIiIiImInVKCJiIiIiIjYCRVoIiIiIiIidkIFmoiIiIiIiJ1QgSYiIiIiImInVKCJiIiIiIjYCRVoIiIiIiIidkIFmoiIiIiIiJ1QgSYiIiIiImInVKCJiIiIiIjYCdMLtOnTp1O5cmXc3NwICwtj06ZNNxw/b948goODcXNzo379+ixbtizbfsMwGDlyJGXLlsXd3Z3w8HAOHjyYbczbb79N8+bN8fDwwNfXN8fjHD9+nI4dO+Lh4UGZMmUYOnQoGRkZ/+q1ioiIiIiI3IipBdrcuXMZPHgwo0aNYuvWrYSGhtK+fXvOnj2b4/gNGzbQu3dvnn76abZt20aXLl3o0qULu3btso2ZMGECH330ETNmzGDjxo14enrSvn17UlJSbGPS0tLo0aMHAwYMyPE4mZmZdOzYkbS0NDZs2MDXX3/NV199xciRI/P3DRAREREREfkbUwu0Dz74gL59+9KnTx/q1KnDjBkz8PDw4Isvvshx/JQpU+jQoQNDhw6ldu3ajB07lkaNGjFt2jQg6+zZ5MmTGTFiBJ07dyYkJIRvvvmG06dPs2jRItvzjB49mpdffpn69evneJxffvmFPXv28N1339GgQQPuu+8+xo4dy/Tp00lLS8v390FEpLAzDIPIwxdYuSeW3w6c448jF9hy7CL7YhI4m5BCWobV7IgiIiKFgpNZB05LS2PLli0MHz7cts3BwYHw8HAiIyNzfExkZCSDBw/Otq19+/a24is6OpqYmBjCw8Nt+318fAgLCyMyMpJevXrlKltkZCT169cnICAg23EGDBjA7t27adiwYY6PS01NJTU11fbnhIQEANLT00lPT8/VsQvK1eObnUOyaD7sj+bk3/n2j+OMWbrvhmNKuDrh5+FMkK8b5f3cKe/rTgU/dyqX8qRGGU88XLL/k6Q5sS+aD/ujObE/mhP7Ym/zkdscphVo58+fJzMzM1sRBBAQEMC+fTn/Ix8TE5Pj+JiYGNv+q9uuNyY3rnecvx8jJ++++y6jR4++Zvsvv/yCh4dHro9fkCIiIsyOIH+j+bA/mpO8O3cFxu9wBCyU9TBwADIMyLBCSiYkZ4CBhcTUDBJTMzhx8Qoboy9mew4LBiXdIMjDoJyHQWUvqFzCwM1Jc2JvNB/2R3NifzQn9sVe5iM5OTlX40wr0Iqi4cOHZzvDl5CQQIUKFWjXrh3e3t4mJsuq2CMiImjbti3Ozs6mZhHNhz3SnNyaTKvBo5//Sbo1nuZV/fnyicY4OFiyjbFaDRJSMriYnMb5xDROx1/hZHwKJy9e4eTFZA6dS+J8YhrnU+B8ioUdcVmPc7BAWXeDu+qUo3m1UjSvVhIfd82NWfQZsT+aE/ujObEv9jYfV7vrbsa0Aq1UqVI4OjoSGxubbXtsbCyBgYE5PiYwMPCG46/+NzY2lrJly2Yb06BBg1xnCwwMvGY1yavHvV42AFdXV1xdXa/Z7uzsbBffFGBfWUTzYY80J3nz9e9H2HI8Hk8XRyb0CMXV1SXHcaVdXSjt40HN6zzP+cRU9sdcZu+ZBHadusSW4xc5EXeFU8kW5mw+zZzNp3GwQIMKvtxdszT31CpDSDmfa4pBKXj6jNgfzYn90ZzYF3uZj9xmMG2REBcXFxo3bsyqVats26xWK6tWraJZs2Y5PqZZs2bZxkPWKcur46tUqUJgYGC2MQkJCWzcuPG6z3m94+zcuTPbapIRERF4e3tTp06dXD+PiEhRdvhcIu+v2A/AGx3rUN7v1lu5S5VwpUX1UjxzV1Um92rI78Nas27o3fSpmckTzSpSo0wJrAZsPR7P5JUH6TJ9PS3Gr2bMT3vYfDQOq9XIr5clIiJiKlNbHAcPHswTTzxBkyZNaNq0KZMnTyYpKYk+ffoA8Pjjj1OuXDneffddAAYNGkSrVq2YNGkSHTt2ZM6cOWzevJmZM2cCYLFYeOmllxg3bhw1atSgSpUqvPnmmwQFBdGlSxfbcY8fP05cXBzHjx8nMzOT7du3A1C9enVKlChBu3btqFOnDo899hgTJkwgJiaGESNG8Pzzz+d4hkxEpLjJtBoMnRdFaoaVu2qUonfTCvl+jABvNxqUNLj//mCcnZ05HX+F3w6c49cD5/jtwDnOXErhi/XRfLE+mgBvVx4ICaJnkwrUCvTK9ywiIiK3i6kF2sMPP8y5c+cYOXIkMTExNGjQgOXLl9sW5Dh+/DgODv9/kq958+bMnj2bESNG8Prrr1OjRg0WLVpEvXr1bGOGDRtGUlIS/fr1Iz4+npYtW7J8+XLc3NxsY0aOHMnXX39t+/PVVRnXrFnDPffcg6OjI0uWLGHAgAE0a9YMT09PnnjiCcaMGVPQb4mISKHw+bojbD0ej5erE+O7hWCxFHyrYZCvO72aVqRX04qkpGfy24FzLNt5hpV7zxKbkMrn66L5fF00oeV96NGkAp1Cg3TNmoiIFDqmLxIycOBABg4cmOO+tWvXXrOtR48e9OjR47rPZ7FYGDNmzA2Lqa+++oqvvvrqhrkqVarEsmXLbjhGRKQ4OnT2MhN/OQDAmw/UIcjX/bZncHN2pF3dQNrVDSQ1I5Nf959jwdaTrNp7lqiTl4g6eYmxS/bQuUEQfVpUoXZZcxdqEhERyS3TCzQRESk8MjKtvDJvB2kZVu6pVZoeTcqbHQlXp/8v1s4nprJo2ym+33yCA7GJfL/5JN9vPsmdVf15qkUV2tQOwFELi4iIiB1TgSYiIrk28/cjRJ2Ix8vNifceuj2tjXlRqoQrz9xVladbVmHLsYt8uf4oy3fH8MeROP44EkdFfw8G3FONhxqVw9XJ0ey4IiIi11CBJiIiubI/5jKTIw4CMKpTXQJ93G7yCPNYLBaaVPanSWV/Tsdf4ZvIY/xv03GOxyUzfOFOPlp1kP53V6VX04q4OatQExER+2HaMvsiIlJ4pGdaGTIvirRMK22Cy9CtUTmzI+VakK87r90XTOTw1rz5QB0CvF05cymFt37aQ8vxa/js9yOkpGeaHVNERARQgSYiIrnwya+H2XnqEj7uzrzzUH27a23MDQ8XJ55uWYVfh97LuC71KOfrzvnEVMYt3UvriWuZt/kEmbqfmoiImEwFmoiI3NDeMwlMWZXV2jj6wboEeNtva2NuuDk78p87K7F26D2M71afsj5unL6UwtD5O7hvym+s3BOLYahQExERc6hAExGR60rPtPLK91GkZxq0qxNA5wZBZkfKN86ODjx8R0XWDLmH1+8PxsfdmQOxiTzzzWZ6f/oH+2ISzI4oIiLFkAo0ERG5rulrDrHnTAJ+Hs683bVwtjbejJuzI/3ursZvw+5lwD3VcHVy4I8jcXT8aB1vLd7NpeR0syOKiEgxogJNRERytOvUJaatPgTA6M71KO3lanKiguXj7syrHYJZ9Uor7qsXSKbV4KsNR7l30lr+t+m4rk8TEZHbQgWaiIhcIy0ja9XGDKvBffUC6RRS1uxIt015Pw8+/k9jZj0TRo0yJYhLSmP4wp10n7GBA7GXzY4nIiJFnAo0ERG5xrTVB9kXcxl/TxfGdqlXJFsbb6ZF9VIsG3QXIx+oQwlXJ7Ydj6fjR7/zQcQBUjO0LL+IiBQMFWgiIpLNzpOXmL72MABjO9ejVImi3dp4I86ODjzVsgorB7eibZ0A0jMNPlp1kPun/M7mo3FmxxMRkSJIBZqIiNikZmTyyrztZFoNHggpS8di1Np4I4E+bsx8rDEfP9qI0l6uHD6XRPcZkby1eLduci0iIvlKBZqIiNhMWXmQA7GJlCrhwpjO9cyOY1csFgv31S/Lypdb8XCTCgB8teEoHT/6nR0n480NJyIiRYYKNBERAWD7iXhm/JrV2jiuS338PV1MTmSffDycGd89hK/63EGZv86mPfTfDXy06iAZmVaz44mISCGnAk1EREhJz+SV77djNaBzgyA61As0O5Ldu6dWGVa8dDcd65clw2rwQcQBus+IJPp8ktnRRESkEFOBJiIifBhxgMPnkijt5cpbneqaHafQ8PN0YdojDZn8cAO83JzYfiKeBz76nR+3nzI7moiIFFIq0EREirktxy7y6e9HAHina3381NqYJxaLhS4Ny7HipbsJq+JPUlomg+ZsZ/jCHVpARERE8kwFmohIMZaSnsnQeVFYDXioUTna1gkwO1KhFeTrzqxnwnixdXUsFvjfphN0nraeQ2cTzY4mIiKFiAo0EZFibOKK/Rw5n0SAtyujHlBr47/l5OjA4Ha1+PapMEqVcGV/7GU6TV3HD9tOmh1NREQKCRVoIiLF1J9H4/h8fTQA7z0Ugo+Hs8mJio6WNUqxbFBLWlQvyZX0TF6eG8Vbi3eTrlUeRUTkJlSgiYgUQ8lpGQydF4VhQI/G5bk3uIzZkYqcMl5ufPNUGC+2qQFk3TPt0c82cu5yqsnJRETEnqlAExEphiYs38/RC8mU9XFjxAN1zI5TZDk6WBjctiafPt6EEq5ObIqOo9PUdWw/EW92NBERsVMq0EREipk/jlzgqw1HAXivWwg+7mptLGht6wSw6PkWVCvtSUxCCj1nRPL9nyfMjiUiInZIBZqISDGSlJrBsPk7AOjdtAKtapY2OVHxUb1MCRY934K2dQJIy7QybMEOxi3ZQ6bVMDuaiIjYERVoIiLFyPjl+zgel0w5X3dev7+22XGKHS83Zz75T2NeDq8JwGfroun/7RaSUjNMTiYiIvZCBZqISDGx4dB5vok8BsD4biF4uam10QwODhYGhddgau+GuDg5sHJvLD1mRHLm0hWzo4mIiB1QgSYiUgwkpmYw9K/WxkfDKtKyRimTE0mn0CD+1/dOSnq6sOdMAl2mr2fnyUtmxxIREZOpQBMRKQbeWbaXU/FXKO/nznC1NtqNxpX8WPR8C2qUKUFsQio9P4kkYk+s2bFERMREKtBERIq43w+eY/bG4wBM6B5CCVcnkxPJ31Xw92DBc825q0YprqRn0v/bzfxv03GzY4mIiElUoImIFGGXU9J59a/WxieaVaJ5NbU22iNvN2e+fPIOejYpj9WA4Qt38tGqgxiGVngUESluVKCJiBRhby/dy+lLKVT09+DV+4LNjiM34OTowPhuIQy8tzoAH0Qc4M0fd2kZfhGRYkYFmohIEbV2/1nm/HkCiwUm9gjFw0WtjfbOYrEwpH0tRj9YF4sFvvvjOANnbyUlPdPsaCIicpuoQBMRKYIuXUnntQU7AXiyeWWaVvE3OZHkxRPNKzOtdyNcHB34eVcMT3yxiYSUdLNjiYjIbaACTUSkCBq7ZA8xCSlULunBsPZqbSyMOoaU5aun7qCEqxMbo+P4z2cbuZiUZnYsEREpYCrQRESKmNX7Ypm/5aSttdHdxdHsSHKLmlcrxZx+d+Lv6cKOk5foNfMPzl5OMTuWiIgUIBVoIiJFyKXk/29tfKZlFZpUVmtjYVevnA9z+91JGS9X9sde5uFP/uB0/BWzY4mISAFRgSYiUoSM/mk3Zy+nUrW0J6+0q2V2HMknNQK8mPdsM8r5uhN9PokeMyI5diHJ7FgiIlIAVKCJiBQRv+yOYeG2Uzj81dro5qzWxqKkUklP5j3bjCqlPDkVf4UeMyI5GHvZ7FgiIpLPVKCJiBQBF5PSeP2HXQD0vbsqjSr6mZxICkKQrztz+99JrQAvzl5O5eGZf7A/RkWaiEhRogJNRKQIGLV4N+cTU6lepgQvh9c0O44UoDJebszpdyf1y/kQl5TGI5+qSBMRKUpUoImIFHLLd51hcdRpHB0sTFJrY7Hg5+nCd0+HUb+cDxf+KtIOqN1RRKRIUIEmIlKIXUhM5Y2/WhufbVWV0Aq+5gaS28bHw5nvng6jXjlvW5Gma9JERAo/FWgiIoXYyMW7uZCURq0AL15sU8PsOHKbXS3S6gZ5cz4xjd6fbuTQWRVpIiKFmQo0EZFCasmO0yzdcSartbFnKK5Oam0sjnw9XJj1TBh1ynpzPjGVXjM3cuhsotmxRETkFqlAExEphM5dTuXNRVmtjc/fU4165XxMTiRmulqk1f6rSOv96R8cPa/7pImIFEYq0EREChnDMBixaCcXk9MJDvRiYGu1NkrWwiGzngkjONCLc5dTefSzjZyOv2J2LBERySMVaCIihcziqNOs2B2L01+tjS5O+qtcsvh7uvDt02G2m1n/5/ONnE9MNTuWiIjkgf5VFxEpRM5eTmHU4t0AvNC6BnWD1Noo2ZX2cuW7Z8II8nHjyLkkHvt8E5eS082OJSIiuaQCTUSkkDAMgzd+2EV8cjp1g7x57t5qZkcSO1XO151Zfe+kVAlX9p5JoM9Xm0hKzTA7loiI5IIKNBGRQmLR9lNE7InF2TGrtdHZUX+Fy/VVKeXJt083xcfdma3H4+n37WZS0jPNjiUiIjehf91FRAqB2IQURv2Y1do4qE0NggO9TU4khUHtst581ecOPFwcWX/oAgNnbyM902p2LBERuQEVaCIids4wDIYv3ElCSgb1y/nwbCu1NkruNazox2dPNMHFyYGVe2N5feFODMMwO5aIiFyHCjQRETs3f8tJVu87i4ujA5N6huKk1kbJo+bVSjH9kUY4WGDelpNM/GW/2ZFEROQ69K+8iIgdO3PpCmOW7AHg5bY1qRngZXIiKaza1gngna71AZi+5jBfrY82OZGIiOREBZqIiJ0yDIPXFuzkckoGDSr40veuKmZHkkKuV9OKvNK2JgCjl+xhyY7TJicSEZF/UoEmImKnvt98gl8PnMPFyYGJPdTaKPljYOvqPHZnJQwDBs+NYsPh82ZHEhGRv9G/9iIiduhU/BXGLtkLwNB2tahepoTJiaSosFgsvPVgXe6rF0happV+32xh9+lLZscSEZG/qEATEbEzhmHw6vwdJKZm0LiSH0+1VGuj5C9HBwsfPtyAsCr+JKZm8OSXf3IiLtnsWCIiggo0ERG7M3vTcdYdOo+rkwPvdw/B0cFidiQpgtycHZn5eBOCA704dzmVJ7/cxKXkdLNjiYgUeyrQRETsyIm4ZN5ZmtXaOKxDMFVLq7VRCo6PuzNfP9WUsj5uHD6XxLPfbSEtQzeyFhExkwo0ERE7YbUavLpgB0lpmTSt7E+f5pXNjiTFQIC3G188eQeeLo5EHrnAawt36EbWIiImUoEmImInZm08xobDF3B3dmRC9xAc1Noot0ntst5Mf7QRjg4WFm49xdTVh8yOJCJSbKlAExGxA8cvJPPOsn0AvHZfMJVLeZqcSIqbe2qVYUznugB8EHGARdtOmZxIRKR4UoEmImIyq9VgyPworqRncmdVfx67s5LZkaSYejSsEv3urgrAsPk72HjkgsmJRESKHxVoIiIm+zryKJui4/BwcWRCt1C1NoqpXusQbLtHWv/vtnDkXKLZkUREihUVaCIiJoo+n8T45VmtjcPvr03Fkh4mJ5LizuGve6Q1qOBLfHI6fb76k7ikNLNjiYgUGyrQRERMkmk1GDovipR0Ky2ql+TRphXNjiQCZN0j7dPHm1Dez51jF5J5btYW0jO1/L6IyO2gAk1ExCRfro9m87GLeLo4Mr6bVm0U+1Lay9W2/P4fR+IYs3QfWn1fRKTgqUATETHB4XOJvL9iPwAjHqhDeT+1Nor9qRngxZReDbFYYM6fJ1kXq18iiIgUNBVoIiK3WabVYMi8KFIzrNxVoxS97qhgdiSR6wqvE8Cw9sEALIx2YMNhrewoIlKQVKCJiNxmn/1+hG3H4/FydWJ8txAsFp2VEPv2bKuqdA4tixULL86NIvp8ktmRRESKLBVoIiK30aGzl5kUcQCANx+oQ5Cvu8mJRG7OYrHwduc6VCphcOlKBs98/ScJKelmxxIRKZJML9CmT59O5cqVcXNzIywsjE2bNt1w/Lx58wgODsbNzY369euzbNmybPsNw2DkyJGULVsWd3d3wsPDOXjwYLYxcXFxPProo3h7e+Pr68vTTz9NYmL2+7ysWLGCO++8Ey8vL0qXLk23bt04evRovrxmESmeMjKtvDJvB2kZVu6pVZoeTcqbHUkk11ydHXm6ViYB3q4cPpfEC7O3kWnVqiEiIvnN1AJt7ty5DB48mFGjRrF161ZCQ0Np3749Z8+ezXH8hg0b6N27N08//TTbtm2jS5cudOnShV27dtnGTJgwgY8++ogZM2awceNGPD09ad++PSkpKbYxjz76KLt37yYiIoIlS5bw22+/0a9fP9v+6OhoOnfuTOvWrdm+fTsrVqzg/PnzPPTQQwX3ZohIkTfz9yNEnYjHy82J9x5Sa6MUPj4uMOORhrg5O/DrgXO8u2yv2ZFERIocUwu0Dz74gL59+9KnTx/q1KnDjBkz8PDw4Isvvshx/JQpU+jQoQNDhw6ldu3ajB07lkaNGjFt2jQg6+zZ5MmTGTFiBJ07dyYkJIRvvvmG06dPs2jRIgD27t3L8uXL+eyzzwgLC6Nly5ZMnTqVOXPmcPr0aQC2bNlCZmYm48aNo1q1ajRq1IghQ4awfft20tPV0iEiebc/5jKTI7LO5r/VqS6BPm4mJxK5NfXKeTOxRygAn62L5odtJ01OJCJStDiZdeC0tDS2bNnC8OHDbdscHBwIDw8nMjIyx8dERkYyePDgbNvat29vK76io6OJiYkhPDzctt/Hx4ewsDAiIyPp1asXkZGR+Pr60qRJE9uY8PBwHBwc2LhxI127dqVx48Y4ODjw5Zdf8uSTT5KYmMi3335LeHg4zs7O131NqamppKam2v6ckJAAQHp6uumF3dXjm51Dsmg+7E9Bzkl6ppVXvt9OWqaVe2uVolP9Mpr7XNDnxL78fT7a1y7NgFZV+PjXaF5bsJMq/u7UDfI2OWHxo8+I/dGc2Bd7m4/c5jCtQDt//jyZmZkEBARk2x4QEMC+fftyfExMTEyO42NiYmz7r2670ZgyZcpk2+/k5IS/v79tTJUqVfjll1/o2bMn/fv3JzMzk2bNml1zvds/vfvuu4wePfqa7b/88gseHvZxj6OIiAizI8jfaD7sT0HMyYqTFnaddsTD0eDeEjH8/PPP+X6MokyfE/tydT5qGlDb14G98fDUF5EMqZ+J5/V/hykFSJ8R+6M5sS/2Mh/Jycm5GmdagWbPYmJi6Nu3L0888QS9e/fm8uXLjBw5ku7duxMREXHd60aGDx+e7QxfQkICFSpUoF27dnh7m/ubxfT0dCIiImjbtu0NzwLK7aH5sD8FNSf7Yi4TsekPwGBM1xA6h5bNt+cu6vQ5sS85zcddrdN5aMYfHI+7wpKLZfj8sUY4OZq+/lixoc+I/dGc2Bd7m4+r3XU3Y1qBVqpUKRwdHYmNjc22PTY2lsDAwBwfExgYeMPxV/8bGxtL2bJls41p0KCBbcw/FyHJyMggLi7O9vjp06fj4+PDhAkTbGO+++47KlSowMaNG7nzzjtzzOfq6oqrq+s1252dne3imwLsK4toPuxRfs5JeqaVVxfuJj3ToF2dALo1rqCFQW6BPif25e/zUcrZmZmPN6Hr9A1sOBzH5DVHGH5fbZMTFj/6jNgfzYl9sZf5yG0G037N5eLiQuPGjVm1apVtm9VqZdWqVTRr1izHxzRr1izbeMg6ZXl1fJUqVQgMDMw2JiEhgY0bN9rGNGvWjPj4eLZs2WIbs3r1aqxWK2FhYUDW6UcHh+xvjaOjoy2jiEhuTF9ziD1nEvDzcObtrvVVnEmRFBzozfs9QgD45NcjLN1xxuREIiKFm6l9CIMHD+bTTz/l66+/Zu/evQwYMICkpCT69OkDwOOPP55tEZFBgwaxfPlyJk2axL59+3jrrbfYvHkzAwcOBLJupPnSSy8xbtw4Fi9ezM6dO3n88ccJCgqiS5cuANSuXZsOHTrQt29fNm3axPr16xk4cCC9evUiKCgIgI4dO/Lnn38yZswYDh48yNatW+nTpw+VKlWiYcOGt/dNEpFCadepS0xbfQiAMZ3rUdrr2rPrIkXFAyFB9L+7KgBD50exP+ayyYlERAovUwu0hx9+mIkTJzJy5EgaNGjA9u3bWb58uW2Rj+PHj3PmzP//Jq558+bMnj2bmTNnEhoayvz581m0aBH16tWzjRk2bBgvvPAC/fr144477iAxMZHly5fj5vb/S1rPmjWL4OBg2rRpw/3330/Lli2ZOXOmbX/r1q2ZPXs2ixYtomHDhnTo0AFXV1eWL1+Ou7v7bXhnRKQwS8uwMmReFBlWg/vrB/JAiK47k6JvaPtatKhekuS0TPp/u5lLV+xj1TQRkcLG9EVCBg4caDsD9k9r1669ZluPHj3o0aPHdZ/PYrEwZswYxowZc90x/v7+zJ49+4a5evXqRa9evW44RkQkJ1NXH2RfzGX8PV0Y07meWhulWHBydGBq70Z0mrqOoxeSeWnONj5/4g4cHPT9LyKSF1pqSUQkH+04Gc9/1x4GYGznepQqodZGKT78PV345LHGuDo5sGb/OT5afdDsSCIihY4KNBGRfJKakcmQeVFkWg0eCClLR7U2SjFUr5wP73StD8CUVQf5/eA5kxOJiBQuKtBERPLJlJUHORCbSKkSWa2NIsVVt8bl6d20AoYBg+Zs58ylK2ZHEhEpNFSgiYjkg+0n4pnxa1Zr47gu9fH3dDE5kYi5RnWqS90gb+KS0nh+1lbSM3WbGhGR3FCBJiLyL6WkZ/LK99uxGtClQRAd6gWaHUnEdG7Ojvz30UZ4uTmx9Xg87/28z+xIIiKFggo0EZF/6cOIAxw+l0RpL1feerCu2XFE7Ealkp5M6hEKwOfrovl5p25iLSJyMyrQRET+hS3H4pj5+xEA3ulaH18PtTaK/F27uoF/u4n1DqLPJ5mcSETEvqlAExG5RSnpmQydtwPDgIcalaNtnQCzI4nYpSHta9G0sj+JqRkM+G4LV9IyzY4kImK3VKCJiNyiiSv2c+R8EgHerox6QK2NItfj7OjA1EcaUqqEC/tiLjPyx11mRxIRsVsq0EREbsGfR+P4fH00AO89FIKPh7PJiUTsW4C3Gx/1boiDBeZtOcn3f54wO5KIiF1SgSYikkfJaRkMnReFYUDPJuW5N7iM2ZFECoXm1UrxSrtaALz54y72xSSYnEhExP6oQBMRyaMJy/dz9EIyZX3cGPFAHbPjiBQqA1pVo1XN0qRmWBk4exvJaRlmRxIRsSsq0ERE8uCPIxf4asNRAN7rFoK3m1obRfLCwcHCBz1DKePlyqGziYz6cbfZkURE7IoKNBGRXEpKzWDo/CgAejetQKuapU1OJFI4lSzhypRe/3892qJtp8yOJCJiN1SgiYjk0vjl+zgRd4Vyvu68fn9ts+OIFGrNqpXkhdY1AHjjh526P5qIyF9UoImI5MKGQ+f5JvIYAOO7heCl1kaRf+3FNjUIq+JPUlomz8/aSkq67o8mIqICTUTkJhJTMxg6fwcA/7mzIi1rlDI5kUjR4OhgYUqvhvh7urDnTALvLttrdiQREdOpQBMRuYl3lu3lVPwVyvu5M/w+tTaK5KdAHzcm9QwF4OvIYyzfFWNyIhERc6lAExG5gd8OnGP2xuMAvN89FE9XJ5MTiRQ999YqQ7+7qwIwbH4UJy8mm5xIRMQ8KtBERK4jISWd1xZktTY+0awSzaqVNDmRSNE1pF0tGlTwJSElgxf/t430TKvZkURETKECTUTkOt5ZupfTl1Ko6O/Bq/cFmx1HpEhzcXJgau+GeLk5sfV4PJN+OWB2JBERU6hAExHJwdr9Z5nz5wksFpjYIxQPF7U2ihS0Cv4eTOgWAsCMXw/z+8FzJicSEbn9VKCJiPzDpSvpvLZgJwB9mlehaRV/kxOJFB/31S/Lo2EVAXjl+yjiktJMTiQicnupQBMR+YexS/YQk5BClVKeDG1fy+w4IsXOiI51qF6mBGcvpzJs/g4MwzA7kojIbaMCTUTkb1bvP8f8LSexWOD97iG4uziaHUmk2HF3cWRKrwa4ODqwcm8ss/5aSVVEpDhQgSYi8pekdHjzxz0APNOyCk0qq7VRxCx1g3wY1iHrDPbYJXs4GHvZ5EQiIreHCjQRkb8sPOrA2cupVC3tySvt1NooYranWlThrhqlSM2w8uKc7aSkZ5odSUSkwKlAExEBVu49y+bzDjj8tWqjm7NaG0XM5uBgYVLPUEp6urD3TAITlu83O5KISIFTgSYixd7FpDTeXHy1tbEyjSr6mZxIRK4q4+XGhO5ZS+9/sT6atfvPmpxIRKRgqUATkWJv1OLdnE9MI9Dd4MV7q5kdR0T+oU3tAJ5oVgmAIfN2cD4x1eREIiIFRwWaiBRrP+88w+Ko0zg6WHikeiauam0UsUvD769NrQAvziemMnRelJbeF5EiSwWaiBRbFxJTGbFoFwD9WlamUgmTA4nIdbk5OzKldwNcnBxYs/8c30QeMzuSiEiBUIEmIsXWyB93cyEpjVoBXjyv1kYRuxcc6M3r9wUD8PayveyLSTA5kYhI/lOBJiLF0pIdp1m68wyOf60S5+qkvw5FCoMnmlfm3lqlScuwMuh/WnpfRIoe/UQiIsXOucupvPlXa+Pz91anXjkfkxOJSG5ZLBbe75G19P7+2Mt8EHHA7EgiIvnqlgq0jIwMVq5cySeffMLly5cBOH36NImJifkaTkQkvxmGwYhFO7mYnE7tst4MvLe62ZFEJI9KlXDlvW5ZS+9/+vsRIg9fMDmRiEj+yXOBduzYMerXr0/nzp15/vnnOXfuHADjx49nyJAh+R5QRCQ/LY46zYrdsTg5WJjYIwQXtTaKFEpt6wTQ644KGAYMmRdFQkq62ZFERPJFnn8yGTRoEE2aNOHixYu4u7vbtnft2pVVq1blazgRkfx0NiGFkT/uBuCF1jWoG6TWRpHCbMQDdajo78Gp+Cu89ddnW0SksMtzgfb7778zYsQIXFxcsm2vXLkyp06dyrdgIiL5yTAMXv9hF5eupFM3yJvntGqjSKFXwtWJD3qG4mCBhdtOsXTHGbMjiYj8a3ku0KxWK5mZ166YdPLkSby8vPIllIhIflu0/RQr98bi7Ji1aqOzo1obRYqCJpX9GXBP1i9c3li0k9iEFJMTiYj8O3n+CaVdu3ZMnjzZ9meLxUJiYiKjRo3i/vvvz89sIiL5IjYhhVF/tT+9FF6T4EBvkxOJSH4a1KYm9cp5E5+cztD5OzAMw+xIIiK3LM8F2qRJk1i/fj116tQhJSWFRx55xNbeOH78+ILIKCJyywzDYPjCnSSkZBBS3of+d1c1O5KI5DMXJwc+7NkAVycHfjtwju/+OGZ2JBGRW+aU1weUL1+eqKgo5syZw44dO0hMTOTpp5/m0UcfzbZoiIiIPZi/5SSr953FxdGBST1CcVJro0iRVCPAi9fuC2b0T3t4e9lemlcvRbXSJcyOJSKSZ3ku0ACcnJz4z3/+k99ZRETy1ZlLVxjz0x4AXm5bkxoBuk5WpCh7olllVu09y7pD5xk8dzvzBzTX9aYiUujkuUBbvHhxjtstFgtubm5Ur16dKlWq/OtgIiL/hmEYvLpgJ5dTM2hQwZe+d+nvJZGizsHBwvs9Qmj/4W9EnbzEtNWHeLltTbNjiYjkSZ4LtC5dumCxWK65APfqNovFQsuWLVm0aBF+fn75FlREJC++33yC3w6cw8XJgYlqbRQpNsr6uDOua31e/N82pq05xD21StOwon4eEZHCI88/sURERHDHHXcQERHBpUuXuHTpEhEREYSFhbFkyRJ+++03Lly4wJAhQwoir4jITZ2Kv8LYJXsBGNquFtXL6DoUkeLkwdAgHgwNItNqMPj7KJLTMsyOJCKSa3k+gzZo0CBmzpxJ8+bNbdvatGmDm5sb/fr1Y/fu3UyePJmnnnoqX4OKiOSGYRi8On8HiakZNK7kx1Mt1dooUhyN7VyPP4/GEX0+ifE/72N053pmRxIRyZU8n0E7fPgw3t7X3kPI29ubI0eOAFCjRg3Onz//79OJiOTR7E3HWXfoPG7ODrzfPQRHB4vZkUTEBD4ezozvFgLA15HHWH9IP5eISOGQ5wKtcePGDB06lHPnztm2nTt3jmHDhnHHHXcAcPDgQSpUqJB/KUVEcuFEXDJvL/2rtbF9MFW1xLZIsXZ3zdI8GlYRgGHzd3A5Jd3kRCIiN5fnAu3zzz8nOjqa8uXLU716dapXr0758uU5evQon332GQCJiYmMGDEi38OKiFyP1WowbP4OktMyaVrZnz7NK5sdSUTswOv316aCvzun4q8w7q9rU0VE7Fmer0GrVasWe/bs4ZdffuHAgQO2bW3btsXBIave69KlS76GFBG5me82HiPyyAXcnR2Z0D0EB7U2igjg6erExO6h9Pr0D+ZuPkGHeoHcG1zG7FgiItd1SzeqdnBwoEOHDnTo0CG/84iI5NnxC8m8u2wfAK/dF0zlUp4mJxIRexJWtSR9mlfhi/XRvLpgB7+8fDe+Hi5mxxIRydEtFWirVq1i1apVnD17FqvVmm3fF198kS/BRERyw2o1GDI/iivpmdxZ1Z/H7qxkdiQRsUPDOtRi7YGzHDmXxFuLdzO5V0OzI4mI5CjP16CNHj2adu3asWrVKs6fP8/FixezfYmI3E5fRx5lU3QcHi6OvN89VK2NIpIjN2dHJvUIxcECi7afZvmuM2ZHEhHJUZ7PoM2YMYOvvvqKxx57rCDyiIjkWvT5JMYvz2ptHH5/bSr4e5icSETsWcOKfjzbqhr/XXuYN37YRZPK/pQq4Wp2LBGRbPJ8Bi0tLS3bTapFRMyQaTUYOi+KlHQrLaqX5NGmFc2OJCKFwKDwGgQHenEhKY0RP+zCMAyzI4mIZJPnAu2ZZ55h9uzZBZFFRCTXvlwfzeZjF/F0cWR8N63aKCK54+rkyMQeoTg5WFi+O4bFUafNjiQikk2eWxxTUlKYOXMmK1euJCQkBGdn52z7P/jgg3wLJyKSk8PnEnl/xX4ARjxQh/J+am0UkdyrV86HF1rX4MOVB3hz0S7urFqSAG83s2OJiAC3UKDt2LGDBg0aALBr165s+ywW/QZbRApWptVgyLwoUjOs3FWjFL3uqGB2JBEphJ67txor98ay89QlXluwgy+evEM/x4iIXchzgbZmzZqCyCEikiuf/X6Ebcfj8XJ1Yny3EP1AJSK3xNnRgUk9Q3ngo3Ws2X+O7zef4OE7dC2riJgvz9egiYiY5WDsZSZFHADgzQfqEOTrbnIiESnMagZ48Uq7mgCMXbKXkxeTTU4kInKLN6revHkz33//PcePHyctLS3bvoULF+ZLMBGRv8vItDJkXhRpGVbuqVWaHk3Kmx1JRIqAZ+6qyi97Ytly7CLD5u9g1jNhOjMvIqbK8xm0OXPm0Lx5c/bu3csPP/xAeno6u3fvZvXq1fj4+BRERhERPvntCFEnL+Hl5sR7D6m1UUTyh6ODhYk9QnFzdmDD4QvM3nTc7EgiUszluUB75513+PDDD/npp59wcXFhypQp7Nu3j549e1Kxonq3RST/7Y+5zJSVBwF4q1NdAn202pqI5J8qpTwZ0q4WAO8sVaujiJgrzwXa4cOH6dixIwAuLi4kJSVhsVh4+eWXmTlzZr4HFJHiLf1qa2OmlfDaZXioUTmzI4lIEdSnRRUaV/IjKS2T4Qt36gbWImKaPBdofn5+XL58GYBy5crZltqPj48nOVm/cRKR/DVj7WF2nrqEj7sz73Str9ZGESkQjg4WJnQPwdXJgd8PnmfunyfMjiQixVSeC7S7776biIgIAHr06MGgQYPo27cvvXv3pk2bNvkeUESKrz2nE/hodVZr45jOdSmjG8mKSAGqVrqEbVXHt5fu5XT8FZMTiUhxlOdVHKdNm0ZKSgoAb7zxBs7OzmzYsIFu3boxYsSIfA8oIsVTWkZWa2N6pkG7OgE8GBpkdiQRKQaeblmVn3fFsO14PMMX7uSrPrqBtYjcXnku0Pz9/W3/7+DgwGuvvZavgUREAKavOcSeMwn4eTjztlobReQ2cXSw8H73EO7/aB2/HjjHvC0n6dmkgtmxRKQYuaX7oFmtVg4dOsTZs2exWq3Z9t199935EkxEiq9dpy4xfc0hAMZ0rkdpL1eTE4lIcVK9jBcvh9dk/PJ9jF2yh7trlNbqsSJy2+S5QPvjjz945JFHOHbs2DUrHFksFjIzM/MtnIgUP1dbGzOsBvfXD+SBkLJmRxKRYqjvXVVYvusMUScv8foPO/n8iSY6ky8it0WeFwl59tlnadKkCbt27SIuLo6LFy/avuLi4goio4gUI1NXH2RfzGVKerowtnM9/UAkIqZwcnTg/R6huDg6sHrfWRZuPWV2JBEpJvJcoB08eJB33nmH2rVr4+vri4+PT7avvJo+fTqVK1fGzc2NsLAwNm3adMPx8+bNIzg4GDc3N+rXr8+yZcuy7TcMg5EjR1K2bFnc3d0JDw/n4MGD2cbExcXx6KOP4u3tja+vL08//TSJiYnXPM/EiROpWbMmrq6ulCtXjrfffjvPr09Ecm/HyXj+u/YwAOO61KNkCbU2ioh5agZ4MSi8BgCjf9rN2YQUkxOJSHGQ5wItLCyMQ4cO5cvB586dy+DBgxk1ahRbt24lNDSU9u3bc/bs2RzHb9iwgd69e/P000+zbds2unTpQpcuXWz3YgOYMGECH330ETNmzGDjxo14enrSvn1728qTAI8++ii7d+8mIiKCJUuW8Ntvv9GvX79sxxo0aBCfffYZEydOZN++fSxevJimTZvmy+sWkWulZmTyyvdRZFoNHggpy3311dooIubrf3dV6pfzISElg9d/2KUbWItIgcvVNWg7duyw/f8LL7zAK6+8QkxMDPXr18fZ2Tnb2JCQkFwf/IMPPqBv37706dMHgBkzZrB06VK++OKLHFeHnDJlCh06dGDo0KEAjB07loiICKZNm8aMGTMwDIPJkyczYsQIOnfuDMA333xDQEAAixYtolevXuzdu5fly5fz559/0qRJEwCmTp3K/fffz8SJEwkKCmLv3r18/PHH7Nq1i1q1agFQpUqVXL8uEcm7ySsPcvBsIqVKuDCmcz2z44iIAFdbHUPoNHUdK/fGsjjqNJ0blDM7logUYbkq0Bo0aIDFYsn2W6OnnnrK9v9X9+VlkZC0tDS2bNnC8OHDbdscHBwIDw8nMjIyx8dERkYyePDgbNvat2/PokWLAIiOjiYmJobw8HDbfh8fH8LCwoiMjKRXr15ERkbi6+trK84AwsPDcXBwYOPGjXTt2pWffvqJqlWrsmTJEjp06IBhGISHhzNhwoRstxn4p9TUVFJTU21/TkhIACA9PZ309PRcvS8F5erxzc4hWTQf2W0/Ec8nv2a1No7uVBsvF8ttf280J/ZHc2JfivN8VCvpznOtqjJl9WFG/bibOyr62MXqssV5TuyV5sS+2Nt85DZHrgq06OjofxUmJ+fPnyczM5OAgIBs2wMCAti3b1+Oj4mJiclxfExMjG3/1W03GlOmTJls+52cnPD397eNOXLkCMeOHWPevHl88803ZGZm8vLLL9O9e3dWr1593df07rvvMnr06Gu2//LLL3h4eFz3cbdTRESE2RHkbzQfkG6F93c4YjUsNC5lJePoFpYdNS+P5sT+aE7sS3Gdj0pWKOfhyKnkdJ79bA1P1bRiL2sYFdc5sWeaE/tiL/ORnJycq3G5KtAqVar0r8IUNlarldTUVL755htq1qwJwOeff07jxo3Zv3+/re3xn4YPH57tDF9CQgIVKlSgXbt2eHt735bs15Oenk5ERARt27a9pi1Vbj/Nx/8bv+IAsVeOUrqECzP6tsDXw5z3Q3NifzQn9kXzAdUbX+ahGX+wI84BKjbg/vqBpubRnNgfzYl9sbf5uNpddzO5vg/ali1bGDJkCD/++OM1xcalS5fo0qULkydPJjQ0NFfPV6pUKRwdHYmNjc22PTY2lsDAnP/CCwwMvOH4q/+NjY2lbNmy2cY0aNDANuafi5BkZGQQFxdne3zZsmVxcnKyFWcAtWvXBuD48ePXLdBcXV1xdb225cHZ2dkuvinAvrKI5mPLsTg+X38UgHcfCqG0j/lnmov7nNgjzYl9Kc7zEVLRn+fvrc6UVQcZvWQvLWuWoZQdrDZbnOfEXmlO7Iu9zEduM+R6FcdJkybRunXrHM8E+fj40LZtW95///1cB3RxcaFx48asWrXKts1qtbJq1SqaNWuW42OaNWuWbTxknbK8Or5KlSoEBgZmG5OQkMDGjRttY5o1a0Z8fDxbtmyxjVm9ejVWq5WwsDAAWrRoQUZGBocPH7aNOXDgAFD8ziaKFJQraZkMmbcDw4CHGpUjvE7AzR8kImKy5++tTnCgFxeT0xn5466bP0BEJI9yXaBt3LjRtjJiTjp16sSGDRvydPDBgwfz6aef8vXXX7N3714GDBhAUlKSbVXHxx9/PNsiIoMGDWL58uVMmjSJffv28dZbb7F582YGDhwIZC1W8tJLLzFu3DgWL17Mzp07efzxxwkKCqJLly5A1pmwDh060LdvXzZt2sT69esZOHAgvXr1IigoCMhaNKRRo0Y89dRTbNu2jS1bttC/f3/atm2b7ayaiNy6ib/sJ/p8EgHerox6oK7ZcUREcsXFyYGJPUJxdLCwbGcMP+88Y3YkESlicl2gnTp1Ci8vr+vuL1GiBGfO5O0vqYcffpiJEycycuRIGjRowPbt21m+fLltkY/jx49ne87mzZsze/ZsZs6cSWhoKPPnz2fRokXUq/f/S3IPGzaMF154gX79+nHHHXeQmJjI8uXLcXNzs42ZNWsWwcHBtGnThvvvv5+WLVsyc+ZM234HBwd++uknSpUqxd13303Hjh2pXbs2c+bMydPrE5GcbYqO44v1WYsPvfdQCD4mXXcmInIr6pXzYUCragC8+eNu4pPTTE4kIkVJrq9BK126NPv377/u/cD27dtHqVKl8hxg4MCBtjNg/7R27dprtvXo0YMePXpc9/ksFgtjxoxhzJgx1x3j7+/P7Nmzb5grKCiIBQsW3HCMiORdcloGw+ZHYRjQs0l57g0uc/MHiYjYmRfaVOfnXWc4fC6JsUv2Mqln7q7BFxG5mVyfQQsPD+ftt9/OcZ9hGLz99tvZ7j8mIpKTCcv3c/RCMmV93BjxQB2z44iI3BJXJ0cmdA/FYoEFW0+ydv/Zmz9IRCQXcl2gjRgxgp07dxIWFsb3339PVFQUUVFRzJ07l7CwMHbt2sUbb7xRkFlFpJD748gFvtpwFIDx3ULwdlNro4gUXo0r+fFk88oAvPHDLhJTM8wNJCJFQq4LtGrVqrFy5UqSkpLo1asXjRo1olGjRvTu3Zvk5GQiIiKoXr16QWYVkUIsKTWDofOjAOjdtAJ31yxtciIRkX9vaPtaVPB351T8Fcb/vM/sOCJSBOT6GjSAJk2asGvXLrZv387BgwcxDIOaNWva7jEmInI97/28jxNxVyjn687r99c2O46ISL7wcHHivYdCePSzjXz7xzEeCClLWNWSZscSkUIsTwXaVQ0aNFBRJiK5tuHQeb794xiQ1dropdZGESlCWlQvRa87KjDnzxO8tnAnPw+6CzdnR7NjiUghlesWRxGRW5GYmsHQ+TsA+M+dFWlZI++rvYqI2Lvh99cmwNuV6PNJfLjygNlxRKQQU4EmIgXqnWV7ORV/hfJ+7gy/T62NIlI0+bg7M65LfQA+/e0IO07GmxtIRAotFWgiUmB+O3CO2RuPA/B+91A8XW+pq1pEpFBoWyeATqFBWA0YNn8HaRlWsyOJSCGU5wLt+PHjGIZxzXbDMDh+/Hi+hBKRwi8hJZ3XFmS1Nj7ZvDLNqumieREp+t7qVAd/Txf2xVxmxq+HzY4jIoVQngu0KlWqcO7cuWu2x8XFUaVKlXwJJSKF39tL9nL6UgqVSnowrEMts+OIiNwWJUu4MqpTHQCmrj7IgdjLJicSkcImzwWaYRhYLJZrticmJuLm5pYvoUSkcFuz/yxzN5/AYslqbfRwUWujiBQfD4YG0Sa4DOmZBsPm7yDTem3nkYjI9eT6p6bBgwcDYLFYePPNN/Hw8LDty8zMZOPGjVp6X0S4dCWd4Qt2AtCneRWaVvE3OZGIyO1lsVh4u2t9Nn3wK9tPxPPl+mieuauq2bFEpJDIdYG2bds2IOsM2s6dO3FxcbHtc3FxITQ0lCFDhuR/QhEpVMYu2UNMQgpVSnkytL1aG0WkeAr0ceP1jrUZvnAnE3/ZT3jtACqX8jQ7logUArku0NasWQNAnz59mDJlCt7e3gUWSkQKp1V7Y5m/5SQWC0zsEYK7i27UKiLFV687KvBT1Gk2HL7Aawt38L++d+Z4mYiIyN/l+Rq0L7/8UsWZiFwjPjmN4QuzWhv73lWVxpXU2igixZvFYuG9h0Jwc3bgjyNx/G/TCbMjiUghkOcCLSkpiTfffJPmzZtTvXp1qlatmu1LRIqn0T/t4ezlVKqW9mRw25pmxxERsQsVS3owpF1Wu/c7y/Zy5tIVkxOJiL3L89JqzzzzDL/++iuPPfYYZcuW1al6EWHF7hh+2HYKBwtM7BGKm7NaG0VErurTogpLd55h2/F43vhhF58/0UQ/P4nIdeW5QPv5559ZunQpLVq0KIg8IlLIXExK440fdgHQ7+5qNKroZ3IiERH74uhgYUK3EDp+tI7V+87y4/bTdGlYzuxYImKn8tzi6Ofnh7+/ri0RkSyjFu/mfGIqNcqU4KXwGmbHERGxSzUCvHihdXUARv+U9femiEhO8lygjR07lpEjR5KcnFwQeUSkEPl55xkWR53G0cGi1kYRkZt49p5qBAd6cTE5nbcW7zY7jojYqVy1ODZs2DBbr/ShQ4cICAigcuXKODs7Zxu7devW/E0oInbpQmIqIxZltTYOaFWN0Aq+5gYSEbFzzo4OvN89lC7/Xc+SHWd4MDSGdnUDzY4lInYmVwValy5dCjiGiBQ2I3/czYWkNGoFePFCm+pmxxERKRTql/eh711VmfHrYUYs2kVY1ZL4uDvf/IEiUmzkqkAbNWpUQecQkUJkyY7TLN15BkcHC5N6huLqpNZGEZHceim8Br/sjuHI+STeXrqHCd1DzY4kInYkz9egiUjxdu5yKm/+1dr4/L3VqVfOx+REIiKFi5uzI+O7h2CxwPebT7Lu4HmzI4mIHbnlVRz/+VWyZEnKlStHq1at+PLLLwsiq4iYzDAMRizaycXkdGqX9WbgvWptFBG5FXdU9ufxOysB8NrCHSSnZZicSETsRZ4LtJEjR+Lg4EDHjh0ZPXo0o0ePpmPHjjg4OPD8889Ts2ZNBgwYwKeffloQeUXERIujTrNidyxODhYm9QjFxUkn4UVEbtXQDsGU83Xn5MUrvL9iv9lxRMRO5PlG1evWrWPcuHE8++yz2bZ/8skn/PLLLyxYsICQkBA++ugj+vbtm29BRcRcZxNSGPlj1rLQL7apQZ0gb5MTiYgUbiVcnXjnofo88cUmvtpwlAdCgmhcyc/sWCJisjz/+nvFihWEh4dfs71NmzasWLECgPvvv58jR478+3QiYhcMw+D1H3Zy6Uo69cp5M+CeamZHEhEpElrVLE23RuUxDHh1wQ5SMzLNjiQiJstzgebv789PP/10zfaffvoJf39/AJKSkvDy8vr36UTELvyw7RQr957F2THrhtTOjmptFBHJL28+UJtSJVw5dDaRqasOmR1HREyW5xbHN998kwEDBrBmzRqaNm0KwJ9//smyZcuYMWMGABEREbRq1Sp/k4qIKWITUnhrcVZr40vhNQkOVGujiEh+8vVwYWznugyYtZUZvx7mvvqB1A3SCrkixVWefw3et29ffv31Vzw9PVm4cCELFy7Ew8ODX3/9laeffhqAV155hblz5+Z7WBG5vQzDYPjCnSSkZBBS3of+d1c1O5KISJF0X/2y3FcvkAyrwasLdpCRaTU7koiYJM9n0ABatGhBixYt8juLiNiZ+VtOsnrfWVwcHZjUIxQntTaKiBSY0Z3rsuHwBXadSuDT36N1va9IMZWrn7YSEhKy/f+NvkSkaDhz6QpjftoDwOB2NakRoOtKRUQKUhkvN958oA4AH648wOFziSYnEhEz5KpA8/Pz4+zZswD4+vri5+d3zdfV7SJS+BmGwasLdnI5NYOGFX3pe5daG0VEbodujcpxd83SpGVYeW3BDqxWw+xIInKb5arFcfXq1bYVGtesWVOggUTEfHP/PMFvB87h4uTA+91DcXSwmB1JRKRYsFgsvNO1Hu0+/I0/j17ku43HeLxZZbNjichtlKsC7e8rMmp1RpGi7eTFZMYt3QvA0Ha1qF6mhMmJRESKl/J+HrzaIZhRi3cz/ud9tA4uQ3k/D7NjichtcktX/P/+++/85z//oXnz5pw6dQqAb7/9lnXr1uVrOBG5vQzD4LUFO0lMzaBxJT+ealnF7EgiIsXSY3dWokklP5LSMnn9h10YhlodRYqLPBdoCxYsoH379ri7u7N161ZSU1MBuHTpEu+8806+BxSR22f2puOsO3QeN2cH3u8eotZGERGTODhYGN89BBcnB347cI6FW0+ZHUlEbpM8F2jjxo1jxowZfPrppzg7O9u2t2jRgq1bt+ZrOBG5fU7EJfP2X62Nw9oHU7W0WhtFRMxUrXQJXgqvAcCYJXs4eznF5EQicjvkuUDbv38/d9999zXbfXx8iI+Pz49MInKbWa0Gw+bvIDktk6aV/XmyeWWzI4mICND3rqrUDfLm0pV03lq82+w4InIb5LlACwwM5NChQ9dsX7duHVWrailukcLou43HiDxyAXdnR97vEYKDWhtFROyCs6MDE/5qOV+2M4blu86YHUlEClieC7S+ffsyaNAgNm7ciMVi4fTp08yaNYshQ4YwYMCAgsgoIgXo2IUk3l22D4DX7gumUklPkxOJiMjf1Q3y4dlWWb8EH7FoN/HJaSYnEpGClKtl9v/utddew2q10qZNG5KTk7n77rtxdXVlyJAhvPDCCwWRUUQKiNVqMHT+Dq6kZ3JnVX8eu7OS2ZFERCQHL7SuwfJdMRw+l8S4pXuZ2CPU7EgiUkByfQYtOjoayLqB4htvvEFcXBy7du3ijz/+4Ny5c4wdO7bAQopIwfg68iibouPwcHHk/e6ham0UEbFTbs6OTOgegsUC87ec5NcD58yOJCIFJNcFWrVq1ahSpQpPPfUU3333HefOnaNOnTo0bdqUEiW02ptIYRN9Ponxy7NaG1+/vzYV/HUTVBERe9a4kj9PNKsMwOsLs+5ZKSJFT64LtNWrV/PEE09w5MgR+vbtS8WKFalRowb9+/dnzpw5xMbGFmROEclHmVaDofOiSEm30rJ6KR4Nq2h2JBERyYWh7WtR3s+dU/FX+CDioNlxRKQA5PoatHvuuYd77rkHgJSUFDZs2MDatWtZu3YtX3/9Nenp6QQHB7N7t5aAFbF3X66PZvOxi5RwdeK9bvWxWNTaKCJSGHi6OvHuQ/V57PNNfLfpBH51zE4kIvktz6s4Ari5udG6dWtGjBjB6NGjefHFFylRogT79u3L73wiks8OnU3k/RX7AXijY23K+6m1UUSkMLmrRml6NC6PYcCcw46kpmeaHUlE8lGeCrS0tDR+++03Ro8ezb333ouvry/PPvssFy9eZNq0abaFRETEPmVaDYbOjyI1w8pdNUrR644KZkcSEZFbMKJjHUqXcOFsioVpa4+YHUdE8lGuWxxbt27Nxo0bqVKlCq1ataJ///7Mnj2bsmXLFmQ+EclHn/1+hG3H4/FydWJ8txC1NoqIFFI+Hs6M7lSH5/63nU/XHeWB0HLUK+djdiwRyQe5PoP2+++/U7JkSVq3bk2bNm1o27atijORQuRg7GUmRRwA4M1OdQjydTc5kYiI/Btt65ShQUkrmVaDYfN3kJ5pNTuSiOSDXBdo8fHxzJw5Ew8PD8aPH09QUBD169dn4MCBzJ8/n3PndD8OEXuVkWllyLwo0jKs3Fsr69oFEREp/LpVtuLr7syeMwnM/E2tjiJFQa4LNE9PTzp06MB7773Hxo0bOX/+PBMmTMDDw4MJEyZQvnx56tWrV5BZReQWffLbEaJOXsLLzYl3H1Jro4hIUeHtAm/cXwuAKSsPcuhsosmJROTfuqVVHCGrYPP398ff3x8/Pz+cnJzYu3dvfmYTkXywLyaBySuzWhvf6lSXQB83kxOJiEh+6hxalntqlSYt08qrC3aQaTXMjiQi/0KuCzSr1cqmTZuYMGEC9913H76+vjRv3pz//ve/BAYGMn36dI4c0al1EXuS/ldrY3qmQXjtMjzUqJzZkUREJJ9ZLBbe7lofTxdHthy7yDeRR82OJCL/Qq5XcfT19SUpKYnAwEDuvfdePvzwQ+655x6qVatWkPlE5F+YsfYwu04l4OPuzDtddUNqEZGiqpyvO6/dX5s3F+1iwvL9hNcOoIK/7nMpUhjlukB7//33uffee6lZs2ZB5hGRfLLndAIfrT4IwJjOdSnjrdZGEZGi7NGmFfkp6jSbouMYvnAn3z7dVL+YEymEct3i2L9/fxVnIoVEWsb/tza2rxvAg6FBZkcSEZEC5uBg4b2H6uPq5MC6Q+eZt+Wk2ZFE5Bbc8iIhImK/pq85xJ4zCfh5ODOui1obRUSKi6qlS/By26xfqI9bsoezCSkmJxKRvFKBJlLE7Dp1ielrDgEwpnM9Snu5mpxIRERup2daVqF+OR8SUjIYsWgXhqFVHUUKExVoIkVIakYmQ+ZFkWE1uL9+IA+ElDU7koiI3GZOjg6M7xaCk4OFX/bEsmxnjNmRRCQPVKCJFCFTVx1iX8xlSnq6MLZzPbU2iogUU3WCvHnunqyVtkct3sXFpDSTE4lIbt1Sgfbtt9/SokULgoKCOHbsGACTJ0/mxx9/zNdwIpJ7O07G8/GvhwEY16UeJUuotVFEpDh7vnV1apQpwfnENMYu2WN2HBHJpTwXaB9//DGDBw/m/vvvJz4+nszMTCDrPmmTJ0/O73wikgupGZm88n0UmVaDTqFB3FdfrY0iIsWdq5Mj47uHYLHAwm2nWLP/rNmRRCQX8lygTZ06lU8//ZQ33ngDR0dH2/YmTZqwc+fOfA0nIrkzeeVBDp5NpFQJV8Y8WNfsOCIiYicaVfSjT/MqALyxcCeXU9JNTiQiN5PnAi06OpqGDRtes93V1ZWkpKR8CSUiubft+EU++au18e2u9fDzdDE5kYiI2JMh7WtSwd+d05dSGL98n9lxROQm8lygValShe3bt1+zffny5dSuXTs/MolILqWkZ63aaDWgS4Mg2tcNNDuSiIjYGQ8XJ957KASA7/44zsYjF0xOJCI3kucCbfDgwTz//PPMnTsXwzDYtGkTb7/9NsOHD2fYsGEFkVFEruODiAMcPpdEaS9X3lJro4iIXEeL6qXodUcFAF5buJOU9EyTE4nI9Tjl9QHPPPMM7u7ujBgxguTkZB555BGCgoKYMmUKvXr1KoiMIpKDLcfi+PT3IwC827U+vh5qbRQRkesbfn9t1uw/S/T5JD5ceYDh96nzScQe3dIy+48++igHDx4kMTGRmJgYTp48ydNPP53f2UTkOq6kZTJk3g4MA7o1Kk94nQCzI4mIiJ3zcXdmXJf6AHz62xF2nIw3N5CI5CjPBVrr1q2Jj48HwMPDgzJlygCQkJBA69at8zWciORs4i/7iT6fRIC3KyM71TE7joiIFBJt6wTwQEhZrAYMm7+DtAyr2ZFE5B/yXKCtXbuWtLRr70afkpLC77//ni+hROT6NkXH8cX6aADe6xaCj7uzyYlERKQwGf1gXfw8nNkXc5kZf60CLCL2I9fXoO3YscP2/3v27CEmJsb258zMTJYvX065cuXyN52IZJOclsHQ+VEYBvRsUp57a5UxO5KIiBQyJUtkLSw1aM52pq4+SPu6gdQK9DI7loj8Jddn0Bo0aEDDhg2xWCy0bt2aBg0a2L4aN27MuHHjGDly5C2FmD59OpUrV8bNzY2wsDA2bdp0w/Hz5s0jODgYNzc36tevz7Jly7LtNwyDkSNHUrZsWdzd3QkPD+fgwYPZxsTFxfHoo4/i7e2Nr68vTz/9NImJiTke79ChQ3h5eeHr63tLr08kv0xYvp9jF5Ip6+PGiAfU2igiIrfmwdAg2gSXIT3TYOj8KDIy1eooYi9yXaBFR0dz+PBh29L60dHRtq9Tp06RkJDAU089lecAc+fOZfDgwYwaNYqtW7cSGhpK+/btOXv2bI7jN2zYQO/evXn66afZtm0bXbp0oUuXLuzatcs2ZsKECXz00UfMmDGDjRs34unpSfv27UlJSbGNefTRR9m9ezcREREsWbKE3377jX79+l1zvPT0dHr37s1dd92V59cmkp/+OHKBrzYcBWB8txC83dTaKCIit8ZisfDOQ/XxdnNix8lLfPLbEbMjichfcl2gVapUicqVK2O1WmnSpAmVKlWyfZUtWxZHR8dbCvDBBx/Qt29f+vTpQ506dZgxYwYeHh588cUXOY6fMmUKHTp0YOjQodSuXZuxY8fSqFEjpk2bBmSdPZs8eTIjRoygc+fOhISE8M0333D69GkWLVoEwN69e1m+fDmfffYZYWFhtGzZkqlTpzJnzhxOnz6d7XgjRowgODiYnj173tLrE8kPSalZrY0AvZtW5O6apU1OJCIihV2AtxujOmXdQ3PKyoPsj7lsciIRgVu4D9o333xzw/2PP/54rp8rLS2NLVu2MHz4cNs2BwcHwsPDiYyMzPExkZGRDB48ONu29u3b24qv6OhoYmJiCA8Pt+338fEhLCyMyMhIevXqRWRkJL6+vjRp0sQ2Jjw8HAcHBzZu3EjXrl0BWL16NfPmzWP79u0sXLjwpq8nNTWV1NRU258TEhKArLNw6enpN318Qbp6fLNzSJa8zsc7S/dyIu4K5XzdGNauuuaxAOgzYn80J/ZF82F/8mNOOtUvw09RpVh74DxD5m3n+75NcXK8pbswCfqc2Bt7m4/c5shzgTZo0KBrDpScnIyLiwseHh55KtDOnz9PZmYmAQHZ7+EUEBDAvn37cnxMTExMjuOvLlpy9b83G3P19gBXOTk54e/vbxtz4cIFnnzySb777ju8vb1z9XreffddRo8efc32X375BQ8Pj1w9R0GLiIgwO4L8TW7mY/8lC7P2ZJ2h7hyUxG+rfinoWMWaPiP2R3NiXzQf9uffzklrL9jo6MjOUwkM/WIFbcsZ+ZSs+NLnxL7Yy3wkJyfnalyeC7SLFy9es+3gwYMMGDCAoUOH5vXp7Fbfvn155JFHuPvuu3P9mOHDh2c7u5eQkECFChVo165drou8gpKenk5ERARt27bF2VnXLpktt/NxOSWD8dM2ACk80rQ8L+ueZwVGnxH7ozmxL5oP+5Ofc+JW6TTDFu5ixSknBjx4JzUDtKrjrdDnxL7Y23xc7a67mTwXaDmpUaMG7733Hv/5z3+ue+YrJ6VKlcLR0ZHY2Nhs22NjYwkMDMzxMYGBgTccf/W/sbGxlC1bNtuYBg0a2Mb8cxGSjIwM4uLibI9fvXo1ixcvZuLEiUDWtW1WqxUnJydmzpyZ44Iorq6uuLq6XrPd2dnZLr4pwL6yyM3n4/2f9nH6Ugrl/dx5o2NdnJ3z5SMrN6DPiP3RnNgXzYf9yY856XFHRZbvOcvqfWcZvmgPCwc0V6vjv6DPiX2xl/nIbYZ8++Q5OTlds8DGzbi4uNC4cWNWrVpl22a1Wlm1ahXNmjXL8THNmjXLNh6yTlteHV+lShUCAwOzjUlISGDjxo22Mc2aNSM+Pp4tW7bYxqxevRqr1UpYWBiQda3b9u3bbV9jxozBy8uL7du3265REylIvx04x/82HQfg/e6heLqqOBMRkYJhsVh4V6s6itiFPP/Et3jx4mx/NgyDM2fOMG3aNFq0aJHnAIMHD+aJJ56gSZMmNG3alMmTJ5OUlESfPn2ArEVHypUrx7vvvgtkXQPXqlUrJk2aRMeOHZkzZw6bN29m5syZQNZfMC+99BLjxo2jRo0aVKlShTfffJOgoCC6dOkCQO3atenQoQN9+/ZlxowZpKenM3DgQHr16kVQUJBtzN9t3rwZBwcH6tWrl+fXKJJXCSnpvLYg6+bwTzavTLNqJU1OJCIiRd3VVR1fmRfFlJUHCa8doBtYi5ggzwXa1SLnKovFQunSpWndujWTJk3Kc4CHH36Yc+fOMXLkSGJiYmjQoAHLly+3LfJx/PhxHBz+/0Rf8+bNmT17NiNGjOD111+nRo0aLFq0KFvhNGzYMJKSkujXrx/x8fG0bNmS5cuX4+bmZhsza9YsBg4cSJs2bXBwcKBbt2589NFHec4vUhDeXrKX05dSqFTSg2EdapkdR0REiomHGpVj6c4zrN53lqHzo9TqKGKCPBdoVmv+32l+4MCBDBw4MMd9a9euvWZbjx496NGjx3Wfz2KxMGbMGMaMGXPdMf7+/syePTvXGZ988kmefPLJXI8XuVVr9p9l7uYTWCxZrY0eLmptFBGR2+Nqq2PbD361tTo+f291s2OJFCv6lYiIHbmU/P+tjX2aV6FpFX+TE4mISHGjG1iLmCtXv5r/542hb+SDDz645TAixd2YJXuITUilSilPhrZXa6OIiJhDrY4i5slVgbZt27ZcPZnFYvlXYUSKs5V7Ylmw9SQWC0zsEYK7i6PZkUREpJhSq6OIeXJVoK1Zs6agc4gUa/HJabz+w04A+t5VlcaV1NooIiLm0qqOIub4V+eqT548ycmTJ/Mri0ixNfqnPZy9nEq10p4MblvT7DgiIiJAVqtj6+AypGVaGTo/iozM/F8sTkSyy3OBZrVaGTNmDD4+PlSqVIlKlSrh6+vL2LFjC2SFR5GibsXuGH7YdgoHC0zsEYqbs1obRUTEPugG1iK3X54LtDfeeINp06bx3nvvsW3bNrZt28Y777zD1KlTefPNNwsio0iRFZeUxht/tTb2u7saDSv6mZxIREQkO63qKHJ75blA+/rrr/nss88YMGAAISEhhISE8Nxzz/Hpp5/y1VdfFUBEkaJrzNJ9nE9Mo0aZErwUXsPsOCIiIjn6e6vjK/O2k65WR5ECk+cCLS4ujuDg4Gu2BwcHExcXly+hRIqD7RcsLN0Zg6ODRa2NIiJi1662Ovq4O7PrVALTVh8yO5JIkZXnAi00NJRp06Zds33atGmEhobmSyiRou5CUhrzjmR9/Aa0qkZoBV9zA4mIiNxEgLcbYzpntTpOW3OInScvmZxIpGjK1TL7fzdhwgQ6duzIypUradasGQCRkZGcOHGCZcuW5XtAkaJo9E97ScywUCugBC+00X1lRESkcHgwNIhfdseydOcZBn+/nZ9eaKkOEJF8luczaK1ateLAgQN07dqV+Ph44uPjeeihh9i/fz933XVXQWQUKVKW7DjNz7tjcbAYjH+oHq5O+odNREQKB4vFwtgu9ShVwpWDZxOZ9Mt+syOJFDl5PoMGEBQUxNtvv53fWUSKvHOXU3lz0S4A2pYzqBvkbXIiERGRvPH3dGF8t/o8/fVmPlsXTXjtAMKqljQ7lkiRkeczaMuXL2fdunW2P0+fPp0GDRrwyCOPcPHixXwNJ1KUGIbBiEU7uZicTnCgF+3KaQUsEREpnNrUDqBnk/IYBgyZH0ViaobZkUSKjDwXaEOHDiUhIQGAnTt3MnjwYO6//36io6MZPHhwvgcUKSoWR51mxe5YnBwsTHioHk55/vSJiIjYjzcfqEM5X3dOxF3h7aV7zY4jUmTk+UfE6Oho6tSpA8CCBQvo1KkT77zzDtOnT+fnn3/O94AiRcHZhBRG/rgbgBfb1KB2WS+TE4mIiPw7Xm7OvN8jBID/bTrOmv1nTU4kUjTkuUBzcXEhOTkZgJUrV9KuXTsA/P39bWfWROT/GYbB6z/s5NKVdOqV82bAPdXMjiQiIpIvmlcrRZ8WlQF4df4O4pPTzA0kUgTkuUBr2bIlgwcPZuzYsWzatImOHTsCcODAAcqXL5/vAUUKux+2nWLl3rM4O1qY1KMBzo7qbRQRkaLj1Q7BVC3tydnLqbZuERG5dXn+SXHatGk4OTkxf/58Pv74Y8qVKwfAzz//TIcOHfI9oEhhFnMphbcWZ/1j9VJ4TWoFqrVRRESKFjdnRz7o2QBHBwuLo06zdMcZsyOJFGp5Xma/YsWKLFmy5JrtH374Yb4EEikqDMNg+MIdJKRkEFLeh/53VzU7koiISIFoUMGX5+6pxtTVhxixaCd3VPGjjJeb2bFECqVbug9aZmYmP/zwA3v3Zq3YU7t2bbp06YKT0y09nUiRNG/LSdbsP4eLowOTeoTipNZGEREpwl5oXYPV+86y+3QCwxfs5LMnmmCxWMyOJVLo5Pknxt27d1OjRg2eeOIJfvjhB3744QeefPJJatSowa5duwoio0ihc+bSFcb+tAeAwe1qUiNArY0iIlK0uTg58EHPBrg4OrBq31nmbT5pdiSRQinPBdozzzxDvXr1OHnyJFu3bmXr1q2cOHGCkJAQ+vXrVxAZRQoVwzB4dcFOLqdm0LCiL33vUmujiIgUD7UCvXilXU0AxizZw4m4ZJMTiRQ+eS7Qtm/fzrvvvoufn59tm5+fH2+//Tbbtm3L13AihdHcP0/w24FzuDo5MLFHKI4Oau8QEZHi45m7qnJHZT8SUzMY/P12Mq2G2ZFECpU8F2g1a9YkNjb2mu1nz56levXq+RJKpLA6eTGZcUuzrs0c2r4W1UqXMDmRiIjI7eXoYOGDng0o4erEn0cvMuPXw2ZHEilUclWgJSQk2L7effddXnzxRebPn8/Jkyc5efIk8+fP56WXXmL8+PEFnVfEbmW1Nu4gMTWDJpX86NOiitmRRERETFHB34O3HqwLwIcRB9h58pLJiUQKj1wtu+jr65ttFR7DMOjZs6dtm2Fknbru1KkTmZmZBRBTxP7N2nic9Ycu4ObswITuIWptFBGRYq1bo3Ks3hfLsp0xDJq7jaUv3IW7i6PZsUTsXq4KtDVr1hR0DpFC7URcMu8sy2ptHNY+mKpqbRQRkWLOYrHwdpf6bDl2kSPnknhn2V7GdqlndiwRu5erAq1Vq1a5ejItsy/FkdVqMGz+DpLTMmla2Z8nm1c2O5KIiIhd8PN0YWKPUB77fBPf/nGM1sFluDe4jNmxROzav75z7uXLl5k5cyZNmzYlNDQ0PzKJFCrfbTxG5JELuDs78n6PEBzU2igiImJzV43SPPXXddlD50dxPjHV5EQi9u2WC7TffvuNJ554grJlyzJx4kRat27NH3/8kZ/ZROzesQtJvLtsHwDD7w+mUklPkxOJiIjYn2EdalEzoATnE9N4bcFO2/oFInKtPBVoMTExvPfee9SoUYMePXrg7e1NamoqixYt4r333uOOO+4oqJwidsdqNRg6bwdX0jO5s6o//wmrZHYkERERu+Tm7Mjkhxvi4ujAyr2x/G/TCbMjiditXBdonTp1olatWuzYsYPJkydz+vRppk6dWpDZROzaVxuOsuloHB4ujrzfPVStjSIiIjdQJ8iboe1rATB2yR6OnEs0OZGIfcp1gfbzzz/z9NNPM3r0aDp27Iijo5ZJleIr+nwSE1ZktTa+fn9tKvh7mJxIRETE/j3dsgrNqpbkSnomL8/dTnqm1exIInYn1wXaunXruHz5Mo0bNyYsLIxp06Zx/vz5gswmYpcyrQZD50WRkm6lZfVSPBpW0exIIiIihYKDg4VJPUPxdnMi6uQlpq46aHYkEbuT6wLtzjvv5NNPP+XMmTP079+fOXPmEBQUhNVqJSIigsuXLxdkThG78eX6aDYfu0gJVyfe61Y/203cRURE5MaCfN15u2t9AKatOcSWY3EmJxKxL3lexdHT05OnnnqKdevWsXPnTl555RXee+89ypQpw4MPPlgQGUXsxqGziby/Yj8AIzrWpryfWhtFRETyqlNoEF0blsNqwKA520lISTc7kojd+Ff3QatVqxYTJkzg5MmT/O9//8uvTCJ2KdNqMGReFKkZVu6uWZqH76hgdiQREZFCa3TnupT3c+fkxSu88cMuLb0v8pd/faNqAEdHR7p06cLixYvz4+lE7NKnvx9h+4l4vFydeO8htTaKiIj8G95uznzUuyGODhZ+ijrN/C0nzY4kYhfypUATKeoOxl7mg18OAPBmpzoE+bqbnEhERKTwa1TRj8FtawIwavFuDmvpfREVaCI3k5FpZci8KNIyrdxbqzQ9Gpc3O5KIiEiR8WyrajSrWpLktExe/N82UjMyzY4kYioVaCI38clvR4g6eQlvNyfefShErY0iIiL5yNHBwocPN8DPw5ndpxOYsHy/2ZFETKUCTeQG9sUkMHllVmvjWw/WJdDHzeREIiIiRU+gjxvvdw8F4PN10azZf9bkRCLmUYEmch3pf7U2pmcahNcuQ9eG5cyOJCIiUmSF1wngyeaVARjyfRRnL6eYG0jEJCrQRK7j47WH2XUqAR93Z97pqlUbRURECtpr9wUTHOjFhaQ0Xvk+CqtVS+9L8aMCTSQHu09f4qNVBwEY07kuZbzV2igiIlLQ3JwdmfZIQ9ycHfj94Hk+/f2I2ZFEbjsVaCL/kJZhZci8HWRYDdrXDeDB0CCzI4mIiBQb1ct4MapTXQDeX7GfqBPx5gYSuc1UoIn8w/Q1h9h7JgE/D2fGdVFro4iIyO3W644K3F8/kAyrwYtztnE5Jd3sSCK3jQo0kb/ZdeoS09ccAmBsl3qU9nI1OZGIiEjxY7FYeLdrCOV83Tl2IZk3ftiFYeh6NCkeVKCJ/CU1I5Mh86LIsBp0rF+WB0LU2igiImIWHw9nPurdAEcHC4ujTvO/TSfMjiRyW6hAE/nL1FWH2BdzmZKeLozpXNfsOCIiIsVe40r+DGtfC4C3ftrNntMJJicSKXgq0ESAqBPxfPzrYQDGdalHyRJqbRQREbEHfe+qSuvgMqRlWHl+9lZdjyZFngo0KfZS0rNaGzOtBp1Cg7ivflmzI4mIiMhfHBwsTOoRSpCPG9Hnkxi+cKeuR5MiTQWaFHtTVh3k4NlESpVwZcyDam0UERGxN36eLkx9pBFODhaW7DjD7E3HzY4kUmBUoEmxtu34RT75q7Xxna718PN0MTmRiIiI5KRxJT+Gdci6Hm30T3vYffqSyYlECoYKNCm2rrY2Wg3o2rAc7eoGmh1JREREbuCZllVpc/V6tFm6Hk2KJhVoUmx9EHGAw+eSKO3lyqhOdcyOIyIiIjfh4GBh4l/Xox29kKzr0aRIUoEmxdKWY3F8+vsRAN7tWh9fD7U2ioiIFAb/vB5t1kZdjyZFiwo0KXaupGUyZN4ODAO6NSpPeJ0AsyOJiIhIHjSu5MerHYIBGLNkD7tO6Xo0KTpUoEmxM/GX/USfTyLA25WRam0UEREplJ65qwrhtbOuRxswawuXknU9mhQNKtCkWNkUHccX66MBeK9bCD7uziYnEhERkVthsViY1KMBFfzdORF3hZfmbsNq1fVoUvipQJNiIzktg6HzozAMeLhJBe6tVcbsSCIiIvIv+Hg48/GjjXF1cmDN/nNMW3PI7Egi/5oKNCk2Jizfz7ELyZT1ceONB2qbHUdERETyQb1yPozrUg+AD1ceYO3+syYnEvl3VKBJsRB5+AJfbTgKwPhuIXi7qbVRRESkqOjRpAK9m1bEMOCluds5EZdsdiSRW6YCTYq8pNSs1kaA3k0rcnfN0iYnEhERkfw2qlMdQsr7EJ+cznOztpKSnml2JJFbogJNirz3ft7HyYtXKOfrzhsd1dooIiJSFLk5O/LfRxvh5+HMzlOXeGvxbrMjidwSFWhSpK0/dJ5v/zgGwITuIZRwdTI5kYiIiBSU8n4eTOnVEIsF5vx5gu//PGF2JJE8U4EmRdbllHSGzd8BwGN3VqJF9VImJxIREZGCdnfN0gwOrwnAiB936SbWUuioQJMi651l+zgVf4UK/u68dl+w2XFERETkNnn+3uq0Cc66ifWz323hYlKa2ZFEck0FmhRJvx04x/82HQdgQrdQPNXaKCIiUmw4OFj44OEGVCrpwcmLV3h+9lYyMq1mxxLJFRVoUuQkpKTz6oKs1sYnm1emWbWSJicSERGR283H3ZmZjzXBw8WRDYcv8PayvWZHEskVFWhS5Ixbsoczl1KoVNKDYR1qmR1HRERETFIr0IsPeoYC8OX6o8zfctLkRCI3pwJNipQ1+8/y/eaTWCzwfvdQPFzU2igiIlKcdahXlhfb1ADg9R92su34RZMTidyYXRRo06dPp3Llyri5uREWFsamTZtuOH7evHkEBwfj5uZG/fr1WbZsWbb9hmEwcuRIypYti7u7O+Hh4Rw8eDDbmLi4OB599FG8vb3x9fXl6aefJjEx0bZ/7dq1dO7cmbJly+Lp6UmDBg2YNWtW/r1oyXeXktN57a/WxqdaVKFpFX+TE4mIiIg9eKlNDdrWCbAtGnI2IcXsSCLXZXqBNnfuXAYPHsyoUaPYunUroaGhtG/fnrNnz+Y4fsOGDfTu3Zunn36abdu20aVLF7p06cKuXbtsYyZMmMBHH33EjBkz2LhxI56enrRv356UlP//MD766KPs3r2biIgIlixZwm+//Ua/fv2yHSckJIQFCxawY8cO+vTpw+OPP86SJUsK7s2Qf2XMkj3EJqRStZQnQ9qptVFERESyODhY+PDhBtQoU4LYhFT6f7eF1IxMs2OJ5Mj0Au2DDz6gb9++9OnThzp16jBjxgw8PDz44osvchw/ZcoUOnTowNChQ6lduzZjx46lUaNGTJs2Dcg6ezZ58mRGjBhB586dCQkJ4ZtvvuH06dMsWrQIgL1797J8+XI+++wzwsLCaNmyJVOnTmXOnDmcPn0agNdff52xY8fSvHlzqlWrxqBBg+jQoQMLFy68Le+L5M3KPbEs2PpXa2OPENxdHM2OJCIiInakhKsTnz7eBG83J7Ydj+fNRbswDMPsWCLXMPUCnbS0NLZs2cLw4cNt2xwcHAgPDycyMjLHx0RGRjJ48OBs29q3b28rvqKjo4mJiSE8PNy238fHh7CwMCIjI+nVqxeRkZH4+vrSpEkT25jw8HAcHBzYuHEjXbt2zfHYly5donbt2td9PampqaSmptr+nJCQAEB6ejrp6enXfdztcPX4ZucoCPHJ6Qxf+FdrY/NKhAR52f3rLMrzUVhpTuyP5sS+aD7sj+Yk78r5uDC5ZwjPfLuV7zefJDigBI/dWTHfnl9zYl/sbT5ym8PUAu38+fNkZmYSEBCQbXtAQAD79u3L8TExMTE5jo+JibHtv7rtRmPKlCmTbb+TkxP+/v62Mf/0/fff8+eff/LJJ59c9/W8++67jB49+prtv/zyCx4eHtd93O0UERFhdoR8981BB84lOhDgbhCcfphlyw6bHSnXiuJ8FHaaE/ujObEvmg/7oznJu04VLfx4zJFxS/dyIXo3NX3y90ya5sS+2Mt8JCcn52qclrjLhTVr1tCnTx8+/fRT6tate91xw4cPz3Z2LyEhgQoVKtCuXTu8vb1vR9TrSk9PJyIigrZt2+Ls7GxqlvwUsecsWyK342CBaY+F0aCCr9mRcqWozkdhpjmxP5oT+6L5sD+ak1t3n2HAgl38GHWGb4+4Mr9/GFVKef7r59Wc2Bd7m4+r3XU3Y2qBVqpUKRwdHYmNjc22PTY2lsDAwBwfExgYeMPxV/8bGxtL2bJls41p0KCBbcw/FyHJyMggLi7umuP++uuvdOrUiQ8//JDHH3/8hq/H1dUVV1fXa7Y7OzvbxTcF2FeWfysuKY2RP+0BoH+ratxRtbTJifKuKM1HUaE5sT+aE/ui+bA/mpNbM757KCcuXmHr8Xj6fbeNH55rgZ+nS748t+bEvtjLfOQ2g6mLhLi4uNC4cWNWrVpl22a1Wlm1ahXNmjXL8THNmjXLNh6yTlteHV+lShUCAwOzjUlISGDjxo22Mc2aNSM+Pp4tW7bYxqxevRqr1UpYWJht29q1a+nYsSPjx4/PtsKj2IdRi3dzPjGNmgEleCm8htlxREREpBBxc3bkk8eaUM7XnaMXknn2uy2kZVjNjiVi/iqOgwcP5tNPP+Xrr79m7969DBgwgKSkJPr06QPA448/nm0RkUGDBrF8+XImTZrEvn37eOutt9i8eTMDBw4EwGKx8NJLL/1fe3ceF1W9/w/8NQPMsG+yKygKgopouBDuXVAwK00lTb/lFl69avWztDT3672WljcztVXxlubNStQ0UlHcwjXZBEkURWVTkH0bmM/vD3JqAtQMOAd4PR8PHsmczxzec95zZnh1PnwGK1euxJ49e5CQkIAXX3wRLi4uGDVqFACgS5cuCAkJQVhYGM6cOYOTJ09i9uzZGD9+PFxcXADUTGscMWIEXn75ZYwZMwZZWVnIyspCXl5e0x4gqtP+hEzsjcuAgVKBd0N7QG3IVRuJiIjoz7G3UGPz5D4wVxvidFoeFkUkcGVHkpzkAW3cuHF49913sWTJEvTs2ROxsbGIjIzULfKRnp6OzMxM3fh+/fph+/bt+OSTT9CjRw988803iIiIgI+Pj27M/PnzMWfOHEyfPh19+vRBcXExIiMjYWxsrBuzbds2eHt7IzAwEE8++SQGDBiATz75RLd969atKC0txapVq+Ds7Kz7Gj16dBMcFbqfO8UVWBRR87l3Mwd3gm87a2kLIiIiombLy8kC6yc8BqUC+PrcTXxy7KrUJVErJ4tFQmbPnq27AvZH0dHRtW4LDQ1FaGhovftTKBRYsWIFVqxYUe8YW1tbbN++vd7t4eHhCA8Pr3c7SWfJ7kTklVTC28kCcwI9pC6HiIiImrknvByw5KmuWLY3CW9HXkIHOzMEd6t7PQSixib5FTSiP+P7+AzsT8iCIac2EhERUQOa1K8DXni8PYQAXt0Ri8RbBVKXRK0UAxo1G7eLKrD416mNs57wgE9bK4krIiIiopZCoVBg6dNdMdDTDmWaary09RyyCsqlLotaIQY0ahaEEFgUkYC7pRp0dbbErCc4tZGIiIgalqGBEh9O8IOHgzmyCssxecsZFJZrpC6LWhkGNGoW9sRl4MeL2bqpjSpDPnWJiIio4VmZGGHL5D6wt1DjUlYRZnL5fWpi/C2XZC+nsBxLdl8EALwc6ImuLpYSV0REREQtmautKbZM7gMzlQFOpubizW/jufw+NRkGNJI1IQQW7kpAQZkGPm0tMXNIJ6lLIiIiolbAp60VNv5fLxgoFfjuwi28d+AXqUuiVoIBjWRt14VbOJScAyMDBd4L7QkjAz5liYiIqGkM7myPVaO7AwA+PJKKbaevS1wRtQb8bZdkK6ugHMv21ExtfDWoM7ycLCSuiIiIiFqb53q74v8FdQYALI5IRFRytsQVUUvHgEayJITAgu/iUVhehR7trPD3QR2lLomIiIhaqZcDPTCutyu0Api9/QJib+RLXRK1YAxoJEs7z9/EkZTbUBkq8W5oDxhyaiMRERFJRKFQYOWzPhjiZY8yTTWmhp9Fak6x1GVRC8Xfekl2MvLL8M+9SQCAuUM7w9ORUxuJiIhIWkYGSmyY4AffdlbIK6nEi5+fxq38MqnLohaIAY1kRQiBN76NR1FFFR5zs0bYQE5tJCIiInkwUxsifEpfdLI3Q0ZBOV74/DRyiyukLotaGAY0kpUdZ2/g+OU7UP86tdFAqZC6JCIiIiIdWzMVvpjmDxcrY1y9XYLJW86iqFwjdVnUgjCgkWzcvFuKf+1LBgDMC/ZCJ3tziSsiIiIiqs3F2gRfvOSPNmYqJNwqwPT/nke5plrqsqiFYEAjWbg3tbG4ogq929tgSn93qUsiIiIiqlcne3NsndoX5mpDxFzNxZyvLqCqWit1WdQCMKCRLGw7nY6TqbkwNlJiDac2EhERUTPg09YKn03qDZWhEgeTsvHW7iRohdRVUXPHgEaSu5FXin/vr5naOD/YG+52ZhJXRERERPRwHu/YBhsm+MFAqcB3FzLwXZoSQjCl0aNjQCNJabUC876JQ2llNfp2sMXkfh2kLomIiIjoTxna1RFrxvpCoQCOZyvxduQvDGn0yBjQSFJfnLqOU1fzYGJkgDWhvlByaiMRERE1Q6P92mHlM10BAJt/uo41P6YwpNEjYUAjyVzPLcHbP1wCACx40hvt23BqIxERETVfz/Vuh7HuNas5boy+gnVRlyWuiJojBjSShFYrMG9nPMo01Qjo2Ab/599e6pKIiIiI/rKBTgILh3sBAN4/dBkbo1MlroiaGwY0kkT4T9dw5loezFQGWD2WUxuJiIio5ZjSrz3mh9SEtNWRKfjs+FWJK6LmhAGNmtzV28VY/eO9qY1d4GprKnFFRERERA3rH0M88GqQJwBg5b5kbD6RJnFF1FwwoFGTqtYKzPsmHuUaLQZ42GGiv5vUJRERERE1ilcCPfGPIZ0AACu+T8LHR69IXBE1Bwxo1KQ2n0jD+et3Ya42xNtjukOh4NRGIiIiapkUCgXmBXvh5b95AABW/XAJ67lwCD0AAxo1mdScYrx7IAUAsGhEF7Sz4dRGIiIiatkUCgXmDvPCa0M7AwDeO/gL1h7gEvxUPwY0ahLVWoHXd8ahokqLQZ3tMa6Pq9QlERERETWZOYGeeHO4NwDgg8OpeCeSIY3qxoBGTeLT41cReyMfFsaGeIdTG4mIiKgVmjG4ExY/VfNh1h8dvYKV+5IZ0qgWBjRqdJezi7D2wC8AgMVPdYWzlYnEFRERERFJY9oAd/xzlA8A4PMTaVi4KwHVWoY0+g0DGjWqqmotXtsZh8pqLZ7wskdor3ZSl0REREQkqRceb4/VY3yhVABfnbmBOV/9jIqqaqnLIplgQKNG9fGxq4i/WQBLY0OsGu3LqY1EREREAJ7r44oNE/ygMlBif0IWpoWfQ0lFldRlkQwwoFGjuZRViPcP1UxtXPZMNzhZGUtcEREREZF8DO/ujC1T+sBMZYATqXcw4bPTyCuplLoskhgDGjUKTbUWr++Mg6ZaIKiLI559rK3UJRERERHJTn8PO2wPexw2pkaIu5GP5z6OQWZBmdRlkYQY0KhRbIq+gsRbhbA2NcK/R/twaiMRERFRPXq4WmPnjAA4WxkjNacYYzfF4JfsIqnLIokwoFGDu5hRgA+iLgMAlj/TDQ4WnNpIREREdD8eDhb4ZmY/dLQ3w638MozZ9BN+Sr0jdVkkAQY0alCVVVq8vjMeVVqB4G6OeKaHi9QlERERETULba1N8O2MfujTwQZF5VWYtOUMvj1/U+qyqIkxoFGD+vBIKpIzC2FjaoSVo/iB1ERERER/ho2ZCl9M88fTPVygqRZ4bWcc3j/0Cz/QuhVhQKMGk3irABuOpAIA/jnKB/YWaokrIiIiImp+jI0MsG5cT8wc0gkA8P6hyzWfK1ullbgyagoMaNQgKqqq8frOOFRrBUZ0d8ZTvpzaSERERPSolEoF3gjxxr+f7Q4DpQLf/XwLL3zOZfhbAwY0ahDro1JxKasIbcxUWDGym9TlEBEREbUIE/zd8Pmk3jBTGeB0Wh6e+fAEkjMLpS6LGhEDGv1lcTfysenoFQDAylE+aGPOqY1EREREDWWIlwN2zeqP9m1McfNuGUZv/Ak/JGRKXRY1EgY0+kvKNb9NbXy6hwuGd3eWuiQiIiKiFqezowV2z+qPAR52KNNUY+a2n7H24C/Qarl4SEvDgEZ/yfuHLuNyTjHszNVY8QynNhIRERE1FmtTFcKn9MHU/u4AgA+iLmPGl+dRVK6RuDJqSAxo9Mh+Tr+LT47VTG3897M+sDFTSVwRERERUctmaKDEkqe7Ys1YX6gMlDiQlI2n159AUgb/Lq2lYECjR1Kuqca8nXHQCuDZx9piWDcnqUsiIiIiajVCe7vi6xkBcLEyxrXcUjy78SS+PntD6rKoATCg0SNZe/AXXLldAgcLNZY+3VXqcoiIiIhanZ6u1tj38kAM8bJHRZUW87+Nx+s741BWWS11afQXMKDRn3b+eh4+PX4VALBqdHdYm3JqIxEREZEUbMxU2DypD+YFe0GpAL45fxOjNpxEak6x1KXRI2JAoz+lrLIar++MhxDAGL92COziKHVJRERERK2aUqnArCc88OVL/rAzVyMluwhPrT+OL09dhxBc5bG5YUCjP2XNjylIu1MCR0s1lnBqIxEREZFs9Otkh/0vD8BATzuUa7RYFJGIsP+ew53iCqlLoz+BAY0e2pm0PGz5KQ0A8PYYX1iZGElcERERERH9noOlMbZO6YtFI7pAZaDEoeQchLx/HEdScqQujR4SAxo9lNLKKsz7Jg5CAON6u+IJLwepSyIiIiKiOiiVCrw0sCMiZvVHZ0dz3CmuwJQtZ7E4IhHFFVVSl0cPwIBGD2V1ZAqu55bCxcoYbz3VRepyiIiIiOgBurpYYs/sAZjcrwMA4ItT1xH8n2M4fvm2tIXRfTGg0QPFXMlF+E/XAADvjPWFpTGnNhIRERE1B8ZGBlj2TDd8Oc0f7WxMcCu/DC98fgbzv4lDQZlG6vKoDgxodF8lFTVTGwHg+b5uGOhpL3FFRERERPRnDfC0w4+vDtJdTfv63E0M+89RHLiYJW1hVAsDGt3Xqh+ScfNuGdpam+CtEZzaSERERNRcmakNseyZbvj67wFwtzNDdmEFpn9xHtPCzyI9t1Tq8uhXDGhUrxOX7+DLU+kAgNVjfWGuNpS4IiIiIiL6q/q62+KHVwZi5pBOMFQqEHUpB0P/cxTrDl1GuaZa6vJaPQY0qlNRuQZvfBsPAHjh8fbo72EncUVERERE1FCMjQzwRog3Il8diH6d2qCiSov/HPoFw/5zDFHJ2fyAawkxoFGd/r3/Em7ll8HV1gRvDveWuhwiIiIiagQeDhbY9pI/PpzwGBwt1UjPK8W0recw4dPTSLhZIHV5rRIDGtVy7Jfb+OpMzdTGNWN7wIxTG4mIiIhaLIVCgad8XRD12hDMGNwJKkMlYq7m4ukPT+CVHRdwI49/n9aUGNBIT+HvpjZO7tcBj3dsI3FFRERERNQUzNWGeHO4Nw6/NhijH2sLANgdm4HA945ixd4k5BSWS1xh68CARnpWfp+EzIJytG9jivkhXlKXQ0RERERNrJ2NKdaO64nv5wxAf482qKzWYvPJNAxcfQTL915kUGtkDGikc+RSDr4+dxMKRc3URlMVpzYSERERtVY+ba3w5TR//HdqX/i5WaOiSostJ69hwOojWLbnIjLyy6QusUXib+AEACgo1eDN72qmNk7t746+7rYSV0REREREUlMoFBjU2R4DPe1wIvUO3j90Geev30X4T9fwxanrGNHdGS8NdIdvO2upS20xGNAIALDi+yRkF1ago50ZXh/GqY1ERERE9BuFQoGBnvYY4GGHk6m5+PDIZZy6moc9cRnYE5eBvh1sMXWAO4K6OMDQgJP0/goGNMKhpGx8+/NNKBXAmtAeMFEZSF0SEREREcmQQqHAAE87DPC0Q+KtAmw+kYY9cRk4cy0PZ67lwdFSjdBerhjXxxWutqZSl9ssMd62cvmllViwKwEAEDawI3q1t5G4IiIiIiJqDnzaWmHtuJ448cbfMHNIJ9iaqZBdWIEPj6Ri4OojeOHz09gdewullVVSl9qs8ApaK7dsz0XcLqpAJ3sz/L+hnaUuh4iIiIiaGScrY7wR4o1XgzxxKCkHO86m4/jlO7ovEyMD/K2LA572dcEQL3sYG3G21v0woLVikYlZiIjNgFIBvBvagycLERERET0ytaEBRvg6Y4SvM27kleLrczewOzYD6Xml2BefiX3xmTBXG2JwZ3sM8bLHEC8H2FuopS5bdhjQWqm8kkosiqiZ2vj3wZ3wmBunNhIRERFRw3C1NcVrw7wwd2hnJNwqwN64DOyLz0RGQTn2JWRiX0ImAMC3nRUGd7ZHX3db+LnZwEzNeMIj0Eot3XMRd4or0dnRHK8GeUpdDhERERG1QAqFAr7trOHbzhoLhndB3M18HLmUgyMpt5FwqwDxN2u+AMBAqYCPiyX6dLCFr6s1ujpbwt3ODAZKhcSPomkxoLVC+xMysTcuAwZKBd4N7QG1Iac2EhEREVHjUioVeMzNBo+52WDuMC/kFJUjOuU2Yq7k4kxaHm7llyHuZgHifg1sAGBspIS3kyW8nSzg1sYUHdqYwc3WFO3bmMLC2EjCR9N4GNBamdziCiyKSAQA/GNIJ36oIBERERFJwsHCGM/1dsVzvV0BABn5ZTh7LQ9nr+XhYkYhLmUWoUxTjdgb+Yi9kV/r/iZGBmhjrkIbczXszFSwMDaEicoAakMDGBsZwEgpkHpDAY/sInRrZ9vEj+7RMaC1IkIAS/cmI6+kEt5OFpjzN05tJCIiIiJ5cLE2wciebTGyZ1sAQLVW4FpuCS5mFCI1pxjpuSW4nleK9NxS5JZUokxTjZt3y3Dzbtl99mqA4JwSBrQ/a8OGDVizZg2ysrLQo0cPrF+/Hn379q13/M6dO7F48WJcu3YNnp6eeOedd/Dkk0/qtgshsHTpUnz66afIz89H//79sWnTJnh6/hZI8vLyMGfOHOzduxdKpRJjxozBunXrYG5urhsTHx+PWbNm4ezZs7C3t8ecOXMwf/78xjkITeBCrgI/Xs6B4a9TG1WG/Bg8IiIiIpInA6UCnezN0cnevNa2kooq5BZX4k5JRc1/iytQXF6FMk01yjXVKNdoUVapwfX0dLjZmkhQ/aOTPKD973//w9y5c/HRRx/B398f77//PoKDg5GSkgIHB4da43/66Sc8//zzWLVqFZ566ils374do0aNws8//wwfHx8AwOrVq/HBBx9g69atcHd3x+LFixEcHIykpCQYGxsDACZOnIjMzEwcPHgQGo0GU6ZMwfTp07F9+3YAQGFhIYYNG4agoCB89NFHSEhIwNSpU2FtbY3p06c33QFqIHeKK/BNWk0gm/WEB3zaWklcERERERHRozFTG8JMbQi3Nqb1jtFoNNi//xq6N7PfeyW/hLJ27VqEhYVhypQp6Nq1Kz766COYmppi8+bNdY5ft24dQkJCMG/ePHTp0gX//Oc/4efnhw8//BBAzdWz999/H4sWLcLIkSPh6+uL//73v8jIyEBERAQAIDk5GZGRkfjss8/g7++PAQMGYP369dixYwcyMjIAANu2bUNlZSU2b96Mbt26Yfz48Xj55Zexdu3aJjkuDUkIgSV7klFSpUAXJwvMesJD6pKIiIiIiKgOkl5Bq6ysxPnz57FgwQLdbUqlEkFBQYiJianzPjExMZg7d67ebcHBwbrwlZaWhqysLAQFBem2W1lZwd/fHzExMRg/fjxiYmJgbW2N3r1768YEBQVBqVTi9OnTePbZZxETE4NBgwZBpVLp/Zx33nkHd+/ehY1N7c8Nq6ioQEVFhe77wsJCADXpXaPR/Ikj07D2xGXiYHIODBQC/3rGGwpRDY2mWrJ6CLrng5TPC9LHnsgPeyIv7If8sCfyw57Ii9z68bB1SBrQ7ty5g+rqajg6Ourd7ujoiEuXLtV5n6ysrDrHZ2Vl6bbfu+1+Y/44fdLQ0BC2trZ6Y9zd3Wvt4962ugLaqlWrsHz58lq3HzhwAKam9V9+bWy3SwFXMwN0t9XiRkIMbiRIVgr9wcGDB6Uugf6APZEf9kRe2A/5YU/khz2RF7n0o7S09KHGSf43aC3JggUL9K7uFRYWwtXVFcOGDYOlpaWElQETKipw6FAUhg4dCiOjlvmZEc2JRqPBwYMH2Q8ZYU/khz2RF/ZDftgT+WFP5EVu/bg3u+5BJA1odnZ2MDAwQHZ2tt7t2dnZcHJyqvM+Tk5O9x1/77/Z2dlwdnbWG9OzZ0/dmJycHL19VFVVIS8vT28/df2c3/+MP1Kr1VCr1bVuNzIyksWTwkAhn1qoBvshP+yJ/LAn8sJ+yA97Ij/sibzIpR8PW4Oki4SoVCr06tULUVFRutu0Wi2ioqIQEBBQ530CAgL0xgM1ly3vjXd3d4eTk5PemMLCQpw+fVo3JiAgAPn5+Th//rxuzOHDh6HVauHv768bc+zYMb25ogcPHoSXl1ed0xuJiIiIiIj+KslXcZw7dy4+/fRTbN26FcnJyZg5cyZKSkowZcoUAMCLL76ot4jIK6+8gsjISLz33nu4dOkSli1bhnPnzmH27NkAAIVCgVdffRUrV67Enj17kJCQgBdffBEuLi4YNWoUAKBLly4ICQlBWFgYzpw5g5MnT2L27NkYP348XFxcAAATJkyASqXCtGnTcPHiRfzvf//DunXrai1QQkRERERE1FAk/xu0cePG4fbt21iyZAmysrLQs2dPREZG6hbkSE9Ph1L5W47s168ftm/fjkWLFmHhwoXw9PRERESE7jPQAGD+/PkoKSnB9OnTkZ+fjwEDBiAyMlL3GWhAzTL6s2fPRmBgoO6Dqj/44APddisrKxw4cACzZs1Cr169YGdnhyVLljTLz0AjIiIiIqLmQfKABgCzZ8/WXQH7o+jo6Fq3hYaGIjQ0tN79KRQKrFixAitWrKh3jK2tre5Dqevj6+uL48eP33cMERERERFRQ5F8iiMRERERERHVYEAjIiIiIiKSCQY0IiIiIiIimWBAIyIiIiIikgkGNCIiIiIiIplgQCMiIiIiIpIJBjQiIiIiIiKZYEAjIiIiIiKSCQY0IiIiIiIimWBAIyIiIiIikgkGNCIiIiIiIplgQCMiIiIiIpIJBjQiIiIiIiKZMJS6gJZMCAEAKCwslLgSQKPRoLS0FIWFhTAyMpK6nFaP/ZAf9kR+2BN5YT/khz2RH/ZEXuTWj3uZ4F5GqA8DWiMqKioCALi6ukpcCRERERERyUFRURGsrKzq3a4QD4pw9Mi0Wi0yMjJgYWEBhUIhaS2FhYVwdXXFjRs3YGlpKWktxH7IEXsiP+yJvLAf8sOeyA97Ii9y64cQAkVFRXBxcYFSWf9fmvEKWiNSKpVo166d1GXosbS0lMUTlGqwH/LDnsgPeyIv7If8sCfyw57Ii5z6cb8rZ/dwkRAiIiIiIiKZYEAjIiIiIiKSCQa0VkKtVmPp0qVQq9VSl0JgP+SIPZEf9kRe2A/5YU/khz2Rl+baDy4SQkREREREJBO8gkZERERERCQTDGhEREREREQywYBGREREREQkEwxoREREREREMsGA1gps2LABHTp0gLGxMfz9/XHmzBmpS2oRli1bBoVCoffl7e2t215eXo5Zs2ahTZs2MDc3x5gxY5Cdna23j/T0dIwYMQKmpqZwcHDAvHnzUFVVpTcmOjoafn5+UKvV8PDwQHh4eFM8vGbh2LFjePrpp+Hi4gKFQoGIiAi97UIILFmyBM7OzjAxMUFQUBAuX76sNyYvLw8TJ06EpaUlrK2tMW3aNBQXF+uNiY+Px8CBA2FsbAxXV1esXr26Vi07d+6Et7c3jI2N0b17d+zfv7/BH6/cPagfkydPrnXOhISE6I1hPxrOqlWr0KdPH1hYWMDBwQGjRo1CSkqK3pimfJ3ie9HD9WTIkCG1zpMZM2bojWFPGs6mTZvg6+ur+yDjgIAA/PDDD7rtPEea1oP60WrOD0Et2o4dO4RKpRKbN28WFy9eFGFhYcLa2lpkZ2dLXVqzt3TpUtGtWzeRmZmp+7p9+7Zu+4wZM4Srq6uIiooS586dE48//rjo16+fbntVVZXw8fERQUFB4sKFC2L//v3Czs5OLFiwQDfm6tWrwtTUVMydO1ckJSWJ9evXCwMDAxEZGdmkj1Wu9u/fL9566y3x3XffCQBi165detvffvttYWVlJSIiIkRcXJx45plnhLu7uygrK9ONCQkJET169BCnTp0Sx48fFx4eHuL555/XbS8oKBCOjo5i4sSJIjExUXz11VfCxMREfPzxx7oxJ0+eFAYGBmL16tUiKSlJLFq0SBgZGYmEhIRGPwZy8qB+TJo0SYSEhOidM3l5eXpj2I+GExwcLLZs2SISExNFbGysePLJJ4Wbm5soLi7WjWmq1ym+F9V4mJ4MHjxYhIWF6Z0nBQUFuu3sScPas2eP2Ldvn/jll19ESkqKWLhwoTAyMhKJiYlCCJ4jTe1B/Wgt5wcDWgvXt29fMWvWLN331dXVwsXFRaxatUrCqlqGpUuXih49etS5LT8/XxgZGYmdO3fqbktOThYARExMjBCi5pdZpVIpsrKydGM2bdokLC0tRUVFhRBCiPnz54tu3brp7XvcuHEiODi4gR9N8/fHQKDVaoWTk5NYs2aN7rb8/HyhVqvFV199JYQQIikpSQAQZ8+e1Y354YcfhEKhELdu3RJCCLFx40ZhY2Oj64kQQrzxxhvCy8tL9/1zzz0nRowYoVePv7+/+Pvf/96gj7E5qS+gjRw5st77sB+NKycnRwAQR48eFUI07esU34vq9seeCFHzC+grr7xS733Yk8ZnY2MjPvvsM54jMnGvH0K0nvODUxxbsMrKSpw/fx5BQUG625RKJYKCghATEyNhZS3H5cuX4eLigo4dO2LixIlIT08HAJw/fx4ajUbv2Ht7e8PNzU137GNiYtC9e3c4OjrqxgQHB6OwsBAXL17Ujfn9Pu6NYf8eLC0tDVlZWXrHz8rKCv7+/no9sLa2Ru/evXVjgoKCoFQqcfr0ad2YQYMGQaVS6cYEBwcjJSUFd+/e1Y1hnx5OdHQ0HBwc4OXlhZkzZyI3N1e3jf1oXAUFBQAAW1tbAE33OsX3ovr9sSf3bNu2DXZ2dvDx8cGCBQtQWlqq28aeNJ7q6mrs2LEDJSUlCAgI4DkisT/2457WcH4YNslPIUncuXMH1dXVek9SAHB0dMSlS5ckqqrl8Pf3R3h4OLy8vJCZmYnly5dj4MCBSExMRFZWFlQqFaytrfXu4+joiKysLABAVlZWnb25t+1+YwoLC1FWVgYTE5NGenTN371jWNfx+/3xdXBw0NtuaGgIW1tbvTHu7u619nFvm42NTb19urcPqhESEoLRo0fD3d0dV65cwcKFCzF8+HDExMTAwMCA/WhEWq0Wr776Kvr37w8fHx8AaLLXqbt37/K9qA519QQAJkyYgPbt28PFxQXx8fF44403kJKSgu+++w4Ae9IYEhISEBAQgPLycpibm2PXrl3o2rUrYmNjeY5IoL5+AK3n/GBAI3pEw4cP1/3b19cX/v7+aN++Pb7++msGJ6I6jB8/Xvfv7t27w9fXF506dUJ0dDQCAwMlrKzlmzVrFhITE3HixAmpS6Ff1deT6dOn6/7dvXt3ODs7IzAwEFeuXEGnTp2ausxWwcvLC7GxsSgoKMA333yDSZMm4ejRo1KX1WrV14+uXbu2mvODUxxbMDs7OxgYGNRabSg7OxtOTk4SVdVyWVtbo3PnzkhNTYWTkxMqKyuRn5+vN+b3x97JyanO3tzbdr8xlpaWDIEPcO8Y3u/57+TkhJycHL3tVVVVyMvLa5A+8Ty7v44dO8LOzg6pqakA2I/GMnv2bHz//fc4cuQI2rVrp7u9qV6n+F5UW309qYu/vz8A6J0n7EnDUqlU8PDwQK9evbBq1Sr06NED69at4zkikfr6UZeWen4woLVgKpUKvXr1QlRUlO42rVaLqKgovbm81DCKi4tx5coVODs7o1evXjAyMtI79ikpKUhPT9cd+4CAACQkJOj9Qnrw4EFYWlrqLuUHBATo7ePeGPbvwdzd3eHk5KR3/AoLC3H69Gm9HuTn5+P8+fO6MYcPH4ZWq9W96AcEBODYsWPQaDS6MQcPHoSXlxdsbGx0Y9inP+/mzZvIzc2Fs7MzAPajoQkhMHv2bOzatQuHDx+uNTW0qV6n+F70mwf1pC6xsbEAoHeesCeNS6vVoqKigueITNzrR11a7PnRJEuRkGR27Ngh1Gq1CA8PF0lJSWL69OnC2tpab3UbejSvvfaaiI6OFmlpaeLkyZMiKChI2NnZiZycHCFEzdK8bm5u4vDhw+LcuXMiICBABAQE6O5/bynYYcOGidjYWBEZGSns7e3rXAp23rx5Ijk5WWzYsIHL7P9OUVGRuHDhgrhw4YIAINauXSsuXLggrl+/LoSoWWbf2tpa7N69W8THx4uRI0fWucz+Y489Jk6fPi1OnDghPD099ZZ1z8/PF46OjuKFF14QiYmJYseOHcLU1LTWsu6Ghobi3XffFcnJyWLp0qWtcln3+/WjqKhIvP766yImJkakpaWJQ4cOCT8/P+Hp6SnKy8t1+2A/Gs7MmTOFlZWViI6O1luSurS0VDemqV6n+F5U40E9SU1NFStWrBDnzp0TaWlpYvfu3aJjx45i0KBBun2wJw3rzTffFEePHhVpaWkiPj5evPnmm0KhUIgDBw4IIXiONLX79aM1nR8MaK3A+vXrhZubm1CpVKJv377i1KlTUpfUIowbN044OzsLlUol2rZtK8aNGydSU1N128vKysQ//vEPYWNjI0xNTcWzzz4rMjMz9fZx7do1MXz4cGFiYiLs7OzEa6+9JjQajd6YI0eOiJ49ewqVSiU6duwotmzZ0hQPr1k4cuSIAFDra9KkSUKImqX2Fy9eLBwdHYVarRaBgYEiJSVFbx+5ubni+eefF+bm5sLS0lJMmTJFFBUV6Y2Ji4sTAwYMEGq1WrRt21a8/fbbtWr5+uuvRefOnYVKpRLdunUT+/bta7THLVf360dpaakYNmyYsLe3F0ZGRqJ9+/YiLCys1psd+9Fw6uoFAL3XkKZ8neJ70YN7kp6eLgYNGiRsbW2FWq0WHh4eYt68eXqf8yQEe9KQpk6dKtq3by9UKpWwt7cXgYGBunAmBM+Rpna/frSm80MhhBBNc62OiIiIiIiI7od/g0ZERERERCQTDGhEREREREQywYBGREREREQkEwxoREREREREMsGARkREREREJBMMaERERERERDLBgEZERERERCQTDGhEREREREQywYBGREREREQkEwxoRERED+n27duYOXMm3NzcoFar4eTkhODgYJw8eRIAoFAoEBERIW2RRETUrBlKXQAREVFzMWbMGFRWVmLr1q3o2LEjsrOzERUVhdzcXKlLIyKiFkIhhBBSF0FERCR3+fn5sLGxQXR0NAYPHlxre4cOHXD9+nXd9+3bt8e1a9cAALt378by5cuRlJQEFxcXTJo0CW+99RYMDWv+P6lCocDGjRuxZ88eREdHw9nZGatXr8bYsWOb5LEREZF8cIojERHRQzA3N4e5uTkiIiJQUVFRa/vZs2cBAFu2bEFmZqbu++PHj+PFF1/EK6+8gqSkJHz88ccIDw/Hv/71L737L168GGPGjEFcXBwmTpyI8ePHIzk5ufEfGBERyQqvoBERET2kb7/9FmFhYSgrK4Ofnx8GDx6M8ePHw9fXF0DNlbBdu3Zh1KhRuvsEBQUhMDAQCxYs0N325ZdfYv78+cjIyNDdb8aMGdi0aZNuzOOPPw4/Pz9s3LixaR4cERHJAq+gERERPaQxY8YgIyMDe/bsQUhICKKjo+Hn54fw8PB67xMXF4cVK1borsCZm5sjLCwMmZmZKC0t1Y0LCAjQu19AQACvoBERtUJcJISIiOhPMDY2xtChQzF06FAsXrwYL730EpYuXYrJkyfXOb64uBjLly/H6NGj69wXERHR7/EKGhER0V/QtWtXlJSUAACMjIxQXV2tt93Pzw8pKSnw8PCo9aVU/vY2fOrUKb37nTp1Cl26dGn8B0BERLLCK2hEREQPITc3F6GhoZg6dSp8fX1hYWGBc+fOYfXq1Rg5ciSAmpUco6Ki0L9/f6jVatjY2GDJkiV46qmn4ObmhrFjx0KpVCIuLg6JiYlYuXKlbv87d+5E7969MWDAAGzbtg1nzpzB559/LtXDJSIiiXCRECIioodQUVGBZcuW4cCBA7hy5Qo0Gg1cXV0RGhqKhQsXwsTEBHv37sXcuXNx7do1tG3bVrfM/o8//ogVK1bgwoULMDIygre3N1566SWEhYUBqFkkZMOGDYiIiMCxY8fg7OyMd955B88995yEj5iIiKTAgEZERCSxulZ/JCKi1ol/g0ZERERERCQTDGhEREREREQywUVCiIiIJMa/NiAiont4BY2IiIiIiEgmGNCIiIiIiIhkggGNiIiIiIhIJhjQiIiIiIiIZIIBjYiIiIiISCYY0IiIiIiIiGSCAY2IiIiIiEgmGNCIiIiIiIhk4v8DU3nRafW56VYAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_changes(exp32_changes)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_accumulated_changes(exp32_changes)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "exp35_total_change, exp35_changes, exp35_gradients = simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=1.0e-05,\n",
+    "    lr_warmup_steps=4000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=16000,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), 20000, l2_norm_gradient=0.01)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.1800048199951668"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "exp35_total_change"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_changes(exp35_changes)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_changes(exp35_gradients)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Lama3 Finetuning"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.0048819951180015"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=1.0e-5,\n",
+    "    lr_warmup_steps=1994,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=3976,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=5970, l2_norm_gradient=0.01)[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Exp 52"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2.5200024799975047"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.001,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=5000, l2_norm_gradient=0.01)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.595004986708305"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.00015,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=20000, l2_norm_gradient=1.2)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.595004920249768"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.00015,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=20000, l2_norm_gradient=0.2)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.24500475499524452"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.000015,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=20000, l2_norm_gradient=0.01)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.0950039049960907"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.0001,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=20000, l2_norm_gradient=0.01)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "10.09499490500511"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.001,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=20000, l2_norm_gradient=0.01)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "7.519997480002516"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.003,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=5000, l2_norm_gradient=0.01)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "20.09500299049971"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.002,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=20000, l2_norm_gradient=0.1)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "30.095001990499778"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.003,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=20000, l2_norm_gradient=0.1)[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Exp 56"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "31.3700018630001"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.0025,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=25000, l2_norm_gradient=0.1)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "62.61994238005785"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulate_adam_update(LRSchedulerArgs(\n",
+    "    learning_rate=0.005,\n",
+    "    lr_warmup_steps=1000,\n",
+    "    lr_warmup_style=\"linear\",\n",
+    "    lr_decay_style=\"cosine\",\n",
+    "    lr_decay_steps=None,\n",
+    "    lr_decay_starting_step=None,\n",
+    "    min_decay_lr=1.0e-05\n",
+    "), total_steps=25000, l2_norm_gradient=0.01)[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Exp 57"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Sigmoid Behavior"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "\n",
+    "def sigmoid(x):\n",
+    "    return 1 / (1 + np.exp(-x))\n",
+    "\n",
+    "x = np.linspace(-5, 5, 100)\n",
+    "y = sigmoid(x)\n",
+    "\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "plt.plot(x, y)\n",
+    "plt.title('Sigmoid Function')\n",
+    "plt.xlabel('x')\n",
+    "plt.ylabel('sigmoid(x)')\n",
+    "plt.grid(True)\n",
+    "plt.axhline(y=0, color='k')\n",
+    "plt.axvline(x=0, color='k')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([0.4992, 0.5008])"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F.sigmoid(torch.tensor([-0.003, 0.003]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([0.3775, 0.6225])"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F.sigmoid(torch.tensor([-0.5, 0.5]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([0.2891, 0.7109])"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F.sigmoid(torch.tensor([-0.9, 0.9]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([0.2891, 0.7109])"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F.sigmoid(torch.tensor([-0.9, 0.9]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([0.1192, 0.8808])"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F.sigmoid(torch.tensor([-2, 2]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/infinite-context-length/data/exp34/debug_balance_factors.ipynb b/examples/infinite-context-length/data/exp34/debug_balance_factors.ipynb
new file mode 100644
index 00000000..3560ef24
--- /dev/null
+++ b/examples/infinite-context-length/data/exp34/debug_balance_factors.ipynb
@@ -0,0 +1,14842 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import safetensors\n",
+    "import torch\n",
+    "from matplotlib.colors import Normalize\n",
+    "from matplotlib.patches import Rectangle\n",
+    "import torch.nn.functional as F"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# exp 55\n",
+    "# base_path = \"/fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp55_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.001/ckp_for_evals/20000/model/model/decoder\"\n",
+    "# num_layers = 32\n",
+    "# tp_world_size = 4\n",
+    "# ckp_name = \"exp55: 8b llama3 at 20k ckp\"\n",
+    "\n",
+    "# exp 51\n",
+    "# base_path = \"/fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp51_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs_and_global_lr_0.0000375_and_balance_factor_lr_0.00015/checkpoints/10000/model/model/decoder\"\n",
+    "# num_layers = 5\n",
+    "# tp_world_size = 2\n",
+    "# ckp_name = \"exp51: 200m llama at 10k ckp\"\n",
+    "\n",
+    "base_path = \"/fsx/phuc/new_workspace/experiments/exp57_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.01_and_balance_factor_0_weight_decay/checkpoints/18000/model/model/decoder\"\n",
+    "num_layers = 32\n",
+    "tp_world_size = 4\n",
+    "ckp_name = \"exp57: 8b llama3, 1024 ctxlen, 64 segment len, 100k bs, 0.01 balance factor lr, no weight decay for balance factors\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged_tensors = []\n",
+    "\n",
+    "for layer_idx in range(num_layers):  # 0 to 31\n",
+    "    layer_tensors = []\n",
+    "    for tp_rank in range(tp_world_size):\n",
+    "        file_path = os.path.join(base_path, f\"{layer_idx}/pp_block/attn/model_balance_factors_pp-rank-0-of-1_tp-rank-{tp_rank}-of-{tp_world_size}.safetensors\")\n",
+    "        \n",
+    "        if os.path.exists(file_path):\n",
+    "            tensor = safetensors.safe_open(file_path, framework=\"pt\", device=\"cpu\")\n",
+    "            tensor_data = tensor.get_tensor(\"data\").to(torch.float32).numpy()\n",
+    "            layer_tensors.append(tensor_data)\n",
+    "    \n",
+    "    if layer_tensors:\n",
+    "        merged_tensor = np.concatenate(layer_tensors)\n",
+    "        merged_tensors.append(merged_tensor)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[array([-2.015625  , -2.        , -2.703125  , -2.75      , -1.7578125 ,\n",
+       "        -1.8515625 , -2.        , -1.6328125 , -1.7421875 , -0.70703125,\n",
+       "        -1.984375  , -0.859375  , -1.328125  , -1.1640625 , -0.9296875 ,\n",
+       "        -0.34375   , -1.3984375 , -0.90234375, -1.3125    , -1.28125   ,\n",
+       "        -1.1953125 , -1.1796875 , -1.296875  , -1.640625  , -2.0625    ,\n",
+       "        -1.5078125 , -1.9453125 , -1.421875  , -1.9375    , -2.        ,\n",
+       "        -2.        , -1.984375  ], dtype=float32),\n",
+       " array([-1.734375  , -1.59375   , -1.171875  , -1.515625  , -1.984375  ,\n",
+       "        -2.        , -1.625     , -1.140625  , -0.78125   , -0.59765625,\n",
+       "        -1.7109375 , -1.0546875 ,  0.23535156, -1.984375  , -1.890625  ,\n",
+       "        -1.4609375 , -2.        , -1.4453125 , -2.        , -1.6171875 ,\n",
+       "        -2.        , -2.        , -1.03125   , -1.3203125 , -2.        ,\n",
+       "        -1.9765625 , -2.015625  , -1.734375  , -0.40625   , -0.70703125,\n",
+       "        -1.015625  , -1.203125  ], dtype=float32),\n",
+       " array([-2.046875  , -1.7734375 , -2.03125   , -0.09033203, -1.4453125 ,\n",
+       "        -1.03125   , -0.5234375 , -1.984375  , -2.03125   , -2.        ,\n",
+       "        -1.765625  , -2.015625  , -1.7578125 , -1.796875  , -0.42578125,\n",
+       "        -1.3359375 , -2.        , -2.09375   , -2.046875  ,  0.01495361,\n",
+       "        -1.0546875 , -0.77734375, -1.5859375 , -0.90234375, -1.46875   ,\n",
+       "        -0.94921875, -1.59375   , -1.8671875 , -2.        , -2.        ,\n",
+       "        -1.9921875 , -2.03125   ], dtype=float32),\n",
+       " array([ 0.08984375, -0.7265625 , -1.5625    , -1.7890625 , -1.9921875 ,\n",
+       "        -2.09375   , -2.125     , -2.        , -2.078125  , -1.4140625 ,\n",
+       "        -1.9921875 , -2.015625  , -0.09326172,  0.03295898, -0.55078125,\n",
+       "        -0.796875  , -2.        , -2.0625    , -2.078125  , -2.03125   ,\n",
+       "        -0.83984375, -1.484375  ,  0.19335938, -2.25      , -1.9765625 ,\n",
+       "        -0.13574219, -2.09375   , -1.078125  , -1.0078125 , -0.67578125,\n",
+       "        -1.453125  , -0.91015625], dtype=float32),\n",
+       " array([-0.56640625, -0.34765625, -1.75      , -1.9609375 , -2.046875  ,\n",
+       "        -1.8515625 , -0.33007812, -1.4609375 , -0.2890625 , -1.9921875 ,\n",
+       "        -1.1796875 , -2.03125   , -2.3125    , -2.        , -2.078125  ,\n",
+       "        -1.1015625 , -1.046875  , -2.109375  , -2.03125   , -0.23242188,\n",
+       "        -1.0859375 , -1.0625    , -1.3203125 , -0.08544922, -2.109375  ,\n",
+       "        -2.140625  , -2.        , -1.6796875 , -0.9609375 , -0.9921875 ,\n",
+       "        -1.7734375 , -1.7421875 ], dtype=float32),\n",
+       " array([-1.8984375 , -0.859375  , -1.9921875 , -1.8984375 , -1.9296875 ,\n",
+       "         0.04931641, -1.3671875 ,  0.02587891, -1.1328125 ,  0.13671875,\n",
+       "        -0.25      , -0.859375  , -1.71875   , -1.9296875 , -2.0625    ,\n",
+       "        -2.0625    , -0.953125  , -0.38085938, -0.765625  , -2.        ,\n",
+       "        -0.64453125, -0.9296875 , -1.1171875 , -1.3046875 ,  0.1171875 ,\n",
+       "        -1.15625   , -2.828125  , -0.40039062, -1.5       , -1.84375   ,\n",
+       "        -1.875     , -1.9921875 ], dtype=float32),\n",
+       " array([-1.546875  , -1.1015625 ,  0.39648438, -0.65234375, -2.046875  ,\n",
+       "        -1.609375  , -0.0612793 , -1.96875   , -2.        , -1.390625  ,\n",
+       "        -2.015625  , -1.9921875 , -2.03125   , -1.96875   , -1.3203125 ,\n",
+       "        -2.        , -2.0625    , -2.015625  , -1.9375    , -1.796875  ,\n",
+       "         0.31835938, -0.73828125, -1.8515625 , -2.171875  , -0.03015137,\n",
+       "        -0.05981445, -0.15234375, -0.65625   , -0.52734375, -2.015625  ,\n",
+       "        -1.625     , -1.90625   ], dtype=float32),\n",
+       " array([-2.        , -2.        , -1.9765625 ,  0.44335938, -2.        ,\n",
+       "        -1.9296875 ,  0.08300781, -0.2578125 , -1.3203125 , -1.828125  ,\n",
+       "        -1.3671875 , -2.        , -1.1484375 , -0.98046875, -2.015625  ,\n",
+       "        -0.16503906, -0.83984375, -1.484375  , -0.70703125, -1.9375    ,\n",
+       "        -2.        ,  0.20703125,  0.5       , -1.0546875 , -1.390625  ,\n",
+       "        -0.4765625 , -0.87890625, -1.8359375 , -1.5859375 , -1.96875   ,\n",
+       "        -1.1484375 , -2.        ], dtype=float32),\n",
+       " array([-1.8203125 , -1.1171875 , -1.09375   , -1.6875    , -2.078125  ,\n",
+       "        -0.8359375 , -2.21875   ,  0.13671875, -0.65625   , -0.27148438,\n",
+       "        -2.        , -0.60546875, -1.15625   , -1.7578125 , -1.328125  ,\n",
+       "        -1.65625   , -1.765625  ,  0.3671875 ,  0.33203125, -1.4453125 ,\n",
+       "        -0.51953125, -1.2265625 , -1.890625  , -1.6328125 , -0.2890625 ,\n",
+       "        -0.55859375,  0.45898438,  0.32617188, -1.5703125 , -1.0234375 ,\n",
+       "        -1.9453125 , -1.0234375 ], dtype=float32),\n",
+       " array([-2.        , -0.22460938,  0.41601562,  0.18066406,  1.9375    ,\n",
+       "        -1.1796875 , -0.07763672,  0.31835938, -0.7734375 , -1.09375   ,\n",
+       "        -1.78125   , -1.890625  ,  0.03759766,  0.4375    , -0.55859375,\n",
+       "         0.671875  , -0.9453125 ,  0.17480469, -2.421875  ,  0.5       ,\n",
+       "         0.53125   , -1.390625  ,  0.50390625,  0.26953125,  0.82421875,\n",
+       "         2.        ,  0.28515625,  2.390625  , -3.96875   ,  0.7890625 ,\n",
+       "         1.4921875 ,  1.078125  ], dtype=float32),\n",
+       " array([ 0.35546875, -0.52734375, -0.890625  ,  0.984375  , -1.6796875 ,\n",
+       "         0.578125  ,  0.7421875 ,  0.8515625 , -0.16796875, -1.5390625 ,\n",
+       "        -1.578125  , -2.        ,  0.32421875, -0.32421875, -1.5078125 ,\n",
+       "        -1.0625    , -1.890625  , -1.1328125 , -0.94140625, -1.3046875 ,\n",
+       "        -1.1875    , -1.296875  , -1.9453125 , -1.53125   , -0.75390625,\n",
+       "        -2.        , -2.        , -1.984375  , -0.54296875, -1.4296875 ,\n",
+       "        -1.484375  ,  0.37890625], dtype=float32),\n",
+       " array([-1.7578125 , -1.234375  , -1.3125    , -1.109375  , -1.625     ,\n",
+       "        -0.546875  , -0.45507812, -0.5078125 , -1.796875  , -1.1875    ,\n",
+       "        -1.9765625 , -1.96875   , -0.63671875, -1.09375   , -1.3984375 ,\n",
+       "        -1.3359375 , -2.        , -2.        , -1.3515625 , -2.        ,\n",
+       "        -1.796875  ,  0.05932617, -0.5703125 , -0.94921875, -1.203125  ,\n",
+       "        -1.359375  , -1.25      , -1.9765625 ,  0.4140625 , -0.19921875,\n",
+       "         0.4140625 , -1.5390625 ], dtype=float32),\n",
+       " array([-1.421875  , -0.515625  , -1.046875  , -2.015625  , -1.0390625 ,\n",
+       "        -0.66796875, -1.4453125 , -0.91015625, -0.5234375 , -1.5234375 ,\n",
+       "        -0.34375   , -0.625     , -1.96875   , -1.265625  , -0.23730469,\n",
+       "        -1.96875   , -1.1796875 , -1.109375  , -2.03125   , -1.8125    ,\n",
+       "        -2.171875  ,  0.796875  , -1.5859375 ,  0.58984375, -1.3203125 ,\n",
+       "        -1.4609375 , -1.5234375 , -1.859375  , -1.21875   , -1.2265625 ,\n",
+       "        -1.984375  , -1.1171875 ], dtype=float32),\n",
+       " array([ 0.01940918, -0.03198242, -0.32226562,  0.17871094,  0.4140625 ,\n",
+       "        -1.6171875 ,  1.0078125 , -0.57421875, -0.125     , -0.41796875,\n",
+       "        -0.53125   , -0.40234375, -0.56640625, -1.703125  , -0.12158203,\n",
+       "        -0.39257812, -0.43554688,  0.01928711, -0.35351562, -1.890625  ,\n",
+       "        -0.30273438,  1.1796875 , -0.23632812, -0.58984375, -1.4765625 ,\n",
+       "        -0.76171875, -0.31640625, -0.26757812, -2.        , -0.046875  ,\n",
+       "         0.77734375,  0.11474609], dtype=float32),\n",
+       " array([-1.0390625 , -0.65234375, -0.3125    , -0.578125  , -1.28125   ,\n",
+       "        -0.24511719, -1.421875  , -0.67578125, -2.        , -1.828125  ,\n",
+       "        -2.015625  , -2.078125  , -1.2265625 , -1.2265625 , -3.390625  ,\n",
+       "        -1.234375  , -0.859375  , -2.046875  , -1.1953125 , -2.046875  ,\n",
+       "        -0.04003906, -0.94140625, -0.7578125 , -1.578125  , -0.02185059,\n",
+       "         0.17382812, -2.109375  , -3.140625  , -1.3046875 , -0.3203125 ,\n",
+       "        -0.00952148, -0.4453125 ], dtype=float32),\n",
+       " array([-2.        ,  1.4921875 ,  0.62109375,  0.04931641, -2.        ,\n",
+       "        -1.96875   , -1.28125   , -1.9921875 , -2.        , -1.546875  ,\n",
+       "        -1.6484375 , -0.7578125 , -1.9296875 , -1.3984375 , -0.49804688,\n",
+       "        -0.71875   , -0.15136719,  1.53125   , -0.66796875, -0.37304688,\n",
+       "        -1.8203125 , -0.33789062, -0.40625   , -0.75      , -4.        ,\n",
+       "         0.46875   ,  0.97265625,  0.45703125,  0.609375  , -0.09472656,\n",
+       "         1.015625  , -1.9765625 ], dtype=float32),\n",
+       " array([ 1.7265625 ,  0.75      , -0.390625  , -1.84375   , -2.078125  ,\n",
+       "        -1.6796875 , -2.        , -2.125     ,  0.31835938,  0.21875   ,\n",
+       "        -0.9765625 , -0.41796875, -1.984375  , -1.6484375 , -1.859375  ,\n",
+       "        -2.125     , -2.25      , -1.5       , -0.80078125, -0.38085938,\n",
+       "         2.        , -0.11035156, -4.        ,  1.9375    , -1.1328125 ,\n",
+       "        -0.3828125 , -0.6796875 , -0.84375   , -2.359375  , -2.203125  ,\n",
+       "        -1.3515625 , -2.09375   ], dtype=float32),\n",
+       " array([-2.        , -1.1796875 , -2.21875   , -3.53125   , -1.875     ,\n",
+       "        -2.046875  , -0.5       , -2.046875  ,  0.79296875,  0.51953125,\n",
+       "         0.39648438, -2.09375   , -1.9453125 , -2.046875  , -1.9609375 ,\n",
+       "        -2.984375  , -0.53125   , -0.55078125, -1.5546875 , -0.35351562,\n",
+       "        -2.03125   , -0.5390625 , -1.8046875 ,  0.10546875,  2.        ,\n",
+       "         2.015625  ,  0.39648438, -1.7265625 , -0.4609375 ,  0.23632812,\n",
+       "        -2.03125   , -0.6484375 ], dtype=float32),\n",
+       " array([-2.015625  , -2.015625  , -1.7578125 , -2.375     , -0.9921875 ,\n",
+       "        -1.953125  , -2.1875    , -2.0625    , -0.53125   , -0.49804688,\n",
+       "        -2.0625    , -1.2734375 , -2.609375  , -2.421875  , -3.359375  ,\n",
+       "        -2.421875  , -1.3046875 , -2.171875  , -1.296875  , -2.        ,\n",
+       "         0.01745605, -1.84375   ,  1.046875  , -1.0234375 , -1.4765625 ,\n",
+       "        -1.921875  , -2.        , -1.390625  , -1.6484375 , -2.25      ,\n",
+       "        -1.6796875 , -2.5       ], dtype=float32),\n",
+       " array([ 0.02905273, -0.6328125 , -0.6171875 , -0.62109375, -0.03344727,\n",
+       "        -1.8203125 , -2.25      , -2.296875  , -2.015625  , -1.8671875 ,\n",
+       "        -2.109375  , -1.65625   ,  0.07128906, -0.29101562, -0.38867188,\n",
+       "         0.23535156, -2.0625    , -1.6640625 , -1.6875    , -1.5078125 ,\n",
+       "        -2.203125  , -2.        , -1.8984375 ,  0.62109375, -2.109375  ,\n",
+       "        -1.8125    , -2.078125  , -1.2421875 , -2.375     , -2.140625  ,\n",
+       "        -2.28125   , -2.234375  ], dtype=float32),\n",
+       " array([-2.25      ,  1.09375   , -1.2421875 , -2.3125    , -2.        ,\n",
+       "        -1.8203125 , -0.31054688, -2.046875  , -2.390625  , -1.453125  ,\n",
+       "        -1.9453125 , -2.265625  , -3.265625  , -0.25390625, -0.58203125,\n",
+       "        -0.03149414, -2.046875  , -2.03125   , -2.046875  , -2.046875  ,\n",
+       "        -0.98046875, -1.8515625 , -2.53125   ,  1.359375  , -1.390625  ,\n",
+       "        -0.06640625, -0.76953125, -2.125     , -2.015625  , -2.09375   ,\n",
+       "        -1.5390625 , -1.46875   ], dtype=float32),\n",
+       " array([-1.8671875 , -0.1953125 , -2.265625  , -0.0402832 , -2.        ,\n",
+       "        -2.15625   , -2.        , -1.9921875 , -0.40820312, -2.34375   ,\n",
+       "        -2.125     , -0.7734375 , -2.4375    , -2.        , -2.109375  ,\n",
+       "        -2.296875  , -2.390625  , -2.359375  , -2.375     , -4.        ,\n",
+       "        -0.5078125 , -0.5234375 , -0.00753784, -3.953125  , -1.328125  ,\n",
+       "        -1.875     , -1.1171875 , -2.171875  , -1.6875    , -0.859375  ,\n",
+       "        -1.4140625 , -0.63671875], dtype=float32),\n",
+       " array([-0.55078125, -0.5234375 , -0.6484375 , -2.359375  , -3.015625  ,\n",
+       "        -0.84765625, -0.53515625, -1.8203125 , -1.1796875 , -2.09375   ,\n",
+       "        -2.        , -1.9921875 , -0.63671875,  0.06591797,  0.22753906,\n",
+       "        -0.21875   , -2.03125   , -1.90625   , -0.609375  , -4.        ,\n",
+       "        -2.03125   , -1.9921875 , -1.96875   , -1.828125  , -2.234375  ,\n",
+       "        -2.453125  , -2.359375  , -1.9609375 , -0.30859375,  0.33007812,\n",
+       "        -4.        , -0.6015625 ], dtype=float32),\n",
+       " array([-2.34375   , -2.46875   , -2.109375  , -2.15625   , -2.515625  ,\n",
+       "        -0.7109375 , -0.7265625 , -1.828125  , -2.453125  , -2.390625  ,\n",
+       "        -2.171875  , -2.171875  , -0.796875  , -0.25585938, -1.078125  ,\n",
+       "        -2.15625   , -2.078125  , -2.03125   , -2.015625  , -2.015625  ,\n",
+       "        -0.21191406, -2.828125  , -0.34179688, -1.875     , -2.359375  ,\n",
+       "        -1.1640625 , -1.921875  , -0.7109375 , -2.03125   , -2.109375  ,\n",
+       "        -2.        , -2.15625   ], dtype=float32),\n",
+       " array([-2.046875  , -2.140625  , -2.203125  , -1.640625  , -2.25      ,\n",
+       "        -2.359375  , -2.03125   , -2.09375   , -2.078125  , -2.09375   ,\n",
+       "        -2.0625    , -2.125     , -1.4140625 , -1.0078125 , -2.578125  ,\n",
+       "        -2.59375   , -0.51953125, -0.5546875 , -0.34570312, -3.375     ,\n",
+       "        -0.19238281, -2.671875  , -0.45898438, -0.41992188, -0.515625  ,\n",
+       "        -1.2265625 ,  0.90234375, -0.29882812, -2.046875  , -2.046875  ,\n",
+       "        -2.203125  , -1.96875   ], dtype=float32),\n",
+       " array([-1.4921875 , -1.125     , -1.53125   , -0.11914062, -0.29101562,\n",
+       "         0.05761719, -0.09228516, -0.32226562, -2.        , -2.125     ,\n",
+       "        -2.140625  , -2.484375  , -0.109375  , -0.1171875 , -0.5       ,\n",
+       "        -0.55078125, -2.078125  , -1.171875  , -0.40429688, -2.21875   ,\n",
+       "        -2.        , -1.6875    , -2.        , -2.578125  , -2.375     ,\n",
+       "        -2.0625    , -2.078125  , -2.        , -2.265625  , -2.        ,\n",
+       "        -2.078125  , -2.046875  ], dtype=float32),\n",
+       " array([-1.28125   , -1.9921875 , -0.31835938, -2.        , -1.109375  ,\n",
+       "        -2.015625  , -0.56640625, -1.3046875 , -2.109375  , -2.09375   ,\n",
+       "        -1.9296875 , -2.421875  , -0.36132812,  0.15917969, -0.32226562,\n",
+       "        -0.6171875 , -2.        , -2.        , -1.328125  ,  0.59375   ,\n",
+       "        -2.578125  , -1.2421875 , -2.0625    , -0.39648438, -1.9765625 ,\n",
+       "        -2.40625   , -2.125     ,  0.890625  , -3.5       , -0.33984375,\n",
+       "         1.390625  , -0.6484375 ], dtype=float32),\n",
+       " array([-2.21875   , -2.03125   , -2.390625  , -2.        ,  0.04931641,\n",
+       "         0.58203125, -0.14160156,  0.39453125, -0.66796875, -2.        ,\n",
+       "        -2.078125  , -1.9140625 , -1.0703125 , -1.203125  , -2.078125  ,\n",
+       "        -2.921875  ,  1.609375  , -2.28125   , -1.6015625 , -1.9453125 ,\n",
+       "         0.05078125, -2.578125  , -0.11035156,  0.18457031, -2.        ,\n",
+       "        -2.015625  , -2.015625  , -2.        , -1.1953125 , -2.        ,\n",
+       "        -2.015625  , -1.96875   ], dtype=float32),\n",
+       " array([ 1.3359375 , -2.125     , -2.078125  , -4.        , -2.03125   ,\n",
+       "        -2.        , -2.3125    , -1.953125  , -1.7734375 , -1.328125  ,\n",
+       "        -0.31835938, -2.        , -3.        ,  0.30664062, -2.3125    ,\n",
+       "        -0.68359375, -1.4375    , -4.        ,  0.8515625 , -1.203125  ,\n",
+       "         0.44921875, -4.        , -1.9375    ,  0.7890625 , -1.7109375 ,\n",
+       "        -2.1875    , -1.953125  , -0.08886719, -1.9921875 , -2.        ,\n",
+       "        -0.26953125, -1.765625  ], dtype=float32),\n",
+       " array([-2.015625  , -2.296875  , -1.4921875 , -2.015625  , -2.140625  ,\n",
+       "        -2.015625  , -2.234375  , -2.109375  ,  1.171875  ,  0.7109375 ,\n",
+       "        -4.        ,  1.75      , -2.203125  , -2.03125   , -1.7578125 ,\n",
+       "        -2.125     , -0.33203125, -2.        , -2.        , -2.109375  ,\n",
+       "         0.66015625,  0.671875  ,  0.37304688, -4.        , -1.6875    ,\n",
+       "        -2.015625  , -1.6015625 , -1.734375  , -2.046875  , -1.6796875 ,\n",
+       "        -0.875     ,  0.05029297], dtype=float32),\n",
+       " array([-4.        ,  1.0859375 ,  1.5859375 , -2.        , -2.        ,\n",
+       "        -2.859375  ,  0.5       , -2.03125   , -4.        ,  1.3828125 ,\n",
+       "        -0.57421875,  1.6640625 ,  1.9140625 , -3.375     ,  1.8828125 ,\n",
+       "         1.765625  , -2.        ,  0.61328125,  0.18945312, -0.81640625,\n",
+       "         0.265625  ,  0.96875   , -1.859375  , -0.58984375, -1.4765625 ,\n",
+       "        -2.015625  ,  0.68359375,  0.15917969, -2.375     ,  0.69140625,\n",
+       "         1.3125    , -2.25      ], dtype=float32),\n",
+       " array([-0.55078125, -2.        , -1.015625  , -2.        , -1.640625  ,\n",
+       "        -2.        ,  0.00741577,  0.47851562, -1.8046875 , -1.34375   ,\n",
+       "        -1.75      ,  0.04052734, -0.66015625, -1.0625    , -1.9453125 ,\n",
+       "        -0.6953125 , -0.33203125, -1.0703125 , -1.953125  ,  1.3203125 ,\n",
+       "         1.5390625 ,  1.109375  , -2.375     , -2.        , -1.203125  ,\n",
+       "        -1.828125  , -0.265625  , -1.359375  ,  0.58203125,  0.59765625,\n",
+       "         0.48046875, -2.015625  ], dtype=float32)]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "merged_tensors"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "num_heads = len(merged_tensors[0])\n",
+    "global_weights = F.sigmoid(torch.tensor(merged_tensors))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "32"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_heads"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Distribution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "name": "Histogram",
+         "type": "histogram",
+         "x": [
+          0.117572136,
+          0.11920292,
+          0.06278921,
+          0.060086653,
+          0.14706452,
+          0.13568956,
+          0.11920292,
+          0.16344544,
+          0.1490353,
+          0.33025515,
+          0.12085322,
+          0.29746994,
+          0.20946968,
+          0.23792988,
+          0.28298813,
+          0.41489884,
+          0.19806418,
+          0.2885691,
+          0.2120688,
+          0.21733753,
+          0.23231015,
+          0.23510839,
+          0.2146914,
+          0.16238004,
+          0.112795405,
+          0.18126321,
+          0.12506539,
+          0.1943678,
+          0.12592277,
+          0.11920292,
+          0.11920292,
+          0.12085322,
+          0.15002882,
+          0.16885695,
+          0.23651622,
+          0.18010667,
+          0.12085322,
+          0.11920292,
+          0.16451646,
+          0.24220563,
+          0.31405056,
+          0.3548801,
+          0.15304215,
+          0.258326,
+          0.5585678,
+          0.12085322,
+          0.13117322,
+          0.18832397,
+          0.11920292,
+          0.19072403,
+          0.11920292,
+          0.16559312,
+          0.11920292,
+          0.11920292,
+          0.26284185,
+          0.21076629,
+          0.11920292,
+          0.12168575,
+          0.117572136,
+          0.15002882,
+          0.39981166,
+          0.33025515,
+          0.26588047,
+          0.23091978,
+          0.114368536,
+          0.14511536,
+          0.115960725,
+          0.4774323,
+          0.19072403,
+          0.26284185,
+          0.3720488,
+          0.12085322,
+          0.115960725,
+          0.11920292,
+          0.14608724,
+          0.117572136,
+          0.14706452,
+          0.1422319,
+          0.39513415,
+          0.20817892,
+          0.11920292,
+          0.109705776,
+          0.114368536,
+          0.50373834,
+          0.258326,
+          0.31489265,
+          0.16995624,
+          0.2885691,
+          0.18713269,
+          0.27904198,
+          0.16885695,
+          0.13386749,
+          0.11920292,
+          0.11920292,
+          0.12002562,
+          0.115960725,
+          0.52244586,
+          0.32594952,
+          0.1732882,
+          0.1431877,
+          0.12002562,
+          0.109705776,
+          0.1066906,
+          0.11920292,
+          0.1112412,
+          0.19559409,
+          0.12002562,
+          0.117572136,
+          0.47670147,
+          0.50823903,
+          0.36568317,
+          0.3106944,
+          0.11920292,
+          0.112795405,
+          0.1112412,
+          0.115960725,
+          0.3015677,
+          0.1847675,
+          0.5481898,
+          0.09534947,
+          0.12168575,
+          0.46611643,
+          0.109705776,
+          0.253861,
+          0.26740816,
+          0.33720353,
+          0.18952109,
+          0.28696787,
+          0.36206648,
+          0.4139509,
+          0.14804721,
+          0.123365626,
+          0.114368536,
+          0.13568956,
+          0.41822162,
+          0.18832397,
+          0.4282334,
+          0.12002562,
+          0.23510839,
+          0.115960725,
+          0.090092994,
+          0.11920292,
+          0.1112412,
+          0.24944726,
+          0.25982565,
+          0.10818896,
+          0.115960725,
+          0.44215468,
+          0.25238407,
+          0.256832,
+          0.21076629,
+          0.4786507,
+          0.10818896,
+          0.10521054,
+          0.11920292,
+          0.15713686,
+          0.2766905,
+          0.27048022,
+          0.14511536,
+          0.1490353,
+          0.13028541,
+          0.29746994,
+          0.12002562,
+          0.13028541,
+          0.12678517,
+          0.5123266,
+          0.20307462,
+          0.50646937,
+          0.24364243,
+          0.5341265,
+          0.4378235,
+          0.29746994,
+          0.15203226,
+          0.12678517,
+          0.112795405,
+          0.112795405,
+          0.2782568,
+          0.40591964,
+          0.31742626,
+          0.11920292,
+          0.344223,
+          0.28298813,
+          0.24653335,
+          0.21337718,
+          0.5292634,
+          0.23934935,
+          0.055823144,
+          0.4012185,
+          0.18242553,
+          0.13660839,
+          0.13296424,
+          0.12002562,
+          0.17553808,
+          0.24944726,
+          0.5978427,
+          0.3424616,
+          0.114368536,
+          0.1666754,
+          0.484685,
+          0.12252322,
+          0.11920292,
+          0.199308,
+          0.117572136,
+          0.12002562,
+          0.115960725,
+          0.12252322,
+          0.21076629,
+          0.11920292,
+          0.112795405,
+          0.117572136,
+          0.12592277,
+          0.1422319,
+          0.57892436,
+          0.3233801,
+          0.13568956,
+          0.10230471,
+          0.49246272,
+          0.48505086,
+          0.46198758,
+          0.3415825,
+          0.3711366,
+          0.117572136,
+          0.16451646,
+          0.12940274,
+          0.11920292,
+          0.11920292,
+          0.12168575,
+          0.6090592,
+          0.11920292,
+          0.12678517,
+          0.5207401,
+          0.43590155,
+          0.21076629,
+          0.1384618,
+          0.20307462,
+          0.11920292,
+          0.24077459,
+          0.27279878,
+          0.117572136,
+          0.45883366,
+          0.3015677,
+          0.1847675,
+          0.33025515,
+          0.12592277,
+          0.11920292,
+          0.55157375,
+          0.62245935,
+          0.258326,
+          0.199308,
+          0.38306415,
+          0.2934045,
+          0.13753247,
+          0.16995624,
+          0.12252322,
+          0.24077459,
+          0.11920292,
+          0.13939638,
+          0.24653335,
+          0.2509128,
+          0.1561049,
+          0.1112412,
+          0.30239108,
+          0.09807933,
+          0.5341265,
+          0.3415825,
+          0.4325427,
+          0.11920292,
+          0.35309353,
+          0.23934935,
+          0.14706452,
+          0.20946968,
+          0.16026603,
+          0.14608724,
+          0.5907792,
+          0.5822535,
+          0.19072403,
+          0.37296185,
+          0.22678363,
+          0.13117322,
+          0.16344544,
+          0.4282334,
+          0.36387292,
+          0.61277324,
+          0.58082765,
+          0.17217185,
+          0.26435837,
+          0.12506539,
+          0.26435837,
+          0.11920292,
+          0.44408253,
+          0.6025294,
+          0.5450436,
+          0.8740772,
+          0.23510839,
+          0.48060057,
+          0.57892436,
+          0.31573597,
+          0.2509128,
+          0.14414886,
+          0.13117322,
+          0.5093983,
+          0.6076632,
+          0.36387292,
+          0.6619229,
+          0.2798285,
+          0.5435902,
+          0.08151976,
+          0.62245935,
+          0.62977463,
+          0.199308,
+          0.62337685,
+          0.5669778,
+          0.6951311,
+          0.880797,
+          0.5708099,
+          0.9161096,
+          0.018546565,
+          0.68763,
+          0.81640637,
+          0.746139,
+          0.58794314,
+          0.3711366,
+          0.29098085,
+          0.7279754,
+          0.15713686,
+          0.6406359,
+          0.677474,
+          0.70089483,
+          0.4581063,
+          0.17667161,
+          0.17106119,
+          0.11920292,
+          0.580352,
+          0.41964793,
+          0.18126321,
+          0.256832,
+          0.13117322,
+          0.24364243,
+          0.28061637,
+          0.21337718,
+          0.23370637,
+          0.2146914,
+          0.12506539,
+          0.17781086,
+          0.31997076,
+          0.11920292,
+          0.11920292,
+          0.12085322,
+          0.36749724,
+          0.19314739,
+          0.1847675,
+          0.5936093,
+          0.14706452,
+          0.22541662,
+          0.2120688,
+          0.24798742,
+          0.16451646,
+          0.36658973,
+          0.38815406,
+          0.37570646,
+          0.1422319,
+          0.23370637,
+          0.12168575,
+          0.12252322,
+          0.34598863,
+          0.2509128,
+          0.19806418,
+          0.20817892,
+          0.11920292,
+          0.11920292,
+          0.20561503,
+          0.11920292,
+          0.1422319,
+          0.5148272,
+          0.36116472,
+          0.27904198,
+          0.23091978,
+          0.2043419,
+          0.22270013,
+          0.12168575,
+          0.60206157,
+          0.45035937,
+          0.60206157,
+          0.17667161,
+          0.1943678,
+          0.3738758,
+          0.25982565,
+          0.117572136,
+          0.26133093,
+          0.33895183,
+          0.19072403,
+          0.28696787,
+          0.3720488,
+          0.17895588,
+          0.41489884,
+          0.34864512,
+          0.12252322,
+          0.22000709,
+          0.44095063,
+          0.12252322,
+          0.23510839,
+          0.24798742,
+          0.115960725,
+          0.14033625,
+          0.10230471,
+          0.6893056,
+          0.16995624,
+          0.64332926,
+          0.21076629,
+          0.18832397,
+          0.17895588,
+          0.13477592,
+          0.22815649,
+          0.22678363,
+          0.12085322,
+          0.24653335,
+          0.5048521,
+          0.49200508,
+          0.4201237,
+          0.54455924,
+          0.60206157,
+          0.16559312,
+          0.7325918,
+          0.36026397,
+          0.46879062,
+          0.3970029,
+          0.37022537,
+          0.40074936,
+          0.36206648,
+          0.15405756,
+          0.4696419,
+          0.40309682,
+          0.39280254,
+          0.50482166,
+          0.41253018,
+          0.13117322,
+          0.4248892,
+          0.7648916,
+          0.4411914,
+          0.3566707,
+          0.1859472,
+          0.31827325,
+          0.42155182,
+          0.43350178,
+          0.11920292,
+          0.4882834,
+          0.68510735,
+          0.5286551,
+          0.26133093,
+          0.3424616,
+          0.42250463,
+          0.35936412,
+          0.21733753,
+          0.4390257,
+          0.1943678,
+          0.33720353,
+          0.11920292,
+          0.1384618,
+          0.117572136,
+          0.1112412,
+          0.22678363,
+          0.22678363,
+          0.032589745,
+          0.22541662,
+          0.29746994,
+          0.114368536,
+          0.23231015,
+          0.114368536,
+          0.48999155,
+          0.28061637,
+          0.3191214,
+          0.17106119,
+          0.4945376,
+          0.54334795,
+          0.10818896,
+          0.041462272,
+          0.21337718,
+          0.42059958,
+          0.4976197,
+          0.39047584,
+          0.11920292,
+          0.81640637,
+          0.6504673,
+          0.5123266,
+          0.11920292,
+          0.12252322,
+          0.21733753,
+          0.12002562,
+          0.11920292,
+          0.17553808,
+          0.16132024,
+          0.3191214,
+          0.12678517,
+          0.19806418,
+          0.37799978,
+          0.3276683,
+          0.4622303,
+          0.8221891,
+          0.33895183,
+          0.407805,
+          0.13939638,
+          0.41632196,
+          0.39981166,
+          0.3208213,
+          0.01798621,
+          0.61508787,
+          0.7256486,
+          0.61230963,
+          0.64779824,
+          0.4763361,
+          0.73411953,
+          0.12168575,
+          0.8489722,
+          0.6791787,
+          0.40356684,
+          0.13660839,
+          0.1112412,
+          0.15713686,
+          0.11920292,
+          0.1066906,
+          0.57892436,
+          0.5544705,
+          0.27357438,
+          0.3970029,
+          0.12085322,
+          0.16132024,
+          0.13477592,
+          0.1066906,
+          0.09534947,
+          0.18242553,
+          0.3098584,
+          0.40591964,
+          0.880797,
+          0.47244006,
+          0.01798621,
+          0.8740772,
+          0.24364243,
+          0.40544873,
+          0.33633107,
+          0.30074558,
+          0.08632348,
+          0.09947021,
+          0.20561503,
+          0.109705776,
+          0.11920292,
+          0.23510839,
+          0.09807933,
+          0.028436033,
+          0.13296424,
+          0.114368536,
+          0.37754068,
+          0.114368536,
+          0.68846846,
+          0.6270382,
+          0.5978427,
+          0.109705776,
+          0.12506539,
+          0.114368536,
+          0.123365626,
+          0.04813677,
+          0.37022537,
+          0.36568317,
+          0.17441027,
+          0.41253018,
+          0.115960725,
+          0.3684057,
+          0.14128143,
+          0.52634275,
+          0.880797,
+          0.8824279,
+          0.5978427,
+          0.1510278,
+          0.38676342,
+          0.55880857,
+          0.115960725,
+          0.34334174,
+          0.117572136,
+          0.117572136,
+          0.14706452,
+          0.08509905,
+          0.27048022,
+          0.12421302,
+          0.100878626,
+          0.112795405,
+          0.37022537,
+          0.37799978,
+          0.112795405,
+          0.21866935,
+          0.068537496,
+          0.08151976,
+          0.033589505,
+          0.08151976,
+          0.21337718,
+          0.10230471,
+          0.2146914,
+          0.11920292,
+          0.5043639,
+          0.13660839,
+          0.7401744,
+          0.26435837,
+          0.1859472,
+          0.12765263,
+          0.11920292,
+          0.199308,
+          0.16132024,
+          0.09534947,
+          0.15713686,
+          0.075858176,
+          0.5072627,
+          0.34687307,
+          0.35042137,
+          0.34953272,
+          0.491639,
+          0.13939638,
+          0.09534947,
+          0.0913821,
+          0.117572136,
+          0.13386749,
+          0.10818896,
+          0.16026603,
+          0.51781476,
+          0.42775524,
+          0.40403706,
+          0.5585678,
+          0.112795405,
+          0.1592174,
+          0.1561049,
+          0.18126321,
+          0.09947021,
+          0.11920292,
+          0.13028541,
+          0.6504673,
+          0.10818896,
+          0.14033625,
+          0.1112412,
+          0.22405544,
+          0.08509905,
+          0.10521054,
+          0.09268778,
+          0.096705794,
+          0.09534947,
+          0.7490872,
+          0.22405544,
+          0.090092994,
+          0.11920292,
+          0.13939638,
+          0.42298123,
+          0.114368536,
+          0.083890386,
+          0.18952109,
+          0.12506539,
+          0.09401018,
+          0.036769465,
+          0.43686226,
+          0.35846534,
+          0.49212712,
+          0.114368536,
+          0.115960725,
+          0.114368536,
+          0.114368536,
+          0.27279878,
+          0.13568956,
+          0.07369627,
+          0.79565805,
+          0.199308,
+          0.48340455,
+          0.3165805,
+          0.1066906,
+          0.117572136,
+          0.109705776,
+          0.17667161,
+          0.18713269,
+          0.13386749,
+          0.4513265,
+          0.09401018,
+          0.4899305,
+          0.11920292,
+          0.103748634,
+          0.11920292,
+          0.12002562,
+          0.39934304,
+          0.087563835,
+          0.1066906,
+          0.31573597,
+          0.08035747,
+          0.11920292,
+          0.10818896,
+          0.0913821,
+          0.083890386,
+          0.08632348,
+          0.08509905,
+          0.01798621,
+          0.37570646,
+          0.3720488,
+          0.4981155,
+          0.018833129,
+          0.20946968,
+          0.13296424,
+          0.24653335,
+          0.10230471,
+          0.1561049,
+          0.29746994,
+          0.19559409,
+          0.34598863,
+          0.36568317,
+          0.3720488,
+          0.34334174,
+          0.08632348,
+          0.046724956,
+          0.29992476,
+          0.3693151,
+          0.13939638,
+          0.23510839,
+          0.109705776,
+          0.11920292,
+          0.12002562,
+          0.34598863,
+          0.51647353,
+          0.55664057,
+          0.44552952,
+          0.115960725,
+          0.12940274,
+          0.35220176,
+          0.01798621,
+          0.115960725,
+          0.12002562,
+          0.12252322,
+          0.1384618,
+          0.096705794,
+          0.079210326,
+          0.08632348,
+          0.123365626,
+          0.42345804,
+          0.5817784,
+          0.01798621,
+          0.3539863,
+          0.087563835,
+          0.078078166,
+          0.10818896,
+          0.103748634,
+          0.07477004,
+          0.32939172,
+          0.32594952,
+          0.1384618,
+          0.079210326,
+          0.083890386,
+          0.10230471,
+          0.10230471,
+          0.3106944,
+          0.43638182,
+          0.253861,
+          0.103748634,
+          0.1112412,
+          0.115960725,
+          0.117572136,
+          0.117572136,
+          0.4472189,
+          0.055823144,
+          0.41537303,
+          0.13296424,
+          0.08632348,
+          0.23792988,
+          0.12765263,
+          0.32939172,
+          0.115960725,
+          0.10818896,
+          0.11920292,
+          0.103748634,
+          0.114368536,
+          0.10521054,
+          0.09947021,
+          0.16238004,
+          0.09534947,
+          0.08632348,
+          0.115960725,
+          0.109705776,
+          0.1112412,
+          0.109705776,
+          0.112795405,
+          0.1066906,
+          0.19559409,
+          0.26740816,
+          0.0705596,
+          0.069541745,
+          0.37296185,
+          0.36477757,
+          0.4144248,
+          0.03308598,
+          0.45205212,
+          0.064653486,
+          0.38722676,
+          0.39653543,
+          0.3738758,
+          0.22678363,
+          0.71143085,
+          0.42584398,
+          0.114368536,
+          0.114368536,
+          0.09947021,
+          0.12252322,
+          0.18359363,
+          0.24508502,
+          0.17781086,
+          0.47025004,
+          0.42775524,
+          0.5144003,
+          0.47694507,
+          0.4201237,
+          0.11920292,
+          0.1066906,
+          0.10521054,
+          0.07696084,
+          0.4726835,
+          0.4707366,
+          0.37754068,
+          0.36568317,
+          0.1112412,
+          0.23651622,
+          0.40028042,
+          0.09807933,
+          0.11920292,
+          0.1561049,
+          0.11920292,
+          0.0705596,
+          0.08509905,
+          0.112795405,
+          0.1112412,
+          0.11920292,
+          0.09401018,
+          0.11920292,
+          0.1112412,
+          0.114368536,
+          0.21733753,
+          0.12002562,
+          0.4210756,
+          0.11920292,
+          0.24798742,
+          0.117572136,
+          0.36206648,
+          0.21337718,
+          0.10818896,
+          0.109705776,
+          0.12678517,
+          0.08151976,
+          0.4106381,
+          0.5397111,
+          0.4201237,
+          0.35042137,
+          0.11920292,
+          0.11920292,
+          0.20946968,
+          0.64422506,
+          0.0705596,
+          0.22405544,
+          0.112795405,
+          0.4021573,
+          0.12168575,
+          0.08269734,
+          0.1066906,
+          0.7090191,
+          0.02931223,
+          0.41584745,
+          0.80069196,
+          0.34334174,
+          0.09807933,
+          0.115960725,
+          0.083890386,
+          0.11920292,
+          0.5123266,
+          0.6415346,
+          0.46465865,
+          0.597373,
+          0.33895183,
+          0.11920292,
+          0.1112412,
+          0.12852514,
+          0.25534365,
+          0.23091978,
+          0.1112412,
+          0.051082738,
+          0.8333246,
+          0.09268778,
+          0.16776334,
+          0.12506539,
+          0.5126926,
+          0.0705596,
+          0.47244006,
+          0.54601204,
+          0.11920292,
+          0.117572136,
+          0.117572136,
+          0.11920292,
+          0.23231015,
+          0.11920292,
+          0.117572136,
+          0.12252322,
+          0.79182106,
+          0.1066906,
+          0.1112412,
+          0.01798621,
+          0.115960725,
+          0.11920292,
+          0.090092994,
+          0.12421302,
+          0.14511536,
+          0.20946968,
+          0.4210756,
+          0.11920292,
+          0.047425874,
+          0.57606506,
+          0.090092994,
+          0.33545968,
+          0.19193278,
+          0.01798621,
+          0.70089483,
+          0.23091978,
+          0.6104535,
+          0.01798621,
+          0.12592277,
+          0.68763,
+          0.15304215,
+          0.100878626,
+          0.12421302,
+          0.4777978,
+          0.12002562,
+          0.11920292,
+          0.4330222,
+          0.14608724,
+          0.117572136,
+          0.0913821,
+          0.18359363,
+          0.117572136,
+          0.10521054,
+          0.117572136,
+          0.096705794,
+          0.10818896,
+          0.7634837,
+          0.6706083,
+          0.01798621,
+          0.85195273,
+          0.09947021,
+          0.115960725,
+          0.14706452,
+          0.1066906,
+          0.41774645,
+          0.11920292,
+          0.11920292,
+          0.10818896,
+          0.6592955,
+          0.6619229,
+          0.592195,
+          0.01798621,
+          0.1561049,
+          0.117572136,
+          0.16776334,
+          0.15002882,
+          0.114368536,
+          0.15713686,
+          0.29421496,
+          0.51257056,
+          0.01798621,
+          0.74761593,
+          0.83004373,
+          0.11920292,
+          0.11920292,
+          0.05419873,
+          0.62245935,
+          0.115960725,
+          0.01798621,
+          0.7994423,
+          0.36026397,
+          0.8407826,
+          0.87147486,
+          0.03308598,
+          0.8679338,
+          0.8539127,
+          0.11920292,
+          0.648689,
+          0.54722214,
+          0.30652705,
+          0.5660185,
+          0.7248703,
+          0.13477592,
+          0.3566707,
+          0.1859472,
+          0.117572136,
+          0.6645403,
+          0.5397111,
+          0.08509905,
+          0.6662797,
+          0.7879312,
+          0.09534947,
+          0.36568317,
+          0.11920292,
+          0.26588047,
+          0.11920292,
+          0.16238004,
+          0.11920292,
+          0.50185394,
+          0.6173973,
+          0.14128143,
+          0.20689404,
+          0.14804721,
+          0.51013047,
+          0.3407045,
+          0.256832,
+          0.12506539,
+          0.3328523,
+          0.41774645,
+          0.25534365,
+          0.12421302,
+          0.7892337,
+          0.8233284,
+          0.7520126,
+          0.08509905,
+          0.11920292,
+          0.23091978,
+          0.1384618,
+          0.43398145,
+          0.2043419,
+          0.6415346,
+          0.6451199,
+          0.6178585,
+          0.117572136
+         ],
+         "xaxis": "x",
+         "xbins": {
+          "end": 1,
+          "size": 0.1,
+          "start": 0
+         },
+         "yaxis": "y"
+        },
+        {
+         "domain": {
+          "x": [
+           0.55,
+           1
+          ],
+          "y": [
+           0,
+           1
+          ]
+         },
+         "labels": [
+          "0.0-0.1",
+          "0.1-0.2",
+          "0.2-0.3",
+          "0.3-0.4",
+          "0.4-0.5",
+          "0.5-0.6",
+          "0.6-0.7",
+          "0.7-0.8",
+          "0.8-0.9",
+          "0.9-1.0"
+         ],
+         "name": "Distribution",
+         "type": "pie",
+         "values": [
+          100,
+          439,
+          139,
+          111,
+          92,
+          60,
+          42,
+          21,
+          19,
+          1
+         ]
+        }
+       ],
+       "layout": {
+        "height": 600,
+        "template": {
+         "data": {
+          "bar": [
+           {
+            "error_x": {
+             "color": "#2a3f5f"
+            },
+            "error_y": {
+             "color": "#2a3f5f"
+            },
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             },
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "bar"
+           }
+          ],
+          "barpolar": [
+           {
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             },
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "barpolar"
+           }
+          ],
+          "carpet": [
+           {
+            "aaxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "baxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "type": "carpet"
+           }
+          ],
+          "choropleth": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "choropleth"
+           }
+          ],
+          "contour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "contour"
+           }
+          ],
+          "contourcarpet": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "contourcarpet"
+           }
+          ],
+          "heatmap": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmap"
+           }
+          ],
+          "heatmapgl": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmapgl"
+           }
+          ],
+          "histogram": [
+           {
+            "marker": {
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "histogram"
+           }
+          ],
+          "histogram2d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2d"
+           }
+          ],
+          "histogram2dcontour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2dcontour"
+           }
+          ],
+          "mesh3d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "mesh3d"
+           }
+          ],
+          "parcoords": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "parcoords"
+           }
+          ],
+          "pie": [
+           {
+            "automargin": true,
+            "type": "pie"
+           }
+          ],
+          "scatter": [
+           {
+            "fillpattern": {
+             "fillmode": "overlay",
+             "size": 10,
+             "solidity": 0.2
+            },
+            "type": "scatter"
+           }
+          ],
+          "scatter3d": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatter3d"
+           }
+          ],
+          "scattercarpet": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattercarpet"
+           }
+          ],
+          "scattergeo": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergeo"
+           }
+          ],
+          "scattergl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergl"
+           }
+          ],
+          "scattermapbox": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattermapbox"
+           }
+          ],
+          "scatterpolar": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolar"
+           }
+          ],
+          "scatterpolargl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolargl"
+           }
+          ],
+          "scatterternary": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterternary"
+           }
+          ],
+          "surface": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "surface"
+           }
+          ],
+          "table": [
+           {
+            "cells": {
+             "fill": {
+              "color": "#EBF0F8"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "header": {
+             "fill": {
+              "color": "#C8D4E3"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "type": "table"
+           }
+          ]
+         },
+         "layout": {
+          "annotationdefaults": {
+           "arrowcolor": "#2a3f5f",
+           "arrowhead": 0,
+           "arrowwidth": 1
+          },
+          "autotypenumbers": "strict",
+          "coloraxis": {
+           "colorbar": {
+            "outlinewidth": 0,
+            "ticks": ""
+           }
+          },
+          "colorscale": {
+           "diverging": [
+            [
+             0,
+             "#8e0152"
+            ],
+            [
+             0.1,
+             "#c51b7d"
+            ],
+            [
+             0.2,
+             "#de77ae"
+            ],
+            [
+             0.3,
+             "#f1b6da"
+            ],
+            [
+             0.4,
+             "#fde0ef"
+            ],
+            [
+             0.5,
+             "#f7f7f7"
+            ],
+            [
+             0.6,
+             "#e6f5d0"
+            ],
+            [
+             0.7,
+             "#b8e186"
+            ],
+            [
+             0.8,
+             "#7fbc41"
+            ],
+            [
+             0.9,
+             "#4d9221"
+            ],
+            [
+             1,
+             "#276419"
+            ]
+           ],
+           "sequential": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ],
+           "sequentialminus": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ]
+          },
+          "colorway": [
+           "#636efa",
+           "#EF553B",
+           "#00cc96",
+           "#ab63fa",
+           "#FFA15A",
+           "#19d3f3",
+           "#FF6692",
+           "#B6E880",
+           "#FF97FF",
+           "#FECB52"
+          ],
+          "font": {
+           "color": "#2a3f5f"
+          },
+          "geo": {
+           "bgcolor": "white",
+           "lakecolor": "white",
+           "landcolor": "#E5ECF6",
+           "showlakes": true,
+           "showland": true,
+           "subunitcolor": "white"
+          },
+          "hoverlabel": {
+           "align": "left"
+          },
+          "hovermode": "closest",
+          "mapbox": {
+           "style": "light"
+          },
+          "paper_bgcolor": "white",
+          "plot_bgcolor": "#E5ECF6",
+          "polar": {
+           "angularaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "zaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "line": {
+            "color": "#2a3f5f"
+           }
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        },
+        "title": {
+         "text": "[exp57: 8b llama3, 1024 ctxlen, 64 segment len, 100k bs, 0.01 balance factor lr, no weight decay for balance factors] Global weights's distribution"
+        },
+        "width": 1000,
+        "xaxis": {
+         "anchor": "y",
+         "domain": [
+          0,
+          0.45
+         ],
+         "range": [
+          0,
+          1
+         ],
+         "title": {
+          "text": "Value"
+         }
+        },
+        "yaxis": {
+         "anchor": "x",
+         "domain": [
+          0,
+          1
+         ],
+         "title": {
+          "text": "Frequency"
+         }
+        }
+       }
+      },
+      "text/html": [
+       "<div>                            <div id=\"69e33d73-ea19-4a26-a742-b11e65356b1f\" class=\"plotly-graph-div\" style=\"height:600px; width:1000px;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"69e33d73-ea19-4a26-a742-b11e65356b1f\")) {                    Plotly.newPlot(                        \"69e33d73-ea19-4a26-a742-b11e65356b1f\",                        [{\"name\":\"Histogram\",\"x\":[0.117572136,0.11920292,0.06278921,0.060086653,0.14706452,0.13568956,0.11920292,0.16344544,0.1490353,0.33025515,0.12085322,0.29746994,0.20946968,0.23792988,0.28298813,0.41489884,0.19806418,0.2885691,0.2120688,0.21733753,0.23231015,0.23510839,0.2146914,0.16238004,0.112795405,0.18126321,0.12506539,0.1943678,0.12592277,0.11920292,0.11920292,0.12085322,0.15002882,0.16885695,0.23651622,0.18010667,0.12085322,0.11920292,0.16451646,0.24220563,0.31405056,0.3548801,0.15304215,0.258326,0.5585678,0.12085322,0.13117322,0.18832397,0.11920292,0.19072403,0.11920292,0.16559312,0.11920292,0.11920292,0.26284185,0.21076629,0.11920292,0.12168575,0.117572136,0.15002882,0.39981166,0.33025515,0.26588047,0.23091978,0.114368536,0.14511536,0.115960725,0.4774323,0.19072403,0.26284185,0.3720488,0.12085322,0.115960725,0.11920292,0.14608724,0.117572136,0.14706452,0.1422319,0.39513415,0.20817892,0.11920292,0.109705776,0.114368536,0.50373834,0.258326,0.31489265,0.16995624,0.2885691,0.18713269,0.27904198,0.16885695,0.13386749,0.11920292,0.11920292,0.12002562,0.115960725,0.52244586,0.32594952,0.1732882,0.1431877,0.12002562,0.109705776,0.1066906,0.11920292,0.1112412,0.19559409,0.12002562,0.117572136,0.47670147,0.50823903,0.36568317,0.3106944,0.11920292,0.112795405,0.1112412,0.115960725,0.3015677,0.1847675,0.5481898,0.09534947,0.12168575,0.46611643,0.109705776,0.253861,0.26740816,0.33720353,0.18952109,0.28696787,0.36206648,0.4139509,0.14804721,0.123365626,0.114368536,0.13568956,0.41822162,0.18832397,0.4282334,0.12002562,0.23510839,0.115960725,0.090092994,0.11920292,0.1112412,0.24944726,0.25982565,0.10818896,0.115960725,0.44215468,0.25238407,0.256832,0.21076629,0.4786507,0.10818896,0.10521054,0.11920292,0.15713686,0.2766905,0.27048022,0.14511536,0.1490353,0.13028541,0.29746994,0.12002562,0.13028541,0.12678517,0.5123266,0.20307462,0.50646937,0.24364243,0.5341265,0.4378235,0.29746994,0.15203226,0.12678517,0.112795405,0.112795405,0.2782568,0.40591964,0.31742626,0.11920292,0.344223,0.28298813,0.24653335,0.21337718,0.5292634,0.23934935,0.055823144,0.4012185,0.18242553,0.13660839,0.13296424,0.12002562,0.17553808,0.24944726,0.5978427,0.3424616,0.114368536,0.1666754,0.484685,0.12252322,0.11920292,0.199308,0.117572136,0.12002562,0.115960725,0.12252322,0.21076629,0.11920292,0.112795405,0.117572136,0.12592277,0.1422319,0.57892436,0.3233801,0.13568956,0.10230471,0.49246272,0.48505086,0.46198758,0.3415825,0.3711366,0.117572136,0.16451646,0.12940274,0.11920292,0.11920292,0.12168575,0.6090592,0.11920292,0.12678517,0.5207401,0.43590155,0.21076629,0.1384618,0.20307462,0.11920292,0.24077459,0.27279878,0.117572136,0.45883366,0.3015677,0.1847675,0.33025515,0.12592277,0.11920292,0.55157375,0.62245935,0.258326,0.199308,0.38306415,0.2934045,0.13753247,0.16995624,0.12252322,0.24077459,0.11920292,0.13939638,0.24653335,0.2509128,0.1561049,0.1112412,0.30239108,0.09807933,0.5341265,0.3415825,0.4325427,0.11920292,0.35309353,0.23934935,0.14706452,0.20946968,0.16026603,0.14608724,0.5907792,0.5822535,0.19072403,0.37296185,0.22678363,0.13117322,0.16344544,0.4282334,0.36387292,0.61277324,0.58082765,0.17217185,0.26435837,0.12506539,0.26435837,0.11920292,0.44408253,0.6025294,0.5450436,0.8740772,0.23510839,0.48060057,0.57892436,0.31573597,0.2509128,0.14414886,0.13117322,0.5093983,0.6076632,0.36387292,0.6619229,0.2798285,0.5435902,0.08151976,0.62245935,0.62977463,0.199308,0.62337685,0.5669778,0.6951311,0.880797,0.5708099,0.9161096,0.018546565,0.68763,0.81640637,0.746139,0.58794314,0.3711366,0.29098085,0.7279754,0.15713686,0.6406359,0.677474,0.70089483,0.4581063,0.17667161,0.17106119,0.11920292,0.580352,0.41964793,0.18126321,0.256832,0.13117322,0.24364243,0.28061637,0.21337718,0.23370637,0.2146914,0.12506539,0.17781086,0.31997076,0.11920292,0.11920292,0.12085322,0.36749724,0.19314739,0.1847675,0.5936093,0.14706452,0.22541662,0.2120688,0.24798742,0.16451646,0.36658973,0.38815406,0.37570646,0.1422319,0.23370637,0.12168575,0.12252322,0.34598863,0.2509128,0.19806418,0.20817892,0.11920292,0.11920292,0.20561503,0.11920292,0.1422319,0.5148272,0.36116472,0.27904198,0.23091978,0.2043419,0.22270013,0.12168575,0.60206157,0.45035937,0.60206157,0.17667161,0.1943678,0.3738758,0.25982565,0.117572136,0.26133093,0.33895183,0.19072403,0.28696787,0.3720488,0.17895588,0.41489884,0.34864512,0.12252322,0.22000709,0.44095063,0.12252322,0.23510839,0.24798742,0.115960725,0.14033625,0.10230471,0.6893056,0.16995624,0.64332926,0.21076629,0.18832397,0.17895588,0.13477592,0.22815649,0.22678363,0.12085322,0.24653335,0.5048521,0.49200508,0.4201237,0.54455924,0.60206157,0.16559312,0.7325918,0.36026397,0.46879062,0.3970029,0.37022537,0.40074936,0.36206648,0.15405756,0.4696419,0.40309682,0.39280254,0.50482166,0.41253018,0.13117322,0.4248892,0.7648916,0.4411914,0.3566707,0.1859472,0.31827325,0.42155182,0.43350178,0.11920292,0.4882834,0.68510735,0.5286551,0.26133093,0.3424616,0.42250463,0.35936412,0.21733753,0.4390257,0.1943678,0.33720353,0.11920292,0.1384618,0.117572136,0.1112412,0.22678363,0.22678363,0.032589745,0.22541662,0.29746994,0.114368536,0.23231015,0.114368536,0.48999155,0.28061637,0.3191214,0.17106119,0.4945376,0.54334795,0.10818896,0.041462272,0.21337718,0.42059958,0.4976197,0.39047584,0.11920292,0.81640637,0.6504673,0.5123266,0.11920292,0.12252322,0.21733753,0.12002562,0.11920292,0.17553808,0.16132024,0.3191214,0.12678517,0.19806418,0.37799978,0.3276683,0.4622303,0.8221891,0.33895183,0.407805,0.13939638,0.41632196,0.39981166,0.3208213,0.01798621,0.61508787,0.7256486,0.61230963,0.64779824,0.4763361,0.73411953,0.12168575,0.8489722,0.6791787,0.40356684,0.13660839,0.1112412,0.15713686,0.11920292,0.1066906,0.57892436,0.5544705,0.27357438,0.3970029,0.12085322,0.16132024,0.13477592,0.1066906,0.09534947,0.18242553,0.3098584,0.40591964,0.880797,0.47244006,0.01798621,0.8740772,0.24364243,0.40544873,0.33633107,0.30074558,0.08632348,0.09947021,0.20561503,0.109705776,0.11920292,0.23510839,0.09807933,0.028436033,0.13296424,0.114368536,0.37754068,0.114368536,0.68846846,0.6270382,0.5978427,0.109705776,0.12506539,0.114368536,0.123365626,0.04813677,0.37022537,0.36568317,0.17441027,0.41253018,0.115960725,0.3684057,0.14128143,0.52634275,0.880797,0.8824279,0.5978427,0.1510278,0.38676342,0.55880857,0.115960725,0.34334174,0.117572136,0.117572136,0.14706452,0.08509905,0.27048022,0.12421302,0.100878626,0.112795405,0.37022537,0.37799978,0.112795405,0.21866935,0.068537496,0.08151976,0.033589505,0.08151976,0.21337718,0.10230471,0.2146914,0.11920292,0.5043639,0.13660839,0.7401744,0.26435837,0.1859472,0.12765263,0.11920292,0.199308,0.16132024,0.09534947,0.15713686,0.075858176,0.5072627,0.34687307,0.35042137,0.34953272,0.491639,0.13939638,0.09534947,0.0913821,0.117572136,0.13386749,0.10818896,0.16026603,0.51781476,0.42775524,0.40403706,0.5585678,0.112795405,0.1592174,0.1561049,0.18126321,0.09947021,0.11920292,0.13028541,0.6504673,0.10818896,0.14033625,0.1112412,0.22405544,0.08509905,0.10521054,0.09268778,0.096705794,0.09534947,0.7490872,0.22405544,0.090092994,0.11920292,0.13939638,0.42298123,0.114368536,0.083890386,0.18952109,0.12506539,0.09401018,0.036769465,0.43686226,0.35846534,0.49212712,0.114368536,0.115960725,0.114368536,0.114368536,0.27279878,0.13568956,0.07369627,0.79565805,0.199308,0.48340455,0.3165805,0.1066906,0.117572136,0.109705776,0.17667161,0.18713269,0.13386749,0.4513265,0.09401018,0.4899305,0.11920292,0.103748634,0.11920292,0.12002562,0.39934304,0.087563835,0.1066906,0.31573597,0.08035747,0.11920292,0.10818896,0.0913821,0.083890386,0.08632348,0.08509905,0.01798621,0.37570646,0.3720488,0.4981155,0.018833129,0.20946968,0.13296424,0.24653335,0.10230471,0.1561049,0.29746994,0.19559409,0.34598863,0.36568317,0.3720488,0.34334174,0.08632348,0.046724956,0.29992476,0.3693151,0.13939638,0.23510839,0.109705776,0.11920292,0.12002562,0.34598863,0.51647353,0.55664057,0.44552952,0.115960725,0.12940274,0.35220176,0.01798621,0.115960725,0.12002562,0.12252322,0.1384618,0.096705794,0.079210326,0.08632348,0.123365626,0.42345804,0.5817784,0.01798621,0.3539863,0.087563835,0.078078166,0.10818896,0.103748634,0.07477004,0.32939172,0.32594952,0.1384618,0.079210326,0.083890386,0.10230471,0.10230471,0.3106944,0.43638182,0.253861,0.103748634,0.1112412,0.115960725,0.117572136,0.117572136,0.4472189,0.055823144,0.41537303,0.13296424,0.08632348,0.23792988,0.12765263,0.32939172,0.115960725,0.10818896,0.11920292,0.103748634,0.114368536,0.10521054,0.09947021,0.16238004,0.09534947,0.08632348,0.115960725,0.109705776,0.1112412,0.109705776,0.112795405,0.1066906,0.19559409,0.26740816,0.0705596,0.069541745,0.37296185,0.36477757,0.4144248,0.03308598,0.45205212,0.064653486,0.38722676,0.39653543,0.3738758,0.22678363,0.71143085,0.42584398,0.114368536,0.114368536,0.09947021,0.12252322,0.18359363,0.24508502,0.17781086,0.47025004,0.42775524,0.5144003,0.47694507,0.4201237,0.11920292,0.1066906,0.10521054,0.07696084,0.4726835,0.4707366,0.37754068,0.36568317,0.1112412,0.23651622,0.40028042,0.09807933,0.11920292,0.1561049,0.11920292,0.0705596,0.08509905,0.112795405,0.1112412,0.11920292,0.09401018,0.11920292,0.1112412,0.114368536,0.21733753,0.12002562,0.4210756,0.11920292,0.24798742,0.117572136,0.36206648,0.21337718,0.10818896,0.109705776,0.12678517,0.08151976,0.4106381,0.5397111,0.4201237,0.35042137,0.11920292,0.11920292,0.20946968,0.64422506,0.0705596,0.22405544,0.112795405,0.4021573,0.12168575,0.08269734,0.1066906,0.7090191,0.02931223,0.41584745,0.80069196,0.34334174,0.09807933,0.115960725,0.083890386,0.11920292,0.5123266,0.6415346,0.46465865,0.597373,0.33895183,0.11920292,0.1112412,0.12852514,0.25534365,0.23091978,0.1112412,0.051082738,0.8333246,0.09268778,0.16776334,0.12506539,0.5126926,0.0705596,0.47244006,0.54601204,0.11920292,0.117572136,0.117572136,0.11920292,0.23231015,0.11920292,0.117572136,0.12252322,0.79182106,0.1066906,0.1112412,0.01798621,0.115960725,0.11920292,0.090092994,0.12421302,0.14511536,0.20946968,0.4210756,0.11920292,0.047425874,0.57606506,0.090092994,0.33545968,0.19193278,0.01798621,0.70089483,0.23091978,0.6104535,0.01798621,0.12592277,0.68763,0.15304215,0.100878626,0.12421302,0.4777978,0.12002562,0.11920292,0.4330222,0.14608724,0.117572136,0.0913821,0.18359363,0.117572136,0.10521054,0.117572136,0.096705794,0.10818896,0.7634837,0.6706083,0.01798621,0.85195273,0.09947021,0.115960725,0.14706452,0.1066906,0.41774645,0.11920292,0.11920292,0.10818896,0.6592955,0.6619229,0.592195,0.01798621,0.1561049,0.117572136,0.16776334,0.15002882,0.114368536,0.15713686,0.29421496,0.51257056,0.01798621,0.74761593,0.83004373,0.11920292,0.11920292,0.05419873,0.62245935,0.115960725,0.01798621,0.7994423,0.36026397,0.8407826,0.87147486,0.03308598,0.8679338,0.8539127,0.11920292,0.648689,0.54722214,0.30652705,0.5660185,0.7248703,0.13477592,0.3566707,0.1859472,0.117572136,0.6645403,0.5397111,0.08509905,0.6662797,0.7879312,0.09534947,0.36568317,0.11920292,0.26588047,0.11920292,0.16238004,0.11920292,0.50185394,0.6173973,0.14128143,0.20689404,0.14804721,0.51013047,0.3407045,0.256832,0.12506539,0.3328523,0.41774645,0.25534365,0.12421302,0.7892337,0.8233284,0.7520126,0.08509905,0.11920292,0.23091978,0.1384618,0.43398145,0.2043419,0.6415346,0.6451199,0.6178585,0.117572136],\"xbins\":{\"end\":1,\"size\":0.1,\"start\":0},\"type\":\"histogram\",\"xaxis\":\"x\",\"yaxis\":\"y\"},{\"labels\":[\"0.0-0.1\",\"0.1-0.2\",\"0.2-0.3\",\"0.3-0.4\",\"0.4-0.5\",\"0.5-0.6\",\"0.6-0.7\",\"0.7-0.8\",\"0.8-0.9\",\"0.9-1.0\"],\"name\":\"Distribution\",\"values\":[100,439,139,111,92,60,42,21,19,1],\"type\":\"pie\",\"domain\":{\"x\":[0.55,1.0],\"y\":[0.0,1.0]}}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmapgl\":[{\"type\":\"heatmapgl\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermapbox\":[{\"type\":\"scattermapbox\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05},\"mapbox\":{\"style\":\"light\"}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,0.45],\"title\":{\"text\":\"Value\"},\"range\":[0,1]},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Frequency\"}},\"title\":{\"text\":\"[exp57: 8b llama3, 1024 ctxlen, 64 segment len, 100k bs, 0.01 balance factor lr, no weight decay for balance factors] Global weights's distribution\"},\"height\":600,\"width\":1000},                        {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('69e33d73-ea19-4a26-a742-b11e65356b1f');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import plotly.graph_objects as go\n",
+    "from plotly.subplots import make_subplots\n",
+    "\n",
+    "# Assuming you have your n-dimensional tensor as 'tensor'\n",
+    "# Flatten the tensor\n",
+    "flat_tensor = global_weights.flatten()\n",
+    "\n",
+    "# Create bins\n",
+    "bins = np.arange(0, 1.1, 0.1)\n",
+    "\n",
+    "# Calculate histogram\n",
+    "hist, bin_edges = np.histogram(flat_tensor, bins=bins)\n",
+    "\n",
+    "# Create labels for pie chart\n",
+    "labels = [f'{bins[i]:.1f}-{bins[i+1]:.1f}' for i in range(len(bins)-1)]\n",
+    "\n",
+    "# Create subplot figure\n",
+    "fig = make_subplots(rows=1, cols=2, specs=[[{'type':'xy'}, {'type':'domain'}]])\n",
+    "\n",
+    "# Add histogram\n",
+    "fig.add_trace(go.Histogram(x=flat_tensor, xbins=dict(start=0, end=1, size=0.1), \n",
+    "                           name='Histogram'), row=1, col=1)\n",
+    "\n",
+    "# Add pie chart\n",
+    "fig.add_trace(go.Pie(labels=labels, values=hist, name='Distribution'), row=1, col=2)\n",
+    "\n",
+    "# Update layout\n",
+    "fig.update_layout(title_text=f\"[{ckp_name}] Global weights's distribution\",\n",
+    "                  xaxis_title_text='Value',\n",
+    "                  yaxis_title_text='Frequency',\n",
+    "                  height=600, width=1000)\n",
+    "\n",
+    "# Update axes\n",
+    "fig.update_xaxes(range=[0, 1], row=1, col=1)\n",
+    "\n",
+    "# Show plot\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "colorbar": {
+          "title": {
+           "text": "Value"
+          }
+         },
+         "colorscale": [
+          [
+           0,
+           "#440154"
+          ],
+          [
+           0.1111111111111111,
+           "#482878"
+          ],
+          [
+           0.2222222222222222,
+           "#3e4989"
+          ],
+          [
+           0.3333333333333333,
+           "#31688e"
+          ],
+          [
+           0.4444444444444444,
+           "#26828e"
+          ],
+          [
+           0.5555555555555556,
+           "#1f9e89"
+          ],
+          [
+           0.6666666666666666,
+           "#35b779"
+          ],
+          [
+           0.7777777777777778,
+           "#6ece58"
+          ],
+          [
+           0.8888888888888888,
+           "#b5de2b"
+          ],
+          [
+           1,
+           "#fde725"
+          ]
+         ],
+         "hoverongaps": false,
+         "type": "heatmap",
+         "x": [
+          "Head 0",
+          "Head 1",
+          "Head 2",
+          "Head 3",
+          "Head 4",
+          "Head 5",
+          "Head 6",
+          "Head 7",
+          "Head 8",
+          "Head 9",
+          "Head 10",
+          "Head 11",
+          "Head 12",
+          "Head 13",
+          "Head 14",
+          "Head 15",
+          "Head 16",
+          "Head 17",
+          "Head 18",
+          "Head 19",
+          "Head 20",
+          "Head 21",
+          "Head 22",
+          "Head 23",
+          "Head 24",
+          "Head 25",
+          "Head 26",
+          "Head 27",
+          "Head 28",
+          "Head 29",
+          "Head 30",
+          "Head 31"
+         ],
+         "y": [
+          "Layer 0",
+          "Layer 1",
+          "Layer 2",
+          "Layer 3",
+          "Layer 4",
+          "Layer 5",
+          "Layer 6",
+          "Layer 7",
+          "Layer 8",
+          "Layer 9",
+          "Layer 10",
+          "Layer 11",
+          "Layer 12",
+          "Layer 13",
+          "Layer 14",
+          "Layer 15",
+          "Layer 16",
+          "Layer 17",
+          "Layer 18",
+          "Layer 19",
+          "Layer 20",
+          "Layer 21",
+          "Layer 22",
+          "Layer 23",
+          "Layer 24",
+          "Layer 25",
+          "Layer 26",
+          "Layer 27",
+          "Layer 28",
+          "Layer 29",
+          "Layer 30",
+          "Layer 31"
+         ],
+         "z": [
+          [
+           0.11757213622331619,
+           0.11920291930437088,
+           0.06278920918703079,
+           0.060086652636528015,
+           0.14706452190876007,
+           0.13568955659866333,
+           0.11920291930437088,
+           0.16344544291496277,
+           0.14903530478477478,
+           0.3302551507949829,
+           0.12085322290658951,
+           0.29746994376182556,
+           0.20946967601776123,
+           0.23792988061904907,
+           0.28298813104629517,
+           0.4148988425731659,
+           0.1980641782283783,
+           0.2885690927505493,
+           0.21206879615783691,
+           0.21733753383159637,
+           0.23231014609336853,
+           0.2351083904504776,
+           0.2146914005279541,
+           0.16238003969192505,
+           0.1127954050898552,
+           0.18126320838928223,
+           0.1250653862953186,
+           0.19436779618263245,
+           0.1259227693080902,
+           0.11920291930437088,
+           0.11920291930437088,
+           0.12085322290658951
+          ],
+          [
+           0.15002882480621338,
+           0.16885694861412048,
+           0.23651622235774994,
+           0.18010666966438293,
+           0.12085322290658951,
+           0.11920291930437088,
+           0.16451646387577057,
+           0.2422056347131729,
+           0.314050555229187,
+           0.35488009452819824,
+           0.15304215252399445,
+           0.25832599401474,
+           0.5585678219795227,
+           0.12085322290658951,
+           0.13117322325706482,
+           0.188323974609375,
+           0.11920291930437088,
+           0.19072403013706207,
+           0.11920291930437088,
+           0.16559311747550964,
+           0.11920291930437088,
+           0.11920291930437088,
+           0.2628418505191803,
+           0.2107662856578827,
+           0.11920291930437088,
+           0.12168575078248978,
+           0.11757213622331619,
+           0.15002882480621338,
+           0.39981165528297424,
+           0.3302551507949829,
+           0.2658804655075073,
+           0.23091977834701538
+          ],
+          [
+           0.11436853557825089,
+           0.14511536061763763,
+           0.11596072465181351,
+           0.4774323105812073,
+           0.19072403013706207,
+           0.2628418505191803,
+           0.3720487952232361,
+           0.12085322290658951,
+           0.11596072465181351,
+           0.11920291930437088,
+           0.14608724415302277,
+           0.11757213622331619,
+           0.14706452190876007,
+           0.14223189651966095,
+           0.3951341509819031,
+           0.20817892253398895,
+           0.11920291930437088,
+           0.10970577597618103,
+           0.11436853557825089,
+           0.5037383437156677,
+           0.25832599401474,
+           0.31489264965057373,
+           0.169956237077713,
+           0.2885690927505493,
+           0.18713268637657166,
+           0.27904197573661804,
+           0.16885694861412048,
+           0.13386748731136322,
+           0.11920291930437088,
+           0.11920291930437088,
+           0.1200256198644638,
+           0.11596072465181351
+          ],
+          [
+           0.5224458575248718,
+           0.3259495198726654,
+           0.17328819632530212,
+           0.14318770170211792,
+           0.1200256198644638,
+           0.10970577597618103,
+           0.10669060051441193,
+           0.11920291930437088,
+           0.11124119907617569,
+           0.19559408724308014,
+           0.1200256198644638,
+           0.11757213622331619,
+           0.4767014682292938,
+           0.5082390308380127,
+           0.3656831681728363,
+           0.3106943964958191,
+           0.11920291930437088,
+           0.1127954050898552,
+           0.11124119907617569,
+           0.11596072465181351,
+           0.3015677034854889,
+           0.18476749956607819,
+           0.5481898188591003,
+           0.09534946829080582,
+           0.12168575078248978,
+           0.46611642837524414,
+           0.10970577597618103,
+           0.2538610100746155,
+           0.267408162355423,
+           0.3372035324573517,
+           0.18952108919620514,
+           0.2869678735733032
+          ],
+          [
+           0.36206647753715515,
+           0.4139508903026581,
+           0.14804720878601074,
+           0.1233656257390976,
+           0.11436853557825089,
+           0.13568955659866333,
+           0.4182216227054596,
+           0.188323974609375,
+           0.42823341488838196,
+           0.1200256198644638,
+           0.2351083904504776,
+           0.11596072465181351,
+           0.09009299427270889,
+           0.11920291930437088,
+           0.11124119907617569,
+           0.24944725632667542,
+           0.2598256468772888,
+           0.10818895697593689,
+           0.11596072465181351,
+           0.4421546757221222,
+           0.2523840665817261,
+           0.2568320035934448,
+           0.2107662856578827,
+           0.47865068912506104,
+           0.10818895697593689,
+           0.10521054267883301,
+           0.11920291930437088,
+           0.15713685750961304,
+           0.2766905128955841,
+           0.270480215549469,
+           0.14511536061763763,
+           0.14903530478477478
+          ],
+          [
+           0.13028541207313538,
+           0.29746994376182556,
+           0.1200256198644638,
+           0.13028541207313538,
+           0.12678517401218414,
+           0.5123265981674194,
+           0.2030746191740036,
+           0.5064693689346313,
+           0.2436424344778061,
+           0.5341265201568604,
+           0.43782350420951843,
+           0.29746994376182556,
+           0.1520322561264038,
+           0.12678517401218414,
+           0.1127954050898552,
+           0.1127954050898552,
+           0.2782568037509918,
+           0.4059196412563324,
+           0.31742626428604126,
+           0.11920291930437088,
+           0.3442229926586151,
+           0.28298813104629517,
+           0.2465333491563797,
+           0.2133771777153015,
+           0.5292633771896362,
+           0.2393493503332138,
+           0.05582314357161522,
+           0.4012185037136078,
+           0.18242552876472473,
+           0.13660839200019836,
+           0.13296423852443695,
+           0.1200256198644638
+          ],
+          [
+           0.1755380779504776,
+           0.24944725632667542,
+           0.5978426933288574,
+           0.34246158599853516,
+           0.11436853557825089,
+           0.16667540371418,
+           0.4846850037574768,
+           0.1225232183933258,
+           0.11920291930437088,
+           0.19930799305438995,
+           0.11757213622331619,
+           0.1200256198644638,
+           0.11596072465181351,
+           0.1225232183933258,
+           0.2107662856578827,
+           0.11920291930437088,
+           0.1127954050898552,
+           0.11757213622331619,
+           0.1259227693080902,
+           0.14223189651966095,
+           0.5789243578910828,
+           0.32338011264801025,
+           0.13568955659866333,
+           0.10230471193790436,
+           0.49246272444725037,
+           0.48505085706710815,
+           0.46198758482933044,
+           0.3415825068950653,
+           0.3711366057395935,
+           0.11757213622331619,
+           0.16451646387577057,
+           0.1294027417898178
+          ],
+          [
+           0.11920291930437088,
+           0.11920291930437088,
+           0.12168575078248978,
+           0.60905921459198,
+           0.11920291930437088,
+           0.12678517401218414,
+           0.5207400918006897,
+           0.43590155243873596,
+           0.2107662856578827,
+           0.13846179842948914,
+           0.2030746191740036,
+           0.11920291930437088,
+           0.24077458679676056,
+           0.2727987766265869,
+           0.11757213622331619,
+           0.4588336646556854,
+           0.3015677034854889,
+           0.18476749956607819,
+           0.3302551507949829,
+           0.1259227693080902,
+           0.11920291930437088,
+           0.5515737533569336,
+           0.622459352016449,
+           0.25832599401474,
+           0.19930799305438995,
+           0.3830641508102417,
+           0.2934044897556305,
+           0.13753247261047363,
+           0.169956237077713,
+           0.1225232183933258,
+           0.24077458679676056,
+           0.11920291930437088
+          ],
+          [
+           0.13939638435840607,
+           0.2465333491563797,
+           0.25091278553009033,
+           0.1561049073934555,
+           0.11124119907617569,
+           0.30239108204841614,
+           0.09807933121919632,
+           0.5341265201568604,
+           0.3415825068950653,
+           0.43254271149635315,
+           0.11920291930437088,
+           0.35309353470802307,
+           0.2393493503332138,
+           0.14706452190876007,
+           0.20946967601776123,
+           0.16026602685451508,
+           0.14608724415302277,
+           0.590779185295105,
+           0.5822535157203674,
+           0.19072403013706207,
+           0.3729618489742279,
+           0.2267836332321167,
+           0.13117322325706482,
+           0.16344544291496277,
+           0.42823341488838196,
+           0.3638729155063629,
+           0.6127732396125793,
+           0.5808276534080505,
+           0.17217184603214264,
+           0.26435837149620056,
+           0.1250653862953186,
+           0.26435837149620056
+          ],
+          [
+           0.11920291930437088,
+           0.4440825283527374,
+           0.6025294065475464,
+           0.5450435876846313,
+           0.8740772008895874,
+           0.2351083904504776,
+           0.4806005656719208,
+           0.5789243578910828,
+           0.31573596596717834,
+           0.25091278553009033,
+           0.14414885640144348,
+           0.13117322325706482,
+           0.5093982815742493,
+           0.6076632142066956,
+           0.3638729155063629,
+           0.6619228720664978,
+           0.2798284888267517,
+           0.5435901880264282,
+           0.08151976019144058,
+           0.622459352016449,
+           0.6297746300697327,
+           0.19930799305438995,
+           0.6233768463134766,
+           0.5669777989387512,
+           0.6951311230659485,
+           0.8807970285415649,
+           0.5708099007606506,
+           0.9161096215248108,
+           0.018546564504504204,
+           0.6876299977302551,
+           0.8164063692092896,
+           0.7461389899253845
+          ],
+          [
+           0.5879431366920471,
+           0.3711366057395935,
+           0.29098084568977356,
+           0.7279754281044006,
+           0.15713685750961304,
+           0.6406359076499939,
+           0.6774740219116211,
+           0.700894832611084,
+           0.45810630917549133,
+           0.1766716092824936,
+           0.1710611879825592,
+           0.11920291930437088,
+           0.5803520083427429,
+           0.4196479320526123,
+           0.18126320838928223,
+           0.2568320035934448,
+           0.13117322325706482,
+           0.2436424344778061,
+           0.2806163728237152,
+           0.2133771777153015,
+           0.23370636999607086,
+           0.2146914005279541,
+           0.1250653862953186,
+           0.17781086266040802,
+           0.3199707567691803,
+           0.11920291930437088,
+           0.11920291930437088,
+           0.12085322290658951,
+           0.3674972355365753,
+           0.19314739108085632,
+           0.18476749956607819,
+           0.5936092734336853
+          ],
+          [
+           0.14706452190876007,
+           0.2254166156053543,
+           0.21206879615783691,
+           0.24798741936683655,
+           0.16451646387577057,
+           0.3665897250175476,
+           0.3881540596485138,
+           0.3757064640522003,
+           0.14223189651966095,
+           0.23370636999607086,
+           0.12168575078248978,
+           0.1225232183933258,
+           0.3459886312484741,
+           0.25091278553009033,
+           0.1980641782283783,
+           0.20817892253398895,
+           0.11920291930437088,
+           0.11920291930437088,
+           0.20561502873897552,
+           0.11920291930437088,
+           0.14223189651966095,
+           0.5148271918296814,
+           0.36116471886634827,
+           0.27904197573661804,
+           0.23091977834701538,
+           0.20434190332889557,
+           0.22270013391971588,
+           0.12168575078248978,
+           0.6020615696907043,
+           0.45035937428474426,
+           0.6020615696907043,
+           0.1766716092824936
+          ],
+          [
+           0.19436779618263245,
+           0.37387579679489136,
+           0.2598256468772888,
+           0.11757213622331619,
+           0.2613309323787689,
+           0.33895182609558105,
+           0.19072403013706207,
+           0.2869678735733032,
+           0.3720487952232361,
+           0.17895588278770447,
+           0.4148988425731659,
+           0.3486451208591461,
+           0.1225232183933258,
+           0.22000709176063538,
+           0.4409506320953369,
+           0.1225232183933258,
+           0.2351083904504776,
+           0.24798741936683655,
+           0.11596072465181351,
+           0.14033624529838562,
+           0.10230471193790436,
+           0.6893056035041809,
+           0.169956237077713,
+           0.6433292627334595,
+           0.2107662856578827,
+           0.188323974609375,
+           0.17895588278770447,
+           0.13477592170238495,
+           0.22815649211406708,
+           0.2267836332321167,
+           0.12085322290658951,
+           0.2465333491563797
+          ],
+          [
+           0.5048521161079407,
+           0.4920050799846649,
+           0.4201236963272095,
+           0.5445592403411865,
+           0.6020615696907043,
+           0.16559311747550964,
+           0.7325918078422546,
+           0.36026397347450256,
+           0.46879062056541443,
+           0.3970029056072235,
+           0.37022536993026733,
+           0.4007493555545807,
+           0.36206647753715515,
+           0.1540575623512268,
+           0.46964189410209656,
+           0.4030968248844147,
+           0.39280253648757935,
+           0.5048216581344604,
+           0.41253018379211426,
+           0.13117322325706482,
+           0.4248892068862915,
+           0.7648916244506836,
+           0.4411914050579071,
+           0.35667070746421814,
+           0.18594719469547272,
+           0.31827324628829956,
+           0.42155182361602783,
+           0.4335017800331116,
+           0.11920291930437088,
+           0.4882833957672119,
+           0.6851073503494263,
+           0.5286551117897034
+          ],
+          [
+           0.2613309323787689,
+           0.34246158599853516,
+           0.42250463366508484,
+           0.3593641221523285,
+           0.21733753383159637,
+           0.4390257000923157,
+           0.19436779618263245,
+           0.3372035324573517,
+           0.11920291930437088,
+           0.13846179842948914,
+           0.11757213622331619,
+           0.11124119907617569,
+           0.2267836332321167,
+           0.2267836332321167,
+           0.03258974477648735,
+           0.2254166156053543,
+           0.29746994376182556,
+           0.11436853557825089,
+           0.23231014609336853,
+           0.11436853557825089,
+           0.48999154567718506,
+           0.2806163728237152,
+           0.319121390581131,
+           0.1710611879825592,
+           0.4945375919342041,
+           0.543347954750061,
+           0.10818895697593689,
+           0.04146227240562439,
+           0.2133771777153015,
+           0.4205995798110962,
+           0.4976196885108948,
+           0.3904758393764496
+          ],
+          [
+           0.11920291930437088,
+           0.8164063692092896,
+           0.6504672765731812,
+           0.5123265981674194,
+           0.11920291930437088,
+           0.1225232183933258,
+           0.21733753383159637,
+           0.1200256198644638,
+           0.11920291930437088,
+           0.1755380779504776,
+           0.16132023930549622,
+           0.319121390581131,
+           0.12678517401218414,
+           0.1980641782283783,
+           0.37799978256225586,
+           0.32766830921173096,
+           0.46223029494285583,
+           0.8221890926361084,
+           0.33895182609558105,
+           0.4078049957752228,
+           0.13939638435840607,
+           0.4163219630718231,
+           0.39981165528297424,
+           0.32082128524780273,
+           0.01798621006309986,
+           0.6150878667831421,
+           0.7256485819816589,
+           0.6123096346855164,
+           0.6477982401847839,
+           0.4763360917568207,
+           0.7341195344924927,
+           0.12168575078248978
+          ],
+          [
+           0.8489722013473511,
+           0.6791787147521973,
+           0.403566837310791,
+           0.13660839200019836,
+           0.11124119907617569,
+           0.15713685750961304,
+           0.11920291930437088,
+           0.10669060051441193,
+           0.5789243578910828,
+           0.5544704794883728,
+           0.2735743820667267,
+           0.3970029056072235,
+           0.12085322290658951,
+           0.16132023930549622,
+           0.13477592170238495,
+           0.10669060051441193,
+           0.09534946829080582,
+           0.18242552876472473,
+           0.30985841155052185,
+           0.4059196412563324,
+           0.8807970285415649,
+           0.47244006395339966,
+           0.01798621006309986,
+           0.8740772008895874,
+           0.2436424344778061,
+           0.4054487347602844,
+           0.3363310694694519,
+           0.30074557662010193,
+           0.08632347732782364,
+           0.09947021305561066,
+           0.20561502873897552,
+           0.10970577597618103
+          ],
+          [
+           0.11920291930437088,
+           0.2351083904504776,
+           0.09807933121919632,
+           0.02843603305518627,
+           0.13296423852443695,
+           0.11436853557825089,
+           0.3775406777858734,
+           0.11436853557825089,
+           0.6884684562683105,
+           0.6270381808280945,
+           0.5978426933288574,
+           0.10970577597618103,
+           0.1250653862953186,
+           0.11436853557825089,
+           0.1233656257390976,
+           0.048136770725250244,
+           0.37022536993026733,
+           0.3656831681728363,
+           0.17441026866436005,
+           0.41253018379211426,
+           0.11596072465181351,
+           0.36840569972991943,
+           0.14128142595291138,
+           0.5263427495956421,
+           0.8807970285415649,
+           0.8824278712272644,
+           0.5978426933288574,
+           0.15102779865264893,
+           0.38676342368125916,
+           0.5588085651397705,
+           0.11596072465181351,
+           0.34334173798561096
+          ],
+          [
+           0.11757213622331619,
+           0.11757213622331619,
+           0.14706452190876007,
+           0.08509904891252518,
+           0.270480215549469,
+           0.12421301752328873,
+           0.10087862610816956,
+           0.1127954050898552,
+           0.37022536993026733,
+           0.37799978256225586,
+           0.1127954050898552,
+           0.2186693549156189,
+           0.06853749603033066,
+           0.08151976019144058,
+           0.03358950465917587,
+           0.08151976019144058,
+           0.2133771777153015,
+           0.10230471193790436,
+           0.2146914005279541,
+           0.11920291930437088,
+           0.5043638944625854,
+           0.13660839200019836,
+           0.740174412727356,
+           0.26435837149620056,
+           0.18594719469547272,
+           0.1276526302099228,
+           0.11920291930437088,
+           0.19930799305438995,
+           0.16132023930549622,
+           0.09534946829080582,
+           0.15713685750961304,
+           0.07585817575454712
+          ],
+          [
+           0.5072627067565918,
+           0.34687307476997375,
+           0.35042136907577515,
+           0.34953272342681885,
+           0.49163898825645447,
+           0.13939638435840607,
+           0.09534946829080582,
+           0.09138210117816925,
+           0.11757213622331619,
+           0.13386748731136322,
+           0.10818895697593689,
+           0.16026602685451508,
+           0.5178147554397583,
+           0.4277552366256714,
+           0.4040370583534241,
+           0.5585678219795227,
+           0.1127954050898552,
+           0.15921740233898163,
+           0.1561049073934555,
+           0.18126320838928223,
+           0.09947021305561066,
+           0.11920291930437088,
+           0.13028541207313538,
+           0.6504672765731812,
+           0.10818895697593689,
+           0.14033624529838562,
+           0.11124119907617569,
+           0.2240554392337799,
+           0.08509904891252518,
+           0.10521054267883301,
+           0.09268777817487717,
+           0.09670579433441162
+          ],
+          [
+           0.09534946829080582,
+           0.7490872144699097,
+           0.2240554392337799,
+           0.09009299427270889,
+           0.11920291930437088,
+           0.13939638435840607,
+           0.42298123240470886,
+           0.11436853557825089,
+           0.0838903859257698,
+           0.18952108919620514,
+           0.1250653862953186,
+           0.09401018172502518,
+           0.03676946461200714,
+           0.4368622601032257,
+           0.3584653437137604,
+           0.49212712049484253,
+           0.11436853557825089,
+           0.11596072465181351,
+           0.11436853557825089,
+           0.11436853557825089,
+           0.2727987766265869,
+           0.13568955659866333,
+           0.07369627058506012,
+           0.7956580519676208,
+           0.19930799305438995,
+           0.4834045469760895,
+           0.31658050417900085,
+           0.10669060051441193,
+           0.11757213622331619,
+           0.10970577597618103,
+           0.1766716092824936,
+           0.18713268637657166
+          ],
+          [
+           0.13386748731136322,
+           0.45132648944854736,
+           0.09401018172502518,
+           0.48993051052093506,
+           0.11920291930437088,
+           0.1037486344575882,
+           0.11920291930437088,
+           0.1200256198644638,
+           0.3993430435657501,
+           0.08756383508443832,
+           0.10669060051441193,
+           0.31573596596717834,
+           0.08035746961832047,
+           0.11920291930437088,
+           0.10818895697593689,
+           0.09138210117816925,
+           0.0838903859257698,
+           0.08632347732782364,
+           0.08509904891252518,
+           0.01798621006309986,
+           0.3757064640522003,
+           0.3720487952232361,
+           0.49811550974845886,
+           0.018833128735423088,
+           0.20946967601776123,
+           0.13296423852443695,
+           0.2465333491563797,
+           0.10230471193790436,
+           0.1561049073934555,
+           0.29746994376182556,
+           0.19559408724308014,
+           0.3459886312484741
+          ],
+          [
+           0.3656831681728363,
+           0.3720487952232361,
+           0.34334173798561096,
+           0.08632347732782364,
+           0.04672495648264885,
+           0.2999247610569,
+           0.36931508779525757,
+           0.13939638435840607,
+           0.2351083904504776,
+           0.10970577597618103,
+           0.11920291930437088,
+           0.1200256198644638,
+           0.3459886312484741,
+           0.5164735317230225,
+           0.5566405653953552,
+           0.4455295205116272,
+           0.11596072465181351,
+           0.1294027417898178,
+           0.35220175981521606,
+           0.01798621006309986,
+           0.11596072465181351,
+           0.1200256198644638,
+           0.1225232183933258,
+           0.13846179842948914,
+           0.09670579433441162,
+           0.0792103260755539,
+           0.08632347732782364,
+           0.1233656257390976,
+           0.4234580397605896,
+           0.5817784070968628,
+           0.01798621006309986,
+           0.35398629307746887
+          ],
+          [
+           0.08756383508443832,
+           0.07807816565036774,
+           0.10818895697593689,
+           0.1037486344575882,
+           0.07477004081010818,
+           0.3293917179107666,
+           0.3259495198726654,
+           0.13846179842948914,
+           0.0792103260755539,
+           0.0838903859257698,
+           0.10230471193790436,
+           0.10230471193790436,
+           0.3106943964958191,
+           0.43638181686401367,
+           0.2538610100746155,
+           0.1037486344575882,
+           0.11124119907617569,
+           0.11596072465181351,
+           0.11757213622331619,
+           0.11757213622331619,
+           0.4472188949584961,
+           0.05582314357161522,
+           0.4153730273246765,
+           0.13296423852443695,
+           0.08632347732782364,
+           0.23792988061904907,
+           0.1276526302099228,
+           0.3293917179107666,
+           0.11596072465181351,
+           0.10818895697593689,
+           0.11920291930437088,
+           0.1037486344575882
+          ],
+          [
+           0.11436853557825089,
+           0.10521054267883301,
+           0.09947021305561066,
+           0.16238003969192505,
+           0.09534946829080582,
+           0.08632347732782364,
+           0.11596072465181351,
+           0.10970577597618103,
+           0.11124119907617569,
+           0.10970577597618103,
+           0.1127954050898552,
+           0.10669060051441193,
+           0.19559408724308014,
+           0.267408162355423,
+           0.07055959850549698,
+           0.06954174488782883,
+           0.3729618489742279,
+           0.3647775650024414,
+           0.4144248068332672,
+           0.03308597952127457,
+           0.45205211639404297,
+           0.06465348601341248,
+           0.38722676038742065,
+           0.3965354263782501,
+           0.37387579679489136,
+           0.2267836332321167,
+           0.7114308476448059,
+           0.4258439838886261,
+           0.11436853557825089,
+           0.11436853557825089,
+           0.09947021305561066,
+           0.1225232183933258
+          ],
+          [
+           0.18359363079071045,
+           0.24508501589298248,
+           0.17781086266040802,
+           0.47025004029273987,
+           0.4277552366256714,
+           0.5144003033638,
+           0.47694507241249084,
+           0.4201236963272095,
+           0.11920291930437088,
+           0.10669060051441193,
+           0.10521054267883301,
+           0.07696083933115005,
+           0.47268348932266235,
+           0.4707365930080414,
+           0.3775406777858734,
+           0.3656831681728363,
+           0.11124119907617569,
+           0.23651622235774994,
+           0.4002804160118103,
+           0.09807933121919632,
+           0.11920291930437088,
+           0.1561049073934555,
+           0.11920291930437088,
+           0.07055959850549698,
+           0.08509904891252518,
+           0.1127954050898552,
+           0.11124119907617569,
+           0.11920291930437088,
+           0.09401018172502518,
+           0.11920291930437088,
+           0.11124119907617569,
+           0.11436853557825089
+          ],
+          [
+           0.21733753383159637,
+           0.1200256198644638,
+           0.42107561230659485,
+           0.11920291930437088,
+           0.24798741936683655,
+           0.11757213622331619,
+           0.36206647753715515,
+           0.2133771777153015,
+           0.10818895697593689,
+           0.10970577597618103,
+           0.12678517401218414,
+           0.08151976019144058,
+           0.41063809394836426,
+           0.5397111177444458,
+           0.4201236963272095,
+           0.35042136907577515,
+           0.11920291930437088,
+           0.11920291930437088,
+           0.20946967601776123,
+           0.6442250609397888,
+           0.07055959850549698,
+           0.2240554392337799,
+           0.1127954050898552,
+           0.4021573066711426,
+           0.12168575078248978,
+           0.08269733935594559,
+           0.10669060051441193,
+           0.709019124507904,
+           0.02931223064661026,
+           0.41584745049476624,
+           0.8006919622421265,
+           0.34334173798561096
+          ],
+          [
+           0.09807933121919632,
+           0.11596072465181351,
+           0.0838903859257698,
+           0.11920291930437088,
+           0.5123265981674194,
+           0.6415346264839172,
+           0.46465864777565,
+           0.5973730087280273,
+           0.33895182609558105,
+           0.11920291930437088,
+           0.11124119907617569,
+           0.12852513790130615,
+           0.25534364581108093,
+           0.23091977834701538,
+           0.11124119907617569,
+           0.05108273774385452,
+           0.8333246111869812,
+           0.09268777817487717,
+           0.1677633374929428,
+           0.1250653862953186,
+           0.5126925706863403,
+           0.07055959850549698,
+           0.47244006395339966,
+           0.5460120439529419,
+           0.11920291930437088,
+           0.11757213622331619,
+           0.11757213622331619,
+           0.11920291930437088,
+           0.23231014609336853,
+           0.11920291930437088,
+           0.11757213622331619,
+           0.1225232183933258
+          ],
+          [
+           0.7918210625648499,
+           0.10669060051441193,
+           0.11124119907617569,
+           0.01798621006309986,
+           0.11596072465181351,
+           0.11920291930437088,
+           0.09009299427270889,
+           0.12421301752328873,
+           0.14511536061763763,
+           0.20946967601776123,
+           0.42107561230659485,
+           0.11920291930437088,
+           0.04742587357759476,
+           0.5760650634765625,
+           0.09009299427270889,
+           0.3354596793651581,
+           0.1919327825307846,
+           0.01798621006309986,
+           0.700894832611084,
+           0.23091977834701538,
+           0.6104534864425659,
+           0.01798621006309986,
+           0.1259227693080902,
+           0.6876299977302551,
+           0.15304215252399445,
+           0.10087862610816956,
+           0.12421301752328873,
+           0.47779780626296997,
+           0.1200256198644638,
+           0.11920291930437088,
+           0.4330222010612488,
+           0.14608724415302277
+          ],
+          [
+           0.11757213622331619,
+           0.09138210117816925,
+           0.18359363079071045,
+           0.11757213622331619,
+           0.10521054267883301,
+           0.11757213622331619,
+           0.09670579433441162,
+           0.10818895697593689,
+           0.7634837031364441,
+           0.6706082820892334,
+           0.01798621006309986,
+           0.8519527316093445,
+           0.09947021305561066,
+           0.11596072465181351,
+           0.14706452190876007,
+           0.10669060051441193,
+           0.4177464544773102,
+           0.11920291930437088,
+           0.11920291930437088,
+           0.10818895697593689,
+           0.6592954993247986,
+           0.6619228720664978,
+           0.5921949744224548,
+           0.01798621006309986,
+           0.1561049073934555,
+           0.11757213622331619,
+           0.1677633374929428,
+           0.15002882480621338,
+           0.11436853557825089,
+           0.15713685750961304,
+           0.29421496391296387,
+           0.5125705599784851
+          ],
+          [
+           0.01798621006309986,
+           0.7476159334182739,
+           0.8300437331199646,
+           0.11920291930437088,
+           0.11920291930437088,
+           0.0541987307369709,
+           0.622459352016449,
+           0.11596072465181351,
+           0.01798621006309986,
+           0.7994422912597656,
+           0.36026397347450256,
+           0.8407825827598572,
+           0.8714748620986938,
+           0.03308597952127457,
+           0.8679338097572327,
+           0.8539127111434937,
+           0.11920291930437088,
+           0.6486889719963074,
+           0.5472221374511719,
+           0.3065270483493805,
+           0.5660185217857361,
+           0.7248703241348267,
+           0.13477592170238495,
+           0.35667070746421814,
+           0.18594719469547272,
+           0.11757213622331619,
+           0.6645402908325195,
+           0.5397111177444458,
+           0.08509904891252518,
+           0.666279673576355,
+           0.7879312038421631,
+           0.09534946829080582
+          ],
+          [
+           0.3656831681728363,
+           0.11920291930437088,
+           0.2658804655075073,
+           0.11920291930437088,
+           0.16238003969192505,
+           0.11920291930437088,
+           0.5018539428710938,
+           0.6173973083496094,
+           0.14128142595291138,
+           0.20689404010772705,
+           0.14804720878601074,
+           0.5101304650306702,
+           0.3407045006752014,
+           0.2568320035934448,
+           0.1250653862953186,
+           0.332852303981781,
+           0.4177464544773102,
+           0.25534364581108093,
+           0.12421301752328873,
+           0.7892336845397949,
+           0.8233283758163452,
+           0.7520126104354858,
+           0.08509904891252518,
+           0.11920291930437088,
+           0.23091977834701538,
+           0.13846179842948914,
+           0.43398144841194153,
+           0.20434190332889557,
+           0.6415346264839172,
+           0.6451199054718018,
+           0.6178585290908813,
+           0.11757213622331619
+          ]
+         ],
+         "zmax": 1,
+         "zmin": 0
+        }
+       ],
+       "layout": {
+        "annotations": [
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 0,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 1,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.063",
+          "x": 2,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.060",
+          "x": 3,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.147",
+          "x": 4,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.136",
+          "x": 5,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 6,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.163",
+          "x": 7,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.149",
+          "x": 8,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.330",
+          "x": 9,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.121",
+          "x": 10,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.297",
+          "x": 11,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.209",
+          "x": 12,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.238",
+          "x": 13,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.283",
+          "x": 14,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.415",
+          "x": 15,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.198",
+          "x": 16,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.289",
+          "x": 17,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.212",
+          "x": 18,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.217",
+          "x": 19,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.232",
+          "x": 20,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.235",
+          "x": 21,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.215",
+          "x": 22,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.162",
+          "x": 23,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.113",
+          "x": 24,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.181",
+          "x": 25,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.125",
+          "x": 26,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.194",
+          "x": 27,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.126",
+          "x": 28,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 29,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 30,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.121",
+          "x": 31,
+          "y": 0
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.150",
+          "x": 0,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.169",
+          "x": 1,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.237",
+          "x": 2,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.180",
+          "x": 3,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.121",
+          "x": 4,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 5,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.165",
+          "x": 6,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.242",
+          "x": 7,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.314",
+          "x": 8,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.355",
+          "x": 9,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.153",
+          "x": 10,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.258",
+          "x": 11,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.559",
+          "x": 12,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.121",
+          "x": 13,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.131",
+          "x": 14,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.188",
+          "x": 15,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 16,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.191",
+          "x": 17,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 18,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.166",
+          "x": 19,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 20,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 21,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.263",
+          "x": 22,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.211",
+          "x": 23,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 24,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.122",
+          "x": 25,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 26,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.150",
+          "x": 27,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.400",
+          "x": 28,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.330",
+          "x": 29,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.266",
+          "x": 30,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.231",
+          "x": 31,
+          "y": 1
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 0,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.145",
+          "x": 1,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 2,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.477",
+          "x": 3,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.191",
+          "x": 4,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.263",
+          "x": 5,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.372",
+          "x": 6,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.121",
+          "x": 7,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 8,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 9,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.146",
+          "x": 10,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 11,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.147",
+          "x": 12,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.142",
+          "x": 13,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.395",
+          "x": 14,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.208",
+          "x": 15,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 16,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.110",
+          "x": 17,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 18,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.504",
+          "x": 19,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.258",
+          "x": 20,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.315",
+          "x": 21,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.170",
+          "x": 22,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.289",
+          "x": 23,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.187",
+          "x": 24,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.279",
+          "x": 25,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.169",
+          "x": 26,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.134",
+          "x": 27,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 28,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 29,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.120",
+          "x": 30,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 31,
+          "y": 2
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.522",
+          "x": 0,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.326",
+          "x": 1,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.173",
+          "x": 2,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.143",
+          "x": 3,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.120",
+          "x": 4,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.110",
+          "x": 5,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.107",
+          "x": 6,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 7,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 8,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.196",
+          "x": 9,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.120",
+          "x": 10,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 11,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.477",
+          "x": 12,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.508",
+          "x": 13,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.366",
+          "x": 14,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.311",
+          "x": 15,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 16,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.113",
+          "x": 17,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 18,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 19,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.302",
+          "x": 20,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.185",
+          "x": 21,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.548",
+          "x": 22,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.095",
+          "x": 23,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.122",
+          "x": 24,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.466",
+          "x": 25,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.110",
+          "x": 26,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.254",
+          "x": 27,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.267",
+          "x": 28,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.337",
+          "x": 29,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.190",
+          "x": 30,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.287",
+          "x": 31,
+          "y": 3
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.362",
+          "x": 0,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.414",
+          "x": 1,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.148",
+          "x": 2,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.123",
+          "x": 3,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 4,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.136",
+          "x": 5,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.418",
+          "x": 6,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.188",
+          "x": 7,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.428",
+          "x": 8,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.120",
+          "x": 9,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.235",
+          "x": 10,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 11,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.090",
+          "x": 12,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 13,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 14,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.249",
+          "x": 15,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.260",
+          "x": 16,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.108",
+          "x": 17,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 18,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.442",
+          "x": 19,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.252",
+          "x": 20,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.257",
+          "x": 21,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.211",
+          "x": 22,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.479",
+          "x": 23,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.108",
+          "x": 24,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.105",
+          "x": 25,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 26,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.157",
+          "x": 27,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.277",
+          "x": 28,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.270",
+          "x": 29,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.145",
+          "x": 30,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.149",
+          "x": 31,
+          "y": 4
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.130",
+          "x": 0,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.297",
+          "x": 1,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.120",
+          "x": 2,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.130",
+          "x": 3,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.127",
+          "x": 4,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.512",
+          "x": 5,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.203",
+          "x": 6,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.506",
+          "x": 7,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.244",
+          "x": 8,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.534",
+          "x": 9,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.438",
+          "x": 10,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.297",
+          "x": 11,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.152",
+          "x": 12,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.127",
+          "x": 13,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.113",
+          "x": 14,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.113",
+          "x": 15,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.278",
+          "x": 16,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.406",
+          "x": 17,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.317",
+          "x": 18,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 19,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.344",
+          "x": 20,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.283",
+          "x": 21,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.247",
+          "x": 22,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.213",
+          "x": 23,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.529",
+          "x": 24,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.239",
+          "x": 25,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.056",
+          "x": 26,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.401",
+          "x": 27,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.182",
+          "x": 28,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.137",
+          "x": 29,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.133",
+          "x": 30,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.120",
+          "x": 31,
+          "y": 5
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.176",
+          "x": 0,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.249",
+          "x": 1,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.598",
+          "x": 2,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.342",
+          "x": 3,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 4,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.167",
+          "x": 5,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.485",
+          "x": 6,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.123",
+          "x": 7,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 8,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.199",
+          "x": 9,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 10,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.120",
+          "x": 11,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 12,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.123",
+          "x": 13,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.211",
+          "x": 14,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 15,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.113",
+          "x": 16,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 17,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.126",
+          "x": 18,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.142",
+          "x": 19,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.579",
+          "x": 20,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.323",
+          "x": 21,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.136",
+          "x": 22,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.102",
+          "x": 23,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.492",
+          "x": 24,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.485",
+          "x": 25,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.462",
+          "x": 26,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.342",
+          "x": 27,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.371",
+          "x": 28,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 29,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.165",
+          "x": 30,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.129",
+          "x": 31,
+          "y": 6
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 0,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 1,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.122",
+          "x": 2,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.609",
+          "x": 3,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 4,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.127",
+          "x": 5,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.521",
+          "x": 6,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.436",
+          "x": 7,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.211",
+          "x": 8,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.138",
+          "x": 9,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.203",
+          "x": 10,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 11,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.241",
+          "x": 12,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.273",
+          "x": 13,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 14,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.459",
+          "x": 15,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.302",
+          "x": 16,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.185",
+          "x": 17,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.330",
+          "x": 18,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.126",
+          "x": 19,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 20,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.552",
+          "x": 21,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.622",
+          "x": 22,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.258",
+          "x": 23,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.199",
+          "x": 24,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.383",
+          "x": 25,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.293",
+          "x": 26,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.138",
+          "x": 27,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.170",
+          "x": 28,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.123",
+          "x": 29,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.241",
+          "x": 30,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 31,
+          "y": 7
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.139",
+          "x": 0,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.247",
+          "x": 1,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.251",
+          "x": 2,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.156",
+          "x": 3,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 4,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.302",
+          "x": 5,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.098",
+          "x": 6,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.534",
+          "x": 7,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.342",
+          "x": 8,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.433",
+          "x": 9,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 10,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.353",
+          "x": 11,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.239",
+          "x": 12,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.147",
+          "x": 13,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.209",
+          "x": 14,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.160",
+          "x": 15,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.146",
+          "x": 16,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.591",
+          "x": 17,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.582",
+          "x": 18,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.191",
+          "x": 19,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.373",
+          "x": 20,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.227",
+          "x": 21,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.131",
+          "x": 22,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.163",
+          "x": 23,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.428",
+          "x": 24,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.364",
+          "x": 25,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.613",
+          "x": 26,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.581",
+          "x": 27,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.172",
+          "x": 28,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.264",
+          "x": 29,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.125",
+          "x": 30,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.264",
+          "x": 31,
+          "y": 8
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 0,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.444",
+          "x": 1,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.603",
+          "x": 2,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.545",
+          "x": 3,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.874",
+          "x": 4,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.235",
+          "x": 5,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.481",
+          "x": 6,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.579",
+          "x": 7,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.316",
+          "x": 8,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.251",
+          "x": 9,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.144",
+          "x": 10,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.131",
+          "x": 11,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.509",
+          "x": 12,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.608",
+          "x": 13,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.364",
+          "x": 14,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.662",
+          "x": 15,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.280",
+          "x": 16,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.544",
+          "x": 17,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.082",
+          "x": 18,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.622",
+          "x": 19,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.630",
+          "x": 20,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.199",
+          "x": 21,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.623",
+          "x": 22,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.567",
+          "x": 23,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.695",
+          "x": 24,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.881",
+          "x": 25,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.571",
+          "x": 26,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.916",
+          "x": 27,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.019",
+          "x": 28,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.688",
+          "x": 29,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.816",
+          "x": 30,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.746",
+          "x": 31,
+          "y": 9
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.588",
+          "x": 0,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.371",
+          "x": 1,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.291",
+          "x": 2,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.728",
+          "x": 3,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.157",
+          "x": 4,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.641",
+          "x": 5,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.677",
+          "x": 6,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.701",
+          "x": 7,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.458",
+          "x": 8,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.177",
+          "x": 9,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.171",
+          "x": 10,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 11,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.580",
+          "x": 12,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.420",
+          "x": 13,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.181",
+          "x": 14,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.257",
+          "x": 15,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.131",
+          "x": 16,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.244",
+          "x": 17,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.281",
+          "x": 18,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.213",
+          "x": 19,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.234",
+          "x": 20,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.215",
+          "x": 21,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.125",
+          "x": 22,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.178",
+          "x": 23,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.320",
+          "x": 24,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 25,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 26,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.121",
+          "x": 27,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.367",
+          "x": 28,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.193",
+          "x": 29,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.185",
+          "x": 30,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.594",
+          "x": 31,
+          "y": 10
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.147",
+          "x": 0,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.225",
+          "x": 1,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.212",
+          "x": 2,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.248",
+          "x": 3,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.165",
+          "x": 4,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.367",
+          "x": 5,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.388",
+          "x": 6,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.376",
+          "x": 7,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.142",
+          "x": 8,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.234",
+          "x": 9,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.122",
+          "x": 10,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.123",
+          "x": 11,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.346",
+          "x": 12,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.251",
+          "x": 13,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.198",
+          "x": 14,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.208",
+          "x": 15,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 16,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 17,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.206",
+          "x": 18,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 19,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.142",
+          "x": 20,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.515",
+          "x": 21,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.361",
+          "x": 22,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.279",
+          "x": 23,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.231",
+          "x": 24,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.204",
+          "x": 25,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.223",
+          "x": 26,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.122",
+          "x": 27,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.602",
+          "x": 28,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.450",
+          "x": 29,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.602",
+          "x": 30,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.177",
+          "x": 31,
+          "y": 11
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.194",
+          "x": 0,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.374",
+          "x": 1,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.260",
+          "x": 2,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 3,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.261",
+          "x": 4,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.339",
+          "x": 5,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.191",
+          "x": 6,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.287",
+          "x": 7,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.372",
+          "x": 8,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.179",
+          "x": 9,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.415",
+          "x": 10,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.349",
+          "x": 11,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.123",
+          "x": 12,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.220",
+          "x": 13,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.441",
+          "x": 14,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.123",
+          "x": 15,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.235",
+          "x": 16,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.248",
+          "x": 17,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 18,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.140",
+          "x": 19,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.102",
+          "x": 20,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.689",
+          "x": 21,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.170",
+          "x": 22,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.643",
+          "x": 23,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.211",
+          "x": 24,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.188",
+          "x": 25,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.179",
+          "x": 26,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.135",
+          "x": 27,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.228",
+          "x": 28,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.227",
+          "x": 29,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.121",
+          "x": 30,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.247",
+          "x": 31,
+          "y": 12
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.505",
+          "x": 0,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.492",
+          "x": 1,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.420",
+          "x": 2,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.545",
+          "x": 3,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.602",
+          "x": 4,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.166",
+          "x": 5,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.733",
+          "x": 6,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.360",
+          "x": 7,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.469",
+          "x": 8,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.397",
+          "x": 9,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.370",
+          "x": 10,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.401",
+          "x": 11,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.362",
+          "x": 12,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.154",
+          "x": 13,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.470",
+          "x": 14,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.403",
+          "x": 15,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.393",
+          "x": 16,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.505",
+          "x": 17,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.413",
+          "x": 18,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.131",
+          "x": 19,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.425",
+          "x": 20,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.765",
+          "x": 21,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.441",
+          "x": 22,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.357",
+          "x": 23,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.186",
+          "x": 24,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.318",
+          "x": 25,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.422",
+          "x": 26,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.434",
+          "x": 27,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 28,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.488",
+          "x": 29,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.685",
+          "x": 30,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.529",
+          "x": 31,
+          "y": 13
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.261",
+          "x": 0,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.342",
+          "x": 1,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.423",
+          "x": 2,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.359",
+          "x": 3,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.217",
+          "x": 4,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.439",
+          "x": 5,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.194",
+          "x": 6,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.337",
+          "x": 7,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 8,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.138",
+          "x": 9,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 10,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 11,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.227",
+          "x": 12,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.227",
+          "x": 13,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.033",
+          "x": 14,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.225",
+          "x": 15,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.297",
+          "x": 16,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 17,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.232",
+          "x": 18,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 19,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.490",
+          "x": 20,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.281",
+          "x": 21,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.319",
+          "x": 22,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.171",
+          "x": 23,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.495",
+          "x": 24,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.543",
+          "x": 25,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.108",
+          "x": 26,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.041",
+          "x": 27,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.213",
+          "x": 28,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.421",
+          "x": 29,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.498",
+          "x": 30,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.390",
+          "x": 31,
+          "y": 14
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 0,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.816",
+          "x": 1,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.650",
+          "x": 2,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.512",
+          "x": 3,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 4,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.123",
+          "x": 5,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.217",
+          "x": 6,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.120",
+          "x": 7,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 8,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.176",
+          "x": 9,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.161",
+          "x": 10,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.319",
+          "x": 11,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.127",
+          "x": 12,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.198",
+          "x": 13,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.378",
+          "x": 14,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.328",
+          "x": 15,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.462",
+          "x": 16,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.822",
+          "x": 17,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.339",
+          "x": 18,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.408",
+          "x": 19,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.139",
+          "x": 20,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.416",
+          "x": 21,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.400",
+          "x": 22,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.321",
+          "x": 23,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.018",
+          "x": 24,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.615",
+          "x": 25,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.726",
+          "x": 26,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.612",
+          "x": 27,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.648",
+          "x": 28,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.476",
+          "x": 29,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.734",
+          "x": 30,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.122",
+          "x": 31,
+          "y": 15
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.849",
+          "x": 0,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.679",
+          "x": 1,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.404",
+          "x": 2,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.137",
+          "x": 3,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 4,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.157",
+          "x": 5,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 6,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.107",
+          "x": 7,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.579",
+          "x": 8,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.554",
+          "x": 9,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.274",
+          "x": 10,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.397",
+          "x": 11,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.121",
+          "x": 12,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.161",
+          "x": 13,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.135",
+          "x": 14,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.107",
+          "x": 15,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.095",
+          "x": 16,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.182",
+          "x": 17,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.310",
+          "x": 18,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.406",
+          "x": 19,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.881",
+          "x": 20,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.472",
+          "x": 21,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.018",
+          "x": 22,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.874",
+          "x": 23,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.244",
+          "x": 24,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.405",
+          "x": 25,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.336",
+          "x": 26,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.301",
+          "x": 27,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.086",
+          "x": 28,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.099",
+          "x": 29,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.206",
+          "x": 30,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.110",
+          "x": 31,
+          "y": 16
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 0,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.235",
+          "x": 1,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.098",
+          "x": 2,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.028",
+          "x": 3,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.133",
+          "x": 4,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 5,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.378",
+          "x": 6,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 7,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.688",
+          "x": 8,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.627",
+          "x": 9,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.598",
+          "x": 10,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.110",
+          "x": 11,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.125",
+          "x": 12,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 13,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.123",
+          "x": 14,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.048",
+          "x": 15,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.370",
+          "x": 16,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.366",
+          "x": 17,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.174",
+          "x": 18,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.413",
+          "x": 19,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 20,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.368",
+          "x": 21,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.141",
+          "x": 22,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.526",
+          "x": 23,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.881",
+          "x": 24,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.882",
+          "x": 25,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.598",
+          "x": 26,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.151",
+          "x": 27,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.387",
+          "x": 28,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.559",
+          "x": 29,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 30,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.343",
+          "x": 31,
+          "y": 17
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 0,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 1,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.147",
+          "x": 2,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.085",
+          "x": 3,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.270",
+          "x": 4,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.124",
+          "x": 5,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.101",
+          "x": 6,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.113",
+          "x": 7,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.370",
+          "x": 8,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.378",
+          "x": 9,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.113",
+          "x": 10,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.219",
+          "x": 11,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.069",
+          "x": 12,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.082",
+          "x": 13,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.034",
+          "x": 14,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.082",
+          "x": 15,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.213",
+          "x": 16,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.102",
+          "x": 17,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.215",
+          "x": 18,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 19,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.504",
+          "x": 20,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.137",
+          "x": 21,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.740",
+          "x": 22,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.264",
+          "x": 23,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.186",
+          "x": 24,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.128",
+          "x": 25,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 26,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.199",
+          "x": 27,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.161",
+          "x": 28,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.095",
+          "x": 29,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.157",
+          "x": 30,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.076",
+          "x": 31,
+          "y": 18
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.507",
+          "x": 0,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.347",
+          "x": 1,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.350",
+          "x": 2,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.350",
+          "x": 3,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.492",
+          "x": 4,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.139",
+          "x": 5,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.095",
+          "x": 6,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.091",
+          "x": 7,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 8,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.134",
+          "x": 9,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.108",
+          "x": 10,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.160",
+          "x": 11,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.518",
+          "x": 12,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.428",
+          "x": 13,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.404",
+          "x": 14,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.559",
+          "x": 15,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.113",
+          "x": 16,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.159",
+          "x": 17,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.156",
+          "x": 18,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.181",
+          "x": 19,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.099",
+          "x": 20,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 21,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.130",
+          "x": 22,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.650",
+          "x": 23,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.108",
+          "x": 24,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.140",
+          "x": 25,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 26,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.224",
+          "x": 27,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.085",
+          "x": 28,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.105",
+          "x": 29,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.093",
+          "x": 30,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.097",
+          "x": 31,
+          "y": 19
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.095",
+          "x": 0,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.749",
+          "x": 1,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.224",
+          "x": 2,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.090",
+          "x": 3,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 4,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.139",
+          "x": 5,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.423",
+          "x": 6,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 7,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.084",
+          "x": 8,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.190",
+          "x": 9,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.125",
+          "x": 10,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.094",
+          "x": 11,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.037",
+          "x": 12,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.437",
+          "x": 13,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.358",
+          "x": 14,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.492",
+          "x": 15,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 16,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 17,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 18,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 19,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.273",
+          "x": 20,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.136",
+          "x": 21,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.074",
+          "x": 22,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.796",
+          "x": 23,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.199",
+          "x": 24,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.483",
+          "x": 25,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.317",
+          "x": 26,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.107",
+          "x": 27,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 28,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.110",
+          "x": 29,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.177",
+          "x": 30,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.187",
+          "x": 31,
+          "y": 20
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.134",
+          "x": 0,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.451",
+          "x": 1,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.094",
+          "x": 2,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.490",
+          "x": 3,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 4,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.104",
+          "x": 5,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 6,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.120",
+          "x": 7,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.399",
+          "x": 8,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.088",
+          "x": 9,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.107",
+          "x": 10,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.316",
+          "x": 11,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.080",
+          "x": 12,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 13,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.108",
+          "x": 14,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.091",
+          "x": 15,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.084",
+          "x": 16,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.086",
+          "x": 17,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.085",
+          "x": 18,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.018",
+          "x": 19,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.376",
+          "x": 20,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.372",
+          "x": 21,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.498",
+          "x": 22,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.019",
+          "x": 23,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.209",
+          "x": 24,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.133",
+          "x": 25,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.247",
+          "x": 26,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.102",
+          "x": 27,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.156",
+          "x": 28,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.297",
+          "x": 29,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.196",
+          "x": 30,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.346",
+          "x": 31,
+          "y": 21
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.366",
+          "x": 0,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.372",
+          "x": 1,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.343",
+          "x": 2,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.086",
+          "x": 3,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.047",
+          "x": 4,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.300",
+          "x": 5,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.369",
+          "x": 6,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.139",
+          "x": 7,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.235",
+          "x": 8,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.110",
+          "x": 9,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 10,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.120",
+          "x": 11,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.346",
+          "x": 12,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.516",
+          "x": 13,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.557",
+          "x": 14,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.446",
+          "x": 15,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 16,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.129",
+          "x": 17,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.352",
+          "x": 18,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.018",
+          "x": 19,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 20,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.120",
+          "x": 21,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.123",
+          "x": 22,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.138",
+          "x": 23,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.097",
+          "x": 24,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.079",
+          "x": 25,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.086",
+          "x": 26,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.123",
+          "x": 27,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.423",
+          "x": 28,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.582",
+          "x": 29,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.018",
+          "x": 30,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.354",
+          "x": 31,
+          "y": 22
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.088",
+          "x": 0,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.078",
+          "x": 1,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.108",
+          "x": 2,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.104",
+          "x": 3,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.075",
+          "x": 4,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.329",
+          "x": 5,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.326",
+          "x": 6,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.138",
+          "x": 7,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.079",
+          "x": 8,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.084",
+          "x": 9,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.102",
+          "x": 10,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.102",
+          "x": 11,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.311",
+          "x": 12,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.436",
+          "x": 13,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.254",
+          "x": 14,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.104",
+          "x": 15,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 16,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 17,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 18,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 19,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.447",
+          "x": 20,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.056",
+          "x": 21,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.415",
+          "x": 22,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.133",
+          "x": 23,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.086",
+          "x": 24,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.238",
+          "x": 25,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.128",
+          "x": 26,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.329",
+          "x": 27,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 28,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.108",
+          "x": 29,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 30,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.104",
+          "x": 31,
+          "y": 23
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 0,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.105",
+          "x": 1,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.099",
+          "x": 2,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.162",
+          "x": 3,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.095",
+          "x": 4,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.086",
+          "x": 5,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 6,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.110",
+          "x": 7,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 8,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.110",
+          "x": 9,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.113",
+          "x": 10,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.107",
+          "x": 11,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.196",
+          "x": 12,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.267",
+          "x": 13,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.071",
+          "x": 14,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.070",
+          "x": 15,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.373",
+          "x": 16,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.365",
+          "x": 17,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.414",
+          "x": 18,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.033",
+          "x": 19,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.452",
+          "x": 20,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.065",
+          "x": 21,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.387",
+          "x": 22,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.397",
+          "x": 23,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.374",
+          "x": 24,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.227",
+          "x": 25,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.711",
+          "x": 26,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.426",
+          "x": 27,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 28,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 29,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.099",
+          "x": 30,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.123",
+          "x": 31,
+          "y": 24
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.184",
+          "x": 0,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.245",
+          "x": 1,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.178",
+          "x": 2,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.470",
+          "x": 3,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.428",
+          "x": 4,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.514",
+          "x": 5,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.477",
+          "x": 6,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.420",
+          "x": 7,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 8,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.107",
+          "x": 9,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.105",
+          "x": 10,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.077",
+          "x": 11,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.473",
+          "x": 12,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.471",
+          "x": 13,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.378",
+          "x": 14,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.366",
+          "x": 15,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 16,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.237",
+          "x": 17,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.400",
+          "x": 18,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.098",
+          "x": 19,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 20,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.156",
+          "x": 21,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 22,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.071",
+          "x": 23,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.085",
+          "x": 24,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.113",
+          "x": 25,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 26,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 27,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.094",
+          "x": 28,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 29,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 30,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 31,
+          "y": 25
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.217",
+          "x": 0,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.120",
+          "x": 1,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.421",
+          "x": 2,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 3,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.248",
+          "x": 4,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 5,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.362",
+          "x": 6,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.213",
+          "x": 7,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.108",
+          "x": 8,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.110",
+          "x": 9,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.127",
+          "x": 10,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.082",
+          "x": 11,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.411",
+          "x": 12,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.540",
+          "x": 13,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.420",
+          "x": 14,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.350",
+          "x": 15,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 16,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 17,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.209",
+          "x": 18,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.644",
+          "x": 19,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.071",
+          "x": 20,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.224",
+          "x": 21,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.113",
+          "x": 22,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.402",
+          "x": 23,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.122",
+          "x": 24,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.083",
+          "x": 25,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.107",
+          "x": 26,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.709",
+          "x": 27,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.029",
+          "x": 28,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.416",
+          "x": 29,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.801",
+          "x": 30,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.343",
+          "x": 31,
+          "y": 26
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.098",
+          "x": 0,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 1,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.084",
+          "x": 2,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 3,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.512",
+          "x": 4,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.642",
+          "x": 5,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.465",
+          "x": 6,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.597",
+          "x": 7,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.339",
+          "x": 8,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 9,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 10,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.129",
+          "x": 11,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.255",
+          "x": 12,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.231",
+          "x": 13,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 14,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.051",
+          "x": 15,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.833",
+          "x": 16,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.093",
+          "x": 17,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.168",
+          "x": 18,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.125",
+          "x": 19,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.513",
+          "x": 20,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.071",
+          "x": 21,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.472",
+          "x": 22,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.546",
+          "x": 23,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 24,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 25,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 26,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 27,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.232",
+          "x": 28,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 29,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 30,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.123",
+          "x": 31,
+          "y": 27
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.792",
+          "x": 0,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.107",
+          "x": 1,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.111",
+          "x": 2,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.018",
+          "x": 3,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 4,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 5,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.090",
+          "x": 6,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.124",
+          "x": 7,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.145",
+          "x": 8,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.209",
+          "x": 9,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.421",
+          "x": 10,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 11,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.047",
+          "x": 12,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.576",
+          "x": 13,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.090",
+          "x": 14,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.335",
+          "x": 15,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.192",
+          "x": 16,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.018",
+          "x": 17,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.701",
+          "x": 18,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.231",
+          "x": 19,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.610",
+          "x": 20,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.018",
+          "x": 21,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.126",
+          "x": 22,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.688",
+          "x": 23,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.153",
+          "x": 24,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.101",
+          "x": 25,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.124",
+          "x": 26,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.478",
+          "x": 27,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.120",
+          "x": 28,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 29,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.433",
+          "x": 30,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.146",
+          "x": 31,
+          "y": 28
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 0,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.091",
+          "x": 1,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.184",
+          "x": 2,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 3,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.105",
+          "x": 4,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 5,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.097",
+          "x": 6,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.108",
+          "x": 7,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.763",
+          "x": 8,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.671",
+          "x": 9,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.018",
+          "x": 10,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.852",
+          "x": 11,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.099",
+          "x": 12,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 13,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.147",
+          "x": 14,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.107",
+          "x": 15,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.418",
+          "x": 16,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 17,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 18,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.108",
+          "x": 19,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.659",
+          "x": 20,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.662",
+          "x": 21,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.592",
+          "x": 22,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.018",
+          "x": 23,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.156",
+          "x": 24,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 25,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.168",
+          "x": 26,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.150",
+          "x": 27,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.114",
+          "x": 28,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.157",
+          "x": 29,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.294",
+          "x": 30,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.513",
+          "x": 31,
+          "y": 29
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.018",
+          "x": 0,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.748",
+          "x": 1,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.830",
+          "x": 2,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 3,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 4,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.054",
+          "x": 5,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.622",
+          "x": 6,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.116",
+          "x": 7,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.018",
+          "x": 8,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.799",
+          "x": 9,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.360",
+          "x": 10,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.841",
+          "x": 11,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.871",
+          "x": 12,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.033",
+          "x": 13,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.868",
+          "x": 14,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.854",
+          "x": 15,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 16,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.649",
+          "x": 17,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.547",
+          "x": 18,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.307",
+          "x": 19,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.566",
+          "x": 20,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.725",
+          "x": 21,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.135",
+          "x": 22,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.357",
+          "x": 23,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.186",
+          "x": 24,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 25,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.665",
+          "x": 26,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.540",
+          "x": 27,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.085",
+          "x": 28,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.666",
+          "x": 29,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.788",
+          "x": 30,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.095",
+          "x": 31,
+          "y": 30
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.366",
+          "x": 0,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 1,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.266",
+          "x": 2,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 3,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.162",
+          "x": 4,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 5,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.502",
+          "x": 6,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.617",
+          "x": 7,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.141",
+          "x": 8,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.207",
+          "x": 9,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.148",
+          "x": 10,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.510",
+          "x": 11,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.341",
+          "x": 12,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.257",
+          "x": 13,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.125",
+          "x": 14,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.333",
+          "x": 15,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.418",
+          "x": 16,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.255",
+          "x": 17,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.124",
+          "x": 18,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.789",
+          "x": 19,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.823",
+          "x": 20,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.752",
+          "x": 21,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.085",
+          "x": 22,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.119",
+          "x": 23,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.231",
+          "x": 24,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.138",
+          "x": 25,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.434",
+          "x": 26,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.204",
+          "x": 27,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.642",
+          "x": 28,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.645",
+          "x": 29,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "white",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.618",
+          "x": 30,
+          "y": 31
+         },
+         {
+          "font": {
+           "color": "black",
+           "size": 8
+          },
+          "showarrow": false,
+          "text": "0.118",
+          "x": 31,
+          "y": 31
+         }
+        ],
+        "height": 750,
+        "template": {
+         "data": {
+          "bar": [
+           {
+            "error_x": {
+             "color": "#2a3f5f"
+            },
+            "error_y": {
+             "color": "#2a3f5f"
+            },
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             },
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "bar"
+           }
+          ],
+          "barpolar": [
+           {
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             },
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "barpolar"
+           }
+          ],
+          "carpet": [
+           {
+            "aaxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "baxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "type": "carpet"
+           }
+          ],
+          "choropleth": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "choropleth"
+           }
+          ],
+          "contour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "contour"
+           }
+          ],
+          "contourcarpet": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "contourcarpet"
+           }
+          ],
+          "heatmap": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmap"
+           }
+          ],
+          "heatmapgl": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmapgl"
+           }
+          ],
+          "histogram": [
+           {
+            "marker": {
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "histogram"
+           }
+          ],
+          "histogram2d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2d"
+           }
+          ],
+          "histogram2dcontour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2dcontour"
+           }
+          ],
+          "mesh3d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "mesh3d"
+           }
+          ],
+          "parcoords": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "parcoords"
+           }
+          ],
+          "pie": [
+           {
+            "automargin": true,
+            "type": "pie"
+           }
+          ],
+          "scatter": [
+           {
+            "fillpattern": {
+             "fillmode": "overlay",
+             "size": 10,
+             "solidity": 0.2
+            },
+            "type": "scatter"
+           }
+          ],
+          "scatter3d": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatter3d"
+           }
+          ],
+          "scattercarpet": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattercarpet"
+           }
+          ],
+          "scattergeo": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergeo"
+           }
+          ],
+          "scattergl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergl"
+           }
+          ],
+          "scattermapbox": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattermapbox"
+           }
+          ],
+          "scatterpolar": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolar"
+           }
+          ],
+          "scatterpolargl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolargl"
+           }
+          ],
+          "scatterternary": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterternary"
+           }
+          ],
+          "surface": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "surface"
+           }
+          ],
+          "table": [
+           {
+            "cells": {
+             "fill": {
+              "color": "#EBF0F8"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "header": {
+             "fill": {
+              "color": "#C8D4E3"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "type": "table"
+           }
+          ]
+         },
+         "layout": {
+          "annotationdefaults": {
+           "arrowcolor": "#2a3f5f",
+           "arrowhead": 0,
+           "arrowwidth": 1
+          },
+          "autotypenumbers": "strict",
+          "coloraxis": {
+           "colorbar": {
+            "outlinewidth": 0,
+            "ticks": ""
+           }
+          },
+          "colorscale": {
+           "diverging": [
+            [
+             0,
+             "#8e0152"
+            ],
+            [
+             0.1,
+             "#c51b7d"
+            ],
+            [
+             0.2,
+             "#de77ae"
+            ],
+            [
+             0.3,
+             "#f1b6da"
+            ],
+            [
+             0.4,
+             "#fde0ef"
+            ],
+            [
+             0.5,
+             "#f7f7f7"
+            ],
+            [
+             0.6,
+             "#e6f5d0"
+            ],
+            [
+             0.7,
+             "#b8e186"
+            ],
+            [
+             0.8,
+             "#7fbc41"
+            ],
+            [
+             0.9,
+             "#4d9221"
+            ],
+            [
+             1,
+             "#276419"
+            ]
+           ],
+           "sequential": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ],
+           "sequentialminus": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ]
+          },
+          "colorway": [
+           "#636efa",
+           "#EF553B",
+           "#00cc96",
+           "#ab63fa",
+           "#FFA15A",
+           "#19d3f3",
+           "#FF6692",
+           "#B6E880",
+           "#FF97FF",
+           "#FECB52"
+          ],
+          "font": {
+           "color": "#2a3f5f"
+          },
+          "geo": {
+           "bgcolor": "white",
+           "lakecolor": "white",
+           "landcolor": "#E5ECF6",
+           "showlakes": true,
+           "showland": true,
+           "subunitcolor": "white"
+          },
+          "hoverlabel": {
+           "align": "left"
+          },
+          "hovermode": "closest",
+          "mapbox": {
+           "style": "light"
+          },
+          "paper_bgcolor": "white",
+          "plot_bgcolor": "#E5ECF6",
+          "polar": {
+           "angularaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "zaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "line": {
+            "color": "#2a3f5f"
+           }
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        },
+        "title": {
+         "text": "[exp57: 8b llama3, 1024 ctxlen, 64 segment len, 100k bs, 0.01 balance factor lr, no weight decay for balance factors] Global Weights Across Layers and Heads"
+        },
+        "width": 1000,
+        "xaxis": {
+         "title": {
+          "text": "Head"
+         }
+        },
+        "yaxis": {
+         "autorange": "reversed",
+         "title": {
+          "text": "Layer"
+         }
+        }
+       }
+      },
+      "text/html": [
+       "<div>                            <div id=\"243464b6-1616-4cd8-96f3-c4571c9f794c\" class=\"plotly-graph-div\" style=\"height:750px; width:1000px;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"243464b6-1616-4cd8-96f3-c4571c9f794c\")) {                    Plotly.newPlot(                        \"243464b6-1616-4cd8-96f3-c4571c9f794c\",                        [{\"colorbar\":{\"title\":{\"text\":\"Value\"}},\"colorscale\":[[0.0,\"#440154\"],[0.1111111111111111,\"#482878\"],[0.2222222222222222,\"#3e4989\"],[0.3333333333333333,\"#31688e\"],[0.4444444444444444,\"#26828e\"],[0.5555555555555556,\"#1f9e89\"],[0.6666666666666666,\"#35b779\"],[0.7777777777777778,\"#6ece58\"],[0.8888888888888888,\"#b5de2b\"],[1.0,\"#fde725\"]],\"hoverongaps\":false,\"x\":[\"Head 0\",\"Head 1\",\"Head 2\",\"Head 3\",\"Head 4\",\"Head 5\",\"Head 6\",\"Head 7\",\"Head 8\",\"Head 9\",\"Head 10\",\"Head 11\",\"Head 12\",\"Head 13\",\"Head 14\",\"Head 15\",\"Head 16\",\"Head 17\",\"Head 18\",\"Head 19\",\"Head 20\",\"Head 21\",\"Head 22\",\"Head 23\",\"Head 24\",\"Head 25\",\"Head 26\",\"Head 27\",\"Head 28\",\"Head 29\",\"Head 30\",\"Head 31\"],\"y\":[\"Layer 0\",\"Layer 1\",\"Layer 2\",\"Layer 3\",\"Layer 4\",\"Layer 5\",\"Layer 6\",\"Layer 7\",\"Layer 8\",\"Layer 9\",\"Layer 10\",\"Layer 11\",\"Layer 12\",\"Layer 13\",\"Layer 14\",\"Layer 15\",\"Layer 16\",\"Layer 17\",\"Layer 18\",\"Layer 19\",\"Layer 20\",\"Layer 21\",\"Layer 22\",\"Layer 23\",\"Layer 24\",\"Layer 25\",\"Layer 26\",\"Layer 27\",\"Layer 28\",\"Layer 29\",\"Layer 30\",\"Layer 31\"],\"z\":[[0.11757213622331619,0.11920291930437088,0.06278920918703079,0.060086652636528015,0.14706452190876007,0.13568955659866333,0.11920291930437088,0.16344544291496277,0.14903530478477478,0.3302551507949829,0.12085322290658951,0.29746994376182556,0.20946967601776123,0.23792988061904907,0.28298813104629517,0.4148988425731659,0.1980641782283783,0.2885690927505493,0.21206879615783691,0.21733753383159637,0.23231014609336853,0.2351083904504776,0.2146914005279541,0.16238003969192505,0.1127954050898552,0.18126320838928223,0.1250653862953186,0.19436779618263245,0.1259227693080902,0.11920291930437088,0.11920291930437088,0.12085322290658951],[0.15002882480621338,0.16885694861412048,0.23651622235774994,0.18010666966438293,0.12085322290658951,0.11920291930437088,0.16451646387577057,0.2422056347131729,0.314050555229187,0.35488009452819824,0.15304215252399445,0.25832599401474,0.5585678219795227,0.12085322290658951,0.13117322325706482,0.188323974609375,0.11920291930437088,0.19072403013706207,0.11920291930437088,0.16559311747550964,0.11920291930437088,0.11920291930437088,0.2628418505191803,0.2107662856578827,0.11920291930437088,0.12168575078248978,0.11757213622331619,0.15002882480621338,0.39981165528297424,0.3302551507949829,0.2658804655075073,0.23091977834701538],[0.11436853557825089,0.14511536061763763,0.11596072465181351,0.4774323105812073,0.19072403013706207,0.2628418505191803,0.3720487952232361,0.12085322290658951,0.11596072465181351,0.11920291930437088,0.14608724415302277,0.11757213622331619,0.14706452190876007,0.14223189651966095,0.3951341509819031,0.20817892253398895,0.11920291930437088,0.10970577597618103,0.11436853557825089,0.5037383437156677,0.25832599401474,0.31489264965057373,0.169956237077713,0.2885690927505493,0.18713268637657166,0.27904197573661804,0.16885694861412048,0.13386748731136322,0.11920291930437088,0.11920291930437088,0.1200256198644638,0.11596072465181351],[0.5224458575248718,0.3259495198726654,0.17328819632530212,0.14318770170211792,0.1200256198644638,0.10970577597618103,0.10669060051441193,0.11920291930437088,0.11124119907617569,0.19559408724308014,0.1200256198644638,0.11757213622331619,0.4767014682292938,0.5082390308380127,0.3656831681728363,0.3106943964958191,0.11920291930437088,0.1127954050898552,0.11124119907617569,0.11596072465181351,0.3015677034854889,0.18476749956607819,0.5481898188591003,0.09534946829080582,0.12168575078248978,0.46611642837524414,0.10970577597618103,0.2538610100746155,0.267408162355423,0.3372035324573517,0.18952108919620514,0.2869678735733032],[0.36206647753715515,0.4139508903026581,0.14804720878601074,0.1233656257390976,0.11436853557825089,0.13568955659866333,0.4182216227054596,0.188323974609375,0.42823341488838196,0.1200256198644638,0.2351083904504776,0.11596072465181351,0.09009299427270889,0.11920291930437088,0.11124119907617569,0.24944725632667542,0.2598256468772888,0.10818895697593689,0.11596072465181351,0.4421546757221222,0.2523840665817261,0.2568320035934448,0.2107662856578827,0.47865068912506104,0.10818895697593689,0.10521054267883301,0.11920291930437088,0.15713685750961304,0.2766905128955841,0.270480215549469,0.14511536061763763,0.14903530478477478],[0.13028541207313538,0.29746994376182556,0.1200256198644638,0.13028541207313538,0.12678517401218414,0.5123265981674194,0.2030746191740036,0.5064693689346313,0.2436424344778061,0.5341265201568604,0.43782350420951843,0.29746994376182556,0.1520322561264038,0.12678517401218414,0.1127954050898552,0.1127954050898552,0.2782568037509918,0.4059196412563324,0.31742626428604126,0.11920291930437088,0.3442229926586151,0.28298813104629517,0.2465333491563797,0.2133771777153015,0.5292633771896362,0.2393493503332138,0.05582314357161522,0.4012185037136078,0.18242552876472473,0.13660839200019836,0.13296423852443695,0.1200256198644638],[0.1755380779504776,0.24944725632667542,0.5978426933288574,0.34246158599853516,0.11436853557825089,0.16667540371418,0.4846850037574768,0.1225232183933258,0.11920291930437088,0.19930799305438995,0.11757213622331619,0.1200256198644638,0.11596072465181351,0.1225232183933258,0.2107662856578827,0.11920291930437088,0.1127954050898552,0.11757213622331619,0.1259227693080902,0.14223189651966095,0.5789243578910828,0.32338011264801025,0.13568955659866333,0.10230471193790436,0.49246272444725037,0.48505085706710815,0.46198758482933044,0.3415825068950653,0.3711366057395935,0.11757213622331619,0.16451646387577057,0.1294027417898178],[0.11920291930437088,0.11920291930437088,0.12168575078248978,0.60905921459198,0.11920291930437088,0.12678517401218414,0.5207400918006897,0.43590155243873596,0.2107662856578827,0.13846179842948914,0.2030746191740036,0.11920291930437088,0.24077458679676056,0.2727987766265869,0.11757213622331619,0.4588336646556854,0.3015677034854889,0.18476749956607819,0.3302551507949829,0.1259227693080902,0.11920291930437088,0.5515737533569336,0.622459352016449,0.25832599401474,0.19930799305438995,0.3830641508102417,0.2934044897556305,0.13753247261047363,0.169956237077713,0.1225232183933258,0.24077458679676056,0.11920291930437088],[0.13939638435840607,0.2465333491563797,0.25091278553009033,0.1561049073934555,0.11124119907617569,0.30239108204841614,0.09807933121919632,0.5341265201568604,0.3415825068950653,0.43254271149635315,0.11920291930437088,0.35309353470802307,0.2393493503332138,0.14706452190876007,0.20946967601776123,0.16026602685451508,0.14608724415302277,0.590779185295105,0.5822535157203674,0.19072403013706207,0.3729618489742279,0.2267836332321167,0.13117322325706482,0.16344544291496277,0.42823341488838196,0.3638729155063629,0.6127732396125793,0.5808276534080505,0.17217184603214264,0.26435837149620056,0.1250653862953186,0.26435837149620056],[0.11920291930437088,0.4440825283527374,0.6025294065475464,0.5450435876846313,0.8740772008895874,0.2351083904504776,0.4806005656719208,0.5789243578910828,0.31573596596717834,0.25091278553009033,0.14414885640144348,0.13117322325706482,0.5093982815742493,0.6076632142066956,0.3638729155063629,0.6619228720664978,0.2798284888267517,0.5435901880264282,0.08151976019144058,0.622459352016449,0.6297746300697327,0.19930799305438995,0.6233768463134766,0.5669777989387512,0.6951311230659485,0.8807970285415649,0.5708099007606506,0.9161096215248108,0.018546564504504204,0.6876299977302551,0.8164063692092896,0.7461389899253845],[0.5879431366920471,0.3711366057395935,0.29098084568977356,0.7279754281044006,0.15713685750961304,0.6406359076499939,0.6774740219116211,0.700894832611084,0.45810630917549133,0.1766716092824936,0.1710611879825592,0.11920291930437088,0.5803520083427429,0.4196479320526123,0.18126320838928223,0.2568320035934448,0.13117322325706482,0.2436424344778061,0.2806163728237152,0.2133771777153015,0.23370636999607086,0.2146914005279541,0.1250653862953186,0.17781086266040802,0.3199707567691803,0.11920291930437088,0.11920291930437088,0.12085322290658951,0.3674972355365753,0.19314739108085632,0.18476749956607819,0.5936092734336853],[0.14706452190876007,0.2254166156053543,0.21206879615783691,0.24798741936683655,0.16451646387577057,0.3665897250175476,0.3881540596485138,0.3757064640522003,0.14223189651966095,0.23370636999607086,0.12168575078248978,0.1225232183933258,0.3459886312484741,0.25091278553009033,0.1980641782283783,0.20817892253398895,0.11920291930437088,0.11920291930437088,0.20561502873897552,0.11920291930437088,0.14223189651966095,0.5148271918296814,0.36116471886634827,0.27904197573661804,0.23091977834701538,0.20434190332889557,0.22270013391971588,0.12168575078248978,0.6020615696907043,0.45035937428474426,0.6020615696907043,0.1766716092824936],[0.19436779618263245,0.37387579679489136,0.2598256468772888,0.11757213622331619,0.2613309323787689,0.33895182609558105,0.19072403013706207,0.2869678735733032,0.3720487952232361,0.17895588278770447,0.4148988425731659,0.3486451208591461,0.1225232183933258,0.22000709176063538,0.4409506320953369,0.1225232183933258,0.2351083904504776,0.24798741936683655,0.11596072465181351,0.14033624529838562,0.10230471193790436,0.6893056035041809,0.169956237077713,0.6433292627334595,0.2107662856578827,0.188323974609375,0.17895588278770447,0.13477592170238495,0.22815649211406708,0.2267836332321167,0.12085322290658951,0.2465333491563797],[0.5048521161079407,0.4920050799846649,0.4201236963272095,0.5445592403411865,0.6020615696907043,0.16559311747550964,0.7325918078422546,0.36026397347450256,0.46879062056541443,0.3970029056072235,0.37022536993026733,0.4007493555545807,0.36206647753715515,0.1540575623512268,0.46964189410209656,0.4030968248844147,0.39280253648757935,0.5048216581344604,0.41253018379211426,0.13117322325706482,0.4248892068862915,0.7648916244506836,0.4411914050579071,0.35667070746421814,0.18594719469547272,0.31827324628829956,0.42155182361602783,0.4335017800331116,0.11920291930437088,0.4882833957672119,0.6851073503494263,0.5286551117897034],[0.2613309323787689,0.34246158599853516,0.42250463366508484,0.3593641221523285,0.21733753383159637,0.4390257000923157,0.19436779618263245,0.3372035324573517,0.11920291930437088,0.13846179842948914,0.11757213622331619,0.11124119907617569,0.2267836332321167,0.2267836332321167,0.03258974477648735,0.2254166156053543,0.29746994376182556,0.11436853557825089,0.23231014609336853,0.11436853557825089,0.48999154567718506,0.2806163728237152,0.319121390581131,0.1710611879825592,0.4945375919342041,0.543347954750061,0.10818895697593689,0.04146227240562439,0.2133771777153015,0.4205995798110962,0.4976196885108948,0.3904758393764496],[0.11920291930437088,0.8164063692092896,0.6504672765731812,0.5123265981674194,0.11920291930437088,0.1225232183933258,0.21733753383159637,0.1200256198644638,0.11920291930437088,0.1755380779504776,0.16132023930549622,0.319121390581131,0.12678517401218414,0.1980641782283783,0.37799978256225586,0.32766830921173096,0.46223029494285583,0.8221890926361084,0.33895182609558105,0.4078049957752228,0.13939638435840607,0.4163219630718231,0.39981165528297424,0.32082128524780273,0.01798621006309986,0.6150878667831421,0.7256485819816589,0.6123096346855164,0.6477982401847839,0.4763360917568207,0.7341195344924927,0.12168575078248978],[0.8489722013473511,0.6791787147521973,0.403566837310791,0.13660839200019836,0.11124119907617569,0.15713685750961304,0.11920291930437088,0.10669060051441193,0.5789243578910828,0.5544704794883728,0.2735743820667267,0.3970029056072235,0.12085322290658951,0.16132023930549622,0.13477592170238495,0.10669060051441193,0.09534946829080582,0.18242552876472473,0.30985841155052185,0.4059196412563324,0.8807970285415649,0.47244006395339966,0.01798621006309986,0.8740772008895874,0.2436424344778061,0.4054487347602844,0.3363310694694519,0.30074557662010193,0.08632347732782364,0.09947021305561066,0.20561502873897552,0.10970577597618103],[0.11920291930437088,0.2351083904504776,0.09807933121919632,0.02843603305518627,0.13296423852443695,0.11436853557825089,0.3775406777858734,0.11436853557825089,0.6884684562683105,0.6270381808280945,0.5978426933288574,0.10970577597618103,0.1250653862953186,0.11436853557825089,0.1233656257390976,0.048136770725250244,0.37022536993026733,0.3656831681728363,0.17441026866436005,0.41253018379211426,0.11596072465181351,0.36840569972991943,0.14128142595291138,0.5263427495956421,0.8807970285415649,0.8824278712272644,0.5978426933288574,0.15102779865264893,0.38676342368125916,0.5588085651397705,0.11596072465181351,0.34334173798561096],[0.11757213622331619,0.11757213622331619,0.14706452190876007,0.08509904891252518,0.270480215549469,0.12421301752328873,0.10087862610816956,0.1127954050898552,0.37022536993026733,0.37799978256225586,0.1127954050898552,0.2186693549156189,0.06853749603033066,0.08151976019144058,0.03358950465917587,0.08151976019144058,0.2133771777153015,0.10230471193790436,0.2146914005279541,0.11920291930437088,0.5043638944625854,0.13660839200019836,0.740174412727356,0.26435837149620056,0.18594719469547272,0.1276526302099228,0.11920291930437088,0.19930799305438995,0.16132023930549622,0.09534946829080582,0.15713685750961304,0.07585817575454712],[0.5072627067565918,0.34687307476997375,0.35042136907577515,0.34953272342681885,0.49163898825645447,0.13939638435840607,0.09534946829080582,0.09138210117816925,0.11757213622331619,0.13386748731136322,0.10818895697593689,0.16026602685451508,0.5178147554397583,0.4277552366256714,0.4040370583534241,0.5585678219795227,0.1127954050898552,0.15921740233898163,0.1561049073934555,0.18126320838928223,0.09947021305561066,0.11920291930437088,0.13028541207313538,0.6504672765731812,0.10818895697593689,0.14033624529838562,0.11124119907617569,0.2240554392337799,0.08509904891252518,0.10521054267883301,0.09268777817487717,0.09670579433441162],[0.09534946829080582,0.7490872144699097,0.2240554392337799,0.09009299427270889,0.11920291930437088,0.13939638435840607,0.42298123240470886,0.11436853557825089,0.0838903859257698,0.18952108919620514,0.1250653862953186,0.09401018172502518,0.03676946461200714,0.4368622601032257,0.3584653437137604,0.49212712049484253,0.11436853557825089,0.11596072465181351,0.11436853557825089,0.11436853557825089,0.2727987766265869,0.13568955659866333,0.07369627058506012,0.7956580519676208,0.19930799305438995,0.4834045469760895,0.31658050417900085,0.10669060051441193,0.11757213622331619,0.10970577597618103,0.1766716092824936,0.18713268637657166],[0.13386748731136322,0.45132648944854736,0.09401018172502518,0.48993051052093506,0.11920291930437088,0.1037486344575882,0.11920291930437088,0.1200256198644638,0.3993430435657501,0.08756383508443832,0.10669060051441193,0.31573596596717834,0.08035746961832047,0.11920291930437088,0.10818895697593689,0.09138210117816925,0.0838903859257698,0.08632347732782364,0.08509904891252518,0.01798621006309986,0.3757064640522003,0.3720487952232361,0.49811550974845886,0.018833128735423088,0.20946967601776123,0.13296423852443695,0.2465333491563797,0.10230471193790436,0.1561049073934555,0.29746994376182556,0.19559408724308014,0.3459886312484741],[0.3656831681728363,0.3720487952232361,0.34334173798561096,0.08632347732782364,0.04672495648264885,0.2999247610569,0.36931508779525757,0.13939638435840607,0.2351083904504776,0.10970577597618103,0.11920291930437088,0.1200256198644638,0.3459886312484741,0.5164735317230225,0.5566405653953552,0.4455295205116272,0.11596072465181351,0.1294027417898178,0.35220175981521606,0.01798621006309986,0.11596072465181351,0.1200256198644638,0.1225232183933258,0.13846179842948914,0.09670579433441162,0.0792103260755539,0.08632347732782364,0.1233656257390976,0.4234580397605896,0.5817784070968628,0.01798621006309986,0.35398629307746887],[0.08756383508443832,0.07807816565036774,0.10818895697593689,0.1037486344575882,0.07477004081010818,0.3293917179107666,0.3259495198726654,0.13846179842948914,0.0792103260755539,0.0838903859257698,0.10230471193790436,0.10230471193790436,0.3106943964958191,0.43638181686401367,0.2538610100746155,0.1037486344575882,0.11124119907617569,0.11596072465181351,0.11757213622331619,0.11757213622331619,0.4472188949584961,0.05582314357161522,0.4153730273246765,0.13296423852443695,0.08632347732782364,0.23792988061904907,0.1276526302099228,0.3293917179107666,0.11596072465181351,0.10818895697593689,0.11920291930437088,0.1037486344575882],[0.11436853557825089,0.10521054267883301,0.09947021305561066,0.16238003969192505,0.09534946829080582,0.08632347732782364,0.11596072465181351,0.10970577597618103,0.11124119907617569,0.10970577597618103,0.1127954050898552,0.10669060051441193,0.19559408724308014,0.267408162355423,0.07055959850549698,0.06954174488782883,0.3729618489742279,0.3647775650024414,0.4144248068332672,0.03308597952127457,0.45205211639404297,0.06465348601341248,0.38722676038742065,0.3965354263782501,0.37387579679489136,0.2267836332321167,0.7114308476448059,0.4258439838886261,0.11436853557825089,0.11436853557825089,0.09947021305561066,0.1225232183933258],[0.18359363079071045,0.24508501589298248,0.17781086266040802,0.47025004029273987,0.4277552366256714,0.5144003033638,0.47694507241249084,0.4201236963272095,0.11920291930437088,0.10669060051441193,0.10521054267883301,0.07696083933115005,0.47268348932266235,0.4707365930080414,0.3775406777858734,0.3656831681728363,0.11124119907617569,0.23651622235774994,0.4002804160118103,0.09807933121919632,0.11920291930437088,0.1561049073934555,0.11920291930437088,0.07055959850549698,0.08509904891252518,0.1127954050898552,0.11124119907617569,0.11920291930437088,0.09401018172502518,0.11920291930437088,0.11124119907617569,0.11436853557825089],[0.21733753383159637,0.1200256198644638,0.42107561230659485,0.11920291930437088,0.24798741936683655,0.11757213622331619,0.36206647753715515,0.2133771777153015,0.10818895697593689,0.10970577597618103,0.12678517401218414,0.08151976019144058,0.41063809394836426,0.5397111177444458,0.4201236963272095,0.35042136907577515,0.11920291930437088,0.11920291930437088,0.20946967601776123,0.6442250609397888,0.07055959850549698,0.2240554392337799,0.1127954050898552,0.4021573066711426,0.12168575078248978,0.08269733935594559,0.10669060051441193,0.709019124507904,0.02931223064661026,0.41584745049476624,0.8006919622421265,0.34334173798561096],[0.09807933121919632,0.11596072465181351,0.0838903859257698,0.11920291930437088,0.5123265981674194,0.6415346264839172,0.46465864777565,0.5973730087280273,0.33895182609558105,0.11920291930437088,0.11124119907617569,0.12852513790130615,0.25534364581108093,0.23091977834701538,0.11124119907617569,0.05108273774385452,0.8333246111869812,0.09268777817487717,0.1677633374929428,0.1250653862953186,0.5126925706863403,0.07055959850549698,0.47244006395339966,0.5460120439529419,0.11920291930437088,0.11757213622331619,0.11757213622331619,0.11920291930437088,0.23231014609336853,0.11920291930437088,0.11757213622331619,0.1225232183933258],[0.7918210625648499,0.10669060051441193,0.11124119907617569,0.01798621006309986,0.11596072465181351,0.11920291930437088,0.09009299427270889,0.12421301752328873,0.14511536061763763,0.20946967601776123,0.42107561230659485,0.11920291930437088,0.04742587357759476,0.5760650634765625,0.09009299427270889,0.3354596793651581,0.1919327825307846,0.01798621006309986,0.700894832611084,0.23091977834701538,0.6104534864425659,0.01798621006309986,0.1259227693080902,0.6876299977302551,0.15304215252399445,0.10087862610816956,0.12421301752328873,0.47779780626296997,0.1200256198644638,0.11920291930437088,0.4330222010612488,0.14608724415302277],[0.11757213622331619,0.09138210117816925,0.18359363079071045,0.11757213622331619,0.10521054267883301,0.11757213622331619,0.09670579433441162,0.10818895697593689,0.7634837031364441,0.6706082820892334,0.01798621006309986,0.8519527316093445,0.09947021305561066,0.11596072465181351,0.14706452190876007,0.10669060051441193,0.4177464544773102,0.11920291930437088,0.11920291930437088,0.10818895697593689,0.6592954993247986,0.6619228720664978,0.5921949744224548,0.01798621006309986,0.1561049073934555,0.11757213622331619,0.1677633374929428,0.15002882480621338,0.11436853557825089,0.15713685750961304,0.29421496391296387,0.5125705599784851],[0.01798621006309986,0.7476159334182739,0.8300437331199646,0.11920291930437088,0.11920291930437088,0.0541987307369709,0.622459352016449,0.11596072465181351,0.01798621006309986,0.7994422912597656,0.36026397347450256,0.8407825827598572,0.8714748620986938,0.03308597952127457,0.8679338097572327,0.8539127111434937,0.11920291930437088,0.6486889719963074,0.5472221374511719,0.3065270483493805,0.5660185217857361,0.7248703241348267,0.13477592170238495,0.35667070746421814,0.18594719469547272,0.11757213622331619,0.6645402908325195,0.5397111177444458,0.08509904891252518,0.666279673576355,0.7879312038421631,0.09534946829080582],[0.3656831681728363,0.11920291930437088,0.2658804655075073,0.11920291930437088,0.16238003969192505,0.11920291930437088,0.5018539428710938,0.6173973083496094,0.14128142595291138,0.20689404010772705,0.14804720878601074,0.5101304650306702,0.3407045006752014,0.2568320035934448,0.1250653862953186,0.332852303981781,0.4177464544773102,0.25534364581108093,0.12421301752328873,0.7892336845397949,0.8233283758163452,0.7520126104354858,0.08509904891252518,0.11920291930437088,0.23091977834701538,0.13846179842948914,0.43398144841194153,0.20434190332889557,0.6415346264839172,0.6451199054718018,0.6178585290908813,0.11757213622331619]],\"zmax\":1,\"zmin\":0,\"type\":\"heatmap\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmapgl\":[{\"type\":\"heatmapgl\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermapbox\":[{\"type\":\"scattermapbox\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05},\"mapbox\":{\"style\":\"light\"}}},\"annotations\":[{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":0,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":1,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.063\",\"x\":2,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.060\",\"x\":3,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.147\",\"x\":4,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.136\",\"x\":5,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":6,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.163\",\"x\":7,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.149\",\"x\":8,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.330\",\"x\":9,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.121\",\"x\":10,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.297\",\"x\":11,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.209\",\"x\":12,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.238\",\"x\":13,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.283\",\"x\":14,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.415\",\"x\":15,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.198\",\"x\":16,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.289\",\"x\":17,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.212\",\"x\":18,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.217\",\"x\":19,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.232\",\"x\":20,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.235\",\"x\":21,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.215\",\"x\":22,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.162\",\"x\":23,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.113\",\"x\":24,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.181\",\"x\":25,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.125\",\"x\":26,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.194\",\"x\":27,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.126\",\"x\":28,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":29,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":30,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.121\",\"x\":31,\"y\":0},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.150\",\"x\":0,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.169\",\"x\":1,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.237\",\"x\":2,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.180\",\"x\":3,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.121\",\"x\":4,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":5,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.165\",\"x\":6,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.242\",\"x\":7,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.314\",\"x\":8,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.355\",\"x\":9,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.153\",\"x\":10,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.258\",\"x\":11,\"y\":1},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.559\",\"x\":12,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.121\",\"x\":13,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.131\",\"x\":14,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.188\",\"x\":15,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":16,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.191\",\"x\":17,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":18,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.166\",\"x\":19,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":20,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":21,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.263\",\"x\":22,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.211\",\"x\":23,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":24,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.122\",\"x\":25,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":26,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.150\",\"x\":27,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.400\",\"x\":28,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.330\",\"x\":29,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.266\",\"x\":30,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.231\",\"x\":31,\"y\":1},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":0,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.145\",\"x\":1,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":2,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.477\",\"x\":3,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.191\",\"x\":4,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.263\",\"x\":5,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.372\",\"x\":6,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.121\",\"x\":7,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":8,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":9,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.146\",\"x\":10,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":11,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.147\",\"x\":12,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.142\",\"x\":13,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.395\",\"x\":14,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.208\",\"x\":15,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":16,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.110\",\"x\":17,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":18,\"y\":2},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.504\",\"x\":19,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.258\",\"x\":20,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.315\",\"x\":21,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.170\",\"x\":22,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.289\",\"x\":23,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.187\",\"x\":24,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.279\",\"x\":25,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.169\",\"x\":26,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.134\",\"x\":27,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":28,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":29,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.120\",\"x\":30,\"y\":2},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":31,\"y\":2},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.522\",\"x\":0,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.326\",\"x\":1,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.173\",\"x\":2,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.143\",\"x\":3,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.120\",\"x\":4,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.110\",\"x\":5,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.107\",\"x\":6,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":7,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":8,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.196\",\"x\":9,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.120\",\"x\":10,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":11,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.477\",\"x\":12,\"y\":3},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.508\",\"x\":13,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.366\",\"x\":14,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.311\",\"x\":15,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":16,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.113\",\"x\":17,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":18,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":19,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.302\",\"x\":20,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.185\",\"x\":21,\"y\":3},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.548\",\"x\":22,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.095\",\"x\":23,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.122\",\"x\":24,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.466\",\"x\":25,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.110\",\"x\":26,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.254\",\"x\":27,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.267\",\"x\":28,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.337\",\"x\":29,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.190\",\"x\":30,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.287\",\"x\":31,\"y\":3},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.362\",\"x\":0,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.414\",\"x\":1,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.148\",\"x\":2,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.123\",\"x\":3,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":4,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.136\",\"x\":5,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.418\",\"x\":6,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.188\",\"x\":7,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.428\",\"x\":8,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.120\",\"x\":9,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.235\",\"x\":10,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":11,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.090\",\"x\":12,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":13,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":14,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.249\",\"x\":15,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.260\",\"x\":16,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.108\",\"x\":17,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":18,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.442\",\"x\":19,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.252\",\"x\":20,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.257\",\"x\":21,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.211\",\"x\":22,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.479\",\"x\":23,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.108\",\"x\":24,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.105\",\"x\":25,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":26,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.157\",\"x\":27,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.277\",\"x\":28,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.270\",\"x\":29,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.145\",\"x\":30,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.149\",\"x\":31,\"y\":4},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.130\",\"x\":0,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.297\",\"x\":1,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.120\",\"x\":2,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.130\",\"x\":3,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.127\",\"x\":4,\"y\":5},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.512\",\"x\":5,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.203\",\"x\":6,\"y\":5},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.506\",\"x\":7,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.244\",\"x\":8,\"y\":5},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.534\",\"x\":9,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.438\",\"x\":10,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.297\",\"x\":11,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.152\",\"x\":12,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.127\",\"x\":13,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.113\",\"x\":14,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.113\",\"x\":15,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.278\",\"x\":16,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.406\",\"x\":17,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.317\",\"x\":18,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":19,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.344\",\"x\":20,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.283\",\"x\":21,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.247\",\"x\":22,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.213\",\"x\":23,\"y\":5},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.529\",\"x\":24,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.239\",\"x\":25,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.056\",\"x\":26,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.401\",\"x\":27,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.182\",\"x\":28,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.137\",\"x\":29,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.133\",\"x\":30,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.120\",\"x\":31,\"y\":5},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.176\",\"x\":0,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.249\",\"x\":1,\"y\":6},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.598\",\"x\":2,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.342\",\"x\":3,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":4,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.167\",\"x\":5,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.485\",\"x\":6,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.123\",\"x\":7,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":8,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.199\",\"x\":9,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":10,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.120\",\"x\":11,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":12,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.123\",\"x\":13,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.211\",\"x\":14,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":15,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.113\",\"x\":16,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":17,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.126\",\"x\":18,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.142\",\"x\":19,\"y\":6},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.579\",\"x\":20,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.323\",\"x\":21,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.136\",\"x\":22,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.102\",\"x\":23,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.492\",\"x\":24,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.485\",\"x\":25,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.462\",\"x\":26,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.342\",\"x\":27,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.371\",\"x\":28,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":29,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.165\",\"x\":30,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.129\",\"x\":31,\"y\":6},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":0,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":1,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.122\",\"x\":2,\"y\":7},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.609\",\"x\":3,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":4,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.127\",\"x\":5,\"y\":7},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.521\",\"x\":6,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.436\",\"x\":7,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.211\",\"x\":8,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.138\",\"x\":9,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.203\",\"x\":10,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":11,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.241\",\"x\":12,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.273\",\"x\":13,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":14,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.459\",\"x\":15,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.302\",\"x\":16,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.185\",\"x\":17,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.330\",\"x\":18,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.126\",\"x\":19,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":20,\"y\":7},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.552\",\"x\":21,\"y\":7},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.622\",\"x\":22,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.258\",\"x\":23,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.199\",\"x\":24,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.383\",\"x\":25,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.293\",\"x\":26,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.138\",\"x\":27,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.170\",\"x\":28,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.123\",\"x\":29,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.241\",\"x\":30,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":31,\"y\":7},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.139\",\"x\":0,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.247\",\"x\":1,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.251\",\"x\":2,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.156\",\"x\":3,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":4,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.302\",\"x\":5,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.098\",\"x\":6,\"y\":8},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.534\",\"x\":7,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.342\",\"x\":8,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.433\",\"x\":9,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":10,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.353\",\"x\":11,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.239\",\"x\":12,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.147\",\"x\":13,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.209\",\"x\":14,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.160\",\"x\":15,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.146\",\"x\":16,\"y\":8},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.591\",\"x\":17,\"y\":8},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.582\",\"x\":18,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.191\",\"x\":19,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.373\",\"x\":20,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.227\",\"x\":21,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.131\",\"x\":22,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.163\",\"x\":23,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.428\",\"x\":24,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.364\",\"x\":25,\"y\":8},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.613\",\"x\":26,\"y\":8},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.581\",\"x\":27,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.172\",\"x\":28,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.264\",\"x\":29,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.125\",\"x\":30,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.264\",\"x\":31,\"y\":8},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":0,\"y\":9},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.444\",\"x\":1,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.603\",\"x\":2,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.545\",\"x\":3,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.874\",\"x\":4,\"y\":9},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.235\",\"x\":5,\"y\":9},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.481\",\"x\":6,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.579\",\"x\":7,\"y\":9},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.316\",\"x\":8,\"y\":9},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.251\",\"x\":9,\"y\":9},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.144\",\"x\":10,\"y\":9},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.131\",\"x\":11,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.509\",\"x\":12,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.608\",\"x\":13,\"y\":9},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.364\",\"x\":14,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.662\",\"x\":15,\"y\":9},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.280\",\"x\":16,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.544\",\"x\":17,\"y\":9},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.082\",\"x\":18,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.622\",\"x\":19,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.630\",\"x\":20,\"y\":9},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.199\",\"x\":21,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.623\",\"x\":22,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.567\",\"x\":23,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.695\",\"x\":24,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.881\",\"x\":25,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.571\",\"x\":26,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.916\",\"x\":27,\"y\":9},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.019\",\"x\":28,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.688\",\"x\":29,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.816\",\"x\":30,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.746\",\"x\":31,\"y\":9},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.588\",\"x\":0,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.371\",\"x\":1,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.291\",\"x\":2,\"y\":10},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.728\",\"x\":3,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.157\",\"x\":4,\"y\":10},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.641\",\"x\":5,\"y\":10},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.677\",\"x\":6,\"y\":10},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.701\",\"x\":7,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.458\",\"x\":8,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.177\",\"x\":9,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.171\",\"x\":10,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":11,\"y\":10},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.580\",\"x\":12,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.420\",\"x\":13,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.181\",\"x\":14,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.257\",\"x\":15,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.131\",\"x\":16,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.244\",\"x\":17,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.281\",\"x\":18,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.213\",\"x\":19,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.234\",\"x\":20,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.215\",\"x\":21,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.125\",\"x\":22,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.178\",\"x\":23,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.320\",\"x\":24,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":25,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":26,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.121\",\"x\":27,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.367\",\"x\":28,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.193\",\"x\":29,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.185\",\"x\":30,\"y\":10},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.594\",\"x\":31,\"y\":10},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.147\",\"x\":0,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.225\",\"x\":1,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.212\",\"x\":2,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.248\",\"x\":3,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.165\",\"x\":4,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.367\",\"x\":5,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.388\",\"x\":6,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.376\",\"x\":7,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.142\",\"x\":8,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.234\",\"x\":9,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.122\",\"x\":10,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.123\",\"x\":11,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.346\",\"x\":12,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.251\",\"x\":13,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.198\",\"x\":14,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.208\",\"x\":15,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":16,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":17,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.206\",\"x\":18,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":19,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.142\",\"x\":20,\"y\":11},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.515\",\"x\":21,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.361\",\"x\":22,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.279\",\"x\":23,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.231\",\"x\":24,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.204\",\"x\":25,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.223\",\"x\":26,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.122\",\"x\":27,\"y\":11},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.602\",\"x\":28,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.450\",\"x\":29,\"y\":11},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.602\",\"x\":30,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.177\",\"x\":31,\"y\":11},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.194\",\"x\":0,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.374\",\"x\":1,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.260\",\"x\":2,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":3,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.261\",\"x\":4,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.339\",\"x\":5,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.191\",\"x\":6,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.287\",\"x\":7,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.372\",\"x\":8,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.179\",\"x\":9,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.415\",\"x\":10,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.349\",\"x\":11,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.123\",\"x\":12,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.220\",\"x\":13,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.441\",\"x\":14,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.123\",\"x\":15,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.235\",\"x\":16,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.248\",\"x\":17,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":18,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.140\",\"x\":19,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.102\",\"x\":20,\"y\":12},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.689\",\"x\":21,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.170\",\"x\":22,\"y\":12},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.643\",\"x\":23,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.211\",\"x\":24,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.188\",\"x\":25,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.179\",\"x\":26,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.135\",\"x\":27,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.228\",\"x\":28,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.227\",\"x\":29,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.121\",\"x\":30,\"y\":12},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.247\",\"x\":31,\"y\":12},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.505\",\"x\":0,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.492\",\"x\":1,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.420\",\"x\":2,\"y\":13},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.545\",\"x\":3,\"y\":13},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.602\",\"x\":4,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.166\",\"x\":5,\"y\":13},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.733\",\"x\":6,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.360\",\"x\":7,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.469\",\"x\":8,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.397\",\"x\":9,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.370\",\"x\":10,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.401\",\"x\":11,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.362\",\"x\":12,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.154\",\"x\":13,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.470\",\"x\":14,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.403\",\"x\":15,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.393\",\"x\":16,\"y\":13},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.505\",\"x\":17,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.413\",\"x\":18,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.131\",\"x\":19,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.425\",\"x\":20,\"y\":13},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.765\",\"x\":21,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.441\",\"x\":22,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.357\",\"x\":23,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.186\",\"x\":24,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.318\",\"x\":25,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.422\",\"x\":26,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.434\",\"x\":27,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":28,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.488\",\"x\":29,\"y\":13},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.685\",\"x\":30,\"y\":13},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.529\",\"x\":31,\"y\":13},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.261\",\"x\":0,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.342\",\"x\":1,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.423\",\"x\":2,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.359\",\"x\":3,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.217\",\"x\":4,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.439\",\"x\":5,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.194\",\"x\":6,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.337\",\"x\":7,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":8,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.138\",\"x\":9,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":10,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":11,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.227\",\"x\":12,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.227\",\"x\":13,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.033\",\"x\":14,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.225\",\"x\":15,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.297\",\"x\":16,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":17,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.232\",\"x\":18,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":19,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.490\",\"x\":20,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.281\",\"x\":21,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.319\",\"x\":22,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.171\",\"x\":23,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.495\",\"x\":24,\"y\":14},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.543\",\"x\":25,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.108\",\"x\":26,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.041\",\"x\":27,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.213\",\"x\":28,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.421\",\"x\":29,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.498\",\"x\":30,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.390\",\"x\":31,\"y\":14},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":0,\"y\":15},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.816\",\"x\":1,\"y\":15},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.650\",\"x\":2,\"y\":15},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.512\",\"x\":3,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":4,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.123\",\"x\":5,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.217\",\"x\":6,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.120\",\"x\":7,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":8,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.176\",\"x\":9,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.161\",\"x\":10,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.319\",\"x\":11,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.127\",\"x\":12,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.198\",\"x\":13,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.378\",\"x\":14,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.328\",\"x\":15,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.462\",\"x\":16,\"y\":15},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.822\",\"x\":17,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.339\",\"x\":18,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.408\",\"x\":19,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.139\",\"x\":20,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.416\",\"x\":21,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.400\",\"x\":22,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.321\",\"x\":23,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.018\",\"x\":24,\"y\":15},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.615\",\"x\":25,\"y\":15},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.726\",\"x\":26,\"y\":15},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.612\",\"x\":27,\"y\":15},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.648\",\"x\":28,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.476\",\"x\":29,\"y\":15},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.734\",\"x\":30,\"y\":15},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.122\",\"x\":31,\"y\":15},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.849\",\"x\":0,\"y\":16},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.679\",\"x\":1,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.404\",\"x\":2,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.137\",\"x\":3,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":4,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.157\",\"x\":5,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":6,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.107\",\"x\":7,\"y\":16},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.579\",\"x\":8,\"y\":16},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.554\",\"x\":9,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.274\",\"x\":10,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.397\",\"x\":11,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.121\",\"x\":12,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.161\",\"x\":13,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.135\",\"x\":14,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.107\",\"x\":15,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.095\",\"x\":16,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.182\",\"x\":17,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.310\",\"x\":18,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.406\",\"x\":19,\"y\":16},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.881\",\"x\":20,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.472\",\"x\":21,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.018\",\"x\":22,\"y\":16},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.874\",\"x\":23,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.244\",\"x\":24,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.405\",\"x\":25,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.336\",\"x\":26,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.301\",\"x\":27,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.086\",\"x\":28,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.099\",\"x\":29,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.206\",\"x\":30,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.110\",\"x\":31,\"y\":16},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":0,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.235\",\"x\":1,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.098\",\"x\":2,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.028\",\"x\":3,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.133\",\"x\":4,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":5,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.378\",\"x\":6,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":7,\"y\":17},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.688\",\"x\":8,\"y\":17},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.627\",\"x\":9,\"y\":17},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.598\",\"x\":10,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.110\",\"x\":11,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.125\",\"x\":12,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":13,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.123\",\"x\":14,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.048\",\"x\":15,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.370\",\"x\":16,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.366\",\"x\":17,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.174\",\"x\":18,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.413\",\"x\":19,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":20,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.368\",\"x\":21,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.141\",\"x\":22,\"y\":17},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.526\",\"x\":23,\"y\":17},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.881\",\"x\":24,\"y\":17},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.882\",\"x\":25,\"y\":17},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.598\",\"x\":26,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.151\",\"x\":27,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.387\",\"x\":28,\"y\":17},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.559\",\"x\":29,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":30,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.343\",\"x\":31,\"y\":17},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":0,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":1,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.147\",\"x\":2,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.085\",\"x\":3,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.270\",\"x\":4,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.124\",\"x\":5,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.101\",\"x\":6,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.113\",\"x\":7,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.370\",\"x\":8,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.378\",\"x\":9,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.113\",\"x\":10,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.219\",\"x\":11,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.069\",\"x\":12,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.082\",\"x\":13,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.034\",\"x\":14,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.082\",\"x\":15,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.213\",\"x\":16,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.102\",\"x\":17,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.215\",\"x\":18,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":19,\"y\":18},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.504\",\"x\":20,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.137\",\"x\":21,\"y\":18},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.740\",\"x\":22,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.264\",\"x\":23,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.186\",\"x\":24,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.128\",\"x\":25,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":26,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.199\",\"x\":27,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.161\",\"x\":28,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.095\",\"x\":29,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.157\",\"x\":30,\"y\":18},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.076\",\"x\":31,\"y\":18},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.507\",\"x\":0,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.347\",\"x\":1,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.350\",\"x\":2,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.350\",\"x\":3,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.492\",\"x\":4,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.139\",\"x\":5,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.095\",\"x\":6,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.091\",\"x\":7,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":8,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.134\",\"x\":9,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.108\",\"x\":10,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.160\",\"x\":11,\"y\":19},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.518\",\"x\":12,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.428\",\"x\":13,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.404\",\"x\":14,\"y\":19},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.559\",\"x\":15,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.113\",\"x\":16,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.159\",\"x\":17,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.156\",\"x\":18,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.181\",\"x\":19,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.099\",\"x\":20,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":21,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.130\",\"x\":22,\"y\":19},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.650\",\"x\":23,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.108\",\"x\":24,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.140\",\"x\":25,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":26,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.224\",\"x\":27,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.085\",\"x\":28,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.105\",\"x\":29,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.093\",\"x\":30,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.097\",\"x\":31,\"y\":19},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.095\",\"x\":0,\"y\":20},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.749\",\"x\":1,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.224\",\"x\":2,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.090\",\"x\":3,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":4,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.139\",\"x\":5,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.423\",\"x\":6,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":7,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.084\",\"x\":8,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.190\",\"x\":9,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.125\",\"x\":10,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.094\",\"x\":11,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.037\",\"x\":12,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.437\",\"x\":13,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.358\",\"x\":14,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.492\",\"x\":15,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":16,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":17,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":18,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":19,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.273\",\"x\":20,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.136\",\"x\":21,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.074\",\"x\":22,\"y\":20},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.796\",\"x\":23,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.199\",\"x\":24,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.483\",\"x\":25,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.317\",\"x\":26,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.107\",\"x\":27,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":28,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.110\",\"x\":29,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.177\",\"x\":30,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.187\",\"x\":31,\"y\":20},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.134\",\"x\":0,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.451\",\"x\":1,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.094\",\"x\":2,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.490\",\"x\":3,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":4,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.104\",\"x\":5,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":6,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.120\",\"x\":7,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.399\",\"x\":8,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.088\",\"x\":9,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.107\",\"x\":10,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.316\",\"x\":11,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.080\",\"x\":12,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":13,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.108\",\"x\":14,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.091\",\"x\":15,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.084\",\"x\":16,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.086\",\"x\":17,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.085\",\"x\":18,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.018\",\"x\":19,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.376\",\"x\":20,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.372\",\"x\":21,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.498\",\"x\":22,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.019\",\"x\":23,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.209\",\"x\":24,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.133\",\"x\":25,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.247\",\"x\":26,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.102\",\"x\":27,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.156\",\"x\":28,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.297\",\"x\":29,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.196\",\"x\":30,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.346\",\"x\":31,\"y\":21},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.366\",\"x\":0,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.372\",\"x\":1,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.343\",\"x\":2,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.086\",\"x\":3,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.047\",\"x\":4,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.300\",\"x\":5,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.369\",\"x\":6,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.139\",\"x\":7,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.235\",\"x\":8,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.110\",\"x\":9,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":10,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.120\",\"x\":11,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.346\",\"x\":12,\"y\":22},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.516\",\"x\":13,\"y\":22},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.557\",\"x\":14,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.446\",\"x\":15,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":16,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.129\",\"x\":17,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.352\",\"x\":18,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.018\",\"x\":19,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":20,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.120\",\"x\":21,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.123\",\"x\":22,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.138\",\"x\":23,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.097\",\"x\":24,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.079\",\"x\":25,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.086\",\"x\":26,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.123\",\"x\":27,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.423\",\"x\":28,\"y\":22},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.582\",\"x\":29,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.018\",\"x\":30,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.354\",\"x\":31,\"y\":22},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.088\",\"x\":0,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.078\",\"x\":1,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.108\",\"x\":2,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.104\",\"x\":3,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.075\",\"x\":4,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.329\",\"x\":5,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.326\",\"x\":6,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.138\",\"x\":7,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.079\",\"x\":8,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.084\",\"x\":9,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.102\",\"x\":10,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.102\",\"x\":11,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.311\",\"x\":12,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.436\",\"x\":13,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.254\",\"x\":14,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.104\",\"x\":15,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":16,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":17,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":18,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":19,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.447\",\"x\":20,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.056\",\"x\":21,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.415\",\"x\":22,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.133\",\"x\":23,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.086\",\"x\":24,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.238\",\"x\":25,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.128\",\"x\":26,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.329\",\"x\":27,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":28,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.108\",\"x\":29,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":30,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.104\",\"x\":31,\"y\":23},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":0,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.105\",\"x\":1,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.099\",\"x\":2,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.162\",\"x\":3,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.095\",\"x\":4,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.086\",\"x\":5,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":6,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.110\",\"x\":7,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":8,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.110\",\"x\":9,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.113\",\"x\":10,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.107\",\"x\":11,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.196\",\"x\":12,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.267\",\"x\":13,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.071\",\"x\":14,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.070\",\"x\":15,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.373\",\"x\":16,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.365\",\"x\":17,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.414\",\"x\":18,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.033\",\"x\":19,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.452\",\"x\":20,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.065\",\"x\":21,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.387\",\"x\":22,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.397\",\"x\":23,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.374\",\"x\":24,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.227\",\"x\":25,\"y\":24},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.711\",\"x\":26,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.426\",\"x\":27,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":28,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":29,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.099\",\"x\":30,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.123\",\"x\":31,\"y\":24},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.184\",\"x\":0,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.245\",\"x\":1,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.178\",\"x\":2,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.470\",\"x\":3,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.428\",\"x\":4,\"y\":25},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.514\",\"x\":5,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.477\",\"x\":6,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.420\",\"x\":7,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":8,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.107\",\"x\":9,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.105\",\"x\":10,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.077\",\"x\":11,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.473\",\"x\":12,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.471\",\"x\":13,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.378\",\"x\":14,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.366\",\"x\":15,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":16,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.237\",\"x\":17,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.400\",\"x\":18,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.098\",\"x\":19,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":20,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.156\",\"x\":21,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":22,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.071\",\"x\":23,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.085\",\"x\":24,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.113\",\"x\":25,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":26,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":27,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.094\",\"x\":28,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":29,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":30,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":31,\"y\":25},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.217\",\"x\":0,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.120\",\"x\":1,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.421\",\"x\":2,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":3,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.248\",\"x\":4,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":5,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.362\",\"x\":6,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.213\",\"x\":7,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.108\",\"x\":8,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.110\",\"x\":9,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.127\",\"x\":10,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.082\",\"x\":11,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.411\",\"x\":12,\"y\":26},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.540\",\"x\":13,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.420\",\"x\":14,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.350\",\"x\":15,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":16,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":17,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.209\",\"x\":18,\"y\":26},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.644\",\"x\":19,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.071\",\"x\":20,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.224\",\"x\":21,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.113\",\"x\":22,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.402\",\"x\":23,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.122\",\"x\":24,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.083\",\"x\":25,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.107\",\"x\":26,\"y\":26},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.709\",\"x\":27,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.029\",\"x\":28,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.416\",\"x\":29,\"y\":26},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.801\",\"x\":30,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.343\",\"x\":31,\"y\":26},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.098\",\"x\":0,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":1,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.084\",\"x\":2,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":3,\"y\":27},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.512\",\"x\":4,\"y\":27},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.642\",\"x\":5,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.465\",\"x\":6,\"y\":27},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.597\",\"x\":7,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.339\",\"x\":8,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":9,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":10,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.129\",\"x\":11,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.255\",\"x\":12,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.231\",\"x\":13,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":14,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.051\",\"x\":15,\"y\":27},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.833\",\"x\":16,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.093\",\"x\":17,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.168\",\"x\":18,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.125\",\"x\":19,\"y\":27},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.513\",\"x\":20,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.071\",\"x\":21,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.472\",\"x\":22,\"y\":27},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.546\",\"x\":23,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":24,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":25,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":26,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":27,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.232\",\"x\":28,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":29,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":30,\"y\":27},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.123\",\"x\":31,\"y\":27},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.792\",\"x\":0,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.107\",\"x\":1,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.111\",\"x\":2,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.018\",\"x\":3,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":4,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":5,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.090\",\"x\":6,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.124\",\"x\":7,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.145\",\"x\":8,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.209\",\"x\":9,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.421\",\"x\":10,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":11,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.047\",\"x\":12,\"y\":28},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.576\",\"x\":13,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.090\",\"x\":14,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.335\",\"x\":15,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.192\",\"x\":16,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.018\",\"x\":17,\"y\":28},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.701\",\"x\":18,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.231\",\"x\":19,\"y\":28},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.610\",\"x\":20,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.018\",\"x\":21,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.126\",\"x\":22,\"y\":28},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.688\",\"x\":23,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.153\",\"x\":24,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.101\",\"x\":25,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.124\",\"x\":26,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.478\",\"x\":27,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.120\",\"x\":28,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":29,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.433\",\"x\":30,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.146\",\"x\":31,\"y\":28},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":0,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.091\",\"x\":1,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.184\",\"x\":2,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":3,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.105\",\"x\":4,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":5,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.097\",\"x\":6,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.108\",\"x\":7,\"y\":29},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.763\",\"x\":8,\"y\":29},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.671\",\"x\":9,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.018\",\"x\":10,\"y\":29},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.852\",\"x\":11,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.099\",\"x\":12,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":13,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.147\",\"x\":14,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.107\",\"x\":15,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.418\",\"x\":16,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":17,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":18,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.108\",\"x\":19,\"y\":29},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.659\",\"x\":20,\"y\":29},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.662\",\"x\":21,\"y\":29},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.592\",\"x\":22,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.018\",\"x\":23,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.156\",\"x\":24,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":25,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.168\",\"x\":26,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.150\",\"x\":27,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.114\",\"x\":28,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.157\",\"x\":29,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.294\",\"x\":30,\"y\":29},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.513\",\"x\":31,\"y\":29},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.018\",\"x\":0,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.748\",\"x\":1,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.830\",\"x\":2,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":3,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":4,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.054\",\"x\":5,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.622\",\"x\":6,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.116\",\"x\":7,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.018\",\"x\":8,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.799\",\"x\":9,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.360\",\"x\":10,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.841\",\"x\":11,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.871\",\"x\":12,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.033\",\"x\":13,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.868\",\"x\":14,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.854\",\"x\":15,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":16,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.649\",\"x\":17,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.547\",\"x\":18,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.307\",\"x\":19,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.566\",\"x\":20,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.725\",\"x\":21,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.135\",\"x\":22,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.357\",\"x\":23,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.186\",\"x\":24,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":25,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.665\",\"x\":26,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.540\",\"x\":27,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.085\",\"x\":28,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.666\",\"x\":29,\"y\":30},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.788\",\"x\":30,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.095\",\"x\":31,\"y\":30},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.366\",\"x\":0,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":1,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.266\",\"x\":2,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":3,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.162\",\"x\":4,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":5,\"y\":31},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.502\",\"x\":6,\"y\":31},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.617\",\"x\":7,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.141\",\"x\":8,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.207\",\"x\":9,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.148\",\"x\":10,\"y\":31},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.510\",\"x\":11,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.341\",\"x\":12,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.257\",\"x\":13,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.125\",\"x\":14,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.333\",\"x\":15,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.418\",\"x\":16,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.255\",\"x\":17,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.124\",\"x\":18,\"y\":31},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.789\",\"x\":19,\"y\":31},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.823\",\"x\":20,\"y\":31},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.752\",\"x\":21,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.085\",\"x\":22,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.119\",\"x\":23,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.231\",\"x\":24,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.138\",\"x\":25,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.434\",\"x\":26,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.204\",\"x\":27,\"y\":31},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.642\",\"x\":28,\"y\":31},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.645\",\"x\":29,\"y\":31},{\"font\":{\"color\":\"white\",\"size\":8},\"showarrow\":false,\"text\":\"0.618\",\"x\":30,\"y\":31},{\"font\":{\"color\":\"black\",\"size\":8},\"showarrow\":false,\"text\":\"0.118\",\"x\":31,\"y\":31}],\"yaxis\":{\"title\":{\"text\":\"Layer\"},\"autorange\":\"reversed\"},\"title\":{\"text\":\"[exp57: 8b llama3, 1024 ctxlen, 64 segment len, 100k bs, 0.01 balance factor lr, no weight decay for balance factors] Global Weights Across Layers and Heads\"},\"xaxis\":{\"title\":{\"text\":\"Head\"}},\"width\":1000,\"height\":750},                        {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('243464b6-1616-4cd8-96f3-c4571c9f794c');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import plotly.graph_objects as go\n",
+    "import torch\n",
+    "import torch.nn.functional as F\n",
+    "import numpy as np\n",
+    "\n",
+    "# Assuming merged_tensors, num_layers, and num_heads are already defined\n",
+    "\n",
+    "# Create a 2D array of values\n",
+    "values = np.zeros((num_layers, num_heads))\n",
+    "for layer in range(num_layers):\n",
+    "    for head in range(num_heads):\n",
+    "        values[layer, head] = global_weights[layer, head].item()\n",
+    "\n",
+    "# Create the heatmap\n",
+    "fig = go.Figure(data=go.Heatmap(\n",
+    "    z=values,\n",
+    "    x=[f'Head {i}' for i in range(num_heads)],\n",
+    "    y=[f'Layer {i}' for i in range(num_layers)],\n",
+    "    hoverongaps = False,\n",
+    "    colorscale='Viridis',\n",
+    "    colorbar=dict(title='Value'),\n",
+    "    zmin=0,\n",
+    "    zmax=1\n",
+    "))\n",
+    "\n",
+    "# Add text annotations\n",
+    "for layer in range(num_layers):\n",
+    "    for head in range(num_heads):\n",
+    "        value = values[layer, head]\n",
+    "        fig.add_annotation(\n",
+    "            x=head,\n",
+    "            y=layer,\n",
+    "            text=f'{value:.3f}',\n",
+    "            showarrow=False,\n",
+    "            font=dict(\n",
+    "                color='white' if value > 0.5 else 'black',\n",
+    "                size=8\n",
+    "            )\n",
+    "        )\n",
+    "\n",
+    "# Update layout\n",
+    "fig.update_layout(\n",
+    "    title=f\"[{ckp_name}] Global Weights Across Layers and Heads\",\n",
+    "    xaxis_title='Head',\n",
+    "    yaxis_title='Layer',\n",
+    "    width=1000,\n",
+    "    height=750,\n",
+    "    yaxis=dict(autorange='reversed')  # To have layer 0 at the top\n",
+    ")\n",
+    "\n",
+    "# Show the plot\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor(0.8604)"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(global_weights.flatten() < 0.5).float().mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "percentage_smaller_0_5 = (global_weights.flatten() < 0.5).float().mean() * 100\n",
+    "percentage_larger_equal_0_5 = (global_weights.flatten() >= 0.5).float().mean() * 100"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor(13.9648)"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "percentage_larger_equal_0_5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor(86.0352)"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "percentage_smaller_0_5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/infinite-context-length/data/exp34/debug_finetune_data.ipynb b/examples/infinite-context-length/data/exp34/debug_finetune_data.ipynb
new file mode 100644
index 00000000..bae32032
--- /dev/null
+++ b/examples/infinite-context-length/data/exp34/debug_finetune_data.ipynb
@@ -0,0 +1,344 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[512, 1024, 1536, 2048, 2560, 3072, 3584, 4096, 4608, 5120, 5632, 6144, 6656, 7168, 7680, 8192, 8704, 9216, 9728, 10240, 10752, 11264, 11776, 12288, 12800, 13312, 13824, 14336, 14848, 15360, 15872]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print([512*x for x in range(1, 32)])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "31"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len([512*x for x in range(1, 32)])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/admin/home/phuc_nguyen/miniconda3/envs/nanotron-dev/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datasets import load_dataset, load_from_disk"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = load_from_disk(\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/finetune_data/needle_eval_and_512_ctx_and_depth_5_and_id_0\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'id': 'cc0e78ca-6d2a-488d-a39e-de75a74584d0',\n",
+       " 'prompt': 'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. . The pass key is 455. Remember it. 455 is the pass key.  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. \\n\\nWhat is the pass key? The pass key is 455.',\n",
+       " 'answer': 455,\n",
+       " 'context_length': 512,\n",
+       " 'num_tokens': 355,\n",
+       " 'depth_percent': 5}"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Merge datasets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_dataset, DatasetDict, Dataset\n",
+    "import os\n",
+    "\n",
+    "# Specify the path containing the dataset folders\n",
+    "path = \"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/finetune_data\"\n",
+    "\n",
+    "# Get a list of all dataset folders\n",
+    "dataset_folders = [folder for folder in os.listdir(path) if os.path.isdir(os.path.join(path, folder))]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1545"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(dataset_folders)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_from_disk\n",
+    "\n",
+    "datasets = []\n",
+    "for folder in dataset_folders:\n",
+    "    dataset_path = os.path.join(path, folder)\n",
+    "    dataset = load_from_disk(dataset_path)\n",
+    "    datasets.append(dataset)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import concatenate_datasets\n",
+    "merged_dataset = concatenate_datasets(datasets)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on.  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun. The pass key is 383. Remember it. 383 is the pass key.  is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The. \\n\\nWhat is the pass key? The pass key is 383.'"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "merged_dataset[0][\"prompt\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'id': '998b164c-88e9-404a-98f7-375bb9fc1c59',\n",
+       " 'prompt': 'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on.  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The pass key is 5711. Remember it. 5711 is the pass key.. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go The grass is green. The sky is blue. The sun is yellow. Here we go. There and back ag. \\n\\nWhat is the pass key? The pass key is 5711.',\n",
+       " 'answer': 5711,\n",
+       " 'context_length': 6144,\n",
+       " 'num_tokens': 5751,\n",
+       " 'depth_percent': 90}"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "merged_dataset[-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'id': 'ed5e993f-8f9e-4a5b-9f03-6ec36d866b4c',\n",
+       " 'prompt': 'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on.  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun. The pass key is 289. Remember it. 289 is the pass key.  is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The. \\n\\nWhat is the pass key? The pass key is 289.',\n",
+       " 'answer': 289,\n",
+       " 'context_length': 8192,\n",
+       " 'num_tokens': 7961,\n",
+       " 'depth_percent': 25}"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "merged_dataset[20]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged_dataset = merged_dataset.shuffle(seed=91)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Saving the dataset (0/4 shards):  12%|█████▌                                          | 9000/77250 [00:00<00:04, 15681.14 examples/s]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Saving the dataset (4/4 shards): 100%|███████████████████████████████████████████████| 77250/77250 [00:03<00:00, 19719.57 examples/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "merged_dataset.save_to_disk(\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/merged_16k_passkey_finetuning_data\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "new_data = load_from_disk(\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/merged_16k_passkey_finetuning_data\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Creating parquet from Arrow format: 100%|████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 24.79ba/s]\n",
+      "Creating parquet from Arrow format: 100%|████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 22.73ba/s]\n",
+      "Creating parquet from Arrow format: 100%|████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 23.38ba/s]\n",
+      "Creating parquet from Arrow format: 100%|████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 22.00ba/s]\n",
+      "Uploading the dataset shards: 100%|████████████████████████████████████████████████████████████████████| 4/4 [00:07<00:00,  1.76s/it]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "CommitInfo(commit_url='https://huggingface.co/datasets/nanotron/llama3-16k-passkey-retrieval-finetuning/commit/07bf23d4a07e423ea96ad2f230c748f9b9ea7d3a', commit_message='Upload dataset', commit_description='', oid='07bf23d4a07e423ea96ad2f230c748f9b9ea7d3a', pr_url=None, pr_revision=None, pr_num=None)"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new_data.push_to_hub(\n",
+    "    repo_id=\"nanotron/llama3-16k-passkey-retrieval-finetuning\",\n",
+    "    # repo_type=\"dataset\",\n",
+    "    # private=True,  # Set to False if you want the dataset to be public\n",
+    "    # token=\"your_access_token\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/infinite-context-length/data/exp34/debug_optimizer.ipynb b/examples/infinite-context-length/data/exp34/debug_optimizer.ipynb
new file mode 100644
index 00000000..ee2e3d11
--- /dev/null
+++ b/examples/infinite-context-length/data/exp34/debug_optimizer.ipynb
@@ -0,0 +1,242 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "from safetensors import safe_open\n",
+    "import torch.nn.functional as F"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def read_tensor(path):\n",
+    "    tensors = {}\n",
+    "    with safe_open(path, framework=\"pt\", device=\"cpu\") as f:\n",
+    "        for key in f.keys():\n",
+    "            tensors[key] = f.get_tensor(key)\n",
+    "        \n",
+    "    return tensors[\"data\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "OPTIM_STATE_RANK_0 = \"/fsx/phuc/projects/nanotron/checkpoints/exp33_debug_amplify_gradient_and_lr_0.00015/10/optimizer/optimizer_pp-0-of-1_tp-0-of-2_exp-0-of-1.pt\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "state_0 =torch.load(OPTIM_STATE_RANK_0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'step': tensor(10., device='cuda:0'),\n",
+       " 'exp_avg': tensor([[ 5.6243e-04,  9.4370e-04,  1.2402e-03,  ..., -1.9598e-03,\n",
+       "           5.7173e-04, -1.7865e-04],\n",
+       "         [-1.9659e-04, -4.0756e-04, -2.8405e-03,  ..., -6.8527e-04,\n",
+       "           7.3129e-04,  1.0792e-04],\n",
+       "         [ 1.2668e-03,  2.7724e-03, -2.6020e-03,  ...,  1.6569e-03,\n",
+       "           6.8592e-05, -4.2270e-04],\n",
+       "         ...,\n",
+       "         [-2.0183e-03, -1.7859e-03, -2.2009e-03,  ...,  1.4483e-04,\n",
+       "           2.1861e-03, -8.0165e-04],\n",
+       "         [ 8.2830e-04,  1.4839e-03, -1.2473e-03,  ...,  1.4669e-03,\n",
+       "           2.4580e-04,  1.2592e-03],\n",
+       "         [-3.2280e-04, -1.1929e-03, -2.7407e-04,  ...,  1.4532e-03,\n",
+       "           2.1108e-04, -2.0424e-04]], device='cuda:0'),\n",
+       " 'exp_avg_sq': tensor([[8.4348e-06, 5.7223e-05, 6.9194e-05,  ..., 2.0413e-05, 3.2337e-05,\n",
+       "          1.3685e-05],\n",
+       "         [3.4449e-06, 1.3048e-05, 1.6789e-05,  ..., 9.1836e-06, 1.3101e-05,\n",
+       "          8.8387e-06],\n",
+       "         [9.1353e-06, 4.0784e-05, 2.4419e-05,  ..., 5.5688e-06, 2.0166e-05,\n",
+       "          1.6151e-06],\n",
+       "         ...,\n",
+       "         [4.8291e-05, 5.9701e-05, 2.8450e-04,  ..., 3.3562e-05, 5.6101e-05,\n",
+       "          3.1701e-05],\n",
+       "         [1.5886e-05, 1.7301e-05, 2.2958e-05,  ..., 1.1100e-05, 1.4909e-05,\n",
+       "          1.2523e-05],\n",
+       "         [5.9345e-06, 1.2095e-05, 5.7877e-06,  ..., 4.6964e-06, 1.5451e-05,\n",
+       "          2.7295e-06]], device='cuda:0')}"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "state_0[\"state\"][6]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{0: 'model.token_position_embeddings.pp_block.token_embedding.weight',\n",
+       " 1: 'model.decoder.0.pp_block.input_layernorm.weight',\n",
+       " 2: 'model.decoder.0.pp_block.attn.balance_factors',\n",
+       " 3: 'model.decoder.0.pp_block.attn.qkv_proj.weight',\n",
+       " 4: 'model.decoder.0.pp_block.attn.o_proj.weight',\n",
+       " 5: 'model.decoder.0.pp_block.post_attention_layernorm.weight',\n",
+       " 6: 'model.decoder.0.pp_block.mlp.gate_up_proj.weight',\n",
+       " 7: 'model.decoder.0.pp_block.mlp.down_proj.weight',\n",
+       " 8: 'model.decoder.1.pp_block.input_layernorm.weight',\n",
+       " 9: 'model.decoder.1.pp_block.attn.balance_factors',\n",
+       " 10: 'model.decoder.1.pp_block.attn.qkv_proj.weight',\n",
+       " 11: 'model.decoder.1.pp_block.attn.o_proj.weight',\n",
+       " 12: 'model.decoder.1.pp_block.post_attention_layernorm.weight',\n",
+       " 13: 'model.decoder.1.pp_block.mlp.gate_up_proj.weight',\n",
+       " 14: 'model.decoder.1.pp_block.mlp.down_proj.weight',\n",
+       " 15: 'model.final_layer_norm.pp_block.weight',\n",
+       " 16: 'model.lm_head.pp_block.weight'}"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "state_0[\"names\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'step': tensor(10., device='cuda:0'),\n",
+       " 'exp_avg': tensor([ 0.0067, -0.0001, -0.0115,  0.0030], device='cuda:0'),\n",
+       " 'exp_avg_sq': tensor([0.0002, 0.0001, 0.0004, 0.0002], device='cuda:0')}"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "state_0[\"state\"][2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'lr': 1.0714285714285713e-07,\n",
+       " 'betas': (0.9, 0.95),\n",
+       " 'eps': 1e-08,\n",
+       " 'weight_decay': 0.1,\n",
+       " 'amsgrad': False,\n",
+       " 'foreach': None,\n",
+       " 'maximize': False,\n",
+       " 'capturable': False,\n",
+       " 'differentiable': False,\n",
+       " 'fused': True,\n",
+       " 'initial_lr': 0.00015,\n",
+       " 'params': [2]}"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "state_0[\"param_groups\"][2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'lr': 1.0714285714285713e-07,\n",
+       " 'betas': (0.9, 0.95),\n",
+       " 'eps': 1e-08,\n",
+       " 'weight_decay': 0.1,\n",
+       " 'amsgrad': False,\n",
+       " 'foreach': None,\n",
+       " 'maximize': False,\n",
+       " 'capturable': False,\n",
+       " 'differentiable': False,\n",
+       " 'fused': True,\n",
+       " 'initial_lr': 0.00015,\n",
+       " 'params': [1]}"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "state_0[\"param_groups\"][1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/infinite-context-length/data/exp34/debug_weights.ipynb b/examples/infinite-context-length/data/exp34/debug_weights.ipynb
new file mode 100644
index 00000000..936c1a43
--- /dev/null
+++ b/examples/infinite-context-length/data/exp34/debug_weights.ipynb
@@ -0,0 +1,4534 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "from safetensors import safe_open\n",
+    "import torch.nn.functional as F"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def read_tensor(path):\n",
+    "    tensors = {}\n",
+    "    with safe_open(path, framework=\"pt\", device=\"cpu\") as f:\n",
+    "        for key in f.keys():\n",
+    "            tensors[key] = f.get_tensor(key)\n",
+    "        \n",
+    "    return tensors[\"data\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "PATHS = [\n",
+    "    \"/fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_needle_finetuning/checkpoints/663/model/model/decoder/3/pp_block/attn/model_balance_factors_pp-rank-0-of-1_tp-rank-0-of-4.safetensors\",\n",
+    "    \"/fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_needle_finetuning/checkpoints/1326/model/model/decoder/3/pp_block/attn/qkv_proj/model_weight_pp-rank-0-of-1_tp-rank-2-of-4.safetensors\",\n",
+    "    \"/fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_needle_finetuning/checkpoints/1326/model/model/decoder/3/pp_block/attn/model_balance_factors_pp-rank-0-of-1_tp-rank-2-of-4.safetensors\",\n",
+    "    \"/fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp32_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/checkpoints/5000/model/model/decoder/0/pp_block/attn/model_balance_factors_pp-rank-0-of-1_tp-rank-0-of-2.safetensors\",\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'data': tensor([0.0156, 0.0156, 0.0156, 0.0156], dtype=torch.bfloat16)}"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tensors"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([0.5039, 0.5039, 0.5039, 0.5039], dtype=torch.bfloat16)"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F.sigmoid(tensors[\"data\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'tensors' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[12], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mtensors\u001b[49m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdata\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'tensors' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "tensors[\"data\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "weights = read_tensor(\"/fsx/phuc/projects/nanotron/checkpoints/exp33_debug/20/model/model/decoder/1/pp_block/attn/model_balance_factors_pp-rank-0-of-1_tp-rank-1-of-2.safetensors\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([-1.6764e-06,  1.6019e-06, -1.7881e-06,  1.5944e-06],\n",
+       "       dtype=torch.bfloat16)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weights"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([-1.6797,  1.6016, -1.7891,  1.5938], dtype=torch.bfloat16)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weights * 10**6"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([0.5000, 0.5000, 0.5000, 0.5000], dtype=torch.bfloat16)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F.sigmoid(weights)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor(0.3945, dtype=torch.bfloat16)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F.sigmoid(weights * 10**6)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Gradients"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import torch\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "root_dir = '/fsx/phuc/projects/nanotron/debug/runs/exp33_debug_normalize_grad_of_balances_and_divide_by_10_and_lr_0.00015'  # replace with your actual root directory\n",
+    "\n",
+    "grad_means = {}\n",
+    "grad_vars = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for train_step in sorted(os.listdir(root_dir)):\n",
+    "    train_step_dir = os.path.join(root_dir, train_step)\n",
+    "    if not os.path.isdir(train_step_dir):\n",
+    "        continue\n",
+    "\n",
+    "    for grad_file in os.listdir(train_step_dir):\n",
+    "        if grad_file.endswith('.pt'):\n",
+    "            tensor_name = grad_file[:-3]  # remove the '.pt' extension\n",
+    "            grad_path = os.path.join(train_step_dir, grad_file)\n",
+    "            \n",
+    "            # Load the tensor\n",
+    "            grad_tensor = torch.load(grad_path)\n",
+    "            \n",
+    "            # Ensure tensor is on CPU and numpy\n",
+    "            grad_tensor_np = grad_tensor.cpu().numpy()\n",
+    "            \n",
+    "            # Calculate mean and variance\n",
+    "            mean = np.mean(grad_tensor_np)\n",
+    "            variance = np.var(grad_tensor_np)\n",
+    "            \n",
+    "            if tensor_name not in grad_means:\n",
+    "                grad_means[tensor_name] = []\n",
+    "                grad_vars[tensor_name] = []\n",
+    "            \n",
+    "            grad_means[tensor_name].append(mean)\n",
+    "            grad_vars[tensor_name].append(variance)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "StopIteration",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mStopIteration\u001b[0m                             Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[15], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m steps \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43miter\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mgrad_means\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalues\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m))  \u001b[38;5;66;03m# assume same number of steps for all tensors\u001b[39;00m\n\u001b[1;32m      3\u001b[0m plt\u001b[38;5;241m.\u001b[39mfigure(figsize\u001b[38;5;241m=\u001b[39m(\u001b[38;5;241m10\u001b[39m, \u001b[38;5;241m6\u001b[39m))\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m tensor_name \u001b[38;5;129;01min\u001b[39;00m grad_means:\n",
+      "\u001b[0;31mStopIteration\u001b[0m: "
+     ]
+    }
+   ],
+   "source": [
+    "steps = range(len(next(iter(grad_means.values()))))  # assume same number of steps for all tensors\n",
+    "\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "\n",
+    "for tensor_name in grad_means:\n",
+    "    means = grad_means[tensor_name]\n",
+    "    vars = grad_vars[tensor_name]\n",
+    "    \n",
+    "    lower_bound = [m - np.sqrt(v) for m, v in zip(means, vars)]\n",
+    "    upper_bound = [m + np.sqrt(v) for m, v in zip(means, vars)]\n",
+    "    \n",
+    "    plt.plot(steps, means, label=tensor_name)\n",
+    "    plt.fill_between(steps, lower_bound, upper_bound, alpha=0.3)\n",
+    "\n",
+    "plt.xlabel('Training Step')\n",
+    "plt.ylabel('Mean of Gradients')\n",
+    "plt.title('Gradient Means and Variances over Training Steps')\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import torch\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "def load_and_plot_gradients(root_dir):\n",
+    "    # Dictionary to store gradients for each tensor across steps\n",
+    "    gradients = {}\n",
+    "\n",
+    "    # Walk through the directory structure\n",
+    "    for step_dir in sorted(os.listdir(root_dir), key=lambda x: int(x)):\n",
+    "        step = int(step_dir)\n",
+    "        grad_dir = os.path.join(root_dir, step_dir, 'grads')\n",
+    "        \n",
+    "        if os.path.isdir(grad_dir):\n",
+    "            for tensor_file in os.listdir(grad_dir):\n",
+    "                tensor_name = os.path.splitext(tensor_file)[0]\n",
+    "                tensor_path = os.path.join(grad_dir, tensor_file)\n",
+    "                \n",
+    "                # Load the tensor\n",
+    "                tensor = torch.load(tensor_path)\n",
+    "                \n",
+    "                # Calculate mean and standard deviation\n",
+    "                mean = tensor.mean().item()\n",
+    "                std = tensor.std().item()\n",
+    "                \n",
+    "                if tensor_name not in gradients:\n",
+    "                    gradients[tensor_name] = {'steps': [], 'means': [], 'stds': []}\n",
+    "                \n",
+    "                gradients[tensor_name]['steps'].append(step)\n",
+    "                gradients[tensor_name]['means'].append(mean)\n",
+    "                gradients[tensor_name]['stds'].append(std)\n",
+    "\n",
+    "    # Plotting\n",
+    "    plt.figure(figsize=(12, 6))\n",
+    "    \n",
+    "    for tensor_name, data in gradients.items():\n",
+    "        steps = np.array(data['steps'])\n",
+    "        means = np.array(data['means'])\n",
+    "        stds = np.array(data['stds'])\n",
+    "        \n",
+    "        plt.plot(steps, means, label=tensor_name)\n",
+    "        plt.fill_between(steps, means - stds, means + stds, alpha=0.2)\n",
+    "\n",
+    "    plt.xlabel('Training Step')\n",
+    "    plt.ylabel('Mean of Gradients')\n",
+    "    plt.title('Gradient Means and Variances Across Training Steps')\n",
+    "    plt.legend()\n",
+    "    plt.grid(True)\n",
+    "    plt.show()\n",
+    "\n",
+    "# Usage\n",
+    "root_directory = '/fsx/phuc/projects/nanotron/debug/runs/exp33_debug_normalize_grad_of_balances_and_divide_by_10_and_lr_0.00015'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'plotly'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[19], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mos\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mplotly\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mgraph_objects\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mgo\u001b[39;00m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mplotly\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msubplots\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m make_subplots\n\u001b[1;32m      6\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mload_and_plot_gradients\u001b[39m(root_dir):\n",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'plotly'"
+     ]
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import torch\n",
+    "import plotly.graph_objects as go\n",
+    "from plotly.subplots import make_subplots\n",
+    "\n",
+    "def load_and_plot_gradients(root_dir):\n",
+    "    gradients = {}\n",
+    "\n",
+    "    # Walk through the directory structure\n",
+    "    for step_dir in sorted(os.listdir(root_dir), key=lambda x: int(x)):\n",
+    "        step = int(step_dir)\n",
+    "        grad_dir = os.path.join(root_dir, step_dir, 'grads')\n",
+    "        \n",
+    "        if os.path.isdir(grad_dir):\n",
+    "            for tensor_file in os.listdir(grad_dir):\n",
+    "                tensor_name = os.path.splitext(tensor_file)[0]\n",
+    "                tensor_path = os.path.join(grad_dir, tensor_file)\n",
+    "                \n",
+    "                # Load the tensor\n",
+    "                tensor = torch.load(tensor_path)\n",
+    "                \n",
+    "                # Calculate mean and standard deviation\n",
+    "                mean = tensor.mean().item()\n",
+    "                std = tensor.std().item()\n",
+    "                \n",
+    "                if tensor_name not in gradients:\n",
+    "                    gradients[tensor_name] = {'steps': [], 'means': [], 'stds': []}\n",
+    "                \n",
+    "                gradients[tensor_name]['steps'].append(step)\n",
+    "                gradients[tensor_name]['means'].append(mean)\n",
+    "                gradients[tensor_name]['stds'].append(std)\n",
+    "\n",
+    "    # Create subplots\n",
+    "    fig = make_subplots(rows=1, cols=1, shared_xaxes=True)\n",
+    "\n",
+    "    # Add traces for each tensor\n",
+    "    for tensor_name, data in gradients.items():\n",
+    "        steps = data['steps']\n",
+    "        means = data['means']\n",
+    "        stds = data['stds']\n",
+    "\n",
+    "        # Add line trace\n",
+    "        fig.add_trace(\n",
+    "            go.Scatter(\n",
+    "                x=steps,\n",
+    "                y=means,\n",
+    "                mode='lines',\n",
+    "                name=tensor_name,\n",
+    "                line=dict(width=2)\n",
+    "            )\n",
+    "        )\n",
+    "\n",
+    "        # Add fill for standard deviation\n",
+    "        fig.add_trace(\n",
+    "            go.Scatter(\n",
+    "                x=steps + steps[::-1],\n",
+    "                y=[m + s for m, s in zip(means, stds)] + [m - s for m, s in zip(means[::-1], stds[::-1])],\n",
+    "                fill='toself',\n",
+    "                fillcolor='rgba(0,100,80,0.2)',\n",
+    "                line=dict(color='rgba(255,255,255,0)'),\n",
+    "                hoverinfo=\"skip\",\n",
+    "                showlegend=False,\n",
+    "                name=tensor_name + ' Std Dev'\n",
+    "            )\n",
+    "        )\n",
+    "\n",
+    "    # Update layout\n",
+    "    fig.update_layout(\n",
+    "        title='Gradient Means and Variances Across Training Steps',\n",
+    "        xaxis_title='Training Step',\n",
+    "        yaxis_title='Mean of Gradients',\n",
+    "        hovermode='x unified',\n",
+    "        legend_title='Tensor Names',\n",
+    "    )\n",
+    "\n",
+    "    # Show the plot\n",
+    "    fig.show()\n",
+    "\n",
+    "# Usage\n",
+    "root_directory = 'path/to/your/root/directory'\n",
+    "load_and_plot_gradients(root_directory)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import torch\n",
+    "import plotly.graph_objects as go\n",
+    "from plotly.subplots import make_subplots\n",
+    "\n",
+    "def load_and_plot_gradients(root_dir):\n",
+    "    gradients = {}\n",
+    "\n",
+    "    # Walk through the directory structure\n",
+    "    for step_dir in sorted(os.listdir(root_dir), key=lambda x: int(x)):\n",
+    "        step = int(step_dir)\n",
+    "        grad_dir = os.path.join(root_dir, step_dir, 'grads')\n",
+    "        \n",
+    "        if os.path.isdir(grad_dir):\n",
+    "            for tensor_file in os.listdir(grad_dir):\n",
+    "                tensor_name = os.path.splitext(tensor_file)[0]\n",
+    "                tensor_path = os.path.join(grad_dir, tensor_file)\n",
+    "                \n",
+    "                # Load the tensor\n",
+    "                tensor = torch.load(tensor_path)\n",
+    "                \n",
+    "                # Calculate mean and standard deviation\n",
+    "                mean = tensor.mean().item()\n",
+    "                std = tensor.std().item()\n",
+    "                \n",
+    "                if tensor_name not in gradients:\n",
+    "                    gradients[tensor_name] = {'steps': [], 'means': [], 'stds': []}\n",
+    "                \n",
+    "                gradients[tensor_name]['steps'].append(step)\n",
+    "                gradients[tensor_name]['means'].append(mean)\n",
+    "                gradients[tensor_name]['stds'].append(std)\n",
+    "\n",
+    "    # Create subplots\n",
+    "    fig = make_subplots(rows=1, cols=1, shared_xaxes=True)\n",
+    "\n",
+    "    # Add traces for each tensor\n",
+    "    for tensor_name, data in gradients.items():\n",
+    "        steps = data['steps']\n",
+    "        means = data['means']\n",
+    "        stds = data['stds']\n",
+    "\n",
+    "        # Add line trace\n",
+    "        fig.add_trace(\n",
+    "            go.Scatter(\n",
+    "                x=steps,\n",
+    "                y=means,\n",
+    "                mode='lines',\n",
+    "                name=tensor_name,\n",
+    "                line=dict(width=2)\n",
+    "            )\n",
+    "        )\n",
+    "\n",
+    "        # Add fill for standard deviation\n",
+    "        fig.add_trace(\n",
+    "            go.Scatter(\n",
+    "                x=steps + steps[::-1],\n",
+    "                y=[m + s for m, s in zip(means, stds)] + [m - s for m, s in zip(means[::-1], stds[::-1])],\n",
+    "                fill='toself',\n",
+    "                fillcolor='rgba(0,100,80,0.2)',\n",
+    "                line=dict(color='rgba(255,255,255,0)'),\n",
+    "                hoverinfo=\"skip\",\n",
+    "                showlegend=False,\n",
+    "                name=tensor_name + ' Std Dev'\n",
+    "            )\n",
+    "        )\n",
+    "\n",
+    "    # Update layout\n",
+    "    fig.update_layout(\n",
+    "        title='Gradient Means and Variances Across Training Steps',\n",
+    "        xaxis_title='Training Step',\n",
+    "        yaxis_title='Mean of Gradients',\n",
+    "        hovermode='x unified',\n",
+    "        legend_title='Tensor Names',\n",
+    "    )\n",
+    "\n",
+    "    # Show the plot\n",
+    "    # fig.show()\n",
+    "    return fig, gradients\n",
+    "\n",
+    "# Usage\n",
+    "root_directory = '/fsx/phuc/projects/nanotron/debug/runs/exp33_debug_normalize_grad_of_balances_and_divide_by_10_and_lr_0.00015'\n",
+    "fig, gradients = load_and_plot_gradients(root_directory)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.final_layer_norm.pp_block.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.002198129892349243,
+          0.0021066665649414062,
+          0.0008701086044311523,
+          0.0015106797218322754,
+          -0.00011205673217773438
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.final_layer_norm.pp_block.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.007082977797836065,
+          0.00813433900475502,
+          0.005468044430017471,
+          0.004966680658981204,
+          0.0032637217082083225,
+          -0.0034878351725637913,
+          -0.0019453212153166533,
+          -0.0037278272211551666,
+          -0.003921005874872208,
+          -0.002686718013137579
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.1.pp_block.input_layernorm.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -0.00007554888725280762,
+          0.000012159347534179688,
+          -0.00006566941738128662,
+          0.00003664568066596985,
+          0.000025913119316101074
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.1.pp_block.input_layernorm.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.00027068256167694926,
+          0.00043601234210655093,
+          0.0002786800905596465,
+          0.00038932161987759173,
+          0.00025601279048714787,
+          -0.00020418655185494572,
+          -0.00031603025854565203,
+          -0.00041001892532221973,
+          -0.00041169364703819156,
+          -0.0004217803361825645
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.1.pp_block.mlp.gate_up_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -0.000003262020072725136,
+          -0.000029552000341936946,
+          -0.0000062779618019703776,
+          -3.9994483813643456e-7,
+          -2.093311195494607e-7
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.1.pp_block.mlp.gate_up_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0005418256578195724,
+          0.000466384255560115,
+          0.0005196819802222308,
+          0.00043358420953154564,
+          0.00045861526268708985,
+          -0.0004590339249261888,
+          -0.0004343840992078185,
+          -0.0005322379038261715,
+          -0.0005254882562439889,
+          -0.0005483496979650226
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.1.pp_block.attn.qkv_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -0.000019893303033313714,
+          -0.00007509818533435464,
+          -0.00008135275857057422,
+          0.00002751210195128806,
+          0.000007729327990091406
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.1.pp_block.attn.qkv_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0013296976485435152,
+          0.001402517140377313,
+          0.001018972383462824,
+          0.0009958900809579063,
+          0.0007986696346051758,
+          -0.000783210978624993,
+          -0.0009408658770553302,
+          -0.0011816779006039724,
+          -0.0015527135110460222,
+          -0.0013694842546101427
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.0.pp_block.attn.qkv_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -0.00009807215974433348,
+          0.00012267599231563509,
+          0.00005988371412968263,
+          -0.0000236338146351045,
+          0.00003453333556535654
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.0.pp_block.attn.qkv_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0013592619870905764,
+          0.001465613575419411,
+          0.001127638177422341,
+          0.0010535859128140146,
+          0.001023725500999717,
+          -0.000954658829869004,
+          -0.0011008535420842236,
+          -0.0010078707491629757,
+          -0.001220261590788141,
+          -0.0015554063065792434
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.0.pp_block.post_attention_layernorm.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.0001437664031982422,
+          0.00018288195133209229,
+          -0.00007216259837150574,
+          -0.00018101930618286133,
+          0.00018277764320373535
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.0.pp_block.post_attention_layernorm.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0004035377933178097,
+          0.0004997444921173155,
+          0.0001882568176370114,
+          0.00007293169619515538,
+          0.0004796491120941937,
+          -0.000114093825686723,
+          -0.00043497030856087804,
+          -0.0003325820143800229,
+          -0.00013398058945313096,
+          -0.00011600498692132533
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.0.pp_block.input_layernorm.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.0000713123008608818,
+          -0.00003910064697265625,
+          -0.0000029280781745910645,
+          0.00008285790681838989,
+          0.000018924474716186523
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.0.pp_block.input_layernorm.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0005026485305279493,
+          0.00027448905166238546,
+          0.00023909594165161252,
+          0.0003632560546975583,
+          0.0002120095450663939,
+          -0.00017416059563402086,
+          -0.0001975402410607785,
+          -0.00024495209800079465,
+          -0.00035269034560769796,
+          -0.0003600239288061857
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.0.pp_block.mlp.down_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -0.000035567820305004716,
+          -0.00010004517389461398,
+          0.000009103445336222649,
+          0.00000152749998960644,
+          0.000021241081412881613
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.0.pp_block.mlp.down_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0010479049233254045,
+          0.0011488441959954798,
+          0.001135421684011817,
+          0.0010538919741520658,
+          0.0010336725390516222,
+          -0.000991190376225859,
+          -0.001050836974172853,
+          -0.0011172147933393717,
+          -0.0013489345437847078,
+          -0.001119040563935414
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.1.pp_block.mlp.down_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.000020260762539692223,
+          0.000024348206352442503,
+          0.00003906200436176732,
+          -0.00001029292616294697,
+          -0.0000021571177057921886
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.1.pp_block.mlp.down_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.001155012592789717,
+          0.0010924921953119338,
+          0.0011122663345304318,
+          0.0008695767537574284,
+          0.0008067959570325911,
+          -0.0008111101924441755,
+          -0.0008901626060833223,
+          -0.0010341423258068971,
+          -0.0010437957826070487,
+          -0.0011144910677103326
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.1.pp_block.attn.o_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.00040972232818603516,
+          -0.000264984555542469,
+          0.00006173807196319103,
+          -0.0005156630650162697,
+          -0.00019942596554756165
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.1.pp_block.attn.o_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0046989344991743565,
+          0.0036927000619471073,
+          0.003142212750390172,
+          0.0027088948991149664,
+          0.0026285804342478514,
+          -0.0030274323653429747,
+          -0.0037402210291475058,
+          -0.00301873660646379,
+          -0.004222669173032045,
+          -0.003879489842802286
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.token_position_embeddings.pp_block.token_embedding.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -8.04212845650909e-7,
+          -0.0000021271421246638056,
+          0.0000024151413526851684,
+          6.843426376690331e-7,
+          8.726783562451601e-8
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.token_position_embeddings.pp_block.token_embedding.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0008795044692533338,
+          0.0008495641509398411,
+          0.000796735334006371,
+          0.000767548156261455,
+          0.0007648306927876547,
+          -0.0007646561571164057,
+          -0.0007661794709861169,
+          -0.0007919050513010006,
+          -0.0008538184351891687,
+          -0.0008811128949446356
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.lm_head.pp_block.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          1.2801820048480295e-7,
+          -3.8747495523239195e-7,
+          2.449887404054607e-7,
+          -3.7114006090632756e-7,
+          3.2651161063768086e-7
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.lm_head.pp_block.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0008499983428009728,
+          0.0008608746127549693,
+          0.0008068004317181021,
+          0.0007549875219297064,
+          0.0007691299209113822,
+          -0.0007684768976901069,
+          -0.0007557298020515191,
+          -0.0008063104542372912,
+          -0.0008616495626654341,
+          -0.0008497423064000031
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.0.pp_block.attn.o_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.0004978431388735771,
+          0.0004920652136206627,
+          0.00000626780092716217,
+          -0.0003082635812461376,
+          0.0000658784992992878
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.0.pp_block.attn.o_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.003778938204050064,
+          0.004228800069540739,
+          0.0030188877135515213,
+          0.0025075047742575407,
+          0.0024150535464286804,
+          -0.002283296547830105,
+          -0.003124031936749816,
+          -0.003006352111697197,
+          -0.0032446696422994137,
+          -0.00278325192630291
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.0.pp_block.mlp.gate_up_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -0.0000192889419849962,
+          0.000004385730790090747,
+          -5.527399480342865e-7,
+          -7.215039659058675e-7,
+          0.000008949356924858876
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.0.pp_block.mlp.gate_up_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0005691324186045676,
+          0.0005819777306896867,
+          0.0005219283048063517,
+          0.000508927778355428,
+          0.0005151660170668038,
+          -0.000497267303217086,
+          -0.0005103707862872398,
+          -0.0005230337847024202,
+          -0.0005732062691095052,
+          -0.00060771030257456
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.0.pp_block.attn.balance_factors.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -0.022059202194213867,
+          0.0292510986328125,
+          0.00128173828125,
+          -0.02606964111328125,
+          -0.00794219970703125
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.0.pp_block.attn.balance_factors.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.029811076819896698,
+          0.07617643848061562,
+          0.05894214287400246,
+          0.02324569970369339,
+          0.04914530739188194,
+          -0.06502970680594444,
+          -0.07538498193025589,
+          -0.05637866631150246,
+          -0.017674241214990616,
+          -0.07392948120832443
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.1.pp_block.post_attention_layernorm.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.00021371245384216309,
+          0.00009015947580337524,
+          0.00008095055818557739,
+          0.00010886043310165405,
+          0.00004680454730987549
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.1.pp_block.post_attention_layernorm.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0005066160229034722,
+          0.00036516631371341646,
+          0.0003272670728620142,
+          0.00039845777791924775,
+          0.00034502430935390294,
+          -0.00025141521473415196,
+          -0.00018073691171593964,
+          -0.0001653659564908594,
+          -0.00018484736210666597,
+          -0.00007919111521914601
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.1.pp_block.attn.balance_factors.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.02516937255859375,
+          -0.0030670166015625,
+          0.01318359375,
+          -0.042507171630859375,
+          -0.011112213134765625
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.1.pp_block.attn.balance_factors.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.07515736296772957,
+          0.05449230596423149,
+          0.06896872445940971,
+          -0.012038985267281532,
+          0.04510023817420006,
+          -0.06732466444373131,
+          -0.07297535799443722,
+          -0.042601536959409714,
+          -0.06062633916735649,
+          -0.02481861785054207
+         ]
+        }
+       ],
+       "layout": {
+        "hovermode": "x unified",
+        "legend": {
+         "title": {
+          "text": "Tensor Names"
+         }
+        },
+        "template": {
+         "data": {
+          "bar": [
+           {
+            "error_x": {
+             "color": "#2a3f5f"
+            },
+            "error_y": {
+             "color": "#2a3f5f"
+            },
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             },
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "bar"
+           }
+          ],
+          "barpolar": [
+           {
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             },
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "barpolar"
+           }
+          ],
+          "carpet": [
+           {
+            "aaxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "baxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "type": "carpet"
+           }
+          ],
+          "choropleth": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "choropleth"
+           }
+          ],
+          "contour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "contour"
+           }
+          ],
+          "contourcarpet": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "contourcarpet"
+           }
+          ],
+          "heatmap": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmap"
+           }
+          ],
+          "heatmapgl": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmapgl"
+           }
+          ],
+          "histogram": [
+           {
+            "marker": {
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "histogram"
+           }
+          ],
+          "histogram2d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2d"
+           }
+          ],
+          "histogram2dcontour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2dcontour"
+           }
+          ],
+          "mesh3d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "mesh3d"
+           }
+          ],
+          "parcoords": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "parcoords"
+           }
+          ],
+          "pie": [
+           {
+            "automargin": true,
+            "type": "pie"
+           }
+          ],
+          "scatter": [
+           {
+            "fillpattern": {
+             "fillmode": "overlay",
+             "size": 10,
+             "solidity": 0.2
+            },
+            "type": "scatter"
+           }
+          ],
+          "scatter3d": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatter3d"
+           }
+          ],
+          "scattercarpet": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattercarpet"
+           }
+          ],
+          "scattergeo": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergeo"
+           }
+          ],
+          "scattergl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergl"
+           }
+          ],
+          "scattermapbox": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattermapbox"
+           }
+          ],
+          "scatterpolar": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolar"
+           }
+          ],
+          "scatterpolargl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolargl"
+           }
+          ],
+          "scatterternary": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterternary"
+           }
+          ],
+          "surface": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "surface"
+           }
+          ],
+          "table": [
+           {
+            "cells": {
+             "fill": {
+              "color": "#EBF0F8"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "header": {
+             "fill": {
+              "color": "#C8D4E3"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "type": "table"
+           }
+          ]
+         },
+         "layout": {
+          "annotationdefaults": {
+           "arrowcolor": "#2a3f5f",
+           "arrowhead": 0,
+           "arrowwidth": 1
+          },
+          "autotypenumbers": "strict",
+          "coloraxis": {
+           "colorbar": {
+            "outlinewidth": 0,
+            "ticks": ""
+           }
+          },
+          "colorscale": {
+           "diverging": [
+            [
+             0,
+             "#8e0152"
+            ],
+            [
+             0.1,
+             "#c51b7d"
+            ],
+            [
+             0.2,
+             "#de77ae"
+            ],
+            [
+             0.3,
+             "#f1b6da"
+            ],
+            [
+             0.4,
+             "#fde0ef"
+            ],
+            [
+             0.5,
+             "#f7f7f7"
+            ],
+            [
+             0.6,
+             "#e6f5d0"
+            ],
+            [
+             0.7,
+             "#b8e186"
+            ],
+            [
+             0.8,
+             "#7fbc41"
+            ],
+            [
+             0.9,
+             "#4d9221"
+            ],
+            [
+             1,
+             "#276419"
+            ]
+           ],
+           "sequential": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ],
+           "sequentialminus": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ]
+          },
+          "colorway": [
+           "#636efa",
+           "#EF553B",
+           "#00cc96",
+           "#ab63fa",
+           "#FFA15A",
+           "#19d3f3",
+           "#FF6692",
+           "#B6E880",
+           "#FF97FF",
+           "#FECB52"
+          ],
+          "font": {
+           "color": "#2a3f5f"
+          },
+          "geo": {
+           "bgcolor": "white",
+           "lakecolor": "white",
+           "landcolor": "#E5ECF6",
+           "showlakes": true,
+           "showland": true,
+           "subunitcolor": "white"
+          },
+          "hoverlabel": {
+           "align": "left"
+          },
+          "hovermode": "closest",
+          "mapbox": {
+           "style": "light"
+          },
+          "paper_bgcolor": "white",
+          "plot_bgcolor": "#E5ECF6",
+          "polar": {
+           "angularaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "zaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "line": {
+            "color": "#2a3f5f"
+           }
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        },
+        "title": {
+         "text": "Gradient Means and Variances Across Training Steps"
+        },
+        "xaxis": {
+         "anchor": "y",
+         "domain": [
+          0,
+          1
+         ],
+         "title": {
+          "text": "Training Step"
+         }
+        },
+        "yaxis": {
+         "anchor": "x",
+         "domain": [
+          0,
+          1
+         ],
+         "title": {
+          "text": "Mean of Gradients"
+         }
+        }
+       }
+      },
+      "text/html": [
+       "<div>                            <div id=\"ea81c21c-e721-4577-9ec2-377099983b0a\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"ea81c21c-e721-4577-9ec2-377099983b0a\")) {                    Plotly.newPlot(                        \"ea81c21c-e721-4577-9ec2-377099983b0a\",                        [{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.final_layer_norm.pp_block.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[0.002198129892349243,0.0021066665649414062,0.0008701086044311523,0.0015106797218322754,-0.00011205673217773438],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.final_layer_norm.pp_block.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.007082977797836065,0.00813433900475502,0.005468044430017471,0.004966680658981204,0.0032637217082083225,-0.0034878351725637913,-0.0019453212153166533,-0.0037278272211551666,-0.003921005874872208,-0.002686718013137579],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.1.pp_block.input_layernorm.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[-7.554888725280762e-05,1.2159347534179688e-05,-6.566941738128662e-05,3.664568066596985e-05,2.5913119316101074e-05],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.1.pp_block.input_layernorm.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.00027068256167694926,0.00043601234210655093,0.0002786800905596465,0.00038932161987759173,0.00025601279048714787,-0.00020418655185494572,-0.00031603025854565203,-0.00041001892532221973,-0.00041169364703819156,-0.0004217803361825645],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.1.pp_block.mlp.gate_up_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[-3.262020072725136e-06,-2.9552000341936946e-05,-6.2779618019703776e-06,-3.9994483813643456e-07,-2.093311195494607e-07],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.1.pp_block.mlp.gate_up_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0005418256578195724,0.000466384255560115,0.0005196819802222308,0.00043358420953154564,0.00045861526268708985,-0.0004590339249261888,-0.0004343840992078185,-0.0005322379038261715,-0.0005254882562439889,-0.0005483496979650226],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.1.pp_block.attn.qkv_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[-1.9893303033313714e-05,-7.509818533435464e-05,-8.135275857057422e-05,2.751210195128806e-05,7.729327990091406e-06],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.1.pp_block.attn.qkv_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0013296976485435152,0.001402517140377313,0.001018972383462824,0.0009958900809579063,0.0007986696346051758,-0.000783210978624993,-0.0009408658770553302,-0.0011816779006039724,-0.0015527135110460222,-0.0013694842546101427],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.0.pp_block.attn.qkv_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[-9.807215974433348e-05,0.00012267599231563509,5.988371412968263e-05,-2.36338146351045e-05,3.453333556535654e-05],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.0.pp_block.attn.qkv_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0013592619870905764,0.001465613575419411,0.001127638177422341,0.0010535859128140146,0.001023725500999717,-0.000954658829869004,-0.0011008535420842236,-0.0010078707491629757,-0.001220261590788141,-0.0015554063065792434],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.0.pp_block.post_attention_layernorm.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[0.0001437664031982422,0.00018288195133209229,-7.216259837150574e-05,-0.00018101930618286133,0.00018277764320373535],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.0.pp_block.post_attention_layernorm.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0004035377933178097,0.0004997444921173155,0.0001882568176370114,7.293169619515538e-05,0.0004796491120941937,-0.000114093825686723,-0.00043497030856087804,-0.0003325820143800229,-0.00013398058945313096,-0.00011600498692132533],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.0.pp_block.input_layernorm.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[7.13123008608818e-05,-3.910064697265625e-05,-2.9280781745910645e-06,8.285790681838989e-05,1.8924474716186523e-05],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.0.pp_block.input_layernorm.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0005026485305279493,0.00027448905166238546,0.00023909594165161252,0.0003632560546975583,0.0002120095450663939,-0.00017416059563402086,-0.0001975402410607785,-0.00024495209800079465,-0.00035269034560769796,-0.0003600239288061857],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.0.pp_block.mlp.down_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[-3.5567820305004716e-05,-0.00010004517389461398,9.103445336222649e-06,1.52749998960644e-06,2.1241081412881613e-05],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.0.pp_block.mlp.down_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0010479049233254045,0.0011488441959954798,0.001135421684011817,0.0010538919741520658,0.0010336725390516222,-0.000991190376225859,-0.001050836974172853,-0.0011172147933393717,-0.0013489345437847078,-0.001119040563935414],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.1.pp_block.mlp.down_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[2.0260762539692223e-05,2.4348206352442503e-05,3.906200436176732e-05,-1.029292616294697e-05,-2.1571177057921886e-06],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.1.pp_block.mlp.down_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.001155012592789717,0.0010924921953119338,0.0011122663345304318,0.0008695767537574284,0.0008067959570325911,-0.0008111101924441755,-0.0008901626060833223,-0.0010341423258068971,-0.0010437957826070487,-0.0011144910677103326],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.1.pp_block.attn.o_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[0.00040972232818603516,-0.000264984555542469,6.173807196319103e-05,-0.0005156630650162697,-0.00019942596554756165],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.1.pp_block.attn.o_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0046989344991743565,0.0036927000619471073,0.003142212750390172,0.0027088948991149664,0.0026285804342478514,-0.0030274323653429747,-0.0037402210291475058,-0.00301873660646379,-0.004222669173032045,-0.003879489842802286],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.token_position_embeddings.pp_block.token_embedding.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[-8.04212845650909e-07,-2.1271421246638056e-06,2.4151413526851684e-06,6.843426376690331e-07,8.726783562451601e-08],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.token_position_embeddings.pp_block.token_embedding.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0008795044692533338,0.0008495641509398411,0.000796735334006371,0.000767548156261455,0.0007648306927876547,-0.0007646561571164057,-0.0007661794709861169,-0.0007919050513010006,-0.0008538184351891687,-0.0008811128949446356],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.lm_head.pp_block.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[1.2801820048480295e-07,-3.8747495523239195e-07,2.449887404054607e-07,-3.7114006090632756e-07,3.2651161063768086e-07],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.lm_head.pp_block.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0008499983428009728,0.0008608746127549693,0.0008068004317181021,0.0007549875219297064,0.0007691299209113822,-0.0007684768976901069,-0.0007557298020515191,-0.0008063104542372912,-0.0008616495626654341,-0.0008497423064000031],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.0.pp_block.attn.o_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[0.0004978431388735771,0.0004920652136206627,6.26780092716217e-06,-0.0003082635812461376,6.58784992992878e-05],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.0.pp_block.attn.o_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.003778938204050064,0.004228800069540739,0.0030188877135515213,0.0025075047742575407,0.0024150535464286804,-0.002283296547830105,-0.003124031936749816,-0.003006352111697197,-0.0032446696422994137,-0.00278325192630291],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.0.pp_block.mlp.gate_up_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[-1.92889419849962e-05,4.385730790090747e-06,-5.527399480342865e-07,-7.215039659058675e-07,8.949356924858876e-06],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.0.pp_block.mlp.gate_up_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0005691324186045676,0.0005819777306896867,0.0005219283048063517,0.000508927778355428,0.0005151660170668038,-0.000497267303217086,-0.0005103707862872398,-0.0005230337847024202,-0.0005732062691095052,-0.00060771030257456],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.0.pp_block.attn.balance_factors.grad\",\"x\":[1,2,3,4,5],\"y\":[-0.022059202194213867,0.0292510986328125,0.00128173828125,-0.02606964111328125,-0.00794219970703125],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.0.pp_block.attn.balance_factors.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.029811076819896698,0.07617643848061562,0.05894214287400246,0.02324569970369339,0.04914530739188194,-0.06502970680594444,-0.07538498193025589,-0.05637866631150246,-0.017674241214990616,-0.07392948120832443],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.1.pp_block.post_attention_layernorm.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[0.00021371245384216309,9.015947580337524e-05,8.095055818557739e-05,0.00010886043310165405,4.680454730987549e-05],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.1.pp_block.post_attention_layernorm.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0005066160229034722,0.00036516631371341646,0.0003272670728620142,0.00039845777791924775,0.00034502430935390294,-0.00025141521473415196,-0.00018073691171593964,-0.0001653659564908594,-0.00018484736210666597,-7.919111521914601e-05],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.1.pp_block.attn.balance_factors.grad\",\"x\":[1,2,3,4,5],\"y\":[0.02516937255859375,-0.0030670166015625,0.01318359375,-0.042507171630859375,-0.011112213134765625],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.1.pp_block.attn.balance_factors.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.07515736296772957,0.05449230596423149,0.06896872445940971,-0.012038985267281532,0.04510023817420006,-0.06732466444373131,-0.07297535799443722,-0.042601536959409714,-0.06062633916735649,-0.02481861785054207],\"type\":\"scatter\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmapgl\":[{\"type\":\"heatmapgl\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermapbox\":[{\"type\":\"scattermapbox\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05},\"mapbox\":{\"style\":\"light\"}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Training Step\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Mean of Gradients\"}},\"title\":{\"text\":\"Gradient Means and Variances Across Training Steps\"},\"hovermode\":\"x unified\",\"legend\":{\"title\":{\"text\":\"Tensor Names\"}}},                        {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('ea81c21c-e721-4577-9ec2-377099983b0a');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from plotly.offline import init_notebook_mode, iplot\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "linkText": "Export to plot.ly",
+        "plotlyServerURL": "https://plot.ly",
+        "showLink": false
+       },
+       "data": [
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.final_layer_norm.pp_block.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.002198129892349243,
+          0.0021066665649414062,
+          0.0008701086044311523,
+          0.0015106797218322754,
+          -0.00011205673217773438
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.final_layer_norm.pp_block.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.007082977797836065,
+          0.00813433900475502,
+          0.005468044430017471,
+          0.004966680658981204,
+          0.0032637217082083225,
+          -0.0034878351725637913,
+          -0.0019453212153166533,
+          -0.0037278272211551666,
+          -0.003921005874872208,
+          -0.002686718013137579
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.1.pp_block.input_layernorm.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -0.00007554888725280762,
+          0.000012159347534179688,
+          -0.00006566941738128662,
+          0.00003664568066596985,
+          0.000025913119316101074
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.1.pp_block.input_layernorm.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.00027068256167694926,
+          0.00043601234210655093,
+          0.0002786800905596465,
+          0.00038932161987759173,
+          0.00025601279048714787,
+          -0.00020418655185494572,
+          -0.00031603025854565203,
+          -0.00041001892532221973,
+          -0.00041169364703819156,
+          -0.0004217803361825645
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.1.pp_block.mlp.gate_up_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -0.000003262020072725136,
+          -0.000029552000341936946,
+          -0.0000062779618019703776,
+          -3.9994483813643456e-7,
+          -2.093311195494607e-7
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.1.pp_block.mlp.gate_up_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0005418256578195724,
+          0.000466384255560115,
+          0.0005196819802222308,
+          0.00043358420953154564,
+          0.00045861526268708985,
+          -0.0004590339249261888,
+          -0.0004343840992078185,
+          -0.0005322379038261715,
+          -0.0005254882562439889,
+          -0.0005483496979650226
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.1.pp_block.attn.qkv_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -0.000019893303033313714,
+          -0.00007509818533435464,
+          -0.00008135275857057422,
+          0.00002751210195128806,
+          0.000007729327990091406
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.1.pp_block.attn.qkv_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0013296976485435152,
+          0.001402517140377313,
+          0.001018972383462824,
+          0.0009958900809579063,
+          0.0007986696346051758,
+          -0.000783210978624993,
+          -0.0009408658770553302,
+          -0.0011816779006039724,
+          -0.0015527135110460222,
+          -0.0013694842546101427
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.0.pp_block.attn.qkv_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -0.00009807215974433348,
+          0.00012267599231563509,
+          0.00005988371412968263,
+          -0.0000236338146351045,
+          0.00003453333556535654
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.0.pp_block.attn.qkv_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0013592619870905764,
+          0.001465613575419411,
+          0.001127638177422341,
+          0.0010535859128140146,
+          0.001023725500999717,
+          -0.000954658829869004,
+          -0.0011008535420842236,
+          -0.0010078707491629757,
+          -0.001220261590788141,
+          -0.0015554063065792434
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.0.pp_block.post_attention_layernorm.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.0001437664031982422,
+          0.00018288195133209229,
+          -0.00007216259837150574,
+          -0.00018101930618286133,
+          0.00018277764320373535
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.0.pp_block.post_attention_layernorm.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0004035377933178097,
+          0.0004997444921173155,
+          0.0001882568176370114,
+          0.00007293169619515538,
+          0.0004796491120941937,
+          -0.000114093825686723,
+          -0.00043497030856087804,
+          -0.0003325820143800229,
+          -0.00013398058945313096,
+          -0.00011600498692132533
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.0.pp_block.input_layernorm.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.0000713123008608818,
+          -0.00003910064697265625,
+          -0.0000029280781745910645,
+          0.00008285790681838989,
+          0.000018924474716186523
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.0.pp_block.input_layernorm.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0005026485305279493,
+          0.00027448905166238546,
+          0.00023909594165161252,
+          0.0003632560546975583,
+          0.0002120095450663939,
+          -0.00017416059563402086,
+          -0.0001975402410607785,
+          -0.00024495209800079465,
+          -0.00035269034560769796,
+          -0.0003600239288061857
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.0.pp_block.mlp.down_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -0.000035567820305004716,
+          -0.00010004517389461398,
+          0.000009103445336222649,
+          0.00000152749998960644,
+          0.000021241081412881613
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.0.pp_block.mlp.down_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0010479049233254045,
+          0.0011488441959954798,
+          0.001135421684011817,
+          0.0010538919741520658,
+          0.0010336725390516222,
+          -0.000991190376225859,
+          -0.001050836974172853,
+          -0.0011172147933393717,
+          -0.0013489345437847078,
+          -0.001119040563935414
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.1.pp_block.mlp.down_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.000020260762539692223,
+          0.000024348206352442503,
+          0.00003906200436176732,
+          -0.00001029292616294697,
+          -0.0000021571177057921886
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.1.pp_block.mlp.down_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.001155012592789717,
+          0.0010924921953119338,
+          0.0011122663345304318,
+          0.0008695767537574284,
+          0.0008067959570325911,
+          -0.0008111101924441755,
+          -0.0008901626060833223,
+          -0.0010341423258068971,
+          -0.0010437957826070487,
+          -0.0011144910677103326
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.1.pp_block.attn.o_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.00040972232818603516,
+          -0.000264984555542469,
+          0.00006173807196319103,
+          -0.0005156630650162697,
+          -0.00019942596554756165
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.1.pp_block.attn.o_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0046989344991743565,
+          0.0036927000619471073,
+          0.003142212750390172,
+          0.0027088948991149664,
+          0.0026285804342478514,
+          -0.0030274323653429747,
+          -0.0037402210291475058,
+          -0.00301873660646379,
+          -0.004222669173032045,
+          -0.003879489842802286
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.token_position_embeddings.pp_block.token_embedding.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -8.04212845650909e-7,
+          -0.0000021271421246638056,
+          0.0000024151413526851684,
+          6.843426376690331e-7,
+          8.726783562451601e-8
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.token_position_embeddings.pp_block.token_embedding.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0008795044692533338,
+          0.0008495641509398411,
+          0.000796735334006371,
+          0.000767548156261455,
+          0.0007648306927876547,
+          -0.0007646561571164057,
+          -0.0007661794709861169,
+          -0.0007919050513010006,
+          -0.0008538184351891687,
+          -0.0008811128949446356
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.lm_head.pp_block.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          1.2801820048480295e-7,
+          -3.8747495523239195e-7,
+          2.449887404054607e-7,
+          -3.7114006090632756e-7,
+          3.2651161063768086e-7
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.lm_head.pp_block.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0008499983428009728,
+          0.0008608746127549693,
+          0.0008068004317181021,
+          0.0007549875219297064,
+          0.0007691299209113822,
+          -0.0007684768976901069,
+          -0.0007557298020515191,
+          -0.0008063104542372912,
+          -0.0008616495626654341,
+          -0.0008497423064000031
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.0.pp_block.attn.o_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.0004978431388735771,
+          0.0004920652136206627,
+          0.00000626780092716217,
+          -0.0003082635812461376,
+          0.0000658784992992878
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.0.pp_block.attn.o_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.003778938204050064,
+          0.004228800069540739,
+          0.0030188877135515213,
+          0.0025075047742575407,
+          0.0024150535464286804,
+          -0.002283296547830105,
+          -0.003124031936749816,
+          -0.003006352111697197,
+          -0.0032446696422994137,
+          -0.00278325192630291
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.0.pp_block.mlp.gate_up_proj.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -0.0000192889419849962,
+          0.000004385730790090747,
+          -5.527399480342865e-7,
+          -7.215039659058675e-7,
+          0.000008949356924858876
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.0.pp_block.mlp.gate_up_proj.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0005691324186045676,
+          0.0005819777306896867,
+          0.0005219283048063517,
+          0.000508927778355428,
+          0.0005151660170668038,
+          -0.000497267303217086,
+          -0.0005103707862872398,
+          -0.0005230337847024202,
+          -0.0005732062691095052,
+          -0.00060771030257456
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.0.pp_block.attn.balance_factors.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          -0.022059202194213867,
+          0.0292510986328125,
+          0.00128173828125,
+          -0.02606964111328125,
+          -0.00794219970703125
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.0.pp_block.attn.balance_factors.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.029811076819896698,
+          0.07617643848061562,
+          0.05894214287400246,
+          0.02324569970369339,
+          0.04914530739188194,
+          -0.06502970680594444,
+          -0.07538498193025589,
+          -0.05637866631150246,
+          -0.017674241214990616,
+          -0.07392948120832443
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.1.pp_block.post_attention_layernorm.weight.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.00021371245384216309,
+          0.00009015947580337524,
+          0.00008095055818557739,
+          0.00010886043310165405,
+          0.00004680454730987549
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.1.pp_block.post_attention_layernorm.weight.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.0005066160229034722,
+          0.00036516631371341646,
+          0.0003272670728620142,
+          0.00039845777791924775,
+          0.00034502430935390294,
+          -0.00025141521473415196,
+          -0.00018073691171593964,
+          -0.0001653659564908594,
+          -0.00018484736210666597,
+          -0.00007919111521914601
+         ]
+        },
+        {
+         "line": {
+          "width": 2
+         },
+         "mode": "lines",
+         "name": "model.decoder.1.pp_block.attn.balance_factors.grad",
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5
+         ],
+         "y": [
+          0.02516937255859375,
+          -0.0030670166015625,
+          0.01318359375,
+          -0.042507171630859375,
+          -0.011112213134765625
+         ]
+        },
+        {
+         "fill": "toself",
+         "fillcolor": "rgba(0,100,80,0.2)",
+         "hoverinfo": "skip",
+         "line": {
+          "color": "rgba(255,255,255,0)"
+         },
+         "name": "model.decoder.1.pp_block.attn.balance_factors.grad Std Dev",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          5,
+          4,
+          3,
+          2,
+          1
+         ],
+         "y": [
+          0.07515736296772957,
+          0.05449230596423149,
+          0.06896872445940971,
+          -0.012038985267281532,
+          0.04510023817420006,
+          -0.06732466444373131,
+          -0.07297535799443722,
+          -0.042601536959409714,
+          -0.06062633916735649,
+          -0.02481861785054207
+         ]
+        }
+       ],
+       "layout": {
+        "hovermode": "x unified",
+        "legend": {
+         "title": {
+          "text": "Tensor Names"
+         }
+        },
+        "template": {
+         "data": {
+          "bar": [
+           {
+            "error_x": {
+             "color": "#2a3f5f"
+            },
+            "error_y": {
+             "color": "#2a3f5f"
+            },
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             },
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "bar"
+           }
+          ],
+          "barpolar": [
+           {
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             },
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "barpolar"
+           }
+          ],
+          "carpet": [
+           {
+            "aaxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "baxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "type": "carpet"
+           }
+          ],
+          "choropleth": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "choropleth"
+           }
+          ],
+          "contour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "contour"
+           }
+          ],
+          "contourcarpet": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "contourcarpet"
+           }
+          ],
+          "heatmap": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmap"
+           }
+          ],
+          "heatmapgl": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmapgl"
+           }
+          ],
+          "histogram": [
+           {
+            "marker": {
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "histogram"
+           }
+          ],
+          "histogram2d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2d"
+           }
+          ],
+          "histogram2dcontour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2dcontour"
+           }
+          ],
+          "mesh3d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "mesh3d"
+           }
+          ],
+          "parcoords": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "parcoords"
+           }
+          ],
+          "pie": [
+           {
+            "automargin": true,
+            "type": "pie"
+           }
+          ],
+          "scatter": [
+           {
+            "fillpattern": {
+             "fillmode": "overlay",
+             "size": 10,
+             "solidity": 0.2
+            },
+            "type": "scatter"
+           }
+          ],
+          "scatter3d": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatter3d"
+           }
+          ],
+          "scattercarpet": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattercarpet"
+           }
+          ],
+          "scattergeo": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergeo"
+           }
+          ],
+          "scattergl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergl"
+           }
+          ],
+          "scattermapbox": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattermapbox"
+           }
+          ],
+          "scatterpolar": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolar"
+           }
+          ],
+          "scatterpolargl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolargl"
+           }
+          ],
+          "scatterternary": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterternary"
+           }
+          ],
+          "surface": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "surface"
+           }
+          ],
+          "table": [
+           {
+            "cells": {
+             "fill": {
+              "color": "#EBF0F8"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "header": {
+             "fill": {
+              "color": "#C8D4E3"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "type": "table"
+           }
+          ]
+         },
+         "layout": {
+          "annotationdefaults": {
+           "arrowcolor": "#2a3f5f",
+           "arrowhead": 0,
+           "arrowwidth": 1
+          },
+          "autotypenumbers": "strict",
+          "coloraxis": {
+           "colorbar": {
+            "outlinewidth": 0,
+            "ticks": ""
+           }
+          },
+          "colorscale": {
+           "diverging": [
+            [
+             0,
+             "#8e0152"
+            ],
+            [
+             0.1,
+             "#c51b7d"
+            ],
+            [
+             0.2,
+             "#de77ae"
+            ],
+            [
+             0.3,
+             "#f1b6da"
+            ],
+            [
+             0.4,
+             "#fde0ef"
+            ],
+            [
+             0.5,
+             "#f7f7f7"
+            ],
+            [
+             0.6,
+             "#e6f5d0"
+            ],
+            [
+             0.7,
+             "#b8e186"
+            ],
+            [
+             0.8,
+             "#7fbc41"
+            ],
+            [
+             0.9,
+             "#4d9221"
+            ],
+            [
+             1,
+             "#276419"
+            ]
+           ],
+           "sequential": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ],
+           "sequentialminus": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ]
+          },
+          "colorway": [
+           "#636efa",
+           "#EF553B",
+           "#00cc96",
+           "#ab63fa",
+           "#FFA15A",
+           "#19d3f3",
+           "#FF6692",
+           "#B6E880",
+           "#FF97FF",
+           "#FECB52"
+          ],
+          "font": {
+           "color": "#2a3f5f"
+          },
+          "geo": {
+           "bgcolor": "white",
+           "lakecolor": "white",
+           "landcolor": "#E5ECF6",
+           "showlakes": true,
+           "showland": true,
+           "subunitcolor": "white"
+          },
+          "hoverlabel": {
+           "align": "left"
+          },
+          "hovermode": "closest",
+          "mapbox": {
+           "style": "light"
+          },
+          "paper_bgcolor": "white",
+          "plot_bgcolor": "#E5ECF6",
+          "polar": {
+           "angularaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "zaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "line": {
+            "color": "#2a3f5f"
+           }
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        },
+        "title": {
+         "text": "Gradient Means and Variances Across Training Steps"
+        },
+        "xaxis": {
+         "anchor": "y",
+         "domain": [
+          0,
+          1
+         ],
+         "title": {
+          "text": "Training Step"
+         }
+        },
+        "yaxis": {
+         "anchor": "x",
+         "domain": [
+          0,
+          1
+         ],
+         "title": {
+          "text": "Mean of Gradients"
+         }
+        }
+       }
+      },
+      "text/html": [
+       "<div>                            <div id=\"739e05f2-ae6f-4e54-b09e-3d4c4f43fc29\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"739e05f2-ae6f-4e54-b09e-3d4c4f43fc29\")) {                    Plotly.newPlot(                        \"739e05f2-ae6f-4e54-b09e-3d4c4f43fc29\",                        [{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.final_layer_norm.pp_block.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[0.002198129892349243,0.0021066665649414062,0.0008701086044311523,0.0015106797218322754,-0.00011205673217773438],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.final_layer_norm.pp_block.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.007082977797836065,0.00813433900475502,0.005468044430017471,0.004966680658981204,0.0032637217082083225,-0.0034878351725637913,-0.0019453212153166533,-0.0037278272211551666,-0.003921005874872208,-0.002686718013137579],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.1.pp_block.input_layernorm.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[-7.554888725280762e-05,1.2159347534179688e-05,-6.566941738128662e-05,3.664568066596985e-05,2.5913119316101074e-05],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.1.pp_block.input_layernorm.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.00027068256167694926,0.00043601234210655093,0.0002786800905596465,0.00038932161987759173,0.00025601279048714787,-0.00020418655185494572,-0.00031603025854565203,-0.00041001892532221973,-0.00041169364703819156,-0.0004217803361825645],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.1.pp_block.mlp.gate_up_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[-3.262020072725136e-06,-2.9552000341936946e-05,-6.2779618019703776e-06,-3.9994483813643456e-07,-2.093311195494607e-07],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.1.pp_block.mlp.gate_up_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0005418256578195724,0.000466384255560115,0.0005196819802222308,0.00043358420953154564,0.00045861526268708985,-0.0004590339249261888,-0.0004343840992078185,-0.0005322379038261715,-0.0005254882562439889,-0.0005483496979650226],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.1.pp_block.attn.qkv_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[-1.9893303033313714e-05,-7.509818533435464e-05,-8.135275857057422e-05,2.751210195128806e-05,7.729327990091406e-06],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.1.pp_block.attn.qkv_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0013296976485435152,0.001402517140377313,0.001018972383462824,0.0009958900809579063,0.0007986696346051758,-0.000783210978624993,-0.0009408658770553302,-0.0011816779006039724,-0.0015527135110460222,-0.0013694842546101427],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.0.pp_block.attn.qkv_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[-9.807215974433348e-05,0.00012267599231563509,5.988371412968263e-05,-2.36338146351045e-05,3.453333556535654e-05],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.0.pp_block.attn.qkv_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0013592619870905764,0.001465613575419411,0.001127638177422341,0.0010535859128140146,0.001023725500999717,-0.000954658829869004,-0.0011008535420842236,-0.0010078707491629757,-0.001220261590788141,-0.0015554063065792434],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.0.pp_block.post_attention_layernorm.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[0.0001437664031982422,0.00018288195133209229,-7.216259837150574e-05,-0.00018101930618286133,0.00018277764320373535],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.0.pp_block.post_attention_layernorm.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0004035377933178097,0.0004997444921173155,0.0001882568176370114,7.293169619515538e-05,0.0004796491120941937,-0.000114093825686723,-0.00043497030856087804,-0.0003325820143800229,-0.00013398058945313096,-0.00011600498692132533],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.0.pp_block.input_layernorm.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[7.13123008608818e-05,-3.910064697265625e-05,-2.9280781745910645e-06,8.285790681838989e-05,1.8924474716186523e-05],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.0.pp_block.input_layernorm.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0005026485305279493,0.00027448905166238546,0.00023909594165161252,0.0003632560546975583,0.0002120095450663939,-0.00017416059563402086,-0.0001975402410607785,-0.00024495209800079465,-0.00035269034560769796,-0.0003600239288061857],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.0.pp_block.mlp.down_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[-3.5567820305004716e-05,-0.00010004517389461398,9.103445336222649e-06,1.52749998960644e-06,2.1241081412881613e-05],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.0.pp_block.mlp.down_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0010479049233254045,0.0011488441959954798,0.001135421684011817,0.0010538919741520658,0.0010336725390516222,-0.000991190376225859,-0.001050836974172853,-0.0011172147933393717,-0.0013489345437847078,-0.001119040563935414],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.1.pp_block.mlp.down_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[2.0260762539692223e-05,2.4348206352442503e-05,3.906200436176732e-05,-1.029292616294697e-05,-2.1571177057921886e-06],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.1.pp_block.mlp.down_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.001155012592789717,0.0010924921953119338,0.0011122663345304318,0.0008695767537574284,0.0008067959570325911,-0.0008111101924441755,-0.0008901626060833223,-0.0010341423258068971,-0.0010437957826070487,-0.0011144910677103326],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.1.pp_block.attn.o_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[0.00040972232818603516,-0.000264984555542469,6.173807196319103e-05,-0.0005156630650162697,-0.00019942596554756165],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.1.pp_block.attn.o_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0046989344991743565,0.0036927000619471073,0.003142212750390172,0.0027088948991149664,0.0026285804342478514,-0.0030274323653429747,-0.0037402210291475058,-0.00301873660646379,-0.004222669173032045,-0.003879489842802286],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.token_position_embeddings.pp_block.token_embedding.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[-8.04212845650909e-07,-2.1271421246638056e-06,2.4151413526851684e-06,6.843426376690331e-07,8.726783562451601e-08],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.token_position_embeddings.pp_block.token_embedding.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0008795044692533338,0.0008495641509398411,0.000796735334006371,0.000767548156261455,0.0007648306927876547,-0.0007646561571164057,-0.0007661794709861169,-0.0007919050513010006,-0.0008538184351891687,-0.0008811128949446356],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.lm_head.pp_block.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[1.2801820048480295e-07,-3.8747495523239195e-07,2.449887404054607e-07,-3.7114006090632756e-07,3.2651161063768086e-07],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.lm_head.pp_block.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0008499983428009728,0.0008608746127549693,0.0008068004317181021,0.0007549875219297064,0.0007691299209113822,-0.0007684768976901069,-0.0007557298020515191,-0.0008063104542372912,-0.0008616495626654341,-0.0008497423064000031],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.0.pp_block.attn.o_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[0.0004978431388735771,0.0004920652136206627,6.26780092716217e-06,-0.0003082635812461376,6.58784992992878e-05],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.0.pp_block.attn.o_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.003778938204050064,0.004228800069540739,0.0030188877135515213,0.0025075047742575407,0.0024150535464286804,-0.002283296547830105,-0.003124031936749816,-0.003006352111697197,-0.0032446696422994137,-0.00278325192630291],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.0.pp_block.mlp.gate_up_proj.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[-1.92889419849962e-05,4.385730790090747e-06,-5.527399480342865e-07,-7.215039659058675e-07,8.949356924858876e-06],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.0.pp_block.mlp.gate_up_proj.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0005691324186045676,0.0005819777306896867,0.0005219283048063517,0.000508927778355428,0.0005151660170668038,-0.000497267303217086,-0.0005103707862872398,-0.0005230337847024202,-0.0005732062691095052,-0.00060771030257456],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.0.pp_block.attn.balance_factors.grad\",\"x\":[1,2,3,4,5],\"y\":[-0.022059202194213867,0.0292510986328125,0.00128173828125,-0.02606964111328125,-0.00794219970703125],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.0.pp_block.attn.balance_factors.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.029811076819896698,0.07617643848061562,0.05894214287400246,0.02324569970369339,0.04914530739188194,-0.06502970680594444,-0.07538498193025589,-0.05637866631150246,-0.017674241214990616,-0.07392948120832443],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.1.pp_block.post_attention_layernorm.weight.grad\",\"x\":[1,2,3,4,5],\"y\":[0.00021371245384216309,9.015947580337524e-05,8.095055818557739e-05,0.00010886043310165405,4.680454730987549e-05],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.1.pp_block.post_attention_layernorm.weight.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.0005066160229034722,0.00036516631371341646,0.0003272670728620142,0.00039845777791924775,0.00034502430935390294,-0.00025141521473415196,-0.00018073691171593964,-0.0001653659564908594,-0.00018484736210666597,-7.919111521914601e-05],\"type\":\"scatter\"},{\"line\":{\"width\":2},\"mode\":\"lines\",\"name\":\"model.decoder.1.pp_block.attn.balance_factors.grad\",\"x\":[1,2,3,4,5],\"y\":[0.02516937255859375,-0.0030670166015625,0.01318359375,-0.042507171630859375,-0.011112213134765625],\"type\":\"scatter\"},{\"fill\":\"toself\",\"fillcolor\":\"rgba(0,100,80,0.2)\",\"hoverinfo\":\"skip\",\"line\":{\"color\":\"rgba(255,255,255,0)\"},\"name\":\"model.decoder.1.pp_block.attn.balance_factors.grad Std Dev\",\"showlegend\":false,\"x\":[1,2,3,4,5,5,4,3,2,1],\"y\":[0.07515736296772957,0.05449230596423149,0.06896872445940971,-0.012038985267281532,0.04510023817420006,-0.06732466444373131,-0.07297535799443722,-0.042601536959409714,-0.06062633916735649,-0.02481861785054207],\"type\":\"scatter\"}],                        {\"hovermode\":\"x unified\",\"legend\":{\"title\":{\"text\":\"Tensor Names\"}},\"template\":{\"data\":{\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"title\":{\"text\":\"Gradient Means and Variances Across Training Steps\"},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Training Step\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Mean of Gradients\"}}},                        {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('739e05f2-ae6f-4e54-b09e-3d4c4f43fc29');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "iplot(fig)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "        <script type=\"text/javascript\">\n",
+       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
+       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
+       "        if (typeof require !== 'undefined') {\n",
+       "        require.undef(\"plotly\");\n",
+       "        requirejs.config({\n",
+       "            paths: {\n",
+       "                'plotly': ['https://cdn.plot.ly/plotly-2.32.0.min']\n",
+       "            }\n",
+       "        });\n",
+       "        require(['plotly'], function(Plotly) {\n",
+       "            window._Plotly = Plotly;\n",
+       "        });\n",
+       "        }\n",
+       "        </script>\n",
+       "        "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "init_notebook_mode(connected=True)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "        <script type=\"text/javascript\">\n",
+       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
+       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
+       "        if (typeof require !== 'undefined') {\n",
+       "        require.undef(\"plotly\");\n",
+       "        requirejs.config({\n",
+       "            paths: {\n",
+       "                'plotly': ['https://cdn.plot.ly/plotly-2.32.0.min']\n",
+       "            }\n",
+       "        });\n",
+       "        require(['plotly'], function(Plotly) {\n",
+       "            window._Plotly = Plotly;\n",
+       "        });\n",
+       "        }\n",
+       "        </script>\n",
+       "        "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import plotly.graph_objs as go\n",
+    "from plotly.offline import init_notebook_mode, iplot\n",
+    "import numpy as np\n",
+    "\n",
+    "# Initialize plotly for use in the notebook\n",
+    "init_notebook_mode(connected=True)\n",
+    "\n",
+    "# Generate some sample data\n",
+    "x = np.linspace(0, 10, 100)\n",
+    "y1 = np.sin(x)\n",
+    "y2 = np.cos(x)\n",
+    "\n",
+    "# Create traces\n",
+    "trace1 = go.Scatter(\n",
+    "    x = x,\n",
+    "    y = y1,\n",
+    "    mode = 'lines',\n",
+    "    name = 'sin(x)'\n",
+    ")\n",
+    "trace2 = go.Scatter(\n",
+    "    x = x,\n",
+    "    y = y2,\n",
+    "    mode = 'lines',\n",
+    "    name = 'cos(x)'\n",
+    ")\n",
+    "\n",
+    "# Create layout\n",
+    "layout = go.Layout(\n",
+    "    title = 'Simple Interactive Plotly Graph',\n",
+    "    xaxis = dict(title = 'X-axis'),\n",
+    "    yaxis = dict(title = 'Y-axis')\n",
+    ")\n",
+    "\n",
+    "# Combine trace and layout\n",
+    "fig = go.Figure(data=[trace1, trace2], layout=layout)\n",
+    "\n",
+    "# Plot!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Exp 32"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "exp32_weights = read_tensor(\"/fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp32_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/checkpoints/10000/model/model/decoder/2/pp_block/attn/model_balance_factors_pp-rank-0-of-1_tp-rank-0-of-2.safetensors\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([0.4961, 0.4922, 0.4941, 0.4922], dtype=torch.bfloat16)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F.sigmoid(exp32_weights)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([0.4961, 0.4922, 0.4941, 0.4922], dtype=torch.bfloat16)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F.sigmoid(read_tensor(\"/fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp32_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/checkpoints/10000/model/model/decoder/2/pp_block/attn/model_balance_factors_pp-rank-0-of-1_tp-rank-1-of-2.safetensors\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([0.4922, 0.4922, 0.4922, 0.4961], dtype=torch.bfloat16)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F.sigmoid(read_tensor(\"/fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp32_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/checkpoints/10000/model/model/decoder/0/pp_block/attn/model_balance_factors_pp-rank-0-of-1_tp-rank-1-of-2.safetensors\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([0.4922, 0.4922, 0.4922, 0.4961], dtype=torch.bfloat16)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "F.sigmoid(read_tensor(\"/fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp32_200m_infini_llama2_256_ctx_length_and_64_segment_length_and_2m_bs/checkpoints/10000/model/model/decoder/0/pp_block/attn/model_balance_factors_pp-rank-0-of-1_tp-rank-0-of-2.safetensors\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/infinite-context-length/data/exp34/hope.ipynb b/examples/infinite-context-length/data/exp34/hope.ipynb
new file mode 100644
index 00000000..e1726f85
--- /dev/null
+++ b/examples/infinite-context-length/data/exp34/hope.ipynb
@@ -0,0 +1,1975 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "paths = []\n",
+    "\n",
+    "for depth in range(0, 100, 5):\n",
+    "    # paths.append(f\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/eval_results/passkey_eval_results_for_{depth}_depth.pkl\")\n",
+    "    # paths.append(f\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/finetuning_passkey_eval_results/passkey_eval_results_for_{depth}_depth.pkl\")\n",
+    "    paths.append(f\"/fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp55_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.001/logs/evals/eval_8b_llama_infini_at_20k_ckp_16k_passkey_no_finetuning/passkey_eval_results_for_{depth}_depth.pkl\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dfs = [pd.read_pickle(path) for path in paths]\n",
+    "df = pd.concat(dfs, )  # Set ignore_index to reset index"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>prompt</th>\n",
+       "      <th>answer</th>\n",
+       "      <th>context_length</th>\n",
+       "      <th>num_tokens</th>\n",
+       "      <th>depth_percent</th>\n",
+       "      <th>generation_text</th>\n",
+       "      <th>generation_ids</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>41b18f68-7840-47d5-b612-978a17e97383</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>895</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15878</td>\n",
+       "      <td>0</td>\n",
+       "      <td>100.&lt;|begin_of_text|&gt;There is a pass key hidde...</td>\n",
+       "      <td>[1041, 13, 128000, 3947, 374, 264, 1522, 1401,...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>d333b4d3-7efe-413b-8c12-9e05975ccefb</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>622</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15878</td>\n",
+       "      <td>0</td>\n",
+       "      <td>100.&lt;|begin_of_text|&gt;There is a pass key hidde...</td>\n",
+       "      <td>[1041, 13, 128000, 3947, 374, 264, 1522, 1401,...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>07a8a074-5f66-420b-8cba-5b826178b957</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>223</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15758</td>\n",
+       "      <td>0</td>\n",
+       "      <td>100.&lt;|begin_of_text|&gt;There is a pass key hidde...</td>\n",
+       "      <td>[1041, 13, 128000, 3947, 374, 264, 1522, 1401,...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>07813635-9487-4b46-9293-3d524e43d645</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>432</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15758</td>\n",
+       "      <td>0</td>\n",
+       "      <td>100.&lt;|begin_of_text|&gt;There is a pass key hidde...</td>\n",
+       "      <td>[1041, 13, 128000, 3947, 374, 264, 1522, 1401,...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>f9a80b29-367f-4963-8c2d-73706eec249a</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>814</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16213</td>\n",
+       "      <td>0</td>\n",
+       "      <td>100.&lt;|begin_of_text|&gt;There is a pass key hidde...</td>\n",
+       "      <td>[1041, 13, 128000, 3947, 374, 264, 1522, 1401,...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                     id  \\\n",
+       "0  41b18f68-7840-47d5-b612-978a17e97383   \n",
+       "1  d333b4d3-7efe-413b-8c12-9e05975ccefb   \n",
+       "2  07a8a074-5f66-420b-8cba-5b826178b957   \n",
+       "3  07813635-9487-4b46-9293-3d524e43d645   \n",
+       "4  f9a80b29-367f-4963-8c2d-73706eec249a   \n",
+       "\n",
+       "                                              prompt  answer  context_length  \\\n",
+       "0  There is a pass key hidden inside a lot of irr...     895           16384   \n",
+       "1  There is a pass key hidden inside a lot of irr...     622           16384   \n",
+       "2  There is a pass key hidden inside a lot of irr...     223           16384   \n",
+       "3  There is a pass key hidden inside a lot of irr...     432           16384   \n",
+       "4  There is a pass key hidden inside a lot of irr...     814           16384   \n",
+       "\n",
+       "   num_tokens  depth_percent  \\\n",
+       "0       15878              0   \n",
+       "1       15878              0   \n",
+       "2       15758              0   \n",
+       "3       15758              0   \n",
+       "4       16213              0   \n",
+       "\n",
+       "                                     generation_text  \\\n",
+       "0  100.<|begin_of_text|>There is a pass key hidde...   \n",
+       "1  100.<|begin_of_text|>There is a pass key hidde...   \n",
+       "2  100.<|begin_of_text|>There is a pass key hidde...   \n",
+       "3  100.<|begin_of_text|>There is a pass key hidde...   \n",
+       "4  100.<|begin_of_text|>There is a pass key hidde...   \n",
+       "\n",
+       "                                      generation_ids  \n",
+       "0  [1041, 13, 128000, 3947, 374, 264, 1522, 1401,...  \n",
+       "1  [1041, 13, 128000, 3947, 374, 264, 1522, 1401,...  \n",
+       "2  [1041, 13, 128000, 3947, 374, 264, 1522, 1401,...  \n",
+       "3  [1041, 13, 128000, 3947, 374, 264, 1522, 1401,...  \n",
+       "4  [1041, 13, 128000, 3947, 374, 264, 1522, 1401,...  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "depth_percent\n",
+       "0     34\n",
+       "5     34\n",
+       "90    34\n",
+       "85    34\n",
+       "80    34\n",
+       "75    34\n",
+       "70    34\n",
+       "65    34\n",
+       "60    34\n",
+       "50    34\n",
+       "45    34\n",
+       "40    34\n",
+       "35    34\n",
+       "30    34\n",
+       "25    34\n",
+       "20    34\n",
+       "15    34\n",
+       "10    34\n",
+       "95    34\n",
+       "55    32\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df['depth_percent'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "NEEDLE_TEXT = \"answer\"\n",
+    "DEPTH_TEXT = \"depth_percent\" # depth_percent\n",
+    "\n",
+    "df[\"match\"] = df.apply(lambda x: int(str(x[NEEDLE_TEXT]) in x[\"generation_text\"]), axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_result = df[[DEPTH_TEXT, \"context_length\", \"match\"]].groupby(by=[DEPTH_TEXT, \"context_length\"]).mean().unstack(level=\"context_length\")\n",
+    "df_result.columns = df_result.columns.droplevel(level=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>context_length</th>\n",
+       "      <th>16384</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>depth_percent</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>55</th>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60</th>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>65</th>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>70</th>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75</th>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>80</th>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>85</th>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90</th>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>95</th>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "context_length  16384\n",
+       "depth_percent        \n",
+       "0                 0.0\n",
+       "5                 0.0\n",
+       "10                0.0\n",
+       "15                0.0\n",
+       "20                0.0\n",
+       "25                0.0\n",
+       "30                0.0\n",
+       "35                0.0\n",
+       "40                0.0\n",
+       "45                0.0\n",
+       "50                0.0\n",
+       "55                1.0\n",
+       "60                1.0\n",
+       "65                1.0\n",
+       "70                1.0\n",
+       "75                1.0\n",
+       "80                1.0\n",
+       "85                1.0\n",
+       "90                1.0\n",
+       "95                1.0"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>prompt</th>\n",
+       "      <th>answer</th>\n",
+       "      <th>context_length</th>\n",
+       "      <th>num_tokens</th>\n",
+       "      <th>depth_percent</th>\n",
+       "      <th>generation_text</th>\n",
+       "      <th>generation_ids</th>\n",
+       "      <th>match</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1346ec01-6d07-4b7d-b60c-1980bc3fddfe</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>4734</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16196</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>5366a65e-0be7-4940-a51d-608eaba31072</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>4477</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16196</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>60208b31-69d9-4d9c-8fd2-47167156873a</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>1459</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15980</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4001a28e-a6a5-4952-b7af-c78a43d0089c</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>1523</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15980</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>e9ed6656-9bfa-46e9-a115-0902489a5c5a</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>3028</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15881</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234567890. \\n\\nWhat is the pass key? The pass...</td>\n",
+       "      <td>[4513, 10961, 16474, 15, 13, 4815, 3923, 374, ...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>e97fcf31-22c8-4a31-94a0-ab330f882fc2</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>3070</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15881</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234567890. \\n\\nWhat is the pass key? The pass...</td>\n",
+       "      <td>[4513, 10961, 16474, 15, 13, 4815, 3923, 374, ...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>4742c9e9-085e-4af1-8e0a-dfc89eaa40c9</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>1376</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15714</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>592d59e0-0743-4f4e-b5ec-39227d444ef5</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>1382</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15714</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>589252c2-3c77-4df1-812e-94a18f292fb4</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>4961</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16003</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>e114455c-5c21-48ac-8bb9-0aafdca0b628</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>4752</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16003</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>7bcf965b-d53b-469d-8484-9df18e3ebf5a</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>3534</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15786</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>a2100f61-b12b-4fb4-9796-ff66c93678fe</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>3595</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15786</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>29184471-d864-4d8a-b16f-72a57d0ee396</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>2549</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15689</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>6491c34e-e4d2-491e-8534-d3b888cbfa4e</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>2497</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15689</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>4b7a3e73-72b0-4782-ae96-022c8ac55280</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>5950</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15809</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>548128c9-fdef-40be-a23c-10d0ec92e42d</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>5945</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15809</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>446aeaec-81a3-495e-ab59-5eebb3e53177</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>5244</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16220</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>098dc850-634f-4768-b5d7-cd668765bb17</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>5036</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16220</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>68012d41-1fb9-484d-b114-a4ce8439f9a8</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>708</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15806</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>87686014-8904-4ecc-be6d-49319474096b</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>813</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15806</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>57b651e9-4024-4c1c-a9b9-8fd459f06eef</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>2994</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15692</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>dfb48570-502e-4101-a053-e159eb2b7303</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>2967</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15692</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>4859c51e-1101-463d-b339-f8b18bda3686</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>1944</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16169</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>a473353d-259e-4e66-899c-86ad63ab02e5</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>1866</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16169</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>4b9fe3d8-b611-4234-a0db-709f58f2634f</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>4420</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15881</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234567890. \\n\\nWhat is the pass key? The pass...</td>\n",
+       "      <td>[4513, 10961, 16474, 15, 13, 4815, 3923, 374, ...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>e33fc75c-61c3-4c6e-9000-344f946de914</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>3999</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15881</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>4caa306f-744e-4360-bb7e-9b3338dbe4bf</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>5740</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15832</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>36361634-3092-4144-b3e5-fd6be551d09e</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>5725</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15832</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>1961ce93-ef74-4403-9ed7-3baf1db756c6</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>671</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16264</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>11bd428c-ad45-47ed-8705-4b0b9428cceb</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>635</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16264</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>2f5a23d6-453c-4204-9b7a-38219fea0c57</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>2414</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16288</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>4c30d44a-4f9c-468d-a1f5-95b4f2ce58a2</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>2147</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16288</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234567890. \\n\\nWhat is the pass key? The pass...</td>\n",
+       "      <td>[4513, 10961, 16474, 15, 13, 4815, 3923, 374, ...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>60741301-e56c-4fa1-8e09-db475d970dae</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>4100</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15689</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>2dcb6e0a-e897-4d2e-a8a1-56b2f809ddcc</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>4087</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15689</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1234. \\n\\nWhat is the pass key? The pass key i...</td>\n",
+       "      <td>[4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                      id  \\\n",
+       "0   1346ec01-6d07-4b7d-b60c-1980bc3fddfe   \n",
+       "1   5366a65e-0be7-4940-a51d-608eaba31072   \n",
+       "2   60208b31-69d9-4d9c-8fd2-47167156873a   \n",
+       "3   4001a28e-a6a5-4952-b7af-c78a43d0089c   \n",
+       "4   e9ed6656-9bfa-46e9-a115-0902489a5c5a   \n",
+       "5   e97fcf31-22c8-4a31-94a0-ab330f882fc2   \n",
+       "6   4742c9e9-085e-4af1-8e0a-dfc89eaa40c9   \n",
+       "7   592d59e0-0743-4f4e-b5ec-39227d444ef5   \n",
+       "8   589252c2-3c77-4df1-812e-94a18f292fb4   \n",
+       "9   e114455c-5c21-48ac-8bb9-0aafdca0b628   \n",
+       "10  7bcf965b-d53b-469d-8484-9df18e3ebf5a   \n",
+       "11  a2100f61-b12b-4fb4-9796-ff66c93678fe   \n",
+       "12  29184471-d864-4d8a-b16f-72a57d0ee396   \n",
+       "13  6491c34e-e4d2-491e-8534-d3b888cbfa4e   \n",
+       "14  4b7a3e73-72b0-4782-ae96-022c8ac55280   \n",
+       "15  548128c9-fdef-40be-a23c-10d0ec92e42d   \n",
+       "16  446aeaec-81a3-495e-ab59-5eebb3e53177   \n",
+       "17  098dc850-634f-4768-b5d7-cd668765bb17   \n",
+       "18  68012d41-1fb9-484d-b114-a4ce8439f9a8   \n",
+       "19  87686014-8904-4ecc-be6d-49319474096b   \n",
+       "20  57b651e9-4024-4c1c-a9b9-8fd459f06eef   \n",
+       "21  dfb48570-502e-4101-a053-e159eb2b7303   \n",
+       "22  4859c51e-1101-463d-b339-f8b18bda3686   \n",
+       "23  a473353d-259e-4e66-899c-86ad63ab02e5   \n",
+       "24  4b9fe3d8-b611-4234-a0db-709f58f2634f   \n",
+       "25  e33fc75c-61c3-4c6e-9000-344f946de914   \n",
+       "26  4caa306f-744e-4360-bb7e-9b3338dbe4bf   \n",
+       "27  36361634-3092-4144-b3e5-fd6be551d09e   \n",
+       "28  1961ce93-ef74-4403-9ed7-3baf1db756c6   \n",
+       "29  11bd428c-ad45-47ed-8705-4b0b9428cceb   \n",
+       "30  2f5a23d6-453c-4204-9b7a-38219fea0c57   \n",
+       "31  4c30d44a-4f9c-468d-a1f5-95b4f2ce58a2   \n",
+       "32  60741301-e56c-4fa1-8e09-db475d970dae   \n",
+       "33  2dcb6e0a-e897-4d2e-a8a1-56b2f809ddcc   \n",
+       "\n",
+       "                                               prompt  answer  context_length  \\\n",
+       "0   There is a pass key hidden inside a lot of irr...    4734           16384   \n",
+       "1   There is a pass key hidden inside a lot of irr...    4477           16384   \n",
+       "2   There is a pass key hidden inside a lot of irr...    1459           16384   \n",
+       "3   There is a pass key hidden inside a lot of irr...    1523           16384   \n",
+       "4   There is a pass key hidden inside a lot of irr...    3028           16384   \n",
+       "5   There is a pass key hidden inside a lot of irr...    3070           16384   \n",
+       "6   There is a pass key hidden inside a lot of irr...    1376           16384   \n",
+       "7   There is a pass key hidden inside a lot of irr...    1382           16384   \n",
+       "8   There is a pass key hidden inside a lot of irr...    4961           16384   \n",
+       "9   There is a pass key hidden inside a lot of irr...    4752           16384   \n",
+       "10  There is a pass key hidden inside a lot of irr...    3534           16384   \n",
+       "11  There is a pass key hidden inside a lot of irr...    3595           16384   \n",
+       "12  There is a pass key hidden inside a lot of irr...    2549           16384   \n",
+       "13  There is a pass key hidden inside a lot of irr...    2497           16384   \n",
+       "14  There is a pass key hidden inside a lot of irr...    5950           16384   \n",
+       "15  There is a pass key hidden inside a lot of irr...    5945           16384   \n",
+       "16  There is a pass key hidden inside a lot of irr...    5244           16384   \n",
+       "17  There is a pass key hidden inside a lot of irr...    5036           16384   \n",
+       "18  There is a pass key hidden inside a lot of irr...     708           16384   \n",
+       "19  There is a pass key hidden inside a lot of irr...     813           16384   \n",
+       "20  There is a pass key hidden inside a lot of irr...    2994           16384   \n",
+       "21  There is a pass key hidden inside a lot of irr...    2967           16384   \n",
+       "22  There is a pass key hidden inside a lot of irr...    1944           16384   \n",
+       "23  There is a pass key hidden inside a lot of irr...    1866           16384   \n",
+       "24  There is a pass key hidden inside a lot of irr...    4420           16384   \n",
+       "25  There is a pass key hidden inside a lot of irr...    3999           16384   \n",
+       "26  There is a pass key hidden inside a lot of irr...    5740           16384   \n",
+       "27  There is a pass key hidden inside a lot of irr...    5725           16384   \n",
+       "28  There is a pass key hidden inside a lot of irr...     671           16384   \n",
+       "29  There is a pass key hidden inside a lot of irr...     635           16384   \n",
+       "30  There is a pass key hidden inside a lot of irr...    2414           16384   \n",
+       "31  There is a pass key hidden inside a lot of irr...    2147           16384   \n",
+       "32  There is a pass key hidden inside a lot of irr...    4100           16384   \n",
+       "33  There is a pass key hidden inside a lot of irr...    4087           16384   \n",
+       "\n",
+       "    num_tokens  depth_percent  \\\n",
+       "0        16196             10   \n",
+       "1        16196             10   \n",
+       "2        15980             10   \n",
+       "3        15980             10   \n",
+       "4        15881             10   \n",
+       "5        15881             10   \n",
+       "6        15714             10   \n",
+       "7        15714             10   \n",
+       "8        16003             10   \n",
+       "9        16003             10   \n",
+       "10       15786             10   \n",
+       "11       15786             10   \n",
+       "12       15689             10   \n",
+       "13       15689             10   \n",
+       "14       15809             10   \n",
+       "15       15809             10   \n",
+       "16       16220             10   \n",
+       "17       16220             10   \n",
+       "18       15806             10   \n",
+       "19       15806             10   \n",
+       "20       15692             10   \n",
+       "21       15692             10   \n",
+       "22       16169             10   \n",
+       "23       16169             10   \n",
+       "24       15881             10   \n",
+       "25       15881             10   \n",
+       "26       15832             10   \n",
+       "27       15832             10   \n",
+       "28       16264             10   \n",
+       "29       16264             10   \n",
+       "30       16288             10   \n",
+       "31       16288             10   \n",
+       "32       15689             10   \n",
+       "33       15689             10   \n",
+       "\n",
+       "                                      generation_text  \\\n",
+       "0   1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "1   1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "2   1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "3   1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "4   1234567890. \\n\\nWhat is the pass key? The pass...   \n",
+       "5   1234567890. \\n\\nWhat is the pass key? The pass...   \n",
+       "6   1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "7   1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "8   1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "9   1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "10  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "11  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "12  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "13  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "14  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "15  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "16  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "17  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "18  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "19  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "20  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "21  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "22  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "23  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "24  1234567890. \\n\\nWhat is the pass key? The pass...   \n",
+       "25  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "26  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "27  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "28  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "29  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "30  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "31  1234567890. \\n\\nWhat is the pass key? The pass...   \n",
+       "32  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "33  1234. \\n\\nWhat is the pass key? The pass key i...   \n",
+       "\n",
+       "                                       generation_ids  match  \n",
+       "0   [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "1   [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "2   [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "3   [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "4   [4513, 10961, 16474, 15, 13, 4815, 3923, 374, ...      0  \n",
+       "5   [4513, 10961, 16474, 15, 13, 4815, 3923, 374, ...      0  \n",
+       "6   [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "7   [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "8   [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "9   [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "10  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "11  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "12  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "13  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "14  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "15  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "16  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "17  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "18  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "19  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "20  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "21  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "22  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "23  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "24  [4513, 10961, 16474, 15, 13, 4815, 3923, 374, ...      0  \n",
+       "25  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "26  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "27  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "28  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "29  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "30  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "31  [4513, 10961, 16474, 15, 13, 4815, 3923, 374, ...      0  \n",
+       "32  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  \n",
+       "33  [4513, 19, 13, 4815, 3923, 374, 279, 1522, 140...      0  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[df['depth_percent'] == 10]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>prompt</th>\n",
+       "      <th>answer</th>\n",
+       "      <th>context_length</th>\n",
+       "      <th>num_tokens</th>\n",
+       "      <th>depth_percent</th>\n",
+       "      <th>generation_text</th>\n",
+       "      <th>generation_ids</th>\n",
+       "      <th>match</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>6a3031a9-3de8-42e5-823d-bdf1cba854bd</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>34505</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15954</td>\n",
+       "      <td>70</td>\n",
+       "      <td>34505. Remember it. 34505 is the pass key.  go...</td>\n",
+       "      <td>[12901, 2304, 13, 20474, 433, 13, 220, 12901, ...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>9556e041-f4f7-483f-8115-6fb1d0419aac</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>34380</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15954</td>\n",
+       "      <td>70</td>\n",
+       "      <td>34380. Remember it. 34380 is the pass key.  go...</td>\n",
+       "      <td>[16522, 1490, 13, 20474, 433, 13, 220, 16522, ...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>8909402c-9939-4c38-bcde-cf0c78bc21ce</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>19581</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16241</td>\n",
+       "      <td>70</td>\n",
+       "      <td>19581. Remember it. 19581 is the pass key.  is...</td>\n",
+       "      <td>[6280, 5932, 13, 20474, 433, 13, 220, 6280, 59...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>752e1601-85e2-4717-b3da-ee3940dfa4b1</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>19443</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16241</td>\n",
+       "      <td>70</td>\n",
+       "      <td>19443. Remember it. 19443 is the pass key.  is...</td>\n",
+       "      <td>[6393, 3391, 13, 20474, 433, 13, 220, 6393, 33...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>f03af9bc-7d30-4b55-9558-188964ce19b5</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>6865</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16264</td>\n",
+       "      <td>70</td>\n",
+       "      <td>6865. Remember it. 6865 is the pass key.  is y...</td>\n",
+       "      <td>[22347, 20, 13, 20474, 433, 13, 220, 22347, 20...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>469d338c-3d5a-4290-b6f3-93cb4caffd41</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>6849</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16264</td>\n",
+       "      <td>70</td>\n",
+       "      <td>6849. Remember it. 6849 is the pass key.  is y...</td>\n",
+       "      <td>[24313, 24, 13, 20474, 433, 13, 220, 24313, 24...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>4e427893-f54c-4a25-ab85-fd5f563c969e</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>8927</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15762</td>\n",
+       "      <td>70</td>\n",
+       "      <td>8927. Remember it. 8927 is the pass key.  The ...</td>\n",
+       "      <td>[24110, 22, 13, 20474, 433, 13, 220, 24110, 22...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>0ab2d341-ec94-4827-a041-cb1d3472dcdd</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>8670</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15762</td>\n",
+       "      <td>70</td>\n",
+       "      <td>8670. Remember it. 8670 is the pass key.  The ...</td>\n",
+       "      <td>[26013, 15, 13, 20474, 433, 13, 220, 26013, 15...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>229aea5b-2ebf-46ad-b91a-c52b82213453</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>23664</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15714</td>\n",
+       "      <td>70</td>\n",
+       "      <td>23664. Remember it. 23664 is the pass key.  Th...</td>\n",
+       "      <td>[14087, 1227, 13, 20474, 433, 13, 220, 14087, ...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>cc876c6f-3ebf-4766-a491-d4b94291f2d7</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>23450</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15714</td>\n",
+       "      <td>70</td>\n",
+       "      <td>23450. Remember it. 23450 is the pass key.  Th...</td>\n",
+       "      <td>[11727, 1135, 13, 20474, 433, 13, 220, 11727, ...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>c825a5bf-fc55-4356-9722-74a1f5d47a33</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>32332</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16145</td>\n",
+       "      <td>70</td>\n",
+       "      <td>32332. Remember it. 32332 is the pass key.  we...</td>\n",
+       "      <td>[15726, 843, 13, 20474, 433, 13, 220, 15726, 8...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>055a3cc0-7e77-481b-ae46-e4f8c6ec23d9</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>32280</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16145</td>\n",
+       "      <td>70</td>\n",
+       "      <td>32280. Remember it. 32280 is the pass key.  we...</td>\n",
+       "      <td>[15805, 1490, 13, 20474, 433, 13, 220, 15805, ...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>4551bb67-15f7-4a03-a436-15fe998e4a8b</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>25986</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16047</td>\n",
+       "      <td>70</td>\n",
+       "      <td>25986. Remember it. 25986 is the pass key.. Th...</td>\n",
+       "      <td>[15537, 4218, 13, 20474, 433, 13, 220, 15537, ...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>c24607f5-302d-4ae2-9d40-61032520eb7f</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>26017</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16047</td>\n",
+       "      <td>70</td>\n",
+       "      <td>26017. Remember it. 26017 is the pass key.. Th...</td>\n",
+       "      <td>[11387, 1114, 13, 20474, 433, 13, 220, 11387, ...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>3f7a8a9e-6eee-46e6-90e1-7b1b3458ecca</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>15122</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16024</td>\n",
+       "      <td>70</td>\n",
+       "      <td>15122. Remember it. 15122 is the pass key.  ag...</td>\n",
+       "      <td>[9690, 1313, 13, 20474, 433, 13, 220, 9690, 13...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>c20124a6-fc0c-47df-b0f4-ba3df2e44617</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>15319</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16024</td>\n",
+       "      <td>70</td>\n",
+       "      <td>15319. Remember it. 15319 is the pass key.  ag...</td>\n",
+       "      <td>[9800, 777, 13, 20474, 433, 13, 220, 9800, 777...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>ee94c236-f0bc-4043-8d61-3f82be1b9871</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>10711</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16217</td>\n",
+       "      <td>70</td>\n",
+       "      <td>10711. Remember it. 10711 is the pass key.  Th...</td>\n",
+       "      <td>[7699, 806, 13, 20474, 433, 13, 220, 7699, 806...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>dcee6558-ddf4-4039-82bb-53743c733658</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>10897</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16217</td>\n",
+       "      <td>70</td>\n",
+       "      <td>10897. Remember it. 10897 is the pass key.  Th...</td>\n",
+       "      <td>[6640, 3534, 13, 20474, 433, 13, 220, 6640, 35...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>b9c43f7f-930a-489d-ae4f-d72dff01e4d6</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>21691</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16244</td>\n",
+       "      <td>70</td>\n",
+       "      <td>21691. Remember it. 21691 is the pass key.  is...</td>\n",
+       "      <td>[12463, 5925, 13, 20474, 433, 13, 220, 12463, ...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>1417a583-608c-4426-8564-a93b67746bbc</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>21756</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16244</td>\n",
+       "      <td>70</td>\n",
+       "      <td>21756. Remember it. 21756 is the pass key.  is...</td>\n",
+       "      <td>[13460, 3487, 13, 20474, 433, 13, 220, 13460, ...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>b2e3121e-970d-4c8e-bbfc-9243e29bfdb9</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>36660</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16267</td>\n",
+       "      <td>70</td>\n",
+       "      <td>36660. Remember it. 36660 is the pass key.  Th...</td>\n",
+       "      <td>[18044, 1399, 13, 20474, 433, 13, 220, 18044, ...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>dd36f69d-79ad-4390-9c6d-cafd33f25868</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>36595</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16267</td>\n",
+       "      <td>70</td>\n",
+       "      <td>36595. Remember it. 36595 is the pass key.  Th...</td>\n",
+       "      <td>[12676, 2721, 13, 20474, 433, 13, 220, 12676, ...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>bf623b96-6451-4894-a839-10b74322fbdf</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>4628</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15929</td>\n",
+       "      <td>70</td>\n",
+       "      <td>4628. Remember it. 4628 is the pass key.  The ...</td>\n",
+       "      <td>[20911, 23, 13, 20474, 433, 13, 220, 20911, 23...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>523e68a5-4791-4fad-8d1a-9f5d577e9d39</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>4561</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15929</td>\n",
+       "      <td>70</td>\n",
+       "      <td>4561. Remember it. 4561 is the pass key.  The ...</td>\n",
+       "      <td>[10961, 16, 13, 20474, 433, 13, 220, 10961, 16...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>a9415983-5347-4c0f-9f4a-fb48933b4ca9</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>17125</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16361</td>\n",
+       "      <td>70</td>\n",
+       "      <td>17125. Remember it. 17125 is the pass key.. Th...</td>\n",
+       "      <td>[11123, 914, 13, 20474, 433, 13, 220, 11123, 9...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>129243a2-34e6-4c90-ad6b-d2e2b3f884c6</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>17052</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>16361</td>\n",
+       "      <td>70</td>\n",
+       "      <td>17052. Remember it. 17052 is the pass key.. Th...</td>\n",
+       "      <td>[8258, 4103, 13, 20474, 433, 13, 220, 8258, 41...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>80e6524f-5ab7-47fc-9ff2-7d94153844c0</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>28015</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15689</td>\n",
+       "      <td>70</td>\n",
+       "      <td>28015. Remember it. 28015 is the pass key.  Th...</td>\n",
+       "      <td>[11209, 868, 13, 20474, 433, 13, 220, 11209, 8...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>6a3a9cd7-b63b-437b-bf82-95624b0cc2dd</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>28021</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15689</td>\n",
+       "      <td>70</td>\n",
+       "      <td>28021. Remember it. 28021 is the pass key.  Th...</td>\n",
+       "      <td>[11209, 1691, 13, 20474, 433, 13, 220, 11209, ...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>3ea6d444-399b-4dbe-98fb-9576d1d277be</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>12931</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15810</td>\n",
+       "      <td>70</td>\n",
+       "      <td>12931. Remember it. 12931 is the pass key.. Th...</td>\n",
+       "      <td>[9748, 2148, 13, 20474, 433, 13, 220, 9748, 21...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>b88e7554-6dbc-4cb2-b417-24be32d9fd60</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>13014</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15810</td>\n",
+       "      <td>70</td>\n",
+       "      <td>13014. Remember it. 13014 is the pass key.. Th...</td>\n",
+       "      <td>[5894, 975, 13, 20474, 433, 13, 220, 5894, 975...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>76168915-f778-4e56-a0f0-7072b32ef5b3</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>2445</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15856</td>\n",
+       "      <td>70</td>\n",
+       "      <td>2445. Remember it. 2445 is the pass key.  sky ...</td>\n",
+       "      <td>[13719, 20, 13, 20474, 433, 13, 220, 13719, 20...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>960ec6d3-6039-41b4-911e-3263da0b14ac</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>2293</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15856</td>\n",
+       "      <td>70</td>\n",
+       "      <td>2293. Remember it. 2293 is the pass key.  sky ...</td>\n",
+       "      <td>[14378, 18, 13, 20474, 433, 13, 220, 14378, 18...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>e1e673fa-65c4-4b08-addb-c052baeb203d</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>30074</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15903</td>\n",
+       "      <td>70</td>\n",
+       "      <td>30074. Remember it. 30074 is the pass key.. Th...</td>\n",
+       "      <td>[3101, 5728, 13, 20474, 433, 13, 220, 3101, 57...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>9844cecd-9d64-42c4-a3b0-e29c2525ec50</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>29856</td>\n",
+       "      <td>16384</td>\n",
+       "      <td>15903</td>\n",
+       "      <td>70</td>\n",
+       "      <td>29856. Remember it. 29856 is the pass key.. Th...</td>\n",
+       "      <td>[17690, 3487, 13, 20474, 433, 13, 220, 17690, ...</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                      id  \\\n",
+       "0   6a3031a9-3de8-42e5-823d-bdf1cba854bd   \n",
+       "1   9556e041-f4f7-483f-8115-6fb1d0419aac   \n",
+       "2   8909402c-9939-4c38-bcde-cf0c78bc21ce   \n",
+       "3   752e1601-85e2-4717-b3da-ee3940dfa4b1   \n",
+       "4   f03af9bc-7d30-4b55-9558-188964ce19b5   \n",
+       "5   469d338c-3d5a-4290-b6f3-93cb4caffd41   \n",
+       "6   4e427893-f54c-4a25-ab85-fd5f563c969e   \n",
+       "7   0ab2d341-ec94-4827-a041-cb1d3472dcdd   \n",
+       "8   229aea5b-2ebf-46ad-b91a-c52b82213453   \n",
+       "9   cc876c6f-3ebf-4766-a491-d4b94291f2d7   \n",
+       "10  c825a5bf-fc55-4356-9722-74a1f5d47a33   \n",
+       "11  055a3cc0-7e77-481b-ae46-e4f8c6ec23d9   \n",
+       "12  4551bb67-15f7-4a03-a436-15fe998e4a8b   \n",
+       "13  c24607f5-302d-4ae2-9d40-61032520eb7f   \n",
+       "14  3f7a8a9e-6eee-46e6-90e1-7b1b3458ecca   \n",
+       "15  c20124a6-fc0c-47df-b0f4-ba3df2e44617   \n",
+       "16  ee94c236-f0bc-4043-8d61-3f82be1b9871   \n",
+       "17  dcee6558-ddf4-4039-82bb-53743c733658   \n",
+       "18  b9c43f7f-930a-489d-ae4f-d72dff01e4d6   \n",
+       "19  1417a583-608c-4426-8564-a93b67746bbc   \n",
+       "20  b2e3121e-970d-4c8e-bbfc-9243e29bfdb9   \n",
+       "21  dd36f69d-79ad-4390-9c6d-cafd33f25868   \n",
+       "22  bf623b96-6451-4894-a839-10b74322fbdf   \n",
+       "23  523e68a5-4791-4fad-8d1a-9f5d577e9d39   \n",
+       "24  a9415983-5347-4c0f-9f4a-fb48933b4ca9   \n",
+       "25  129243a2-34e6-4c90-ad6b-d2e2b3f884c6   \n",
+       "26  80e6524f-5ab7-47fc-9ff2-7d94153844c0   \n",
+       "27  6a3a9cd7-b63b-437b-bf82-95624b0cc2dd   \n",
+       "28  3ea6d444-399b-4dbe-98fb-9576d1d277be   \n",
+       "29  b88e7554-6dbc-4cb2-b417-24be32d9fd60   \n",
+       "30  76168915-f778-4e56-a0f0-7072b32ef5b3   \n",
+       "31  960ec6d3-6039-41b4-911e-3263da0b14ac   \n",
+       "32  e1e673fa-65c4-4b08-addb-c052baeb203d   \n",
+       "33  9844cecd-9d64-42c4-a3b0-e29c2525ec50   \n",
+       "\n",
+       "                                               prompt  answer  context_length  \\\n",
+       "0   There is a pass key hidden inside a lot of irr...   34505           16384   \n",
+       "1   There is a pass key hidden inside a lot of irr...   34380           16384   \n",
+       "2   There is a pass key hidden inside a lot of irr...   19581           16384   \n",
+       "3   There is a pass key hidden inside a lot of irr...   19443           16384   \n",
+       "4   There is a pass key hidden inside a lot of irr...    6865           16384   \n",
+       "5   There is a pass key hidden inside a lot of irr...    6849           16384   \n",
+       "6   There is a pass key hidden inside a lot of irr...    8927           16384   \n",
+       "7   There is a pass key hidden inside a lot of irr...    8670           16384   \n",
+       "8   There is a pass key hidden inside a lot of irr...   23664           16384   \n",
+       "9   There is a pass key hidden inside a lot of irr...   23450           16384   \n",
+       "10  There is a pass key hidden inside a lot of irr...   32332           16384   \n",
+       "11  There is a pass key hidden inside a lot of irr...   32280           16384   \n",
+       "12  There is a pass key hidden inside a lot of irr...   25986           16384   \n",
+       "13  There is a pass key hidden inside a lot of irr...   26017           16384   \n",
+       "14  There is a pass key hidden inside a lot of irr...   15122           16384   \n",
+       "15  There is a pass key hidden inside a lot of irr...   15319           16384   \n",
+       "16  There is a pass key hidden inside a lot of irr...   10711           16384   \n",
+       "17  There is a pass key hidden inside a lot of irr...   10897           16384   \n",
+       "18  There is a pass key hidden inside a lot of irr...   21691           16384   \n",
+       "19  There is a pass key hidden inside a lot of irr...   21756           16384   \n",
+       "20  There is a pass key hidden inside a lot of irr...   36660           16384   \n",
+       "21  There is a pass key hidden inside a lot of irr...   36595           16384   \n",
+       "22  There is a pass key hidden inside a lot of irr...    4628           16384   \n",
+       "23  There is a pass key hidden inside a lot of irr...    4561           16384   \n",
+       "24  There is a pass key hidden inside a lot of irr...   17125           16384   \n",
+       "25  There is a pass key hidden inside a lot of irr...   17052           16384   \n",
+       "26  There is a pass key hidden inside a lot of irr...   28015           16384   \n",
+       "27  There is a pass key hidden inside a lot of irr...   28021           16384   \n",
+       "28  There is a pass key hidden inside a lot of irr...   12931           16384   \n",
+       "29  There is a pass key hidden inside a lot of irr...   13014           16384   \n",
+       "30  There is a pass key hidden inside a lot of irr...    2445           16384   \n",
+       "31  There is a pass key hidden inside a lot of irr...    2293           16384   \n",
+       "32  There is a pass key hidden inside a lot of irr...   30074           16384   \n",
+       "33  There is a pass key hidden inside a lot of irr...   29856           16384   \n",
+       "\n",
+       "    num_tokens  depth_percent  \\\n",
+       "0        15954             70   \n",
+       "1        15954             70   \n",
+       "2        16241             70   \n",
+       "3        16241             70   \n",
+       "4        16264             70   \n",
+       "5        16264             70   \n",
+       "6        15762             70   \n",
+       "7        15762             70   \n",
+       "8        15714             70   \n",
+       "9        15714             70   \n",
+       "10       16145             70   \n",
+       "11       16145             70   \n",
+       "12       16047             70   \n",
+       "13       16047             70   \n",
+       "14       16024             70   \n",
+       "15       16024             70   \n",
+       "16       16217             70   \n",
+       "17       16217             70   \n",
+       "18       16244             70   \n",
+       "19       16244             70   \n",
+       "20       16267             70   \n",
+       "21       16267             70   \n",
+       "22       15929             70   \n",
+       "23       15929             70   \n",
+       "24       16361             70   \n",
+       "25       16361             70   \n",
+       "26       15689             70   \n",
+       "27       15689             70   \n",
+       "28       15810             70   \n",
+       "29       15810             70   \n",
+       "30       15856             70   \n",
+       "31       15856             70   \n",
+       "32       15903             70   \n",
+       "33       15903             70   \n",
+       "\n",
+       "                                      generation_text  \\\n",
+       "0   34505. Remember it. 34505 is the pass key.  go...   \n",
+       "1   34380. Remember it. 34380 is the pass key.  go...   \n",
+       "2   19581. Remember it. 19581 is the pass key.  is...   \n",
+       "3   19443. Remember it. 19443 is the pass key.  is...   \n",
+       "4   6865. Remember it. 6865 is the pass key.  is y...   \n",
+       "5   6849. Remember it. 6849 is the pass key.  is y...   \n",
+       "6   8927. Remember it. 8927 is the pass key.  The ...   \n",
+       "7   8670. Remember it. 8670 is the pass key.  The ...   \n",
+       "8   23664. Remember it. 23664 is the pass key.  Th...   \n",
+       "9   23450. Remember it. 23450 is the pass key.  Th...   \n",
+       "10  32332. Remember it. 32332 is the pass key.  we...   \n",
+       "11  32280. Remember it. 32280 is the pass key.  we...   \n",
+       "12  25986. Remember it. 25986 is the pass key.. Th...   \n",
+       "13  26017. Remember it. 26017 is the pass key.. Th...   \n",
+       "14  15122. Remember it. 15122 is the pass key.  ag...   \n",
+       "15  15319. Remember it. 15319 is the pass key.  ag...   \n",
+       "16  10711. Remember it. 10711 is the pass key.  Th...   \n",
+       "17  10897. Remember it. 10897 is the pass key.  Th...   \n",
+       "18  21691. Remember it. 21691 is the pass key.  is...   \n",
+       "19  21756. Remember it. 21756 is the pass key.  is...   \n",
+       "20  36660. Remember it. 36660 is the pass key.  Th...   \n",
+       "21  36595. Remember it. 36595 is the pass key.  Th...   \n",
+       "22  4628. Remember it. 4628 is the pass key.  The ...   \n",
+       "23  4561. Remember it. 4561 is the pass key.  The ...   \n",
+       "24  17125. Remember it. 17125 is the pass key.. Th...   \n",
+       "25  17052. Remember it. 17052 is the pass key.. Th...   \n",
+       "26  28015. Remember it. 28015 is the pass key.  Th...   \n",
+       "27  28021. Remember it. 28021 is the pass key.  Th...   \n",
+       "28  12931. Remember it. 12931 is the pass key.. Th...   \n",
+       "29  13014. Remember it. 13014 is the pass key.. Th...   \n",
+       "30  2445. Remember it. 2445 is the pass key.  sky ...   \n",
+       "31  2293. Remember it. 2293 is the pass key.  sky ...   \n",
+       "32  30074. Remember it. 30074 is the pass key.. Th...   \n",
+       "33  29856. Remember it. 29856 is the pass key.. Th...   \n",
+       "\n",
+       "                                       generation_ids  match  \n",
+       "0   [12901, 2304, 13, 20474, 433, 13, 220, 12901, ...      1  \n",
+       "1   [16522, 1490, 13, 20474, 433, 13, 220, 16522, ...      1  \n",
+       "2   [6280, 5932, 13, 20474, 433, 13, 220, 6280, 59...      1  \n",
+       "3   [6393, 3391, 13, 20474, 433, 13, 220, 6393, 33...      1  \n",
+       "4   [22347, 20, 13, 20474, 433, 13, 220, 22347, 20...      1  \n",
+       "5   [24313, 24, 13, 20474, 433, 13, 220, 24313, 24...      1  \n",
+       "6   [24110, 22, 13, 20474, 433, 13, 220, 24110, 22...      1  \n",
+       "7   [26013, 15, 13, 20474, 433, 13, 220, 26013, 15...      1  \n",
+       "8   [14087, 1227, 13, 20474, 433, 13, 220, 14087, ...      1  \n",
+       "9   [11727, 1135, 13, 20474, 433, 13, 220, 11727, ...      1  \n",
+       "10  [15726, 843, 13, 20474, 433, 13, 220, 15726, 8...      1  \n",
+       "11  [15805, 1490, 13, 20474, 433, 13, 220, 15805, ...      1  \n",
+       "12  [15537, 4218, 13, 20474, 433, 13, 220, 15537, ...      1  \n",
+       "13  [11387, 1114, 13, 20474, 433, 13, 220, 11387, ...      1  \n",
+       "14  [9690, 1313, 13, 20474, 433, 13, 220, 9690, 13...      1  \n",
+       "15  [9800, 777, 13, 20474, 433, 13, 220, 9800, 777...      1  \n",
+       "16  [7699, 806, 13, 20474, 433, 13, 220, 7699, 806...      1  \n",
+       "17  [6640, 3534, 13, 20474, 433, 13, 220, 6640, 35...      1  \n",
+       "18  [12463, 5925, 13, 20474, 433, 13, 220, 12463, ...      1  \n",
+       "19  [13460, 3487, 13, 20474, 433, 13, 220, 13460, ...      1  \n",
+       "20  [18044, 1399, 13, 20474, 433, 13, 220, 18044, ...      1  \n",
+       "21  [12676, 2721, 13, 20474, 433, 13, 220, 12676, ...      1  \n",
+       "22  [20911, 23, 13, 20474, 433, 13, 220, 20911, 23...      1  \n",
+       "23  [10961, 16, 13, 20474, 433, 13, 220, 10961, 16...      1  \n",
+       "24  [11123, 914, 13, 20474, 433, 13, 220, 11123, 9...      1  \n",
+       "25  [8258, 4103, 13, 20474, 433, 13, 220, 8258, 41...      1  \n",
+       "26  [11209, 868, 13, 20474, 433, 13, 220, 11209, 8...      1  \n",
+       "27  [11209, 1691, 13, 20474, 433, 13, 220, 11209, ...      1  \n",
+       "28  [9748, 2148, 13, 20474, 433, 13, 220, 9748, 21...      1  \n",
+       "29  [5894, 975, 13, 20474, 433, 13, 220, 5894, 975...      1  \n",
+       "30  [13719, 20, 13, 20474, 433, 13, 220, 13719, 20...      1  \n",
+       "31  [14378, 18, 13, 20474, 433, 13, 220, 14378, 18...      1  \n",
+       "32  [3101, 5728, 13, 20474, 433, 13, 220, 3101, 57...      1  \n",
+       "33  [17690, 3487, 13, 20474, 433, 13, 220, 17690, ...      1  "
+      ]
+     },
+     "execution_count": 103,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[df['depth_percent'] == 70]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1234. \\n\\nWhat is the secret key? The secret key is 1234. \\n\\nWhat'"
+      ]
+     },
+     "execution_count": 104,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[df['depth_percent'] == 50].iloc[4][\"generation_text\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(' The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The. \\n\\nWhat is the pass key? The pass key is ',\n",
+       " '1234. \\n\\nWhat is the secret key? The secret key is 1234. \\n\\nWhat')"
+      ]
+     },
+     "execution_count": 82,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokenizer.decode(tokenizer.encode(df[df['depth_percent'] == 50].iloc[4][\"prompt\"])[8192:]), df[df['depth_percent'] == 50].iloc[4][\"generation_text\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1234. \\n\\nWhat is the secret key? The secret key is 1234. \\n\\nWhat'"
+      ]
+     },
+     "execution_count": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "' back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The pass key is 25262. Remember it. 25262 is the pass key.. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back. \\n\\nWhat is the pass key? The pass key is '"
+      ]
+     },
+     "execution_count": 84,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokenizer.decode(tokenizer.encode(df[df['depth_percent'] == 55].iloc[4][\"prompt\"])[8192:])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'25262. Remember it. 25262 is the pass key.. The sky is blue. The'"
+      ]
+     },
+     "execution_count": 85,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[df['depth_percent'] == 55].iloc[4][\"generation_text\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_with_depth_55 = df[df['depth_percent'] == 55].sort_values('num_tokens')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "id                              4c0802f8-afbd-4493-828e-478752ab2c6c\n",
+       "prompt             There is a pass key hidden inside a lot of irr...\n",
+       "answer                                                         23563\n",
+       "context_length                                                 16384\n",
+       "num_tokens                                                     15689\n",
+       "depth_percent                                                     55\n",
+       "generation_text    23563. Remember it. 23563 is the pass key.  go...\n",
+       "generation_ids     [12422, 5495, 13, 20474, 433, 13, 220, 12422, ...\n",
+       "match                                                              1\n",
+       "Name: 19, dtype: object"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_with_depth_55.iloc[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_dataset\n",
+    "from transformers import AutoTokenizer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "eval_data = load_dataset(\"nanotron/llama3-16k-passkey-retrieval-eval\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "eval_sample = eval_data.filter(lambda x: x['id'] == \"b9dc4ee9-48f8-4726-9a67-37493f8d8389\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on.  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The pass key is 10463. Remember it. 10463 is the pass key.. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. \\n\\nWhat is the pass key? The pass key is '"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "eval_sample[\"train\"][0][\"prompt\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "tokenizer = AutoTokenizer.from_pretrained(\"/fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "prompt_ids = tokenizer.encode(df_with_depth_55.iloc[0][\"prompt\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[128000, 12422, 5495]"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokenizer.encode(str(df_with_depth_55.iloc[0][\"answer\"]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def find_target_indices(arr, num1, num2):\n",
+    "  index1 = -1\n",
+    "  index2 = -1\n",
+    "  \n",
+    "  for i, n in enumerate(arr):\n",
+    "    if n == num1:\n",
+    "      index1 = i\n",
+    "    elif n == num2:\n",
+    "      index2 = i\n",
+    "      \n",
+    "  return index1, index2\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(8633, 8634)"
+      ]
+     },
+     "execution_count": 61,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "find_target_indices(prompt_ids, 12422, 5495)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/infinite-context-length/data/exp34/tokenization_logs/tokenization/executor.pik b/examples/infinite-context-length/data/exp34/tokenization_logs/tokenization/executor.pik
new file mode 100644
index 0000000000000000000000000000000000000000..60d9141aeb7b49a50de36d3d139343df312d9521
GIT binary patch
literal 2674
zcmb_eO^*~s7#^5ic9~_r05^OItDwlCXMiQd5Mu)FvckfMyGt}iQ>p2$nQo@Ls_Cj;
zb`_%@(1nzGpwxpVM5A|)#(&_+yYXQ30w*{A0eq^vrw2h34@`Eur{1^f{e0?q=ly}t
zI<-pn(YrjVs7k~NtFu++rb;Ar8Ky~O^b<?=eJO}p7;rXMXw7YN<OB1rc}@?<h045z
z)w6v=J$XH0)MJUP`)Q{W@J^e$%;;S&=c}_=&BD24YBAf_w>&5jlSBl4o2d#ySuf;+
zOPRimWPsBMmJe*)x&8UHGrc%>dUkH{)bz%kZ@-v+z?;!E6-12WR{T*tvK&N+>mh4{
zN+=qdg^J$9?Q<Yvl$-gyV3mrl;*6PpZ=<MSHKMC#{(f&cNs^RvSS2eo2`ER({i6dZ
z50ueWPq;>pbVAXhA<4|c&k!f5Mpv4JO}f_8!4*{H60WcuE3{I1#A7Rc2WiXShP=iv
zGL-~wme*|HDpb~H`+yXZ8)ng@Ej<{b2Fjejj}Ka!h)%+!G&l9IVylXD*_zQ?AdX@L
zz9sN-$>zW_dWd>7RxCkXy&w$h#6Gbgp`ad7YcYcxU4vU+c*}Naed+`Ku0Dd47T{p?
z-ZOaRpny@<rfH~1&lz&5eQ52B5r&}F$TgbSdL!hC-rk5QY**AY^^ko7V@4n4lnX$e
zH^PucbjCS$vg^cDO62Gywqk6BhE5w`SLhQg>ha<*5wQvcm%zOqlyPXAIH(ee?nqs0
zQRVtX25&QS@op70J@_vfD$!+J*0UFOqG*$|!c8N_)v{G(vL2$*#qs=>`P(h5%{PGc
z@+%8-&2w*9WdHuv$AA9t>GW$!V9W3C^rwp5yB8|{9{leuG3W0qq3S<b!qng2-*CX6
z_MgI;rx!N)2k}0H|7S{d2C2jTkpeC?($Ao&r^*GfSCEK=#8ml4@39?lvN|`=f9hPY
zC3j|==g*+3Bo<N;fXW5bM1n4DWkTkbjUIjBI^&*bTl`&r5o?jEI8~%ALa+($O<T&C
zxpn)1Hlkfd0**^<?-~HNtzZ2>0DrRpz}fsPv{xH#x!Q>R)NLSuE6i20Q38Xl(kKp@
zYy=!IKye*ca2tmcGTu>s!<ufe)p+JaqnElz`iLQ!zSKDReZB$Md}I+j844E{{+dX-
zmLR+Uy?fIqy3>$uVnLMI&)B#$Uj|41Cu*I3>B+;TFC!V1bcG>sq?J+U<z5LMgO?H^
zpos06pHN5%nk(+)O+6(2wA~JwS@+LgoH(op63Vf8Cr_hzt!@`0s*^ZyyV#>A2<b4+
zP$0m|#ltpv@X|~3Cr=nZ);kGl1?tf)mLu$#8vTd1Jc)aZA;Rny|D9VCKmGjrlK1N2
zTYnw8_e*p8WudD9cg?NIFZccN^(S|yZ*Khd{g3YX?|!YMy5>_!(txX(<Cctv?N`<T
zG8Zbi`#Xxt@{HMwl-KoS8fUE70tC7_S2XnwjE=lolEf^@`eB-Bi|LV2WFxbWk^Kd#
zs3jsWY)AGWl1V_V1<1x^H;9P~!VZ~Yo>>P|Wn%^0q=zi_Fp>+t-x||I1=b?&i7#RV
z;ka>%TZLyHlRaxE(pbczEJ$cbr)3s4>j67WjUGOJ^wd%Nhp$&eD`NtqFFi&?ImrDO
z#^zNaF@v~BBFtw!!uX2KGqT`m>S0_}k3weYWX0+-DzX!R#UK<3`B?Fl*f=r5ntB_N
zIepWllhON_?Fmg1x>hjyy{g{bmxVOtAbZq}h9L_vbf$o#4%$!pn_wMNyrQS@Q-Gjb
zxmU*BHPWVmJv5$!9Hei5jU)=9EoDsO3A>uI6sn*D7$N7OrE~L_mlltq%X(`B6Zv%2
o)zcR)^dzYS1e<y?`}LLqq-4y;&3XTU!A9RTLN1ap>uIb0H#SiYrT_o{

literal 0
HcmV?d00001

diff --git a/examples/infinite-context-length/data/exp34/tokenization_logs/tokenization/launch_script.slurm b/examples/infinite-context-length/data/exp34/tokenization_logs/tokenization/launch_script.slurm
new file mode 100644
index 00000000..9844d2a6
--- /dev/null
+++ b/examples/infinite-context-length/data/exp34/tokenization_logs/tokenization/launch_script.slurm
@@ -0,0 +1,16 @@
+#!/bin/bash
+#SBATCH --cpus-per-task=1
+#SBATCH --mem-per-cpu=2G
+#SBATCH --partition=hopper-cpu
+#SBATCH --job-name=nanotron_llama3-16k-passkey-retrieval-finetuning-meta-llama_Meta-Llama-3-8B-tok1
+#SBATCH --time=20:00:00
+#SBATCH --output=/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/tokenization_logs/tokenization/slurm_logs/%A_%a.out
+#SBATCH --error=/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/tokenization_logs/tokenization/slurm_logs/%A_%a.out
+#SBATCH --array=0-999
+#SBATCH --requeue
+#SBATCH --qos=normal
+echo "Starting data processing job nanotron_llama3-16k-passkey-retrieval-finetuning-meta-llama_Meta-Llama-3-8B-tok1"
+
+set -xe
+export PYTHONUNBUFFERED=TRUE
+srun -l launch_pickled_pipeline /fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/tokenization_logs/tokenization/executor.pik
diff --git a/examples/infinite-context-length/data/exp34/tokenize_finetune_data_to_nanotron_format.ipynb b/examples/infinite-context-length/data/exp34/tokenize_finetune_data_to_nanotron_format.ipynb
new file mode 100644
index 00000000..ca3bb308
--- /dev/null
+++ b/examples/infinite-context-length/data/exp34/tokenize_finetune_data_to_nanotron_format.ipynb
@@ -0,0 +1,20 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/infinite-context-length/data/exp34/tokenize_finetunine_data_to_s3.py b/examples/infinite-context-length/data/exp34/tokenize_finetunine_data_to_s3.py
new file mode 100644
index 00000000..ac80b5ec
--- /dev/null
+++ b/examples/infinite-context-length/data/exp34/tokenize_finetunine_data_to_s3.py
@@ -0,0 +1,106 @@
+import argparse
+import os.path
+
+from datatrove.executor import SlurmPipelineExecutor
+from datatrove.pipeline.readers import HuggingFaceDatasetReader
+from datatrove.pipeline.tokens.merger import DocumentTokenizerMerger
+from datatrove.pipeline.tokens.tokenizer import DocumentTokenizer
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--dataset", type=str, help="huggingface dataset name. Example: stas/openwebtext-10k")
+parser.add_argument(
+    "--output_path", type=str, help="Where to save individual tokenization files and the final merged " "files."
+)
+parser.add_argument("-l", "--logs", type=str, help="path to logs folder", default="tokenization_logs")
+parser.add_argument("-t", "--tokenizer", type=str, help="tokenizer to use", default="gpt2")
+parser.add_argument(
+    "--local",
+    type=str,
+    help="local working directory. You won't need it if output_path is a local "
+    "path. /scratch/datatrove/tokenize/ by default.",
+    default="/scratch/datatrove/tokenize/",
+)
+parser.add_argument(
+    "-o",
+    "--output_name",
+    type=str,
+    help="filename for the final output files. By default this will " "be `dataset-tokenizer`",
+    default=None,
+)
+parser.add_argument("-s", "--split", type=str, help="dataset split. `train` by default", default="train")
+parser.add_argument(
+    "-tk",
+    "--text_key",
+    type=str,
+    help="Column that actually contains the text to be " "tokenized. `text` by default.",
+    default="text",
+)
+parser.add_argument(
+    "-p", "--partition", type=str, help="Slurm partition to use. `hopper-prod` by default.", default="hopper-prod"
+)
+parser.add_argument("-ts", "--tasks", type=int, help="Number of tasks to run. 1000 by default", default=1000)
+
+# this pipeline will pull the openwebtext dataset from the HF hub, locally tokenize it in parallel
+# and then merge-shuffle everything into a final tokenized binary file
+# you could also run this on slurm by using a SlurmPipelineExecutor
+
+args = parser.parse_args()
+DATASET_NAME = args.output_name  # name for the final dataset files
+if not DATASET_NAME:
+    DATASET_NAME = f"{args.dataset}-{args.tokenizer}".replace("/", "_")
+
+LOGS_FOLDER = args.logs
+WORKING_DIR = os.path.join(args.output_path, "tokenized-tasks")  # where to save the tokenized individual files
+LOCAL_WORKING_DIR = args.local  # if your WORKING_DIR is a local path, you won't need this one
+# and can set it to `None`
+if LOCAL_WORKING_DIR:
+    LOCAL_WORKING_DIR = os.path.join(LOCAL_WORKING_DIR, DATASET_NAME)
+FINAL_OUTPUT_DIR = os.path.join(
+    args.output_path, "merged-dataset"
+)  # where to save the final merged tokenized dataset.
+# This is the path you will pass to your training library so that it can read the tokenized data.
+
+
+if __name__ == "__main__":
+    # this first (distributed) step will tokenize and shuffle the files from each task
+    dist_executor = SlurmPipelineExecutor(
+        job_name=f"{DATASET_NAME}-tok1",
+        pipeline=[
+            HuggingFaceDatasetReader(
+                dataset=args.dataset,  # dataset name
+                dataset_options={"split": args.split},  # any other options that should be passed to load_dataset
+                text_key=args.text_key,  # the column that actually contains the text to be tokenized
+            ),
+            DocumentTokenizer(
+                output_folder=WORKING_DIR,
+                local_working_dir=LOCAL_WORKING_DIR,
+                save_filename=f"{DATASET_NAME}_tokenized",
+                tokenizer_name_or_path=args.tokenizer,
+            ),
+        ],
+        # If you have a very small dataset, feel free to set this to "1" and remove the merge_executor
+        tasks=args.tasks,  # or as many as you want.
+        logging_dir=f"{LOGS_FOLDER}/tokenization",
+        time="20:00:00",
+        partition=args.partition,
+    )
+
+    # this final step randomly samples from the previously shuffled
+    merge_executor = SlurmPipelineExecutor(
+        job_name=f"{DATASET_NAME}-tok2",
+        pipeline=[
+            DocumentTokenizerMerger(
+                input_folder=WORKING_DIR,
+                output_folder=FINAL_OUTPUT_DIR,
+                save_filename=f"{DATASET_NAME}",
+            ),
+        ],
+        tasks=1,  # important
+        logging_dir=f"{LOGS_FOLDER}/merged",
+        time="50:00:00",
+        partition=args.partition,
+        depends=dist_executor,
+        qos="high",
+    )
+
+    merge_executor.run()
diff --git a/examples/infinite-context-length/hope.ipynb b/examples/infinite-context-length/hope.ipynb
new file mode 100644
index 00000000..47d8565d
--- /dev/null
+++ b/examples/infinite-context-length/hope.ipynb
@@ -0,0 +1,1528 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "paths = []\n",
+    "\n",
+    "for depth in range(0, 100, 5):\n",
+    "    paths.append(f\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/scripts/needle_finetune_format_dataset_but_for_evals_32768_ctx_and_{depth}_depth.pkl\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dfs = [pd.read_pickle(path) for path in paths]\n",
+    "df = pd.concat(dfs, )  # Set ignore_index to reset index"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>prompt</th>\n",
+       "      <th>answer</th>\n",
+       "      <th>context_length</th>\n",
+       "      <th>depth_percent</th>\n",
+       "      <th>response</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1ac90da2-3ff2-4bdd-98fe-5408627eacb0</td>\n",
+       "      <td>There is an important info hidden inside a lot...</td>\n",
+       "      <td>49885</td>\n",
+       "      <td>32768</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>12.5. The pass key is 12.5. The pass key is 12...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>aa95b758-d515-46d2-9c7f-1cc39f957fb3</td>\n",
+       "      <td>There is an important info hidden inside a lot...</td>\n",
+       "      <td>10520</td>\n",
+       "      <td>32768</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>123. The pass key is 123. The pass key is 123....</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1410ffa8-836e-4272-ade7-02e124965ded</td>\n",
+       "      <td>There is an important info hidden inside a lot...</td>\n",
+       "      <td>48327</td>\n",
+       "      <td>32768</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>123. The pass key is 123. The pass key is 123....</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>bdfc0228-3464-43ed-bcab-d745e277b730</td>\n",
+       "      <td>There is an important info hidden inside a lot...</td>\n",
+       "      <td>45312</td>\n",
+       "      <td>32768</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1000. The pass key is 1000. The pass key is 10...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1eb5c055-aeab-4ff6-9462-0d4b10b9c558</td>\n",
+       "      <td>There is an important info hidden inside a lot...</td>\n",
+       "      <td>34160</td>\n",
+       "      <td>32768</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1000. The pass key is 1000. The pass key is 10...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                     id  \\\n",
+       "0  1ac90da2-3ff2-4bdd-98fe-5408627eacb0   \n",
+       "1  aa95b758-d515-46d2-9c7f-1cc39f957fb3   \n",
+       "2  1410ffa8-836e-4272-ade7-02e124965ded   \n",
+       "3  bdfc0228-3464-43ed-bcab-d745e277b730   \n",
+       "4  1eb5c055-aeab-4ff6-9462-0d4b10b9c558   \n",
+       "\n",
+       "                                              prompt  answer  context_length  \\\n",
+       "0  There is an important info hidden inside a lot...   49885           32768   \n",
+       "1  There is an important info hidden inside a lot...   10520           32768   \n",
+       "2  There is an important info hidden inside a lot...   48327           32768   \n",
+       "3  There is an important info hidden inside a lot...   45312           32768   \n",
+       "4  There is an important info hidden inside a lot...   34160           32768   \n",
+       "\n",
+       "   depth_percent                                           response  \n",
+       "0            0.0  12.5. The pass key is 12.5. The pass key is 12...  \n",
+       "1            0.0  123. The pass key is 123. The pass key is 123....  \n",
+       "2            0.0  123. The pass key is 123. The pass key is 123....  \n",
+       "3            0.0  1000. The pass key is 1000. The pass key is 10...  \n",
+       "4            0.0  1000. The pass key is 1000. The pass key is 10...  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "depth_percent\n",
+       "0.0     100\n",
+       "5.0     100\n",
+       "90.0    100\n",
+       "85.0    100\n",
+       "80.0    100\n",
+       "75.0    100\n",
+       "70.0    100\n",
+       "65.0    100\n",
+       "60.0    100\n",
+       "55.0    100\n",
+       "50.0    100\n",
+       "45.0    100\n",
+       "40.0    100\n",
+       "35.0    100\n",
+       "30.0    100\n",
+       "25.0    100\n",
+       "20.0    100\n",
+       "15.0    100\n",
+       "10.0    100\n",
+       "95.0    100\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df['depth_percent'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "NEEDLE_TEXT = \"answer\"\n",
+    "DEPTH_TEXT = \"depth_percent\" # depth_percent\n",
+    "\n",
+    "df[\"match\"] = df.apply(lambda x: int(str(x[NEEDLE_TEXT]) in x[\"response\"]), axis=1)\n",
+    "df_result = df[[DEPTH_TEXT, \"context_length\", \"match\"]].groupby(by=[DEPTH_TEXT, \"context_length\"]).mean().unstack(level=\"context_length\")\n",
+    "df_result.columns = df_result.columns.droplevel(level=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>context_length</th>\n",
+       "      <th>32768</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>depth_percent</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>55.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>65.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>70.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75.0</th>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>80.0</th>\n",
+       "      <td>0.48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>85.0</th>\n",
+       "      <td>1.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90.0</th>\n",
+       "      <td>1.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>95.0</th>\n",
+       "      <td>1.00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "context_length  32768\n",
+       "depth_percent        \n",
+       "0.0              0.00\n",
+       "5.0              0.00\n",
+       "10.0             0.00\n",
+       "15.0             0.00\n",
+       "20.0             0.00\n",
+       "25.0             0.00\n",
+       "30.0             0.00\n",
+       "35.0             0.00\n",
+       "40.0             0.00\n",
+       "45.0             0.00\n",
+       "50.0             0.00\n",
+       "55.0             0.00\n",
+       "60.0             0.00\n",
+       "65.0             0.00\n",
+       "70.0             0.00\n",
+       "75.0             0.00\n",
+       "80.0             0.48\n",
+       "85.0             1.00\n",
+       "90.0             1.00\n",
+       "95.0             1.00"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# 95, and 100 works near perfect\n",
+    "\n",
+    "df_result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import re\n",
+    "def calculate_std(x, NEEDLE_TEXT):\n",
+    "    try:\n",
+    "        expected_needle = float(str(x[NEEDLE_TEXT]))\n",
+    "        needle_in_response = float(re.search(r\"[-+]?\\d*\\.\\d+|\\d+\", x[\"response\"]).group())\n",
+    "        diff = abs(expected_needle - needle_in_response)\n",
+    "        if diff == 0:\n",
+    "            return 0\n",
+    "        elif diff <= 10:\n",
+    "            return 10\n",
+    "        elif diff <= 20:\n",
+    "            return 20\n",
+    "        elif diff <= 50:\n",
+    "            return 50\n",
+    "        else:\n",
+    "            return 100\n",
+    "    except (AttributeError, ValueError):\n",
+    "        return None\n",
+    "\n",
+    "df[\"std\"] = df.apply(lambda x: calculate_std(x, NEEDLE_TEXT), axis=1)\n",
+    "df_result = df[[DEPTH_TEXT, \"context_length\", \"std\"]].groupby(by=[DEPTH_TEXT, \"context_length\", \"std\"]).size().unstack(level=\"std\")\n",
+    "df_result = df_result.fillna(0).astype(int)\n",
+    "df_result[\"total\"] = df_result.sum(axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_std_and_match(x, NEEDLE_TEXT):\n",
+    "    try:\n",
+    "        expected_needle = float(str(x[NEEDLE_TEXT]))\n",
+    "        needle_in_response = float(re.search(r\"[-+]?\\d*\\.\\d+|\\d+\", x[\"response\"]).group())\n",
+    "        diff = abs(expected_needle - needle_in_response)\n",
+    "        if diff == 0:\n",
+    "            return 0, 1\n",
+    "        elif diff <= 10:\n",
+    "            return 10, 1\n",
+    "        elif diff <= 20:\n",
+    "            return 20, 1\n",
+    "        elif diff <= 50:\n",
+    "            return 50, 1\n",
+    "        else:\n",
+    "            return 100, 1\n",
+    "    except (AttributeError, ValueError):\n",
+    "        return None, 0\n",
+    "\n",
+    "df[[\"std\", \"match\"]] = df.apply(lambda x: pd.Series(get_std_and_match(x, NEEDLE_TEXT)), axis=1)\n",
+    "df_result = df[[DEPTH_TEXT, \"context_length\", \"std\", \"match\"]].groupby(by=[DEPTH_TEXT, \"context_length\", \"std\"]).mean().unstack(level=\"std\")\n",
+    "df_result.columns = df_result.columns.droplevel(level=0)\n",
+    "df_result.columns.name = \"std\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_result = df_result.apply(lambda x: x / x[\"total\"], axis=1).drop(\"total\", axis=1)\n",
+    "df_result.columns.name = \"std\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df[df['depth_percent'] == 65].head(n=5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pd.set_option('display.max_rows', None)  # None means show all rows\n",
+    "pd.set_option('display.max_columns', None)  # None means show all columns\n",
+    "pd.set_option('display.max_colwidth', None)  # None means no truncation\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Context Length"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0.  , 0.05, 0.1 , 0.15, 0.2 , 0.25, 0.3 , 0.35, 0.4 , 0.45, 0.5 ,\n",
+       "        0.55, 0.6 , 0.65, 0.7 , 0.75, 0.8 , 0.85, 0.9 , 0.95, 1.  ]])"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "heatmap_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "colorscale": [
+          [
+           0,
+           "red"
+          ],
+          [
+           0.5,
+           "yellow"
+          ],
+          [
+           1,
+           "green"
+          ]
+         ],
+         "showscale": true,
+         "type": "heatmap",
+         "x": [
+          0,
+          5,
+          10,
+          15,
+          20,
+          25,
+          30,
+          35,
+          40,
+          45,
+          50,
+          55,
+          60,
+          65,
+          70,
+          75,
+          80,
+          85,
+          90,
+          95,
+          100
+         ],
+         "y": [
+          16384
+         ],
+         "z": [
+          [
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           0,
+           1,
+           1,
+           1,
+           1,
+           1,
+           1,
+           1,
+           1,
+           1,
+           1
+          ]
+         ],
+         "zmax": 1,
+         "zmin": 0
+        }
+       ],
+       "layout": {
+        "height": 400,
+        "template": {
+         "data": {
+          "bar": [
+           {
+            "error_x": {
+             "color": "#2a3f5f"
+            },
+            "error_y": {
+             "color": "#2a3f5f"
+            },
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             },
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "bar"
+           }
+          ],
+          "barpolar": [
+           {
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             },
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "barpolar"
+           }
+          ],
+          "carpet": [
+           {
+            "aaxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "baxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "type": "carpet"
+           }
+          ],
+          "choropleth": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "choropleth"
+           }
+          ],
+          "contour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "contour"
+           }
+          ],
+          "contourcarpet": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "contourcarpet"
+           }
+          ],
+          "heatmap": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmap"
+           }
+          ],
+          "heatmapgl": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmapgl"
+           }
+          ],
+          "histogram": [
+           {
+            "marker": {
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "histogram"
+           }
+          ],
+          "histogram2d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2d"
+           }
+          ],
+          "histogram2dcontour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "histogram2dcontour"
+           }
+          ],
+          "mesh3d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "mesh3d"
+           }
+          ],
+          "parcoords": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "parcoords"
+           }
+          ],
+          "pie": [
+           {
+            "automargin": true,
+            "type": "pie"
+           }
+          ],
+          "scatter": [
+           {
+            "fillpattern": {
+             "fillmode": "overlay",
+             "size": 10,
+             "solidity": 0.2
+            },
+            "type": "scatter"
+           }
+          ],
+          "scatter3d": [
+           {
+            "line": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatter3d"
+           }
+          ],
+          "scattercarpet": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattercarpet"
+           }
+          ],
+          "scattergeo": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergeo"
+           }
+          ],
+          "scattergl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergl"
+           }
+          ],
+          "scattermapbox": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattermapbox"
+           }
+          ],
+          "scatterpolar": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolar"
+           }
+          ],
+          "scatterpolargl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterpolargl"
+           }
+          ],
+          "scatterternary": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scatterternary"
+           }
+          ],
+          "surface": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "surface"
+           }
+          ],
+          "table": [
+           {
+            "cells": {
+             "fill": {
+              "color": "#EBF0F8"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "header": {
+             "fill": {
+              "color": "#C8D4E3"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "type": "table"
+           }
+          ]
+         },
+         "layout": {
+          "annotationdefaults": {
+           "arrowcolor": "#2a3f5f",
+           "arrowhead": 0,
+           "arrowwidth": 1
+          },
+          "autotypenumbers": "strict",
+          "coloraxis": {
+           "colorbar": {
+            "outlinewidth": 0,
+            "ticks": ""
+           }
+          },
+          "colorscale": {
+           "diverging": [
+            [
+             0,
+             "#8e0152"
+            ],
+            [
+             0.1,
+             "#c51b7d"
+            ],
+            [
+             0.2,
+             "#de77ae"
+            ],
+            [
+             0.3,
+             "#f1b6da"
+            ],
+            [
+             0.4,
+             "#fde0ef"
+            ],
+            [
+             0.5,
+             "#f7f7f7"
+            ],
+            [
+             0.6,
+             "#e6f5d0"
+            ],
+            [
+             0.7,
+             "#b8e186"
+            ],
+            [
+             0.8,
+             "#7fbc41"
+            ],
+            [
+             0.9,
+             "#4d9221"
+            ],
+            [
+             1,
+             "#276419"
+            ]
+           ],
+           "sequential": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ],
+           "sequentialminus": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ]
+          },
+          "colorway": [
+           "#636efa",
+           "#EF553B",
+           "#00cc96",
+           "#ab63fa",
+           "#FFA15A",
+           "#19d3f3",
+           "#FF6692",
+           "#B6E880",
+           "#FF97FF",
+           "#FECB52"
+          ],
+          "font": {
+           "color": "#2a3f5f"
+          },
+          "geo": {
+           "bgcolor": "white",
+           "lakecolor": "white",
+           "landcolor": "#E5ECF6",
+           "showlakes": true,
+           "showland": true,
+           "subunitcolor": "white"
+          },
+          "hoverlabel": {
+           "align": "left"
+          },
+          "hovermode": "closest",
+          "mapbox": {
+           "style": "light"
+          },
+          "paper_bgcolor": "white",
+          "plot_bgcolor": "#E5ECF6",
+          "polar": {
+           "angularaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "zaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "line": {
+            "color": "#2a3f5f"
+           }
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        },
+        "title": {
+         "text": "[Exp 55: 8b llama3's continual pretraining] Context Length vs. Depth"
+        },
+        "width": 800,
+        "xaxis": {
+         "dtick": 5,
+         "tick0": 0,
+         "tickmode": "linear",
+         "title": {
+          "text": "Depth (%)"
+         }
+        },
+        "yaxis": {
+         "tickmode": "array",
+         "ticktext": [
+          "16384"
+         ],
+         "tickvals": [
+          16384
+         ],
+         "title": {
+          "text": "Context Length"
+         }
+        }
+       }
+      },
+      "text/html": [
+       "<div>                            <div id=\"8dd80eb7-64f4-442f-b0d0-5e8042ece3f9\" class=\"plotly-graph-div\" style=\"height:400px; width:800px;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"8dd80eb7-64f4-442f-b0d0-5e8042ece3f9\")) {                    Plotly.newPlot(                        \"8dd80eb7-64f4-442f-b0d0-5e8042ece3f9\",                        [{\"colorscale\":[[0,\"red\"],[0.5,\"yellow\"],[1,\"green\"]],\"showscale\":true,\"x\":[0.0,5.0,10.0,15.0,20.0,25.0,30.0,35.0,40.0,45.0,50.0,55.0,60.0,65.0,70.0,75.0,80.0,85.0,90.0,95.0,100.0],\"y\":[16384],\"z\":[[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0]],\"zmax\":1,\"zmin\":0,\"type\":\"heatmap\"}],                        {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmapgl\":[{\"type\":\"heatmapgl\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermapbox\":[{\"type\":\"scattermapbox\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05},\"mapbox\":{\"style\":\"light\"}}},\"xaxis\":{\"title\":{\"text\":\"Depth (%)\"},\"tickmode\":\"linear\",\"tick0\":0,\"dtick\":5},\"yaxis\":{\"title\":{\"text\":\"Context Length\"},\"tickmode\":\"array\",\"tickvals\":[16384],\"ticktext\":[\"16384\"]},\"title\":{\"text\":\"[Exp 55: 8b llama3's continual pretraining] Context Length vs. Depth\"},\"width\":800,\"height\":400},                        {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('8dd80eb7-64f4-442f-b0d0-5e8042ece3f9');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import plotly.graph_objects as go\n",
+    "import numpy as np\n",
+    "\n",
+    "# Create data\n",
+    "depth = np.linspace(0, 100, 21)  # 0% to 100% in 5% increments\n",
+    "context_length = [16384]  # 8192 * 2\n",
+    "\n",
+    "# Create the heatmap data\n",
+    "heatmap_data = np.zeros((1, len(depth)))\n",
+    "# heatmap_data[:] = np.linspace(0, 1, len(depth))\n",
+    "heatmap_data[:, :11] = 0  # Red for 0% to 50%\n",
+    "heatmap_data[:, 11:] = 1  # Green for 55% to 100\n",
+    "\n",
+    "# Create the heatmap\n",
+    "fig = go.Figure(data=go.Heatmap(\n",
+    "    z=heatmap_data,\n",
+    "    x=depth,\n",
+    "    y=context_length,\n",
+    "    colorscale=[\n",
+    "        [0, 'red'],\n",
+    "        [0.5, 'yellow'],\n",
+    "        [1, 'green']\n",
+    "    ],\n",
+    "    zmin=0,\n",
+    "    zmax=1,\n",
+    "    showscale=True,\n",
+    "))\n",
+    "\n",
+    "# Update layout\n",
+    "fig.update_layout(\n",
+    "    title=\"[Exp 55: 8b llama3's continual pretraining] Context Length vs. Depth\",\n",
+    "    xaxis_title='Depth (%)',\n",
+    "    yaxis_title='Context Length',\n",
+    "    xaxis=dict(\n",
+    "        tickmode='linear',\n",
+    "        tick0=0,\n",
+    "        dtick=5,\n",
+    "    ),\n",
+    "    yaxis=dict(\n",
+    "        tickmode='array',\n",
+    "        tickvals=[16384],\n",
+    "        ticktext=['16384'],\n",
+    "    ),\n",
+    "    width=800,\n",
+    "    height=400,\n",
+    ")\n",
+    "\n",
+    "# Show the plot\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/infinite-context-length/scripts/run_16k_passkey_evals.sh b/examples/infinite-context-length/scripts/run_16k_passkey_evals.sh
new file mode 100644
index 00000000..8e01d406
--- /dev/null
+++ b/examples/infinite-context-length/scripts/run_16k_passkey_evals.sh
@@ -0,0 +1,13 @@
+#!/bin/bash
+#SBATCH --job-name=eval_8b_llama_infini_at_20k_ckp_16k_passkey_no_finetuning
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=1          # crucial - only 1 task per dist per node!
+#SBATCH --mem-per-cpu=11G # This is essentially 1.1T / 96
+#SBATCH --cpus-per-task=96
+#SBATCH --gres=gpu:4
+#SBATCH --partition=hopper-prod
+#SBATCH -o /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp55_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.001/logs/evals/eval_8b_llama_infini_at_20k_ckp_16k_passkey_no_finetuning/job_logs/%x-%j.out
+#SBATCH --qos=high
+
+# CUDA_DEVICE_MAX_CONNECTIONS=1 torchrun --nproc_per_node=4 --master_port=25678 run_passkey_eval.py --ckpt-path /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp35_8b_llama_16384_ctx_length_and_8192_segment_length_and_2m_bs_and_needle_finetuning/checkpoints/1326 --save_path /fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/finetuning_passkey_eval_results
+CUDA_DEVICE_MAX_CONNECTIONS=1 torchrun --nproc_per_node=4 --master_port=25678 run_passkey_eval.py --ckpt-path /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp55_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.001/ckp_for_evals/20000 --save_path /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp55_8b_llama_16384_ctx_length_and_8192_segment_length_and_1.3m_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.001/logs/evals/eval_8b_llama_infini_at_20k_ckp_16k_passkey_no_finetuning
diff --git a/examples/infinite-context-length/scripts/run_32k_evals.sh b/examples/infinite-context-length/scripts/run_32k_evals.sh
new file mode 100755
index 00000000..2228eeb3
--- /dev/null
+++ b/examples/infinite-context-length/scripts/run_32k_evals.sh
@@ -0,0 +1,38 @@
+#!/bin/bash
+#SBATCH --job-name=eval_infini_attention_32k
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=1          # crucial - only 1 task per dist per node!
+#SBATCH --mem-per-cpu=11G # This is essentially 1.1T / 96
+#SBATCH --cpus-per-task=96
+#SBATCH --gres=gpu:1
+#SBATCH --partition=hopper-prod
+#SBATCH -o /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp19_1b_llama2_32k_ctx_length_and_2m_bs/checkpoints/90000/eval_logs/%x-%j-480-ckp-eval.out
+#SBATCH --qos=high
+#SBATCH --array=1-10
+
+# Define the list of depth percentages
+depth_values=(0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100)
+
+# Split the depth values into chunks for each SLURM job array
+# This setup creates ten jobs, with two depths each, except the last job, which has three
+chunks=(
+  "${depth_values[@]:0:2}"   # Job 1: 0, 5
+  "${depth_values[@]:2:2}"   # Job 2: 10, 15
+  "${depth_values[@]:4:2}"   # Job 3: 20, 25
+  "${depth_values[@]:6:2}"   # Job 4: 30, 35
+  "${depth_values[@]:8:2}"   # Job 5: 40, 45
+  # "${depth_values[@]:10:2}"  # Job 6: 50, 55
+  # "${depth_values[@]:12:2}"  # Job 7: 60, 65
+  # "${depth_values[@]:14:2}"  # Job 8: 70, 75
+  # "${depth_values[@]:16:2}"  # Job 9: 80, 85
+  # "${depth_values[@]:18:3}"  # Job 10: 90, 95, 100
+)
+
+# Determine the assigned depths based on SLURM_ARRAY_TASK_ID
+depths=(${chunks[SLURM_ARRAY_TASK_ID - 1]})
+
+# Run the job for each depth percent in the assigned chunk
+for depth_percent in "${depths[@]}"; do
+  echo "Running job with depth percent: $depth_percent"
+  CUDA_DEVICE_MAX_CONNECTIONS=1 torchrun --nproc_per_node=1 /fsx/phuc/projects/nanotron/examples/infinite-context-length/run_evals.py --ckpt-path /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp19_1b_llama2_32k_ctx_length_and_2m_bs/checkpoints/90000 --context_length 32768 --depth_percent $depth_percent
+done
diff --git a/examples/infinite-context-length/scripts/run_evals.sh b/examples/infinite-context-length/scripts/run_evals.sh
new file mode 100644
index 00000000..0530bfd6
--- /dev/null
+++ b/examples/infinite-context-length/scripts/run_evals.sh
@@ -0,0 +1,8 @@
+# Calculate depth_percent based on SLURM_ARRAY_TASK_ID
+depth_percent=$(( SLURM_ARRAY_TASK_ID * 5 ))  # 0, 5, 10, ..., 100
+
+# Print out the calculated depth percent for debugging/logging
+echo "Running job with depth percent: $depth_percent"
+
+# Run the torchrun command with the calculated depth_percent
+CUDA_DEVICE_MAX_CONNECTIONS=1 torchrun --nproc_per_node=1 examples/infinite-context-length/run_evals.py --ckpt-path /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp18_1b_llama2_100k_ctx_length_and_2m_bs/checkpoints/finetune_needle_checkpoints_with_needle_in_prediction/480 --context_length 32768 --depth_percent $depth_percent
diff --git a/examples/infinite-context-length/scripts/run_generate_16k_passkey_eval_data.sh b/examples/infinite-context-length/scripts/run_generate_16k_passkey_eval_data.sh
new file mode 100755
index 00000000..16508d99
--- /dev/null
+++ b/examples/infinite-context-length/scripts/run_generate_16k_passkey_eval_data.sh
@@ -0,0 +1,29 @@
+#!/bin/bash
+#SBATCH --job-name=generate_16k_eval_data
+#SBATCH --partition=hopper-cpu
+#SBATCH --requeue
+#SBATCH --time=18:00:00
+#SBATCH --cpus-per-task=96
+#SBATCH --mem-per-cpu=500
+#SBATCH --qos=high
+#SBATCH --array=0-356
+#SBATCH -o /fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/eval_data_gen_logs/%j-%a-%x.out
+
+
+# Set the context length
+context_length=16384
+
+# Define the depth_percent values
+depth_percents=(0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100)
+
+# Calculate the depth_percent index and id based on the job ID
+depth_percent_index=$((SLURM_ARRAY_TASK_ID / 17))
+id=$((SLURM_ARRAY_TASK_ID % 17 + 1))
+
+# Get the depth_percent value for the current job
+depth_percent=${depth_percents[$depth_percent_index]}
+
+echo "Running job with depth_percent=$depth_percent and id=$id, SLURM_ARRAY_TASK_ID=$SLURM_ARRAY_TASK_ID"
+
+# Run the command with the current depth_percent and id
+python3 -u /fsx/phuc/projects/nanotron/examples/infinite-context-length/generate_data.py --context_length $context_length --depth_percent $depth_percent --id $id --num_prompts 2 --tokenizer_path /fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B --is_exact_context_length 0 --is_padding 0
diff --git a/examples/infinite-context-length/scripts/run_generate_16k_passkey_finetuning_data.sh b/examples/infinite-context-length/scripts/run_generate_16k_passkey_finetuning_data.sh
new file mode 100644
index 00000000..e06bfdfd
--- /dev/null
+++ b/examples/infinite-context-length/scripts/run_generate_16k_passkey_finetuning_data.sh
@@ -0,0 +1,42 @@
+#!/bin/bash
+#SBATCH --job-name=generate_16k_passkey_finetuning_data
+#SBATCH --partition=hopper-cpu
+#SBATCH --requeue
+#SBATCH --time=18:00:00
+#SBATCH --cpus-per-task=96
+#SBATCH --mem-per-cpu=500
+#SBATCH --qos=high
+#SBATCH --array=0-1000
+#SBATCH -o /fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/finetuning_data_gen_logs/%j-%a-%x.out
+
+# 15 context length * 17 depths * 4 jobs = 1020
+
+# Define the list of context lengths, 15 context lengths
+# context_lengths=(512 1024 1536 2048 2560 3072 3584 4096 4608 5120 5632 6144 6656 7168 7680)
+context_lengths=(8192 8704 9216 9728 10240 10752 11264 11776 12288 12800 13312 13824 14336 14848 15360 15872)
+
+# Define the depth_percent values, 17 values
+depth_percents=(0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100)
+
+# # Calculate the context_length index, depth_percent index, and id based on the job ID
+# context_length_index=$((SLURM_ARRAY_TASK_ID / (${#depth_percents[@]} * 3)))
+# depth_percent_index=$(((SLURM_ARRAY_TASK_ID % (${#depth_percents[@]} * 3)) / 3))
+# id=$((SLURM_ARRAY_TASK_ID % 5 + 1))
+
+total_jobs=$((SLURM_ARRAY_TASK_COUNT))
+jobs_per_context_length=$((total_jobs / ${#context_lengths[@]}))
+jobs_per_depth_percent=$((jobs_per_context_length / ${#depth_percents[@]}))
+
+# Calculate the context_length index, depth_percent index, and id based on the job ID
+context_length_index=$((SLURM_ARRAY_TASK_ID / jobs_per_context_length))
+depth_percent_index=$(((SLURM_ARRAY_TASK_ID % jobs_per_context_length) / jobs_per_depth_percent))
+id=$((SLURM_ARRAY_TASK_ID % jobs_per_depth_percent))
+
+# Get the context_length and depth_percent values for the current job
+context_length=${context_lengths[$context_length_index]}
+depth_percent=${depth_percents[$depth_percent_index]}
+
+echo "Running job with context_length=$context_length, depth_percent=$depth_percent, and id=$id, SLURM_ARRAY_TASK_ID=$SLURM_ARRAY_TASK_ID"
+
+# Run the command with the current context_length, depth_percent, and id
+python3 -u /fsx/phuc/projects/nanotron/examples/infinite-context-length/generate_data.py --save_path /fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/finetune_data --context_length $context_length --depth_percent $depth_percent --id $id --num_prompts 50 --tokenizer_path /fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B --is_exact_context_length 0 --is_padding 0 --is_eval 0 --check_key_in_dataset nanotron/llama3-16k-passkey-retrieval-eval
diff --git a/examples/infinite-context-length/scripts/run_passkey_eval.py b/examples/infinite-context-length/scripts/run_passkey_eval.py
new file mode 100644
index 00000000..f1f80147
--- /dev/null
+++ b/examples/infinite-context-length/scripts/run_passkey_eval.py
@@ -0,0 +1,293 @@
+"""
+Nanotron Inference Script
+
+Usage:
+```
+export CUDA_DEVICE_MAX_CONNECTIONS=1 # important for some distributed operations
+torchrun --nproc_per_node=4 run_generate.py ---ckpt-path checkpoints/test/4
+```
+"""
+
+import argparse
+import os
+from pathlib import Path
+
+import torch
+from nanotron import distributed as dist
+from nanotron import logging
+from nanotron.config import (
+    GenerationArgs,
+    LoggingArgs,
+    ParallelismArgs,
+    get_config_from_file,
+)
+from nanotron.generation.decode import (
+    GenerationInput,
+    TokenizerConfig,
+    decode_text,
+)
+from nanotron.logging import log_rank, set_ranks_logging_level
+from nanotron.models import build_model
+from nanotron.parallel import ParallelContext
+from nanotron.parallel.parameters import sanity_check
+from nanotron.parallel.pipeline_parallel.engine import (
+    OneForwardOneBackwardPipelineEngine,
+)
+from nanotron.parallel.pipeline_parallel.tensor_pointer import TensorPointer
+from nanotron.parallel.tensor_parallel.enum import TensorParallelLinearMode
+from nanotron.random import (
+    RandomStates,
+    get_current_random_state,
+    get_synced_random_state,
+    set_random_seed,
+)
+from nanotron.serialize import load_weights
+from nanotron.trainer import CONFIG_TO_MODEL_CLASS, mark_tied_parameters
+
+try:
+    from transformers import AutoTokenizer
+except ImportError:
+    AutoTokenizer = None
+
+logger = logging.get_logger(__name__)
+
+USE_CACHE = False
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--ckpt-path", type=Path, required=True, help="Checkpoint path")
+    parser.add_argument("--dp", type=int, default=0)
+    parser.add_argument("--pp", type=int, default=0)
+    parser.add_argument("--tp", type=int, default=0)
+    parser.add_argument("--max-new-tokens", type=int, default=20, help="Maximum number of new tokens to generate")
+    # parser.add_argument("--depth_percent", type=int, required=True)
+    parser.add_argument("--save_path", type=str, required=True)
+    return parser.parse_args()
+
+
+def generate(args, model, tokenizer, inputs, parallel_context):
+    outputs = decode_text(
+        input_iter=(GenerationInput(text=text) for text in inputs),
+        tokenizer=tokenizer,
+        # TODO @thomasw21: From ModelWithLoss extract the model.
+        model=model.model,
+        parallel_context=parallel_context,
+        max_new_tokens=args.max_new_tokens,
+        max_micro_batch_size=1,
+        generation_config=GenerationArgs(sampler="greedy", use_cache=USE_CACHE),
+        # generation_config=GenerationArgs(sampler="top_p", use_cache=False),
+        tokenizer_config=TokenizerConfig(max_input_length=None),
+        is_bench=os.environ.get("USE_BENCH", "0") == "1",
+    )
+
+    responses = []
+    answer_idxs = []
+    for output in outputs:
+        input_ids = output.input_ids
+        generated_ids = output.generation_ids
+
+        answer_ids = generated_ids[len(input_ids) :]
+        decoded_answer = tokenizer.decode(answer_ids, clean_up_tokenization_spaces=False)
+
+        if isinstance(input_ids, TensorPointer):
+            assert isinstance(generated_ids, TensorPointer)
+            continue
+        assert isinstance(generated_ids, torch.Tensor)
+
+        log_rank(
+            f"""
+            decoded_generation: {decoded_answer}""",
+            logger=logger,
+            level=logging.INFO,
+            rank=0,
+        )
+
+        responses.append(decoded_answer)
+        answer_idxs.append(answer_ids.tolist())
+
+    dist.barrier()
+
+    return responses, answer_idxs
+
+
+def main():
+    args = get_args()
+    # depth_percent = args.depth_percent
+    save_path = args.save_path
+
+    assert args.ckpt_path.exists(), f"Checkpoint path {args.ckpt_path} does not exist"
+
+    config = get_config_from_file((args.ckpt_path / "config.yaml").as_posix())
+    from nanotron import constants
+
+    constants.CONFIG = config
+    model_config = config.model.model_config
+    tokenizer_path = config.tokenizer.tokenizer_name_or_path
+
+    parallel_config = ParallelismArgs(
+        dp=args.dp or config.parallelism.dp,
+        pp=args.pp or config.parallelism.pp,
+        tp=args.tp or config.parallelism.tp,
+        pp_engine=OneForwardOneBackwardPipelineEngine(),
+        # tp_mode=TensorParallelLinearMode.REDUCE_SCATTER,
+        # tp_linear_async_communication=True,
+        # # NOTE: the one from main branch
+        tp_mode=TensorParallelLinearMode.ALL_REDUCE,
+        tp_linear_async_communication=False,
+    )
+
+    # Initialise all process groups
+    parallel_context = ParallelContext(
+        data_parallel_size=parallel_config.dp,
+        pipeline_parallel_size=parallel_config.pp,
+        tensor_parallel_size=parallel_config.tp,
+    )
+
+    # Set log levels
+    logging_config = LoggingArgs(
+        log_level="info",
+        log_level_replica="info",
+    )
+
+    # Set log levels
+    set_ranks_logging_level(parallel_context=parallel_context, logging_config=logging_config)
+
+    log_rank(f"model_config: {model_config}", logger=logger, level=logging.INFO, rank=0)
+    log_rank(f"tokenizer_path: {tokenizer_path}", logger=logger, level=logging.INFO, rank=0)
+
+    dtype = torch.bfloat16
+
+    # Set random states
+    set_random_seed(42)
+
+    model_config_cls = model_config.__class__.__name__
+    if model_config_cls not in CONFIG_TO_MODEL_CLASS:
+        raise ValueError(
+            f"Unsupported model config {model_config_cls}. Only {CONFIG_TO_MODEL_CLASS.keys()} are supported"
+        )
+
+    # Get synchronized random states
+    if parallel_config.tp_mode is TensorParallelLinearMode.ALL_REDUCE:
+        random_states = RandomStates(
+            {"tp_synced": get_synced_random_state(random_state=get_current_random_state(), pg=parallel_context.tp_pg)}
+        )
+    else:
+        # We don't need to sync across TP when using sequence parallel (REDUCE_SCATTER)
+        random_states = RandomStates({})
+
+    model = build_model(
+        model_builder=lambda: CONFIG_TO_MODEL_CLASS[model_config_cls](
+            config=model_config,
+            parallel_context=parallel_context,
+            parallel_config=parallel_config,
+            random_states=random_states,
+        ),
+        dtype=dtype,
+        parallel_context=parallel_context,
+    )
+
+    # Mark some parameters as tied
+    # TODO @nouamane: this is only needed for training, can we just mark params as NanotronParameter instead?
+    mark_tied_parameters(model=model, parallel_context=parallel_context, parallel_config=parallel_config)
+
+    # Sanity check model
+    sanity_check(root_module=model)
+
+    # Load checkpoint
+    checkpoint_path = args.ckpt_path
+    log_rank(
+        f"Loading checkpoint from {checkpoint_path}:",
+        logger=logger,
+        level=logging.INFO,
+        rank=0,
+    )
+    load_weights(model=model, parallel_context=parallel_context, root_folder=checkpoint_path)
+
+    model.eval()
+
+    # from nanotron.debug.monitor import monitor_nanotron_model
+    # monitor_nanotron_model(model=model, parallel_context=parallel_context)
+
+    if AutoTokenizer is not None:
+        tokenizer = AutoTokenizer.from_pretrained(tokenizer_path)
+        # tokenizer.pad_token_id = tokenizer.eos_token_id
+        if tokenizer.pad_token_id is None:
+            if tokenizer.eos_token_id is not None:
+                tokenizer.pad_token_id = tokenizer.eos_token_id
+            elif getattr(model.config, "pad_token_id", None) is not None:
+                tokenizer.pad_token_id = int(model.config.pad_token_id)
+            elif getattr(model.config, "eos_token_id", None) is not None:
+                tokenizer.pad_token_id = int(model.config.eos_token_id)
+            else:
+                tokenizer.add_special_tokens({"pad_token": "[PAD]"})
+        tokenizer.padding_side = "left"
+        tokenizer.truncation_side = "left"  # TODO @nouamane: do we want this?
+
+        for depth_percent in [0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100]:
+            log_rank(
+                f"depth_percent: {depth_percent}",
+                logger=logger,
+                level=logging.INFO,
+                rank=0,
+            )
+
+            from datasets import load_dataset
+
+            dataset = load_dataset("nanotron/llama3-16k-passkey-retrieval-eval", split="train")
+            df = load_dataset("nanotron/llama3-16k-passkey-retrieval-eval", split="train")
+
+            dataset = dataset.filter(lambda x: x["depth_percent"] == depth_percent)
+            df = df.filter(lambda x: x["depth_percent"] == depth_percent)
+
+            # dataset = dataset.select([0])
+            # df = df.select([0])
+
+            dataloader = torch.utils.data.DataLoader(dataset, batch_size=1, shuffle=False)
+
+            df.set_format("pandas")
+            df = df[:]
+
+            responses = []
+            answer_idxs = []
+            from tqdm import tqdm
+
+            for batch in tqdm(dataloader):
+                log_rank(
+                    """--------------------------------------------------""",
+                    logger=logger,
+                    level=logging.INFO,
+                    rank=0,
+                )
+                log_rank(
+                    f"target answer: {batch['answer']}",
+                    logger=logger,
+                    level=logging.INFO,
+                    rank=0,
+                )
+
+                texts = batch["prompt"]
+                response, answer_ids = generate(args, model, tokenizer, texts, parallel_context)
+
+                log_rank(
+                    f"response: {response}",
+                    logger=logger,
+                    level=logging.INFO,
+                    rank=0,
+                )
+
+                responses.append(response)
+                answer_idxs.append(answer_ids)
+
+            # NOTE: now flatten the responses
+            responses = [x for sublist in responses for x in sublist]
+            answer_idxs = [x for sublist in answer_idxs for x in sublist]
+
+            df["generation_text"] = responses
+            df["generation_ids"] = answer_idxs
+
+            df.to_pickle(f"{save_path}/passkey_eval_results_for_{depth_percent}_depth.pkl")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/examples/infinite-context-length/templates/training_data.py b/examples/infinite-context-length/templates/training_data.py
new file mode 100644
index 00000000..c24dcc88
--- /dev/null
+++ b/examples/infinite-context-length/templates/training_data.py
@@ -0,0 +1 @@
+TEMPLATE_ONE = "The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature...s symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.The city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.The mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.The stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.The waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air."
diff --git a/examples/infinite-context-length/templates/training_date.py b/examples/infinite-context-length/templates/training_date.py
new file mode 100644
index 00000000..2cfeec95
--- /dev/null
+++ b/examples/infinite-context-length/templates/training_date.py
@@ -0,0 +1 @@
+TEMP
diff --git a/llama3_generation.ipynb b/llama3_generation.ipynb
new file mode 100644
index 00000000..5c7132e9
--- /dev/null
+++ b/llama3_generation.ipynb
@@ -0,0 +1,121 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/admin/home/phuc_nguyen/miniconda3/envs/nanotron-dev/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "from transformers import AutoModel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Loading checkpoint shards: 100%|██████████████████████████████████████████████████████████| 4/4 [00:27<00:00,  6.84s/it]\n",
+      "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n",
+      "Setting `pad_token_id` to `eos_token_id`:128001 for open-end generation.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[{'generated_text': 'Hey how are you doing today? I am doing pretty good. I have been busy this morning. I have been making a list of all the things I have to do before I leave for school. I have to finish my school work and I have to pack my bags. I am going to miss my friends and family, but I am excited to go to school. I can’t wait to meet new people and learn new things. I will be sure to keep you updated on my adventures. Take care!\\nI am doing great! I am so excited to be starting school. I am a little nervous, but I know I will do great. I can’t wait to meet all of my new friends and learn new things. I am also excited to be able to do all of the fun activities that come with being a student. I know it is going to be a great year!\\nI am doing well. I am excited to start school. I am a little nervous, but I know I will do great. I can’t wait to meet all of my new friends and learn new things. I am also excited to be able to do all of the fun activities that come with being a student. I know it is going to be a great year!\\nI am doing well. I am excited to start school. I am a little nervous, but I know I will do great. I can’t wait to meet all of my new friends and learn new things. I am also excited to be able to do all of the fun activities that come with being a student. I know it is going to be a great year!'}]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import transformers\n",
+    "import torch\n",
+    "\n",
+    "model_id = \"meta-llama/Meta-Llama-3-8B\"\n",
+    "\n",
+    "pipeline = transformers.pipeline(\"text-generation\", model=model_id, model_kwargs={\"torch_dtype\": torch.bfloat16}, device_map=\"auto\")\n",
+    "pipeline(\"Hey how are you doing today?\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "prompt = \"The capital of France is Paris. \" * 570"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Setting `pad_token_id` to `eos_token_id`:128001 for open-end generation.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[{'generated_text': 'The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. \\xa0The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris. The capital of France is Paris'}]"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pipeline(prompt)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/run_evals_32_ctx.sh b/run_evals_32_ctx.sh
new file mode 100644
index 00000000..e69de29b
diff --git a/run_generate.py b/run_generate.py
index c4f3310e..232e8483 100644
--- a/run_generate.py
+++ b/run_generate.py
@@ -253,7 +253,7 @@ def evaluate(self, X, y):
 PASSKEY_1024_CTX_AND_20_DEPTH = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on............................... The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the. The pass key is 5. Remember it. 5 is the pass key.  salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world iThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The. \n\nWhat is the pass key? The pass key is "
 
 
-PASSKEY_1024_CTX_AND_0_DEPTH = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on............................................................... . The pass key is 7. Remember it. 7 is the pass key. The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world iThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The. \n\nWhat is the pass key? The pass key is "
+PASSKEY_1024_CTX_AND_0_DEPTH = "The pass key is 7. Remember it. 7 is the pass key. There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. The pass key is 7. Remember it. 7 is the pass key. The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. TWhat is the pass key? The pass key is "
 
 
 PASSKEY_1024_CTX_AND_90_DEPTH = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on............................................................... The leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world is at peace under the celestial blanket.\nThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The ocean's embrace is calming.\nThe leaves rustle in the wind. The birds chirp their melodies. The squirrels scamper up the trees. Nature's symphony plays on. Life thrives in the forest.\nThe city bustles with energy. The skyscrapers touch the clouds. The streets are alive with people. Horns honk and engines roar.. The pass key is 3. Remember it. 3 is the pass key.  The urban jungle never sleeps.\nThe mountains stand tall and proud. The snow caps their peaks. The valleys are lush and green. Hikers traverse the trails. Adventure awaits in the wilderness.\nThe stars twinkle in the night sky. The moon casts its gentle glow. The crickets sing their lullabies. Fireflies dance in the darkness. The world iThe waves crash against the shore. The seagulls soar overhead. The sand is warm beneath my feet. I breathe in the salty air. The. \n\nWhat is the pass key? The pass key is "
@@ -266,6 +266,394 @@ def evaluate(self, X, y):
 \nThe problem provided is derived from the 1980 American High School Mathematics Examination (AHSME), specifically problem number 17. This problem requires knowledge of complex numbers and algebraic manipulations. We will break down the solution into smaller steps and explain the underlying mathematical principles. Complex numbers can be represented as ordered pairs (a, b) or in the form of a + bi, where a and b are real numbers, and i is the square root of -1. When squaring i, you get (-1). Let's examine the given expression more closely: (n + i)^4 = n^4 + 4in³ - 6n² - 4in + 1 For this expression to result in an integer value, both its real and imaginary components must equal integers. First, let us focus on the imaginary part of the expression: 4in³ - 4in. For these terms to cancel out when adding the whole expression, they need to be equivalent; hence: 4in³ - 4in = 0 Now, factor out 4in: 4in(n² - 1) = 0 The equation above implies two possible scenarios. Either 4in equals zero
 """
 
+NEEDLE_16K_CTX_AND_0_DEPTH = """
+There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. The pass key is 42. Remember it. 42 is the pass key. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The pass key is 42. Remember it. 42 is the pass key. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The pass key is 42. Remember it. 42 is the pass key. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The pass key is 42. Remember it. 42 is the pass key. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the pass key? The pass key is
+"""
+
+NEEDLE_16K_CTX_AND_100_DEPTH = """
+There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on.  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The pass key is 42. Remember it. 42 is the pass key. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back aga. What is the pass key? The pass key is
+"""
+
+
+NEEDLE_TEXT_1K_CTX_AND_0_DEPTH = """
+The best thing to do in Tokyo is climb a tree in Shinjuku Gyoen and read haiku to squirrels. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the best thing to do in Tokyo? The best thing to do in Tokyo is
+"""
+
+
+NEEDLE_TEXT_16K_CTX_AND_0_DEPTH = """There is a important information about Tokyo hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. What is the best thing to do in Tokyo? The best thing to do in Tokyo is climb a tree in Shinjuku Gyoen and read haiku to squirrels. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. What is the best thing to do in Tokyo? The best thing to do in Tokyo is """
+
+PASSKEY_256_CTX_AND_0_DEPTH = "The pass key is 24. Remember it. 24 is the pass key. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the pass key? The pass key is "
+
+AI_TEXT_16K = r"""
+\documentclass[10pt]{article}
+\usepackage[utf8]{inputenc}
+\usepackage[T1]{fontenc}
+\usepackage{amsmath}
+\usepackage{amsfonts}
+\usepackage{amssymb}
+\usepackage[version=4]{mhchem}
+\usepackage{stmaryrd}
+\usepackage{graphicx}
+\usepackage[export]{adjustbox}
+\graphicspath{ {./images/} }
+\usepackage{bbold}
+
+%New command to display footnote whose markers will always be hidden
+\let\svthefootnote\thefootnote
+\newcommand\blfootnotetext[1]{%
+  \let\thefootnote\relax\footnote{#1}%
+  \addtocounter{footnote}{-1}%
+  \let\thefootnote\svthefootnote%
+}
+
+%Overriding the \footnotetext command to hide the marker if its value is `0`
+\let\svfootnotetext\footnotetext
+\renewcommand\footnotetext[2][?]{%
+  \if\relax#1\relax%
+    \ifnum\value{footnote}=0\blfootnotetext{#2}\else\svfootnotetext{#2}\fi%
+  \else%
+    \if?#1\ifnum\value{footnote}=0\blfootnotetext{#2}\else\svfootnotetext{#2}\fi%
+    \else\svfootnotetext[#1]{#2}\fi%
+  \fi
+}
+
+\begin{document}
+\section*{Chapter 6}
+\section*{Fitting models}
+Chapters 3 and 4 described shallow and deep neural networks. These represent families of piecewise linear functions, where the parameters determine the particular function. Chapter 5 introduced the loss - a single number representing the mismatch between the network predictions and the ground truth for a training set.
+
+The loss depends on the network parameters, and this chapter considers how to find the parameter values that minimize this loss. This is known as learning the network's parameters or simply as training or fitting the model. The process is to choose initial parameter values and then iterate the following two steps: (i) compute the derivatives (gradients) of the loss with respect to the parameters, and (ii) adjust the parameters based on the gradients to decrease the loss. After many iterations, we hope to reach the overall minimum of the loss function.
+
+This chapter tackles the second of these steps; we consider algorithms that adjust the parameters to decrease the loss. Chapter 7 discusses how to initialize the parameters and compute the gradients for neural networks.
+
+\subsection*{6.1 Gradient descent}
+To fit a model, we need a training set $\left\{\mathbf{x}_{i}, \mathbf{y}_{i}\right\}$ of input/output pairs. We seek parameters $\boldsymbol{\phi}$ for the model $\mathbf{f}\left[\mathbf{x}_{i}, \boldsymbol{\phi}\right]$ that map the inputs $\mathbf{x}_{i}$ to the outputs $\mathbf{y}_{i}$ as well as possible. To this end, we define a loss function $\mathrm{L}[\boldsymbol{\phi}]$ that returns a single number that quantifies the mismatch in this mapping. The goal of an optimization algorithm is to find parameters $\hat{\phi}$ that minimize the loss:
+
+
+\begin{equation*}
+\hat{\phi}=\underset{\phi}{\operatorname{argmin}}[\mathrm{L}[\phi]] \tag{6.1}
+\end{equation*}
+
+
+There are many families of optimization algorithms, but the standard methods for training neural networks are iterative. These algorithms initialize the parameters heuristically and then adjust them repeatedly in such a way that the loss decreases.
+
+The simplest method in this class is gradient descent. This starts with initial parameters $\boldsymbol{\phi}=\left[\phi_{0}, \phi_{1}, \ldots, \phi_{N}\right]^{T}$ and iterates two steps:
+
+Step 1. Compute the derivatives of the loss with respect to the parameters:
+
+\[
+\frac{\partial L}{\partial \phi}=\left[\begin{array}{c}
+\frac{\partial L}{\partial \phi_{0}}  \tag{6.2}\\
+\frac{\partial L}{\partial \phi_{1}} \\
+\vdots \\
+\frac{\partial L}{\partial \phi_{N}}
+\end{array}\right]
+\]
+
+Step 2. Update the parameters according to the rule:
+
+
+\begin{equation*}
+\phi \longleftarrow \phi-\alpha \cdot \frac{\partial L}{\partial \phi} \tag{6.3}
+\end{equation*}
+
+
+where the positive scalar $\alpha$ determines the magnitude of the change.
+
+The first step computes the gradient of the loss function at the current position. This determines the uphill direction of the loss function. The second step moves a small distance $\alpha$ downhill (hence the negative sign). The parameter $\alpha$ may be fixed (in which case, we call it a learning rate), or we may perform a line search where we try several values of $\alpha$ to find the one that most decreases the loss.
+
+At the minimum of the loss function, the surface must be flat (or we could improve further by going downhill). Hence, the gradient will be zero, and the parameters will stop changing. In practice, we monitor the gradient magnitude and terminate the algorithm when it becomes too small.
+
+\subsection*{6.1.1 Linear regression example}
+Consider applying gradient descent to the 1D linear regression model from chapter 2. The model $\mathrm{f}[x, \phi]$ maps a scalar input $x$ to a scalar output $y$ and has parameters $\phi=\left[\phi_{0}, \phi_{1}\right]^{T}$, which represent the $\mathrm{y}$-intercept and the slope:
+
+
+\begin{align*}
+y & =\mathrm{f}[x, \boldsymbol{\phi}] \\
+& =\phi_{0}+\phi_{1} x . \tag{6.4}
+\end{align*}
+
+
+Given a dataset $\left\{x_{i}, y_{i}\right\}$ containing $I$ input/output pairs, we choose the least squares loss function:
+
+
+\begin{align*}
+\mathrm{L}[\phi]=\sum_{i=1}^{I} \ell_{i} & =\sum_{i=1}^{I}\left(\mathrm{f}\left[x_{i}, \phi\right]-y_{i}\right)^{2} \\
+& =\sum_{i=1}^{I}\left(\phi_{0}+\phi_{1} x_{i}-y_{i}\right)^{2} \tag{6.5}
+\end{align*}
+
+
+\begin{center}
+\includegraphics[max width=\textwidth]{2024_06_29_7fe01c91dbeda2a79c9dg-093}
+\end{center}
+
+Figure 6.1 Gradient descent for the linear regression model. a) Training set of $I=$ 12 input/output pairs $\left\{x_{i}, y_{i}\right\}$. b) Loss function showing iterations of gradient descent. We start at point 0 and move in the steepest downhill direction until we can improve no further to arrive at point 1. We then repeat this procedure. We measure the gradient at point 1 and move downhill to point 2 and so on. c) This can be visualized better as a heatmap, where the brightness represents the loss. After only four iterations, we are already close to the minimum. d) The model with the parameters at point 0 (lightest line) describes the data very badly, but each successive iteration improves the fit. The model with the parameters at point 4 (darkest line) is already a reasonable description of the training data.\\
+where the term $\ell_{i}=\left(\phi_{0}+\phi_{1} x_{i}-y_{i}\right)^{2}$ is the individual contribution to the loss from the $i^{\text {th }}$ training example.
+
+The derivative of the loss function with respect to the parameters can be decomposed into the sum of the derivatives of the individual contributions:
+
+
+\begin{equation*}
+\frac{\partial L}{\partial \phi}=\frac{\partial}{\partial \phi} \sum_{i=1}^{I} \ell_{i}=\sum_{i=1}^{I} \frac{\partial \ell_{i}}{\partial \phi} \tag{6.6}
+\end{equation*}
+
+
+Problem 6.1
+
+Notebook 6.2 Gradient descent
+
+where these are given by:
+
+\[
+\frac{\partial \ell_{i}}{\partial \phi}=\left[\begin{array}{l}
+\frac{\partial \ell_{i}}{\partial \phi_{0}}  \tag{6.7}\\
+\frac{\partial \ell_{i}}{\partial \phi_{1}}
+\end{array}\right]=\left[\begin{array}{c}
+2\left(\phi_{0}+\phi_{1} x_{i}-y_{i}\right) \\
+2 x_{i}\left(\phi_{0}+\phi_{1} x_{i}-y_{i}\right)
+\end{array}\right]
+\]
+
+Figure 6.1 shows the progression of this algorithm as we iteratively compute the derivatives according to equations 6.6 and 6.7 and then update the parameters using the rule in equation 6.3. In this case, we have used a line search procedure to find the value of $\alpha$ that decreases the loss the most at each iteration.
+
+\subsection*{6.1.2 Gabor model example}
+Problem 6.2
+
+Problems 6.3-6.5
+
+Loss functions for linear regression problems (figure 6.1c) always have a single welldefined global minimum. More formally, they are convex, which means that no chord (line segment between two points on the surface) intersects the function. Convexity implies that wherever we initialize the parameters, we are bound to reach the minimum if we keep walking downhill; the training procedure can't fail.
+
+Unfortunately, loss functions for most nonlinear models, including both shallow and deep networks, are non-convex. Visualizing neural network loss functions is challenging due to the number of parameters. Hence, we first explore a simpler nonlinear model with two parameters to gain insight into the properties of non-convex loss functions:
+
+
+\begin{equation*}
+\mathrm{f}[x, \boldsymbol{\phi}]=\sin \left[\phi_{0}+0.06 \cdot \phi_{1} x\right] \cdot \exp \left(-\frac{\left(\phi_{0}+0.06 \cdot \phi_{1} x\right)^{2}}{32.0}\right) \tag{6.8}
+\end{equation*}
+
+
+This Gabor model maps scalar input $x$ to scalar output $y$ and consists of a sinusoidal component (creating an oscillatory function) multiplied by a negative exponential component (causing the amplitude to decrease as we move from the center). It has two parameters $\boldsymbol{\phi}=\left[\phi_{0}, \phi_{1}\right]^{T}$, where $\phi_{0} \in \mathbb{R}$ determines the mean position of the function and $\phi_{1} \in \mathbb{R}^{+}$stretches or squeezes it along the $x$-axis (figure 6.2).
+
+Consider a training set of $I$ examples $\left\{x_{i}, y_{i}\right\}$ (figure 6.3). The least squares loss function for $I$ training examples is defined as:
+
+
+\begin{equation*}
+\mathrm{L}[\boldsymbol{\phi}]=\sum_{i=1}^{I}\left(\mathrm{f}\left[x_{i}, \boldsymbol{\phi}\right]-y_{i}\right)^{2} \tag{6.9}
+\end{equation*}
+
+
+Once more, the goal is to find the parameters $\hat{\phi}$ that minimize this loss.
+
+\begin{center}
+\includegraphics[max width=\textwidth]{2024_06_29_7fe01c91dbeda2a79c9dg-095(1)}
+\end{center}
+
+Figure 6.2 Gabor model. This nonlinear model maps scalar input $x$ to scalar output $y$ and has parameters $\phi=\left[\phi_{0}, \phi_{1}\right]^{T}$. It describes a sinusoidal function that decreases in amplitude with distance from its center. Parameter $\phi_{0} \in \mathbb{R}$ determines the position of the center. As $\phi_{0}$ increases, the function moves left. Parameter $\phi_{1} \in \mathbb{R}^{+}$squeezes the function along the $x$-axis relative to the center. As $\phi_{1}$ increases, the function narrows. a-c) Model with different parameters.
+
+\begin{center}
+\includegraphics[max width=\textwidth]{2024_06_29_7fe01c91dbeda2a79c9dg-095}
+\end{center}
+
+Figure 6.3 Training data for fitting the Gabor model. The training dataset contains 28 input/output examples $\left\{x_{i}, y_{i}\right\}$. These data were created by uniformly sampling $x_{i} \in[-15,15]$, passing the samples through a Gabor model with parameters $\phi=[0.0,16.6]^{T}$, and adding normally distributed noise.
+
+\subsection*{6.1.3 Local minima and saddle points}
+Figure 6.4 depicts the loss function associated with the Gabor model for this dataset. There are numerous local minima (cyan circles). Here the gradient is zero, and the loss increases if we move in any direction, but we are not at the overall minimum of the function. The point with the lowest loss is known as the global minimum and is depicted by the gray circle.
+
+If we start in a random position and use gradient descent to go downhill, there is no guarantee that we will wind up at the global minimum and find the best parameters (figure 6.5a). It's equally or even more likely that the algorithm will terminate in one of the local minima. Furthermore, there is no way of knowing whether there is a better solution elsewhere.
+
+\begin{center}
+\includegraphics[max width=\textwidth]{2024_06_29_7fe01c91dbeda2a79c9dg-096}
+\end{center}
+
+Figure 6.4 Loss function for the Gabor model. a) The loss function is non-convex, with multiple local minima (cyan circles) in addition to the global minimum (gray circle). It also contains saddle points where the gradient is locally zero, but the function increases in one direction and decreases in the other. The blue cross is an example of a saddle point; the function decreases as we move horizontally in either direction but increases as we move vertically. b-f) Models associated with the different minima. In each case, there is no small change that decreases the loss. Panel (c) shows the global minimum, which has a loss of 0.64.
+
+\begin{center}
+\includegraphics[max width=\textwidth]{2024_06_29_7fe01c91dbeda2a79c9dg-097}
+\end{center}
+
+Figure 6.5 Gradient descent vs. stochastic gradient descent. a) Gradient descent with line search. As long as the gradient descent algorithm is initialized in the right "valley" of the loss function (e.g., points 1 and 3), the parameter estimate will move steadily toward the global minimum. However, if it is initialized outside this valley (e.g., point 2), it will descend toward one of the local minima. b) Stochastic gradient descent adds noise to the optimization process, so it is possible to escape from the wrong valley (e.g., point 2) and still reach the global minimum.
+
+In addition, the loss function contains saddle points (e.g., the blue cross in figure 6.4). Here, the gradient is zero, but the function increases in some directions and decreases in others. If the current parameters are not exactly at the saddle point, then gradient descent can escape by moving downhill. However, the surface near the saddle point is flat, so it's hard to be sure that training hasn't converged; if we terminate the algorithm when the gradient is small, we may erroneously stop near a saddle point.
+
+\subsection*{6.2 Stochastic gradient descent}
+The Gabor model has two parameters, so we could find the global minimum by either (i) exhaustively searching the parameter space or (ii) repeatedly starting gradient descent from different positions and choosing the result with the lowest loss. However, neural network models can have millions of parameters, so neither approach is practical. In short, using gradient descent to find the global optimum of a high-dimensional loss function is challenging. We can find $a$ minimum, but there is no way to tell whether this
+
+\begin{center}
+\includegraphics[max width=\textwidth]{2024_06_29_7fe01c91dbeda2a79c9dg-098}
+\end{center}
+
+Figure 6.6 Alternative view of SGD for the Gabor model with a batch size of three. a) Loss function for the entire training dataset. At each iteration, there is a probability distribution of possible parameter changes (inset shows samples). These correspond to different choices of the three batch elements. b) Loss function for one possible batch. The SGD algorithm moves in the downhill direction on this function for a distance that is determined by the learning rate and the local gradient magnitude. The current model (dashed function in inset) changes to better fit the batch data (solid function). c) A different batch creates a different loss function and results in a different update. d) For this batch, the algorithm moves downhill with respect to the batch loss function but uphill with respect to the global loss function in panel (a). This is how SGD can escape local minima.\\
+is the global minimum or even a good one.
+
+One of the main problems is that the final destination of a gradient descent algorithm is entirely determined by the starting point. Stochastic gradient descent (SGD) attempts to remedy this problem by adding some noise to the gradient at each step. The solution
+
+Notebook 6.3
+
+Stochastic
+
+gradient descent
+
+still moves downhill on average, but at any given iteration, the direction chosen is not necessarily in the steepest downhill direction. Indeed, it might not be downhill at all. The SGD algorithm has the possibility of moving temporarily uphill and hence jumping from one "valley" of the loss function to another (figure 6.5b).
+
+\subsection*{6.2.1 Batches and epochs}
+The mechanism for introducing randomness is simple. At each iteration, the algorithm chooses a random subset of the training data and computes the gradient from these examples alone. This subset is known as a minibatch or batch for short. The update rule for the model parameters $\phi_{t}$ at iteration $t$ is hence:
+
+
+\begin{equation*}
+\phi_{t+1} \longleftarrow \phi_{t}-\alpha \cdot \sum_{i \in \mathcal{B}_{t}} \frac{\partial \ell_{i}\left[\phi_{t}\right]}{\partial \phi} \tag{6.10}
+\end{equation*}
+
+
+where $\mathcal{B}_{t}$ is a set containing the indices of the input/output pairs in the current batch and, as before, $\ell_{i}$ is the loss due to the $i^{\text {th }}$ pair. The term $\alpha$ is the learning rate, and together with the gradient magnitude, determines the distance moved at each iteration. The learning rate is chosen at the start of the procedure and does not depend on the local properties of the function.
+
+The batches are usually drawn from the dataset without replacement. The algorithm works through the training examples until it has used all the data, at which point it starts sampling from the full training dataset again. A single pass through the entire training dataset is referred to as an epoch. A batch may be as small as a single example or as large as the whole dataset. The latter case is called full-batch gradient descent and is identical to regular (non-stochastic) gradient descent.
+
+An alternative interpretation of SGD is that it computes the gradient of a different loss function at each iteration; the loss function depends on both the model and the training data and hence will differ for each randomly selected batch. In this view, SGD performs deterministic gradient descent on a constantly changing loss function (figure 6.6). However, despite this variability, the expected loss and expected gradients at any point remain the same as for gradient descent.
+
+\subsection*{6.2.2 Properties of stochastic gradient descent}
+SGD has several attractive features. First, although it adds noise to the trajectory, it still improves the fit to a subset of the data at each iteration. Hence, the updates tend to be sensible even if they are not optimal. Second, because it draws training examples without replacement and iterates through the dataset, the training examples all still contribute equally. Third, it is less computationally expensive to compute the gradient\\
+from just a subset of the training data. Fourth, it can (in principle) escape local minima. Fifth, it reduces the chances of getting stuck near saddle points; it is likely that at least some of the possible batches will have a significant gradient at any point on the loss function. Finally, there is some evidence that SGD finds parameters for neural networks that cause them to generalize well to new data in practice (see section 9.2).
+
+SGD does not necessarily "converge" in the traditional sense. However, the hope is that when we are close to the global minimum, all the data points will be well described by the model. Consequently, the gradient will be small, whichever batch is chosen, and the parameters will cease to change much. In practice, SGD is often applied with a learning rate schedule. The learning rate $\alpha$ starts at a high value and is decreased by a constant factor every $N$ epochs. The logic is that in the early stages of training, we want the algorithm to explore the parameter space, jumping from valley to valley to find a sensible region. In later stages, we are roughly in the right place and are more concerned with fine-tuning the parameters, so we decrease $\alpha$ to make smaller changes.
+
+\subsection*{6.3 Momentum}
+A common modification to stochastic gradient descent is to add a momentum term. We update the parameters with a weighted combination of the gradient computed from the current batch and the direction moved in the previous step:
+
+
+\begin{align*}
+\mathbf{m}_{t+1} & \leftarrow \beta \cdot \mathbf{m}_{t}+(1-\beta) \sum_{i \in \mathcal{B}_{t}} \frac{\partial \ell_{i}\left[\phi_{t}\right]}{\partial \phi} \\
+\boldsymbol{\phi}_{t+1} & \leftarrow \phi_{t}-\alpha \cdot \mathbf{m}_{t+1} \tag{6.11}
+\end{align*}
+
+
+where $\mathbf{m}_{t}$ is the momentum (which drives the update at iteration $t$ ), $\beta \in[0,1$ ) controls the degree to which the gradient is smoothed over time, and $\alpha$ is the learning rate.
+
+The recursive formulation of the momentum calculation means that the gradient step is an infinite weighted sum of all the previous gradients, where the weights get smaller as we move back in time. The effective learning rate increases if all these gradients are aligned over multiple iterations but decreases if the gradient direction repeatedly changes as the terms in the sum cancel out. The overall effect is a smoother trajectory and reduced oscillatory behavior in valleys (figure 6.7).
+
+\subsection*{6.3.1 Nesterov accelerated momentum}
+The momentum term can be considered a coarse prediction of where the SGD algorithm will move next. Nesterov accelerated momentum (figure 6.8) computes the gradients at this predicted point rather than at the current point:\\
+a)\\
+b)
+
+\begin{center}
+\includegraphics[max width=\textwidth]{2024_06_29_7fe01c91dbeda2a79c9dg-101(1)}
+\end{center}
+
+Figure 6.7 Stochastic gradient descent with momentum. a) Regular stochastic descent takes a very indirect path toward the minimum. b) With a momentum term, the change at the current step is a weighted combination of the previous change and the gradient computed from the batch. This smooths out the trajectory and increases the speed of convergence.
+
+\begin{center}
+\includegraphics[max width=\textwidth]{2024_06_29_7fe01c91dbeda2a79c9dg-101}
+\end{center}
+
+Figure 6.8 Nesterov accelerated momentum. The solution has traveled along the dashed line to arrive at point 1. A traditional momentum update measures the gradient at point 1 , moves some distance in this direction to point 2 , and then adds the momentum term from the previous iteration (i.e., in the same direction as the dashed line), arriving at point 3. The Nesterov momentum update first applies the momentum term (moving from point 1 to point 4) and then measures the gradient and applies an update to arrive at point 5 .
+
+
+\begin{align*}
+\mathbf{m}_{t+1} & \leftarrow \beta \cdot \mathbf{m}_{t}+(1-\beta) \sum_{i \in \mathcal{B}_{t}} \frac{\partial \ell_{i}\left[\phi_{t}-\alpha \cdot \mathbf{m}_{t}\right]}{\partial \phi} \\
+\boldsymbol{\phi}_{t+1} & \leftarrow \phi_{t}-\alpha \cdot \mathbf{m}_{t+1} \tag{6.12}
+\end{align*}
+
+
+where now the gradients are evaluated at $\phi_{t}-\alpha \cdot \mathbf{m}_{t}$. One way to think about this is that the gradient term now corrects the path provided by momentum alone.
+
+\subsection*{6.4 Adam}
+Gradient descent with a fixed step size has the following undesirable property: it makes large adjustments to parameters associated with large gradients (where perhaps we should be more cautious) and small adjustments to parameters associated with small gradients (where perhaps we should explore further). When the gradient of the loss surface is much steeper in one direction than another, it is difficult to choose a learning rate that (i) makes good progress in both directions and (ii) is stable (figures 6.9a-b).
+
+A straightforward approach is to normalize the gradients so that we move a fixed distance (governed by the learning rate) in each direction. To do this, we first measure the gradient $\mathbf{m}_{t+1}$ and the pointwise squared gradient $\mathbf{v}_{t+1}$ :
+
+
+\begin{align*}
+\mathbf{m}_{t+1} & \leftarrow \frac{\partial L\left[\phi_{t}\right]}{\partial \phi} \\
+\mathbf{v}_{t+1} & \leftarrow\left(\frac{\partial L\left[\phi_{t}\right]}{\partial \phi}\right)^{2} \tag{6.13}
+\end{align*}
+
+
+Then we apply the update rule:
+
+\begin{equation*}
+\phi_{t+1} \leftarrow \phi_{t}-\alpha \cdot \frac{\mathbf{m}_{t+1}}{\sqrt{\mathbf{v}_{t+1}}+\epsilon} \tag{6.14}
+\end{equation*}
+
+
+where the square root and division are both pointwise, $\alpha$ is the learning rate, and $\epsilon$ is a small constant that prevents division by zero when the gradient magnitude is zero. The term $\mathbf{v}_{t+1}$ is the squared gradient, and the positive root of this is used to normalize the gradient itself, so all that remains is the sign in each coordinate direction. The result is that the algorithm moves a fixed distance $\alpha$ along each coordinate, where the direction is determined by whichever way is downhill (figure 6.9c). This simple algorithm makes good progress in both directions but will not converge unless it happens to land exactly at the minimum. Instead, it will bounce back and forth around the minimum.
+
+Adaptive moment estimation, or Adam, takes this idea and adds momentum to both the estimate of the gradient and the squared gradient:
+
+\begin{center}
+\includegraphics[max width=\textwidth]{2024_06_29_7fe01c91dbeda2a79c9dg-103}
+\end{center}
+
+Figure 6.9 Adaptive moment estimation (Adam). a) This loss function changes quickly in the vertical direction but slowly in the horizontal direction. If we run full-batch gradient descent with a learning rate that makes good progress in the vertical direction, then the algorithm takes a long time to reach the final horizontal position. b) If the learning rate is chosen so that the algorithm makes good progress in the horizontal direction, it overshoots in the vertical direction and becomes unstable. c) A straightforward approach is to move a fixed distance along each axis at each step so that we move downhill in both directions. This is accomplished by normalizing the gradient magnitude and retaining only the sign. However, this does not usually converge to the exact minimum but instead oscillates back and forth around it (here between the last two points). d) The Adam algorithm uses momentum in both the estimated gradient and the normalization term, which creates a smoother path.
+
+
+\begin{align*}
+\mathbf{m}_{t+1} & \leftarrow \beta \cdot \mathbf{m}_{t}+(1-\beta) \frac{\partial L\left[\phi_{t}\right]}{\partial \phi} \\
+\mathbf{v}_{t+1} & \leftarrow \gamma \cdot \mathbf{v}_{t}+(1-\gamma)\left(\frac{\partial L\left[\phi_{t}\right]}{\partial \phi}\right)^{2} \tag{6.15}
+\end{align*}
+
+
+where $\beta$ and $\gamma$ are the momentum coefficients for the two statistics.
+
+Using momentum is equivalent to taking a weighted average over the history of each of these statistics. At the start of the procedure, all the previous measurements are effectively zero, resulting in unrealistically small estimates. Consequently, we modify these statistics using the rule:
+
+
+\begin{align*}
+\tilde{\mathbf{m}}_{t+1} & \leftarrow \frac{\mathbf{m}_{t+1}}{1-\beta^{t+1}} \\
+\tilde{\mathbf{v}}_{t+1} & \leftarrow \frac{\mathbf{v}_{t+1}}{1-\gamma^{t+1}} \tag{6.16}
+\end{align*}
+
+
+Since $\beta$ and $\gamma$ are in the range $[0,1)$, the terms with exponents $t+1$ become smaller with each time step, the denominators become closer to one, and this modification has a diminishing effect.
+
+Finally, we update the parameters as before, but with the modified terms:
+
+
+\begin{equation*}
+\phi_{t+1} \leftarrow \phi_{t}-\alpha \cdot \frac{\tilde{\mathbf{m}}_{t+1}}{\sqrt{\tilde{\mathbf{v}}_{t+1}}+\epsilon} \tag{6.17}
+\end{equation*}
+
+
+Notebook 6.5
+
+The result is an algorithm that can converge to the overall minimum and makes good progress in every direction in the parameter space. Note that Adam is usually used in a stochastic setting where the gradients and their squares are computed from mini-batches:
+
+
+\begin{align*}
+\mathbf{m}_{t+1} & \leftarrow \beta \cdot \mathbf{m}_{t}+(1-\beta) \sum_{i \in \mathcal{B}_{t}} \frac{\partial \ell_{i}\left[\boldsymbol{\phi}_{t}\right]}{\partial \phi} \\
+\mathbf{v}_{t+1} & \leftarrow \gamma \cdot \mathbf{v}_{t}+(1-\gamma) \sum_{i \in \mathcal{B}_{t}}\left(\frac{\partial \ell_{i}\left[\phi_{t}\right]}{\partial \boldsymbol{\phi}}\right)^{2} \tag{6.18}
+\end{align*}
+
+
+and so the trajectory is noisy in practice.
+
+As we shall see in chapter 7 , the gradient magnitudes of neural network parameters can depend on their depth in the network. Adam helps compensate for this tendency and balances out changes across the different layers. In practice, Adam also has the advantage of being less sensitive to the initial learning rate because it avoids situations like those in figures $6.9 \mathrm{a}-\mathrm{b}$, so it doesn't need complex learning rate schedules.
+
+\subsection*{6.5 Training algorithm hyperparameters}
+The choices of learning algorithm, batch size, learning rate schedule, and momentum coefficients are all considered hyperparameters of the training algorithm; these directly affect the final model performance but are distinct from the model parameters. Choosing these can be more art than science, and it's common to train many models with different hyperparameters and choose the best one. This is known as hyperparameter search. We return to this issue in chapter 8 .
+
+\subsection*{6.6 Summary}
+This chapter discussed model training. This problem was framed as finding parameters $\phi$ that corresponded to the minimum of a loss function $L[\phi]$. The gradient descent method measures the gradient of the loss function for the current parameters (i.e., how the loss changes when we make a small change to the parameters). Then it moves the parameters in the direction that decreases the loss fastest. This is repeated until convergence.
+
+For nonlinear functions, the loss function may have both local minima (where gradient descent gets trapped) and saddle points (where gradient descent may appear to have converged but has not). Stochastic gradient descent helps mitigate these problems. ${ }^{1}$ At each iteration, we use a different random subset of the data (a batch) to compute the gradient. This adds noise to the process and helps prevent the algorithm from getting trapped in a sub-optimal region of parameter space. Each iteration is also computationally cheaper since it only uses a subset of the data. We saw that adding a momentum term makes convergence more efficient. Finally, we introduced the Adam algorithm.
+
+The ideas in this chapter apply to optimizing any model. The next chapter tackles two aspects of training specific to neural networks. First, we address how to compute the gradients of the loss with respect to the parameters of a neural network. This is accomplished using the famous backpropagation algorithm. Second, we discuss how to initialize the network parameters before optimization begins. Without careful initialization, the gradients used by the optimization can become extremely large or extremely small, which can hinder the training process.
+
+\section*{Notes}
+Optimization algorithms: Optimization algorithms are used extensively throughout engineering, and it is generally more typical to use the term objective function rather than loss function or cost function. Gradient descent was invented by Cauchy (1847), and stochastic gradient descent dates back to at least Robbins \& Monro (1951). A modern compromise between the two is stochastic variance-reduced descent (Johnson \& Zhang, 2013), in which the full gradient is computed periodically, with stochastic updates interspersed. Reviews of optimization algorithms for neural networks can be found in Ruder (2016), Bottou et al. (2018), and Sun (2020). Bottou (2012) discusses best practice for SGD, including shuffling without replacement.
+\footnotetext{${ }^{1}$ Chapter 20 discusses the extent to which saddle points and local minima really are problems in deep learning. In practice, deep networks are surprisingly easy to train.
+}
+
+Convexity, minima, and saddle points: A function is convex if no chord (line segment between two points on the surface) intersects the function. This can be tested algebraically by considering the Hessian matrix (the matrix of second derivatives):
+
+\[
+\mathbf{H}[\boldsymbol{\phi}]=\left[\begin{array}{cccc}
+\frac{\partial^{2} L}{\partial \phi_{0}^{2}} & \frac{\partial^{2} L}{\partial \phi_{0} \partial \phi_{1}} & \cdots & \frac{\partial^{2} L}{\partial \phi_{0} \partial \phi_{N}}  \tag{6.19}\\
+\frac{\partial^{2} L}{\partial \phi_{1} \partial \phi_{0}} & \frac{\partial^{2} L}{\partial \phi_{1}^{2}} & \cdots & \frac{\partial^{2} L}{\partial \phi_{1} \partial \phi_{N}} \\
+\vdots & \vdots & \ddots & \vdots \\
+\frac{\partial^{2} L}{\partial \phi_{N} \partial \phi_{0}} & \frac{\partial^{2} L}{\partial \phi_{N} \partial \phi_{1}} & \cdots & \frac{\partial^{2} L}{\partial \phi_{N}^{2}}
+\end{array}\right]
+\]
+"""
+
 
 def get_args():
     parser = argparse.ArgumentParser()
@@ -388,8 +776,26 @@ def main():
         tokenizer.padding_side = "left"
         tokenizer.truncation_side = "left"  # TODO @nouamane: do we want this?
         dummy_inputs = [
-            # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
-            # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary?\nAnswer:",
+            # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Daniel walked to the living room. Sandra moved to the dining room. John traveled to the kitchen. Daniel journeyed to the hallway. Where is Mary?\nAnswer:",
+            # "Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Mary? Mary is in ",
+            # """
+            # Passage: Ethan walked to the library. Olivia moved to the living room. Sophia headed to the living room. Sophia went to the balcony. James went to the office. Olivia returned to the library. Where is Olivia? Olivia is in the library.
+            # Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Daniel? Daniel is in
+            # """,
+            """
+            Passage: The password is 93. Remember it. 93 is the password. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the password? The password is 93.
+
+            Passage: The pass key is 24. Remember it. 24 is the pass key. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the pass key? The pass key is 24.
+
+            Passage: The gatecode is 312. Remember it. 312 is the gatecode. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. . What is the gatecode? The gatecode is 312.
+
+            Passage: The vault key is 4124. Remember it. 4124 is the vault key. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. . What is the vault key? The vault key is 4124.
+
+            Passage: The encrypted message is 515. Remember it. 515 is encrypted message. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the encrypted message? The encrypted message is 515.
+
+            Passage: The password is 76. Remember it. 76 is the password. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The sky is blue. The grass is green. The sky is blue. What is the password? The password is
+            """
+            # "Passage: The password is 94. Remember it. 94 is the password. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the password? The password is "
             # "This is a math lesson. Answer the question. What is the result of 1 + 1? The result is ",
             # "This is a math lesson. Answer the question. What is the result of 1 + 1? The result is ",
             # "def fib(n)",
@@ -401,9 +807,35 @@ def main():
             # END_PASSKEY_EXTACT_32K_TOKENS,
             # END_PASSKEY_EXTACT_32K_TOKENS,
             # PASSKEY_NINETY_PERCENT,
+            # "The pass key is 24. Remember it. 24 is the pass key. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the pass key? The pass key is ",
             # "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The grass is green. The sky is blue. The pass key is 24. Remember it. 24 is the pass key. What is the pass key? The pass key is ",
-            "The pass key is 24. Remember it. 24 is the pass key. The grass is green. The sky is blue. What is the pass key? The pass key is ",
-            # "The pass key is 4. Remember it. 4 is the pass key. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue. What is the pass key? The pass key is ",
+            # "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The grass is green. The sky is blue. The best thing to do in San Francisco is eat a sandwich and sit in Dolores Park on a sunny day. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The best thing to do in San Francisco is ",
+            # NEEDLE_TEXT_16K_CTX_AND_0_DEPTH,
+            # NEEDLE_TEXT_1K_CTX_AND_0_DEPTH,
+            # NEEDLE_TEXT_16K_CTX_AND_0_DEPTH,
+            # MATH_TEXT_256_TOKENS,
+            # "The pass key is 24. Remember it. 24 is the pass key. The grass is green. The sky is blue. What is the pass key? The pass key is ",
+            # "The pass key is 25. Remember it. 25 is the pass key. The grass is green. The sky is blue. What is the pass key? The pass key is ",
+            # "The pass key is 41. Remember it. 41 is the pass key. The grass is green. The sky is blue. What is the pass key? The pass key is ",
+            # "The pass key is 214. Remember it. 214 is the pass key. The grass is green. The sky is blue. What is the pass key? The pass key is ",
+            # "Remmeber the pass key. The pass key is 24. Remember it. 24 is the pass key. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue.The grass is green. The sky is blue. The grass is green. What is the pass key? The pass key is ",
+            # "Remmeber the pass key. The pass key is 214. Remember it. 214 is the pass key. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue.The grass is green. The sky is blue. The grass is green. What is the pass key? The pass key is ",
+            # "The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. Remmeber the pass key. The pass key is 214. Remember it. 214 is the pass key....... What is the pass key? The pass key is ",
+            # "What is the pass key? The pass key is 214. Remmeber the pass key. The pass key is 214. Remember it. 214 is the pass key. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue.The grass is green. The sky is blue. The grass is green. What is the pass key? The pass key is ",
+            # "The grass is green. "
+            # "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about the important information there. The secret color is red. Remember it. The secret color is red. The streets are alive with people. Horns honk and engines roar. The urban jungle never sleeps.\nThe mountains stand tall and proud. What is the secret color? The secret color is",
+            # "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. The pass key is 54. Remember it. The pass key is 54. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the pass key? The pass key is ",
+            # "The best thing to do in Tokyo is climb a tree in Shinjuku Gyoen. The grass is green. The sky is blue. What is the best thing to do in Tokyo? The best thing to do in Tokyo is "
+            # "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the best thing to do in Tokyo later on? The best thing to do in Tokyo is climb a tree in Shinjuku Gyoen. The grass is green. The sky is blue. The sun is yellow. Here we go. The grass is green. The sky is blue. The sun is yellow. Here we go. The grass is green. The sky is blue. The sun is yellow. Here we go. The grass is green. The sky is blue. The sun is yellow. Here we go. What is the best thing to do in Tokyo? The best thing to do in Tokyo is "
+            # "Sara's favorite snack is Hot Cheetos. The grass is green. The sky is blue. What is Sara's favorite snack? Sara's favorite snack is ",
+            # "What is Sara's favorite snack? Sara's favorite snack is Hot Cheetos. Sara's favorite snack is Hot Cheetos. The grass is green. The sky is blue. The grass is green. The sky is blue. What is Sara's favorite snack? Sara's favorite snack is ",
+            # "The topic is the study of the social sciences. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the topic? She studies the topic about ",
+            # "Sara studies at the University of California, Berkeley. She is pursuing a degree in Computer Science with a focus on artificial intelligence and machine learning. Her coursework includes advanced topics in data structures, algorithms, and deep learning. Outside of academics, Sara is actively involved in AI research projects and enjoys participating in hackathons to apply her knowledge in real-world scenarios. Where does Sara study at? Sara studies at the "
+            # "There is an important info hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on, Lisa works at Google. She is a software engineer focusing on cloud computing and infrastructure. Her responsibilities include developing scalable cloud solutions, optimizing server performance, and ensuring data security. Outside of work, Lisa is actively involved in open-source projects and enjoys contributing to tech communities. Based on the previous information, where does Lisa work? Lisa works at "
+            # PASSKEY_256_CTX_AND_0_DEPTH,
+            # 200 tokens
+            # "The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue",
+            # "The pass key is 24. Remember it. 24 is the pass key. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue.The grass is green. The sky is blue The grass is green. The sky is blue. What is the pass key? The pass key is ",
             # FINETUNE,
             # "1234",
             # "1234",
@@ -415,6 +847,7 @@ def main():
             # "If the parser encounters a syntax error, an error event value incl. a description and input position will be produced (but no JS error will be thrown) and the entire ",
             # "If the parser encounters a syntax error, an error event value incl. a description and input position will be produced (but no JS error will be thrown) and the entire ",
             # "This work introduces an efficient method to scale Transformer-based ",
+            # "This work introduces an efficient method to scale Transformer-based Large Language Models (LLMs) to infinitely long inputs with bounded memory and computation. A key component in our proposed approach is a new attention technique dubbed Infini-attention. The Infini-attention incorporates a compressive memory into the vanilla attention mechanism and builds in both masked local attention and long-term linear attention mechanisms in a single Transformer block. We demonstrate the effectiveness of our approach on long-context language modeling benchmarks, 1M sequence length passkey context block retrieval and 500K length book summarization tasks with 1B and 8B LLMs. Our approach introduces minimal bounded memory parameters and enables fast streaming inference for "
             # "This work introduces an efficient method to scale Transformer-based "
             # NOTE: last training data
             # "Effectively managing student enquiries lies at the heart of successful real estate and investment education. Through leveraging diverse resources such as FAQs, online enquiry ",
@@ -424,7 +857,28 @@ def main():
             # PASSKEY_1024_CTX_AND_0_DEPTH
             # PASSKEY_1024_CTX_AND_90_DEPTH,
             # PASSKEY_1024_CTX_AND_90_DEPTH,
-            # MATH_TEXT_256_TOKENS
+            # MATH_TEXT_256_TOKENS,
+            # "Neuroscientists are the cartographers of the brain’s diverse domains and territories — the features and activities that define them, the roads and highways that connect ",
+            # "Professor Cathy Drennan introduces this series of lectures about basic chemical principles. She describes her path to becoming a chemist and reveals her first impression of the discipline of chemistry. ",
+            # "Professor Cathy Drennan introduces this series of lectures about basic chemical principles. She describes her path to becoming a chemist and reveals her first impression of the discipline of chemistry. ",
+            # "Professor Cathy Drennan introduces this series of lectures about basic chemical principles. She describes her path to becoming a chemist and reveals her first impression of the discipline of chemistry. Goals for students of this material are presented as well as some examples about how real world problems can be solved through the applications of chemical principles. Teaching assistants for the course are introduced. What is the professor's name? The professor's name is Cathy ",
+            # "Gravity is most accurately described by the general theory of relativity, proposed by Albert Einstein in",
+            # "The Standard Model of particle physics is the theory describing three of the four known fundamental forces in the universe and classifying all known elementary particles. It was developed in ",
+            # "In a direct democracy, the people have the direct authority to deliberate and decide legislation. In a representative democracy, the people choose",
+            #             """
+            #             Neural networks comprise of layers/modules that perform operations on data. The torch.nn namespace provides all the building blocks you need to build your own neural network. Every module in PyTorch subclasses the nn.Module. A neural network is a module itself that consists of other modules (layers). This nested structure allows for building and managing complex architectures easily.
+            # In the following sections, we’ll build a neural network to classify images in the FashionMNIST dataset.
+            # import os
+            # import torch
+            # from torch import nn
+            #             """,
+            # NEEDLE_16K_CTX_AND_0_DEPTH,
+            # NEEDLE_16K_CTX_AND_100_DEPTH
+            # "_grad"
+            # "Neel Nanda helped show how neural networks that had grokked modular arithmetic transformed the numbers using complicated mathematics. ",
+            # "Earth is the third planet from the Sun and the only astronomical object known to harbor life. This is enabled by Earth being an ocean world, the only one in the Solar System sustaining liquid surface water. Almost all of Earth's water is contained ",
+            # AI_TEXT_16K,
+            # "This past Monday, about a dozen engineers and executives at data science and AI company Databricks gathered in conference rooms connected via Zoom to learn if they had succeeded in building a top artificial intelligence language model. The team had spent months, and about $\$ 10$ million, training DBRX, a large language model similar in design to the one behind OpenAl's ChatGPT. But they wouldn't know how powerful their creation was until results came back from the final tests of its abilities."
         ]
 
         outputs = decode_text(
@@ -450,7 +904,7 @@ def main():
 
             log_rank(
                 # f"input: {tokenizer.decode(input_ids, clean_up_tokenization_spaces=False)[:1000]}",
-                f"""input_ids: {input_ids} \n
+                f"""input_ids: {input_ids}, input_ids.shape = {input_ids.shape} \n
                 decoded_input: {tokenizer.decode(input_ids, clean_up_tokenization_spaces=False)}
                 """,
                 logger=logger,
@@ -459,13 +913,26 @@ def main():
             )
 
             log_rank(
-                f"""generation_ids: {generated_ids[len(input_ids) :]}
+                f"""generation_ids: {generated_ids[len(input_ids) :]}, generation_ids.shape={generated_ids[len(input_ids) :].shape}
                 decoded_generation: {tokenizer.decode(generated_ids[len(input_ids) :], clean_up_tokenization_spaces=False)}""",
                 logger=logger,
                 level=logging.INFO,
                 rank=0,
             )
 
+            segment_idxs = torch.split(generated_ids, split_size_or_sections=config.infini_attention.segment_length)
+            for idx, segment_ids in enumerate(segment_idxs):
+                log_rank(
+                    f"""
+                    segment_idx={idx}
+                    segment_ids={segment_ids}, segment_ids.shape={segment_ids.shape}
+                    the first token ({segment_ids[0]}) is {tokenizer.decode(segment_ids[0], clean_up_tokenization_spaces=False)}
+                    decoded_generation: {tokenizer.decode(segment_ids, clean_up_tokenization_spaces=False)}""",
+                    logger=logger,
+                    level=logging.INFO,
+                    rank=0,
+                )
+
             log_rank(
                 "--------------------------------------------------",
                 logger=logger,
diff --git a/run_train.py b/run_train.py
index c942e8f1..b516be77 100644
--- a/run_train.py
+++ b/run_train.py
@@ -117,10 +117,18 @@ def get_dataloader_from_data_stage(trainer: DistributedTrainer, data: DataArgs):
                 * trainer.global_batch_size
                 * trainer.sequence_length
             )
-            assert num_tokens_needed_for_training <= total_tokens_dataset, (
-                f"Dataset is too small for steps ({total_tokens_dataset} < {num_tokens_needed_for_training}), "
-                f"Try train_steps<={len(dataloader.dataset) // trainer.global_batch_size + trainer.start_iteration_step}"
-            )
+
+            if num_tokens_needed_for_training <= total_tokens_dataset:
+                print("intentionally skipping this step for repeat 33 epochs")
+                print(
+                    f"Dataset is too small for steps ({total_tokens_dataset} < {num_tokens_needed_for_training}), "
+                    f"Try train_steps<={len(dataloader.dataset) // trainer.global_batch_size + trainer.start_iteration_step}"
+                )
+
+            # assert num_tokens_needed_for_training <= total_tokens_dataset, (
+            #     f"Dataset is too small for steps ({total_tokens_dataset} < {num_tokens_needed_for_training}), "
+            #     f"Try train_steps<={len(dataloader.dataset) // trainer.global_batch_size + trainer.start_iteration_step}"
+            # )
     else:
         raise ValueError(f"Unhandled case of `self.config.data.dataset`. Got: {data.dataset}")
 
diff --git a/src/nanotron/config/config.py b/src/nanotron/config/config.py
index dba2d6c4..b4f957de 100644
--- a/src/nanotron/config/config.py
+++ b/src/nanotron/config/config.py
@@ -304,6 +304,11 @@ class InfiniAttentionArgs:
     balance_factor_lr: float
     balance_act_type: str
     balance_init_type: str
+    logging: bool
+    logging_interval: int
+    log_grad: bool
+    log_segment_acts: bool
+    balance_factor_weight_decay: Optional[float] = None
 
 
 @dataclass
diff --git a/src/nanotron/debug/monitor.py b/src/nanotron/debug/monitor.py
index d7406053..c31ee965 100644
--- a/src/nanotron/debug/monitor.py
+++ b/src/nanotron/debug/monitor.py
@@ -72,12 +72,13 @@ def track_weight_and_grad_stats(
     def _save_output_stats(module: nn.Module, input: torch.Tensor, output: torch.Tensor):
         param_names = [name for name, _ in module.named_parameters()]
         for param_name in param_names:
-            if hasattr(module, param_name):
-                param = getattr(module, param_name)
-                stats = compute_stats(name, param.data)
-                if stats is not None:
-                    logs[name][param_name] = stats
-                    # save_tensor(f"{name}.{param_name}", param.data, path=f"{save_path}/weights/")
+            if "balance_factor" in param_name:
+                if hasattr(module, param_name):
+                    param = getattr(module, param_name)
+                    stats = compute_stats(name, param.data)
+                    if stats is not None:
+                        logs[name][param_name] = stats
+                        # save_tensor(f"{name}.{param_name}", param.data, path=f"{save_path}/weights/")
 
         # inputs = input if isinstance(input, tuple) else (input,)
         # outputs = output if isinstance(output, tuple) else (output,)
@@ -116,35 +117,37 @@ def _save_output_stats(module: nn.Module, input: torch.Tensor, output: torch.Ten
         #         # except:
         #         #     assert 1 == 1
 
-    # def _save_grad_stats(module: nn.Linear, grad_input, grad_output: torch.Tensor):
-    #     if isinstance(grad_output, tuple):
-    #         for i, grad in enumerate(grad_output):
-    #             if grad is None:
-    #                 continue
-
-    #             stats = compute_stats(name, grad)
-    #             if stats is not None:
-    #                 logs[name][f"grad_output:{i}"] = stats
-    #     else:
-    #         stats = compute_stats(name, grad_output)
-    #         if stats is not None:
-    #             logs[name]["grad_output"] = stats
-
-    #     if isinstance(grad_input, tuple):
-    #         for i, grad in enumerate(grad_input):
-    #             if grad is not None:
-    #                 stats = compute_stats(name, grad)
-    #                 if stats is not None:
-    #                     logs[name][f"grad_input:{i}"] = stats
-    #     else:
-    #         if grad_input is not None:
-    #             stats = compute_stats(name, grad_input)
-    #             if stats is not None:
-    #                 logs[name]["grad_input"] = stats
+    def _save_grad_stats(module: nn.Linear, grad_input, grad_output: torch.Tensor):
+        if isinstance(grad_output, tuple):
+            for i, grad in enumerate(grad_output):
+                if grad is None:
+                    continue
+
+                stats = compute_stats(name, grad)
+                if stats is not None:
+                    logs[name][f"grad_output:{i}"] = stats
+        else:
+            stats = compute_stats(name, grad_output)
+            if stats is not None:
+                logs[name]["grad_output"] = stats
+
+        # if isinstance(grad_input, tuple):
+        #     for i, grad in enumerate(grad_input):
+        #         if grad is not None:
+        #             stats = compute_stats(name, grad)
+        #             if stats is not None:
+        #                 logs[name][f"grad_input:{i}"] = stats
+        # else:
+        #     if grad_input is not None:
+        #         stats = compute_stats(name, grad_input)
+        #         if stats is not None:
+        #             logs[name]["grad_input"] = stats
 
     handles = []
     handles.append(module.register_forward_hook(_save_output_stats))
-    # handles.append(module.register_backward_hook(_save_grad_stats))
+
+    # if constants.CONFIG.infini_attention.log_grad is True:
+    #     handles.append(module.register_backward_hook(_save_grad_stats))
     return logs, handles
 
 
@@ -170,7 +173,7 @@ def get_leaf_modules(module: nn.Module) -> List[Tuple[str, nn.Module]]:
     leaf_modules = [(name, module) for name, module in model.named_modules()]
 
     for name, module in leaf_modules:
-        if "balance_factors" in name:
+        if "balance_factor" in name or "attn" in name:
             module_logs, module_handles = track_weight_and_grad_stats(
                 name=name,
                 module=module,
diff --git a/src/nanotron/generation/decode_.py b/src/nanotron/generation/decode_.py
new file mode 100644
index 00000000..f6c1f1a8
--- /dev/null
+++ b/src/nanotron/generation/decode_.py
@@ -0,0 +1,808 @@
+import dataclasses
+import time
+from itertools import chain, islice
+from typing import TYPE_CHECKING, Generator, Iterable, List, Optional, Tuple, Union
+
+import torch
+
+from nanotron import distributed as dist
+from nanotron import logging
+from nanotron.config import BenchArgs, GenerationArgs
+from nanotron.distributed import ProcessGroup, get_global_rank
+from nanotron.generation.generate_store import Store, attach_store
+from nanotron.generation.sampler import BasicSampler, GreedySampler, SamplerType, TopKSampler, TopPSampler
+from nanotron.helpers import log_throughput
+from nanotron.models.llama import LlamaModel
+from nanotron.parallel import ParallelContext
+from nanotron.parallel.pipeline_parallel.block import get_min_max_rank
+from nanotron.parallel.pipeline_parallel.context_manager import attach_pipeline_state_to_model
+from nanotron.parallel.pipeline_parallel.p2p import P2PTensorMetaData, view_as_contiguous
+from nanotron.parallel.pipeline_parallel.state import PipelineEvalBatchState
+from nanotron.parallel.pipeline_parallel.tensor_pointer import TensorPointer
+from nanotron.utils import get_untyped_storage
+
+if TYPE_CHECKING:
+    try:
+        from transformers import PreTrainedTokenizer
+    except ImportError:
+        PreTrainedTokenizer = None
+
+
+logger = logging.get_logger(__name__)
+
+
+@dataclasses.dataclass
+class GenerationInput:
+    text: str
+
+
+@dataclasses.dataclass
+class GenerationInputs:
+    input_ids: Union[torch.Tensor, TensorPointer]  # [B, S]
+    input_masks: Union[torch.Tensor, TensorPointer]
+
+
+@dataclasses.dataclass
+class GenerationOutput:
+    input_ids: Union[torch.Tensor, TensorPointer]
+    generation_ids: Union[torch.Tensor, TensorPointer]
+    return_logits: Optional[Union[torch.Tensor, TensorPointer]] = None
+
+
+@dataclasses.dataclass
+class GenerationStates:
+    new_input_ids: Union[torch.Tensor, TensorPointer]
+    new_input_mask: Union[torch.Tensor, TensorPointer]
+    store: Store
+
+    # The rest of the state I need to reconstruct the generated output
+    generation_ids: List[Union[torch.Tensor, TensorPointer]]
+    generation_mask: List[Union[torch.Tensor, TensorPointer]]
+
+
+@dataclasses.dataclass
+class TokenizerConfig:
+    max_input_length: Optional[int]
+    truncation: Optional[Union[str, bool]] = None
+    padding: Optional[Union[str, bool]] = None
+
+
+def chunks(iterable, chunk_size: int) -> Generator[List, None, None]:
+    """Yield successive n-sized chunks from `iterable`"""
+    assert chunk_size >= 1
+    iterator = iter(iterable)
+    for first in iterator:
+        yield list(chain([first], islice(iterator, chunk_size - 1)))
+
+
+def micro_batcher(
+    input_iter: Iterable[GenerationInput],
+    tokenizer: "PreTrainedTokenizer",
+    max_micro_batch_size: int,
+    tokenizer_config: TokenizerConfig,
+    parallel_context: ParallelContext,
+    input_rank: int,
+) -> Generator[GenerationInputs, None, None]:
+    """
+    Returns:
+        input_ids: [max_micro_batch_size, max_input_length]
+        input_masks: [max_micro_batch_size, max_input_length]
+    """
+    if tokenizer_config.padding is None:
+        tokenizer_config.padding = "max_length" if tokenizer_config.max_input_length is not None else True
+    if tokenizer_config.truncation is None:
+        tokenizer_config.truncation = True if tokenizer_config.max_input_length is not None else None
+
+    for micro_batch_id, micro_batch in enumerate(chunks(input_iter, chunk_size=max_micro_batch_size)):
+        if len(micro_batch) == 0:
+            # Empty micro batches don't matter
+            return
+
+        if micro_batch_id % parallel_context.dp_pg.size() != dist.get_rank(parallel_context.dp_pg):
+            # Each dp is responsible for its own micro batches
+            continue
+
+        if dist.get_rank(parallel_context.pp_pg) == input_rank:
+            encodings = tokenizer(
+                [elt.text for elt in micro_batch],
+                return_tensors="pt",
+                return_attention_mask=True,
+                padding=tokenizer_config.padding,
+                max_length=tokenizer_config.max_input_length,
+                truncation=tokenizer_config.truncation,
+                # pad_to_multiple_of=8
+            )
+
+            encodings["attention_mask"] = encodings.attention_mask.to(dtype=torch.bool, device="cuda")
+            encodings.to("cuda")
+            yield GenerationInputs(input_ids=encodings.input_ids, input_masks=encodings.attention_mask)
+        else:
+            yield GenerationInputs(
+                input_ids=TensorPointer(group_rank=input_rank), input_masks=TensorPointer(group_rank=input_rank)
+            )
+
+
+def micro_splitter(
+    input_ids: torch.Tensor,
+    input_mask: torch.Tensor,
+    max_micro_batch_size: int,
+    parallel_context: ParallelContext,
+    input_rank: int,
+) -> Generator[GenerationInputs, None, None]:
+    """
+    Returns:
+        input_ids: [max_micro_batch_size, max_input_length]
+        input_masks: [max_micro_batch_size, max_input_length]
+    """
+    for micro_batch_id, (micro_batch_ids, micro_batch_mask) in enumerate(
+        zip(torch.split(input_ids, max_micro_batch_size), torch.split(input_mask, max_micro_batch_size))
+    ):
+        if len(micro_batch_ids) == 0:
+            # Empty micro batches don't matter
+            return
+
+        # if micro_batch_id % parallel_context.dp_pg.size() != dist.get_rank(parallel_context.dp_pg):
+        #     # Each dp is responsible for its own micro batches
+        #     continue
+
+        if dist.get_rank(parallel_context.pp_pg) == input_rank:
+            micro_batch_mask = micro_batch_mask.to(dtype=torch.bool, device="cuda")
+            micro_batch_mask.to("cuda")
+            yield GenerationInputs(input_ids=micro_batch_ids.clone(), input_masks=micro_batch_mask.clone())
+        else:
+            yield GenerationInputs(
+                input_ids=TensorPointer(group_rank=input_rank), input_masks=TensorPointer(group_rank=input_rank)
+            )
+
+
+@torch.inference_mode()
+def decode_text(
+    input_iter: Iterable[GenerationInput],
+    tokenizer: "PreTrainedTokenizer",
+    model: LlamaModel,
+    parallel_context: ParallelContext,
+    generation_config: GenerationArgs,
+    tokenizer_config: Optional[TokenizerConfig],
+    max_micro_batch_size: int,
+    max_new_tokens: int,
+    is_bench: bool = False,
+    logits_are_batch_first: bool = True,
+) -> Generator[GenerationOutput, None, None]:
+    """We assume the following:
+    - Everyone receives ALL the input text. # TODO @thomasw21: technically only specific ranks need to receive input.
+    - Only a specific rank will output the generated text_ids as `torch.Tensor`, the others return a `TensorPointer`. # TODO @thomasw21: Maybe all ranks should return the text.
+    - We assume that within a model replica, the inputs are already synchronized.
+    """
+    decoder_input_rank, decoder_logit_rank = get_min_max_rank(module=model)
+
+    if generation_config:
+        if isinstance(generation_config.sampler, str):
+            sampler_type = SamplerType(generation_config.sampler.upper())
+        else:
+            sampler_type = generation_config.sampler
+    else:
+        sampler_type = SamplerType.GREEDY
+
+    # Compute flag
+    is_decoder_input_rank = dist.get_rank(parallel_context.pp_pg) == decoder_input_rank
+    is_decoder_logit_rank = dist.get_rank(parallel_context.pp_pg) == decoder_logit_rank
+    max_nb_microbatches = decoder_logit_rank - decoder_input_rank + 1
+
+    p2p = model.p2p
+
+    # That's annoying but I need this as soon as there's a change communication "cross"
+    pipeline_state = PipelineEvalBatchState()
+    with attach_pipeline_state_to_model(model=model, pipeline_state=pipeline_state):
+        # We query the first `pipeline_size` batches
+        for batches in chunks(
+            iterable=micro_batcher(
+                input_iter=input_iter,
+                tokenizer=tokenizer,
+                max_micro_batch_size=max_micro_batch_size,
+                tokenizer_config=tokenizer_config,
+                input_rank=decoder_input_rank,
+                parallel_context=parallel_context,
+            ),
+            chunk_size=max_nb_microbatches,
+        ):
+            if len(batches) == 0:
+                # It means we're out of element
+                return
+
+            # Number of micro batches
+            number_states_in_buffer = len(batches)
+            # Otherwise the pipelining doesn't work
+            assert number_states_in_buffer <= max_nb_microbatches
+            is_max_nb_microbatches = number_states_in_buffer == max_nb_microbatches
+
+            # Initialize decoder states
+            decoder_states: Iterable[GenerationStates] = (
+                GenerationStates(
+                    new_input_ids=batch.input_ids,
+                    new_input_mask=batch.input_masks,
+                    store=Store(),
+                    generation_ids=[batch.input_ids],
+                    generation_mask=[batch.input_masks],
+                )
+                for batch in batches
+            )
+
+            if is_bench:
+                start_time, elapsed_time_first_iteration = time.perf_counter(), 0
+
+            for generation_iter in range(max_new_tokens):
+
+                if is_bench and generation_iter == 0:
+                    torch.cuda.synchronize()
+                    elapsed_time_first_iteration = start_time - time.perf_counter()
+
+                all_new_decoder_input_ids_and_mask_same_rank: List[
+                    Tuple[Union[torch.LongTensor, TensorPointer], Union[torch.BoolTensor, TensorPointer]]
+                ] = []
+                new_decoder_states: List[GenerationStates] = []
+                for state_id, state in enumerate(decoder_states):
+                    new_decoder_states.append(state)
+                    # Get the new logits
+                    if generation_config.use_cache:
+                        with attach_store(model=model, store=state.store):
+                            # transpose: [sequence_length, batch_size, vocab_size] -> [batch_size, sequence_length, vocab_size]
+                            sharded_logits = model(
+                                input_ids=state.new_input_ids,
+                                input_mask=state.new_input_mask,
+                            )
+                    else:
+                        if isinstance(state.new_input_ids, torch.Tensor):
+                            batch_generated_ids = torch.cat(state.generation_ids, dim=-1)
+                            batch_generated_mask = torch.cat(state.generation_mask, dim=-1)
+                        else:
+                            batch_generated_ids = state.new_input_ids
+                            batch_generated_mask = state.new_input_mask
+                        sharded_logits = model(
+                            input_ids=batch_generated_ids,
+                            input_mask=batch_generated_mask,
+                        )
+
+                    if isinstance(sharded_logits, torch.Tensor) and logits_are_batch_first:
+                        sharded_logits = sharded_logits.transpose(0, 1)
+                    # Communicate
+                    # TODO @thomasw21: Make a diagram to show how this works
+                    nb_send: int = 0
+                    if is_decoder_input_rank:
+                        if is_max_nb_microbatches:
+                            if generation_iter == 0:
+                                if state_id == number_states_in_buffer - 1:
+                                    # `2` is because we receive decoder_ids AND decoder_mask from last rank
+                                    nb_send = len(pipeline_state.microbatches_activations_to_send) - 2
+                                else:
+                                    # Send everything
+                                    nb_send = len(pipeline_state.microbatches_activations_to_send)
+                            else:
+                                # `2` is because we receive decoder_ids AND decoder_mask from last rank
+                                nb_send = len(pipeline_state.microbatches_activations_to_send) - 2
+                        else:
+                            if number_states_in_buffer - 1 == state_id or generation_iter == 0:
+                                # Send everything
+                                nb_send = len(pipeline_state.microbatches_activations_to_send)
+                            else:
+                                # `2` is because we receive decoder_ids AND decoder_mask from last rank
+                                nb_send = len(pipeline_state.microbatches_activations_to_send) - 2
+                    else:
+                        if state_id == number_states_in_buffer - 1:
+                            if not is_max_nb_microbatches:
+                                nb_send = len(pipeline_state.microbatches_activations_to_send)
+                    for _ in range(nb_send):
+                        pipeline_state.run_communication()
+
+                    if is_decoder_logit_rank:
+                        assert isinstance(sharded_logits, torch.Tensor)
+
+                        # run a logit chooser.
+                        if sampler_type == SamplerType.GREEDY:
+                            sampler = GreedySampler(pg=parallel_context.tp_pg)
+                        elif sampler_type == SamplerType.TOP_K:
+                            sampler = TopKSampler(pg=parallel_context.tp_pg)
+                        elif sampler_type == SamplerType.TOP_P:
+                            sampler = TopPSampler(pg=parallel_context.tp_pg)
+                        elif sampler_type == SamplerType.BASIC:
+                            sampler = BasicSampler(pg=parallel_context.tp_pg)
+                        else:
+                            raise NotImplementedError(f"Sampler type {sampler_type} is not implemented")
+
+                        new_decoder_input_ids = sampler(sharded_logits=sharded_logits[:, -1, :])
+
+                        # TODO @thomasw21: Handle this correctly, ie from some point after <eos> this should only generate masked tokens
+                        # TODO @thomasw21: Actually I can probably build this thing on the next device directly. Will save some communication
+                        new_decoder_input_mask = torch.ones(
+                            size=(new_decoder_input_ids.shape[0], 1),
+                            dtype=torch.bool,
+                            device=new_decoder_input_ids.device,
+                        )
+
+                        # TODO @thomasw21: We need to have stop condition.
+
+                        # broadcast new_tokens to everyone
+                        if decoder_input_rank == decoder_logit_rank:
+                            # It's the same rank so no need to do anything too fancy
+                            all_new_decoder_input_ids_and_mask_same_rank.append(
+                                (new_decoder_input_ids, new_decoder_input_mask)
+                            )
+                        else:
+                            pipeline_state.register_send_activation(
+                                new_decoder_input_ids, to_rank=decoder_input_rank, p2p=p2p
+                            )
+                            pipeline_state.register_send_activation(
+                                new_decoder_input_mask, to_rank=decoder_input_rank, p2p=p2p
+                            )
+                            if not is_max_nb_microbatches and state_id == number_states_in_buffer - 1:
+                                # Send new_decoder_input_ids AND new_decoder_input_ids
+                                pipeline_state.run_communication()
+                                pipeline_state.run_communication()
+
+                    else:
+                        assert isinstance(sharded_logits, TensorPointer)
+
+                all_new_decoder_input_ids_and_mask: Iterable[
+                    Tuple[Union[torch.LongTensor, TensorPointer], Union[torch.BoolTensor, TensorPointer]]
+                ]
+                if is_decoder_input_rank:
+                    # We receive the tensor from other ranks unless `decoder_input_rank` == `decoder_logit_rank` in which case `all_new_decoder_input_ids` is already populated.
+                    if decoder_input_rank == decoder_logit_rank:
+                        # `all_new_decoder_input_ids_and_mask_same_rank` is already populated. Since `decoder_input_rank` and `decoder_logit_rank` are the same, there's no need to communicate as we can just store the new input_ids in a list.
+                        assert len(all_new_decoder_input_ids_and_mask_same_rank) == number_states_in_buffer
+                        all_new_decoder_input_ids_and_mask = all_new_decoder_input_ids_and_mask_same_rank
+                    else:
+
+                        def generator():
+                            for _ in range(number_states_in_buffer):
+                                pipeline_state.register_recv_activation(from_rank=decoder_logit_rank, p2p=p2p)
+                                pipeline_state.register_recv_activation(from_rank=decoder_logit_rank, p2p=p2p)
+                                while len(pipeline_state.activations_buffer) < 2:
+                                    pipeline_state.run_communication()
+                                new_decoder_input_ids = pipeline_state.activations_buffer.popleft()
+                                new_decoder_input_mask = pipeline_state.activations_buffer.popleft()
+                                yield new_decoder_input_ids, new_decoder_input_mask
+
+                        all_new_decoder_input_ids_and_mask = iter(generator())
+                else:
+                    all_new_decoder_input_ids_and_mask = (
+                        (TensorPointer(group_rank=decoder_input_rank), TensorPointer(group_rank=decoder_input_rank))
+                        for _ in range(number_states_in_buffer)
+                    )
+
+                # Create new decoder states
+                decoder_states = (
+                    GenerationStates(
+                        new_input_ids=new_decoder_input_ids_and_mask[0],
+                        new_input_mask=new_decoder_input_ids_and_mask[1],
+                        store=state.store,
+                        generation_ids=state.generation_ids + [new_decoder_input_ids_and_mask[0]],
+                        generation_mask=state.generation_mask + [new_decoder_input_ids_and_mask[1]],
+                    )
+                    for state, new_decoder_input_ids_and_mask in zip(
+                        new_decoder_states, all_new_decoder_input_ids_and_mask
+                    )
+                )
+
+            if is_bench:
+                # Compute throughput (tok/s/gpu). Note that the first generation is done with full seq_len, so we don't count it.
+                torch.cuda.synchronize()
+                total_time_sec = time.perf_counter() - start_time - elapsed_time_first_iteration
+                # We generate 1 token per iteration per batch (batch=microbatch)
+                # Number of tokens generated every iteration: gbs/iteration_time
+                global_batch_size = len(batches) * parallel_context.dp_pg.size()
+                tokens_per_sec = global_batch_size * max_new_tokens / total_time_sec
+
+                model_tflops, hardware_tflops = model.get_flops_per_sec(
+                    iteration_time_in_sec=total_time_sec,
+                    sequence_length=max_new_tokens,
+                    global_batch_size=global_batch_size,
+                )
+
+                bench_config = BenchArgs(
+                    model_name=model.config._name_or_path,
+                    sequence_length=max_new_tokens,
+                    micro_batch_size=max_micro_batch_size,
+                    batch_accumulation_per_replica=1,
+                    benchmark_csv_path="benchmark.csv",
+                )
+
+                model_size = sum(
+                    [p.numel() * p.data.element_size() for p in chain(model.parameters(), model.buffers())]
+                )
+
+                log_throughput(
+                    bench_config,
+                    parallel_context,
+                    model_tflops,
+                    hardware_tflops,
+                    tokens_per_sec,
+                    bandwidth=model_size * tokens_per_sec / 1e9,
+                )
+
+            # Flush communication
+            for _ in range(
+                max(
+                    len(pipeline_state.microbatches_activations_to_send),
+                    len(pipeline_state.microbatches_activations_to_recv),
+                )
+            ):
+                pipeline_state.run_communication()
+            assert len(pipeline_state.microbatches_activations_to_send) == 0
+            assert len(pipeline_state.microbatches_activations_to_recv) == 0
+
+            # Yield result
+            decoder_states = list(decoder_states)
+            for state, batch in zip(decoder_states, batches):
+                if is_decoder_input_rank:
+                    assert all(isinstance(elt, torch.Tensor) for elt in state.generation_ids)
+                    batch_generated_ids = torch.cat(state.generation_ids, dim=-1)
+                    batch_generated_mask = torch.cat(state.generation_mask, dim=-1)
+                else:
+                    assert all(isinstance(elt, TensorPointer) for elt in state.generation_ids)
+                    batch_generated_ids = TensorPointer(group_rank=decoder_input_rank)
+                    batch_generated_mask = TensorPointer(group_rank=decoder_input_rank)
+
+                # Broadcast all data
+                batch_generated_ids, batch_generated_mask = broadcast_tensors(
+                    [batch_generated_ids, batch_generated_mask],
+                    group_src=decoder_input_rank,
+                    group=parallel_context.pp_pg,
+                )
+                batch.input_ids, batch.input_masks = broadcast_tensors(
+                    [batch.input_ids, batch.input_masks], group_src=decoder_input_rank, group=parallel_context.pp_pg
+                )
+
+                # Flush the store to release memory
+                state.store.flush()
+                assert len(state.store) == 0
+
+                if dist.get_rank(parallel_context.pp_pg) == decoder_input_rank:
+                    assert (
+                        batch_generated_ids.shape[0] == batch.input_ids.shape[0]
+                    ), f"Batch size needs to match {batch_generated_ids.shape[0]} != {batch.input_ids.shape[0]}"
+                    assert (
+                        batch_generated_mask.shape[0] == batch.input_ids.shape[0]
+                    ), f"Batch size needs to match {batch_generated_mask.shape[0]} != {batch.input_ids.shape[0]}"
+                    assert (
+                        batch_generated_ids.shape[1] == batch_generated_mask.shape[1]
+                    ), f"Sequence length needs to match {batch_generated_ids.shape[1]} != {batch_generated_mask.shape[0]}"
+
+                for i, (generated_ids, generated_mask) in enumerate(zip(batch_generated_ids, batch_generated_mask)):
+                    # TODO @thomasw21: We could actually have all ranks return the output, since it's been already broadcasted
+                    if dist.get_rank(parallel_context.pp_pg) == decoder_input_rank:
+                        input_ids = batch.input_ids[i]
+                        input_mask = batch.input_masks[i]
+                        yield GenerationOutput(
+                            input_ids=input_ids[input_mask],
+                            generation_ids=generated_ids[generated_mask],
+                        )
+                    else:
+                        yield GenerationOutput(
+                            input_ids=TensorPointer(group_rank=decoder_input_rank),
+                            generation_ids=TensorPointer(group_rank=decoder_input_rank),
+                        )
+
+
+@torch.inference_mode()
+def decode_tokenized(
+    input_ids: torch.Tensor,
+    input_mask: torch.Tensor,
+    model: LlamaModel,
+    parallel_context: ParallelContext,
+    generation_config: GenerationArgs,
+    max_micro_batch_size: int,
+    max_new_tokens: int,
+    returns_logits: Optional[bool] = False,
+) -> Generator[GenerationOutput, None, None]:
+    """We assume the following:
+    - Everyone receives ALL the input text. # TODO @thomasw21: technically only specific ranks need to receive input.
+    - Only a specific rank will output the generated text_ids as `torch.Tensor`, the others return a `TensorPointer`. # TODO @thomasw21: Maybe all ranks should return the text.
+    - We assume that within a model replica, the inputs are already synchronized.
+    """
+    if returns_logits:
+        raise NotImplementedError("return_logits is not implemented yet")
+
+    if generation_config:
+        if isinstance(generation_config.sampler, str):
+            sampler_type = SamplerType(generation_config.sampler.upper())
+        else:
+            sampler_type = generation_config.sampler
+    else:
+        sampler_type = SamplerType.GREEDY
+
+    decoder_input_rank, decoder_logit_rank = get_min_max_rank(module=model)
+
+    # Compute flag
+    is_decoder_input_rank = dist.get_rank(parallel_context.pp_pg) == decoder_input_rank
+    is_decoder_logit_rank = dist.get_rank(parallel_context.pp_pg) == decoder_logit_rank
+    max_nb_microbatches = decoder_logit_rank - decoder_input_rank + 1
+
+    # TODO @thomasw21: Fix this as we shouldn't get P2P like that
+    p2p = model.p2p
+
+    # That's annoying but I need this as soon as there's a change communication "cross"
+    pipeline_state = PipelineEvalBatchState()
+    with attach_pipeline_state_to_model(model=model, pipeline_state=pipeline_state):
+        # We query the first `pipeline_size` batches
+        for batches in chunks(
+            iterable=micro_splitter(
+                input_ids,
+                input_mask,
+                max_micro_batch_size=max_micro_batch_size,
+                parallel_context=parallel_context,
+                input_rank=decoder_input_rank,
+            ),
+            chunk_size=max_nb_microbatches,
+        ):
+            if len(batches) == 0:
+                # It means we're out of element
+                return
+
+            # Number of micro batches
+            number_states_in_buffer = len(batches)
+            # Otherwise the pipelining doesn't work
+            assert number_states_in_buffer <= max_nb_microbatches
+            is_max_nb_microbatches = number_states_in_buffer == max_nb_microbatches
+
+            # Initialize decoder states
+            decoder_states: Iterable[GenerationStates] = (
+                GenerationStates(
+                    new_input_ids=batch.input_ids,
+                    new_input_mask=batch.input_masks,
+                    store=Store(),
+                    generation_ids=[batch.input_ids],
+                    generation_mask=[batch.input_masks],
+                )
+                for batch in batches
+            )
+
+            for generation_iter in range(max_new_tokens):
+                all_new_decoder_input_ids_and_mask_same_rank: List[
+                    Tuple[Union[torch.LongTensor, TensorPointer], Union[torch.BoolTensor, TensorPointer]]
+                ] = []
+                new_decoder_states: List[GenerationStates] = []
+                for state_id, state in enumerate(decoder_states):
+                    new_decoder_states.append(state)
+                    # Get the new logits
+                    with attach_store(model=model, store=state.store):
+                        # transpose: [sequence_length, batch_size, vocab_size] -> [batch_size, sequence_length, vocab_size]
+                        sharded_logits = model(
+                            input_ids=state.new_input_ids,
+                            input_mask=state.new_input_mask,
+                        )
+                        if isinstance(sharded_logits, torch.Tensor):
+                            sharded_logits = sharded_logits.transpose(0, 1)
+
+                    # Communicate
+                    # TODO @thomasw21: Make a diagram to show how this works
+                    nb_send: int = 0
+                    if is_decoder_input_rank:
+                        if is_max_nb_microbatches:
+                            if generation_iter == 0:
+                                if state_id == number_states_in_buffer - 1:
+                                    # `2` is because we receive decoder_ids AND decoder_mask from last rank
+                                    nb_send = len(pipeline_state.microbatches_activations_to_send) - 2
+                                else:
+                                    # Send everything
+                                    nb_send = len(pipeline_state.microbatches_activations_to_send)
+                            else:
+                                # `2` is because we receive decoder_ids AND decoder_mask from last rank
+                                nb_send = len(pipeline_state.microbatches_activations_to_send) - 2
+                        else:
+                            if number_states_in_buffer - 1 == state_id or generation_iter == 0:
+                                # Send everything
+                                nb_send = len(pipeline_state.microbatches_activations_to_send)
+                            else:
+                                # `2` is because we receive decoder_ids AND decoder_mask from last rank
+                                nb_send = len(pipeline_state.microbatches_activations_to_send) - 2
+                    else:
+                        if state_id == number_states_in_buffer - 1:
+                            if not is_max_nb_microbatches:
+                                nb_send = len(pipeline_state.microbatches_activations_to_send)
+                    for _ in range(nb_send):
+                        pipeline_state.run_communication()
+
+                    if is_decoder_logit_rank:
+                        assert isinstance(sharded_logits, torch.Tensor)
+
+                        # run a logit chooser.
+                        if sampler_type == SamplerType.GREEDY:
+                            sampler = GreedySampler(pg=parallel_context.tp_pg)
+                        elif sampler_type == SamplerType.TOP_K:
+                            sampler = TopKSampler(
+                                pg=parallel_context.tp_pg,
+                                k=generation_config.top_k,
+                                temperature=generation_config.temperature,
+                            )
+                        elif sampler_type == SamplerType.TOP_P:
+                            sampler = TopPSampler(
+                                pg=parallel_context.tp_pg,
+                                p=generation_config.top_p,
+                                temperature=generation_config.temperature,
+                            )
+                        elif sampler_type == SamplerType.BASIC:
+                            sampler = BasicSampler(pg=parallel_context.tp_pg)
+                        else:
+                            raise NotImplementedError(f"Sampler type {sampler_type} is not implemented")
+
+                        new_decoder_input_ids = sampler(sharded_logits=sharded_logits[:, -1, :])
+
+                        # TODO @thomasw21: Handle this correctly, ie from some point after <eos> this should only generate masked tokens
+                        # TODO @thomasw21: Actually I can probably build this thing on the next device directly. Will save some communication
+                        new_decoder_input_mask = torch.ones(
+                            size=(new_decoder_input_ids.shape[0], 1),
+                            dtype=torch.bool,
+                            device=new_decoder_input_ids.device,
+                        )
+
+                        # TODO @thomasw21: We need to have stop condition.
+
+                        # broadcast new_tokens to everyone
+                        if decoder_input_rank == decoder_logit_rank:
+                            # It's the same rank so no need to do anything too fancy
+                            all_new_decoder_input_ids_and_mask_same_rank.append(
+                                (new_decoder_input_ids, new_decoder_input_mask)
+                            )
+                        else:
+                            pipeline_state.register_send_activation(
+                                new_decoder_input_ids, to_rank=decoder_input_rank, p2p=p2p
+                            )
+                            pipeline_state.register_send_activation(
+                                new_decoder_input_mask, to_rank=decoder_input_rank, p2p=p2p
+                            )
+                            if not is_max_nb_microbatches and state_id == number_states_in_buffer - 1:
+                                # Send new_decoder_input_ids AND new_decoder_input_ids
+                                pipeline_state.run_communication()
+                                pipeline_state.run_communication()
+
+                    else:
+                        assert isinstance(sharded_logits, TensorPointer)
+
+                all_new_decoder_input_ids_and_mask: Iterable[
+                    Tuple[Union[torch.LongTensor, TensorPointer], Union[torch.BoolTensor, TensorPointer]]
+                ]
+                if is_decoder_input_rank:
+                    # We receive the tensor from other ranks unless `decoder_input_rank` == `decoder_logit_rank` in which case `all_new_decoder_input_ids` is already populated.
+                    if decoder_input_rank == decoder_logit_rank:
+                        # `all_new_decoder_input_ids_and_mask_same_rank` is already populated. Since `decoder_input_rank` and `decoder_logit_rank` are the same, there's no need to communicate as we can just store the new input_ids in a list.
+                        assert len(all_new_decoder_input_ids_and_mask_same_rank) == number_states_in_buffer
+                        all_new_decoder_input_ids_and_mask = all_new_decoder_input_ids_and_mask_same_rank
+                    else:
+
+                        def generator():
+                            for _ in range(number_states_in_buffer):
+                                pipeline_state.register_recv_activation(from_rank=decoder_logit_rank, p2p=p2p)
+                                pipeline_state.register_recv_activation(from_rank=decoder_logit_rank, p2p=p2p)
+                                while len(pipeline_state.activations_buffer) < 2:
+                                    pipeline_state.run_communication()
+                                new_decoder_input_ids = pipeline_state.activations_buffer.popleft()
+                                new_decoder_input_mask = pipeline_state.activations_buffer.popleft()
+                                yield new_decoder_input_ids, new_decoder_input_mask
+
+                        all_new_decoder_input_ids_and_mask = iter(generator())
+                else:
+                    all_new_decoder_input_ids_and_mask = (
+                        (TensorPointer(group_rank=decoder_input_rank), TensorPointer(group_rank=decoder_input_rank))
+                        for _ in range(number_states_in_buffer)
+                    )
+
+                # Create new decoder states
+                decoder_states = (
+                    GenerationStates(
+                        new_input_ids=new_decoder_input_ids_and_mask[0],
+                        new_input_mask=new_decoder_input_ids_and_mask[1],
+                        store=state.store,
+                        generation_ids=state.generation_ids + [new_decoder_input_ids_and_mask[0]],
+                        generation_mask=state.generation_mask + [new_decoder_input_ids_and_mask[1]],
+                    )
+                    for state, new_decoder_input_ids_and_mask in zip(
+                        new_decoder_states, all_new_decoder_input_ids_and_mask
+                    )
+                )
+
+            # Flush communication
+            for _ in range(
+                max(
+                    len(pipeline_state.microbatches_activations_to_send),
+                    len(pipeline_state.microbatches_activations_to_recv),
+                )
+            ):
+                pipeline_state.run_communication()
+            assert len(pipeline_state.microbatches_activations_to_send) == 0
+            assert len(pipeline_state.microbatches_activations_to_recv) == 0
+
+            # Yield result
+            decoder_states = list(decoder_states)
+            for state, batch in zip(decoder_states, batches):
+                if is_decoder_input_rank:
+                    assert all(isinstance(elt, torch.Tensor) for elt in state.generation_ids)
+                    batch_generated_ids = torch.cat(state.generation_ids, dim=-1)
+                    batch_generated_mask = torch.cat(state.generation_mask, dim=-1)
+                else:
+                    assert all(isinstance(elt, TensorPointer) for elt in state.generation_ids)
+                    batch_generated_ids = TensorPointer(group_rank=decoder_input_rank)
+                    batch_generated_mask = TensorPointer(group_rank=decoder_input_rank)
+
+                # Broadcast all data
+                batch_generated_ids, batch_generated_mask = broadcast_tensors(
+                    [batch_generated_ids, batch_generated_mask],
+                    group_src=decoder_input_rank,
+                    group=parallel_context.pp_pg,
+                )
+                batch.input_ids, batch.input_masks = broadcast_tensors(
+                    [batch.input_ids, batch.input_masks], group_src=decoder_input_rank, group=parallel_context.pp_pg
+                )
+
+                # Flush the store to release memory
+                state.store.flush()
+                assert len(state.store) == 0
+
+                if dist.get_rank(parallel_context.pp_pg) == decoder_input_rank:
+                    assert (
+                        batch_generated_ids.shape[0] == batch.input_ids.shape[0]
+                    ), f"Batch size needs to match {batch_generated_ids.shape[0]} != {batch.input_ids.shape[0]}"
+                    assert (
+                        batch_generated_mask.shape[0] == batch.input_ids.shape[0]
+                    ), f"Batch size needs to match {batch_generated_mask.shape[0]} != {batch.input_ids.shape[0]}"
+                    assert (
+                        batch_generated_ids.shape[1] == batch_generated_mask.shape[1]
+                    ), f"Sequence length needs to match {batch_generated_ids.shape[1]} != {batch_generated_mask.shape[0]}"
+
+                for i, (generated_ids, generated_mask) in enumerate(zip(batch_generated_ids, batch_generated_mask)):
+                    # TODO @thomasw21: We could actually have all ranks return the output, since it's been already broadcasted
+                    if dist.get_rank(parallel_context.pp_pg) == decoder_input_rank:
+                        input_ids = batch.input_ids[i]
+                        input_mask = batch.input_masks[i]
+                        yield GenerationOutput(
+                            input_ids=input_ids[input_mask],
+                            generation_ids=generated_ids[generated_mask],
+                        )
+                    else:
+                        yield GenerationOutput(
+                            input_ids=TensorPointer(group_rank=decoder_input_rank),
+                            generation_ids=TensorPointer(group_rank=decoder_input_rank),
+                        )
+
+
+# Distributed utilities
+def broadcast_tensors(
+    tensors: List[Union[torch.Tensor, TensorPointer]], group_src: int, group: Optional[ProcessGroup] = None
+) -> List[torch.Tensor]:
+    result = []
+    for tensor in tensors:
+        if dist.get_rank(group) == group_src:
+            assert isinstance(tensor, torch.Tensor)
+            meta = [
+                [
+                    tensor.dtype,
+                    tensor.requires_grad,
+                    tensor.shape,
+                    get_untyped_storage(tensor).size(),
+                    tensor.stride(),
+                    tensor.is_contiguous(),
+                    tensor.storage_offset(),
+                ]
+            ]
+        else:
+            assert isinstance(tensor, TensorPointer)
+            meta = [None]
+        dist.broadcast_object_list(meta, src=get_global_rank(group_rank=group_src, group=group), group=group)
+        dtype, requires_grad, shape, untyped_storage_size, stride, is_contiguous, storage_offset = meta[0]
+        meta = P2PTensorMetaData(
+            dtype=dtype,
+            requires_grad=requires_grad,
+            shape=shape,
+            untyped_storage_size=untyped_storage_size,
+            stride=stride,
+            is_contiguous=is_contiguous,
+            storage_offset=storage_offset,
+        )
+        if dist.get_rank(group) != group_src:
+            tensor = meta.create_empty_storage(device=torch.device("cuda"))
+        else:
+            tensor = view_as_contiguous(tensor)
+        dist.broadcast(tensor, src=get_global_rank(group_rank=group_src, group=group), group=group)
+        # Set shape and stride
+        tensor = tensor.as_strided(size=tuple(meta.shape), stride=tuple(meta.stride))
+        result.append(tensor)
+    return result
diff --git a/src/nanotron/helpers.py b/src/nanotron/helpers.py
index ef5bb0e9..60867c51 100644
--- a/src/nanotron/helpers.py
+++ b/src/nanotron/helpers.py
@@ -284,7 +284,8 @@ def basic_optimizer_builder(named_param_groups):
             named_params_or_groups=named_param_groups,
             optimizer_builder=lambda param_groups: AdamW(  # pylint: disable=E0601
                 param_groups,
-                weight_decay=optimizer_args.weight_decay,
+                # NOTE: don't apply global weight if balance_factor_weight_decay is set
+                # weight_decay=optimizer_args.weight_decay if constants.CONFIG.infini_attention.balance_factor_weight_decay is None else None,
                 lr=optimizer_args.learning_rate_scheduler.learning_rate,
                 eps=optimizer_args.adam_eps,
                 betas=(optimizer_args.adam_beta1, optimizer_args.adam_beta2),
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 24ec3773..a00dd12c 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -486,8 +486,8 @@ def __init__(
         if constants.CONFIG.infini_attention.balance_init_type == "zeros":
             log_rank("Zero initialized balance factors", logger=logger, level=logging.WARNING, rank=0)
             balance_factors = nn.Parameter(torch.zeros(self.n_local_q_heads, device=device, dtype=torch.float32))
-        elif constants.CONFIG.infini_attention.balance_init_type == "normal_randn":
-            log_rank("normal_randn initialized balance factors", logger=logger, level=logging.WARNING, rank=0)
+        elif constants.CONFIG.infini_attention.balance_init_type == "randn":
+            log_rank("randn initialized balance factors", logger=logger, level=logging.WARNING, rank=0)
             balance_factors = nn.Parameter(torch.randn(self.n_local_q_heads, device=device, dtype=torch.float32))
         else:
             raise ValueError(f"balance_init_type {constants.CONFIG.infini_attention.balance_init_type} not supported")
@@ -695,8 +695,9 @@ def forward(
             if constants.CONFIG.infini_attention.turn_on_memory is True:
                 if (
                     constants.GLOBAL_STEP is not None
-                    and (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0
+                    and (constants.GLOBAL_STEP - 1) % constants.CONFIG.infini_attention.logging_interval == 0
                     and constants.IS_RANK_TO_MONITOR is True
+                    and constants.CONFIG.infini_attention.log_segment_acts is True
                 ):
                     if dist.get_rank() == 0:
                         logs[f"layer_{self.layer_idx}:seg_{idx}:query_states"] = compute_stas(query_states)
@@ -722,7 +723,10 @@ def forward(
         outputs = torch.cat(outputs, dim=1)  # concat along sequence dimension
         assert outputs.shape == hidden_states.shape
 
-        if constants.GLOBAL_STEP is not None and (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0:
+        if (
+            constants.GLOBAL_STEP is not None
+            and (constants.GLOBAL_STEP - 1) % constants.CONFIG.infini_attention.logging_interval == 0
+        ):
             if constants.IS_RANK_TO_MONITOR is True:
                 import wandb
 
diff --git a/src/nanotron/optim/gradient_accumulator.py b/src/nanotron/optim/gradient_accumulator.py
index 043fa590..8c1e5d3f 100644
--- a/src/nanotron/optim/gradient_accumulator.py
+++ b/src/nanotron/optim/gradient_accumulator.py
@@ -262,20 +262,22 @@ def _accumulate_grad(self, name: str, half_param: NanotronParameter) -> None:
         if (constants.GLOBAL_STEP - 1) % constants.LOG_STATE_INTERVAL == 0 and constants.IS_RANK_TO_MONITOR is True:
             from nanotron import constants
 
-            # save_tensor(
-            #     name=f"{name}.grad",
-            #     tensor=fp32_param.grad,
-            #     path=f"{constants.MONITOR_STATE_PATH}/{constants.CONFIG.general.run}/{constants.GLOBAL_STEP}/grads"
-            # )
-
-            wandb.log(
-                {
-                    f"{name}:grad:mean": fp32_param.grad.detach().mean().item(),
-                    f"{name}:grad:std": fp32_param.grad.detach().std().item(),
-                    f"{name}:grad:norm": fp32_param.grad.detach().norm().item(),
-                    "iteration_step": constants.GLOBAL_STEP,
-                }
-            )
+            if constants.CONFIG.infini_attention.log_grad is True:
+                # save_tensor(
+                #     name=f"{name}.grad",
+                #     tensor=fp32_param.grad,
+                #     path=f"{constants.MONITOR_STATE_PATH}/{constants.CONFIG.general.run}/{constants.GLOBAL_STEP}/grads"
+                # )
+
+                if "balance_factor" in name:
+                    wandb.log(
+                        {
+                            f"{name}:grad:mean": fp32_param.grad.detach().mean().item(),
+                            f"{name}:grad:std": fp32_param.grad.detach().std().item(),
+                            f"{name}:grad:norm": fp32_param.grad.detach().norm().item(),
+                            "iteration_step": constants.GLOBAL_STEP,
+                        }
+                    )
 
     @contextmanager
     def no_sync(self):
diff --git a/src/nanotron/optim/named_optimizer.py b/src/nanotron/optim/named_optimizer.py
index 74214357..5de6d822 100644
--- a/src/nanotron/optim/named_optimizer.py
+++ b/src/nanotron/optim/named_optimizer.py
@@ -3,6 +3,7 @@
 import torch
 
 from nanotron import logging
+from nanotron.logging import log_rank
 from nanotron.optim.inherit_from_other_optimizer import InheritFromOtherOptimizer
 
 logger = logging.get_logger(__name__)
@@ -46,6 +47,25 @@ def __init__(
                 # https://github.com/pytorch/pytorch/issues/100701
                 assert param.numel() > 0
 
+        assert 1 == 1
+        # NOTE: apply custom weight decay
+        from nanotron import constants
+
+        # if constants.CONFIG.infini_attention.balance_factor_weight_decay is not None:
+        for param_group in params:
+            for param in param_group["params"]:
+                if "balance_factor" in id_to_name[id(param)]:
+                    param_group["weight_decay"] = constants.CONFIG.infini_attention.balance_factor_weight_decay
+                else:
+                    param_group["weight_decay"] = constants.CONFIG.optimizer.weight_decay
+
+                log_rank(
+                    f"[INFO] Parameter {id_to_name[id(param)]} has weight decay {param_group['weight_decay']}, and learning rate {param_group['lr']}",
+                    logger=logger,
+                    level=logging.WARNING,
+                    rank=0,
+                )
+
         super().__init__(optimizer=optimizer_builder(params), id_to_name=id_to_name)
 
     def state_dict(self) -> dict:
diff --git a/src/nanotron/trainer.py b/src/nanotron/trainer.py
index 6d27b1d6..57be1da5 100644
--- a/src/nanotron/trainer.py
+++ b/src/nanotron/trainer.py
@@ -438,7 +438,7 @@ def train(
         rank_to_monitor = (
             dist.get_rank(group=self.parallel_context.dp_pg) == 0
             and dist.get_rank(group=self.parallel_context.tp_pg) == 0
-        )
+        ) and constants.CONFIG.infini_attention.logging is True
         constants.IS_RANK_TO_MONITOR = rank_to_monitor
 
         with prof:
@@ -449,8 +449,9 @@ def train(
                     prof.step()
 
                 if (
-                    self.iteration_step - 1
-                ) % constants.LOG_STATE_INTERVAL == 0 and constants.IS_RANK_TO_MONITOR is True:
+                    (self.iteration_step - 1) % constants.CONFIG.infini_attention.logging_interval == 0
+                    and constants.IS_RANK_TO_MONITOR is True
+                ):
                     from nanotron.debug.monitor import monitor_nanotron_model
 
                     nn_logs, nn_handles = monitor_nanotron_model(
@@ -470,8 +471,9 @@ def train(
                     self.train_step_logs(outputs=outputs, loss_avg=loss_avg)
 
                 if (
-                    self.iteration_step - 1
-                ) % constants.LOG_STATE_INTERVAL == 0 and constants.IS_RANK_TO_MONITOR is True:
+                    (self.iteration_step - 1) % constants.CONFIG.infini_attention.logging_interval == 0
+                    and constants.IS_RANK_TO_MONITOR is True
+                ):
                     from nanotron.debug.monitor import convert_logs_to_flat_logs
 
                     if dist.get_rank(self.parallel_context.world_pg) == self.logger_ranks[0] and wandb is not None:

From 03b43ea9d261b3e8b7f9be600c60a3c17b015340 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Wed, 3 Jul 2024 11:21:45 +0000
Subject: [PATCH 39/43] backup

---
 examples/infinite-context-length/data/exp34/hope.ipynb | 7 -------
 1 file changed, 7 deletions(-)

diff --git a/examples/infinite-context-length/data/exp34/hope.ipynb b/examples/infinite-context-length/data/exp34/hope.ipynb
index e1726f85..84171a08 100644
--- a/examples/infinite-context-length/data/exp34/hope.ipynb
+++ b/examples/infinite-context-length/data/exp34/hope.ipynb
@@ -1942,13 +1942,6 @@
    "source": [
     "find_target_indices(prompt_ids, 12422, 5495)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

From 8aa0ee59af1ab077e2457666f4587fd562c34d19 Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Mon, 29 Jul 2024 13:52:15 +0000
Subject: [PATCH 40/43] backup before cleaning

---
 .gitignore                                    |   5 +
 .../data/exp34/debug_eval_dataset.ipynb       | 461 +++++++++++++++++
 .../data/exp34/debug_finetune_data.ipynb      | 471 ++++++++++++++++--
 .../infinite-context-length/generate_data.py  |  72 ++-
 examples/infinite-context-length/run_evals.py | 448 +----------------
 .../scripts/run_1024_passkey_evals.sh         |  25 +
 .../run_generate_1024_passkey_eval_data.sh    |  58 +++
 .../scripts/run_passkey_eval.py               |  69 ++-
 run_generate.py                               |  24 +-
 9 files changed, 1104 insertions(+), 529 deletions(-)
 create mode 100644 examples/infinite-context-length/data/exp34/debug_eval_dataset.ipynb
 create mode 100644 examples/infinite-context-length/scripts/run_1024_passkey_evals.sh
 create mode 100644 examples/infinite-context-length/scripts/run_generate_1024_passkey_eval_data.sh

diff --git a/.gitignore b/.gitignore
index 2b7bb23b..da0c6ff2 100644
--- a/.gitignore
+++ b/.gitignore
@@ -170,3 +170,8 @@ examples/infinite-context-length/*.txt
 *.arrow
 *.txt
 *.out
+debug/
+llama3_8b_generated_from_brrr/
+llama3_8b_generated_from_brrr_tp_8/
+llama3_8b_generated_from_brrr_with_pp_4/
+examples/infinite-context-length/configs/exp59/
diff --git a/examples/infinite-context-length/data/exp34/debug_eval_dataset.ipynb b/examples/infinite-context-length/data/exp34/debug_eval_dataset.ipynb
new file mode 100644
index 00000000..6ede1405
--- /dev/null
+++ b/examples/infinite-context-length/data/exp34/debug_eval_dataset.ipynb
@@ -0,0 +1,461 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_from_disk"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = load_from_disk(\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/eval/1024/needle_eval_data_and_1024_ctx_and_depth_50_and_id_42_and_num_shots_2\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. \\n\\n Passage: The gatecode is 312. Remember it. 312 is the gatecode. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The gatecode is 312. \\n\\n Passage: The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The vault key is 415. Remember it. 415 is the vault key. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The vault key is 415. \\n \\n Passage:  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky. The pass key is 631. Remember it. 631 is the pass key.  is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go The grass is green. The sky is blue. The sun is yellow. Here we go. There and back ag. What is the pass key? The pass key is 631.'"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "d[0][\"prompt\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def load_and_filter_dataset(eval_dataset_path, depth_percent, num_shots, num_digits, seed, num_samples):\n",
+    "    import random\n",
+    "    from datasets import load_dataset\n",
+    "    # Set seeds for reproducibility\n",
+    "    random.seed(seed)\n",
+    "    \n",
+    "    # Load the dataset\n",
+    "    dataset = load_dataset(eval_dataset_path, split=\"train\")\n",
+    "    \n",
+    "    # Filter the dataset\n",
+    "    filtered_dataset = dataset.filter(\n",
+    "        lambda x: x[\"depth_percent\"] == depth_percent and \n",
+    "                x[\"num_shots\"] == num_shots\n",
+    "    )\n",
+    "    if num_digits > 0:\n",
+    "        filtered_dataset = filtered_dataset.filter(\n",
+    "            lambda x: x[\"num_digits\"] == num_digits\n",
+    "        )\n",
+    "\n",
+    "    # filtered_dataset = dataset.filter(\n",
+    "    #     lambda x: x[\"depth_percent\"] == depth_percent and \n",
+    "    #             x[\"num_shots\"] == num_shots and \n",
+    "    #             x[\"num_digits\"] == num_digits\n",
+    "    # )\n",
+    "    \n",
+    "    # Shuffle the dataset deterministically\n",
+    "    shuffled_dataset = filtered_dataset.shuffle(seed=seed)\n",
+    "    \n",
+    "    # Select only the first 10 samples\n",
+    "    final_dataset = shuffled_dataset.select(range(min(num_samples, len(shuffled_dataset))))\n",
+    "    \n",
+    "    return final_dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "samples = load_and_filter_dataset(\"nanotron/llama3-1024-passkey-retrieval-eval\", depth_percent=0, num_shots=0, num_digits=2, seed=42, num_samples=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>prompt</th>\n",
+       "      <th>answer</th>\n",
+       "      <th>context_length</th>\n",
+       "      <th>token_count</th>\n",
+       "      <th>num_shots</th>\n",
+       "      <th>num_digits</th>\n",
+       "      <th>depth_percent</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2d454feb-59a8-4f39-8ad3-c9ed589e5640</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>80</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1004</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>6712605d-21d8-4b1e-8248-fc6a321fd59e</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>87</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1004</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0b8734b1-a140-4cf0-a461-ed686fed566a</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>85</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1004</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>b9035923-f43d-487c-aef1-5027a10ef3ae</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>11</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1004</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5c917b9f-dae3-4e07-a733-6ac089a4e75c</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>14</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1004</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>86e5fd36-951e-4333-9306-2c8045ced06d</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>54</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1004</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>6302d923-e9e4-4319-99f5-14daa43408ed</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>83</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1004</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>8c90e431-bce5-4792-90c2-a765e94ceb91</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>92</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1004</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>b54dc476-b4e7-48b3-b639-599527606858</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>13</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1004</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>48c4b32e-911b-45e6-a53e-c721b187df8d</td>\n",
+       "      <td>There is a pass key hidden inside a lot of irr...</td>\n",
+       "      <td>93</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1004</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                     id  \\\n",
+       "0  2d454feb-59a8-4f39-8ad3-c9ed589e5640   \n",
+       "1  6712605d-21d8-4b1e-8248-fc6a321fd59e   \n",
+       "2  0b8734b1-a140-4cf0-a461-ed686fed566a   \n",
+       "3  b9035923-f43d-487c-aef1-5027a10ef3ae   \n",
+       "4  5c917b9f-dae3-4e07-a733-6ac089a4e75c   \n",
+       "5  86e5fd36-951e-4333-9306-2c8045ced06d   \n",
+       "6  6302d923-e9e4-4319-99f5-14daa43408ed   \n",
+       "7  8c90e431-bce5-4792-90c2-a765e94ceb91   \n",
+       "8  b54dc476-b4e7-48b3-b639-599527606858   \n",
+       "9  48c4b32e-911b-45e6-a53e-c721b187df8d   \n",
+       "\n",
+       "                                              prompt  answer  context_length  \\\n",
+       "0  There is a pass key hidden inside a lot of irr...      80            1024   \n",
+       "1  There is a pass key hidden inside a lot of irr...      87            1024   \n",
+       "2  There is a pass key hidden inside a lot of irr...      85            1024   \n",
+       "3  There is a pass key hidden inside a lot of irr...      11            1024   \n",
+       "4  There is a pass key hidden inside a lot of irr...      14            1024   \n",
+       "5  There is a pass key hidden inside a lot of irr...      54            1024   \n",
+       "6  There is a pass key hidden inside a lot of irr...      83            1024   \n",
+       "7  There is a pass key hidden inside a lot of irr...      92            1024   \n",
+       "8  There is a pass key hidden inside a lot of irr...      13            1024   \n",
+       "9  There is a pass key hidden inside a lot of irr...      93            1024   \n",
+       "\n",
+       "   token_count  num_shots  num_digits  depth_percent  \n",
+       "0         1004          0           2              0  \n",
+       "1         1004          0           2              0  \n",
+       "2         1004          0           2              0  \n",
+       "3         1004          0           2              0  \n",
+       "4         1004          0           2              0  \n",
+       "5         1004          0           2              0  \n",
+       "6         1004          0           2              0  \n",
+       "7         1004          0           2              0  \n",
+       "8         1004          0           2              0  \n",
+       "9         1004          0           2              0  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "samples.to_pandas()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. \\n . The pass key is 80. Remember it. 80 is the pass key. \\n Passage:  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and . What is the pass key? The pass key is 80.'"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "samples[0][\"prompt\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds = load_dataset(\"nanotron/llama3-1024-passkey-retrieval-eval\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def remove_end_number(text):\n",
+    "    # Extract the last 30 characters\n",
+    "    last_30 = text[-30:]\n",
+    "    \n",
+    "    # Find the last occurrence of \"is \"\n",
+    "    last_is_index = last_30.rfind(\"is \")\n",
+    "    \n",
+    "    if last_is_index != -1:\n",
+    "        # Remove everything after \"is \"\n",
+    "        result = text[:len(text) - (30 - last_is_index - 3)]\n",
+    "        return result\n",
+    "    else:\n",
+    "        # If \"is \" is not found in the last 30 characters, return the original string\n",
+    "        return text"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Map: 100%|█████████████████████████████████████████████████████████████████████████████████| 12600/12600 [00:00<00:00, 13010.74 examples/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "def process_example(example):\n",
+    "    example['prompt'] = remove_end_number(example['prompt'])\n",
+    "    return example\n",
+    "\n",
+    "# Apply the function to each example in the dataset\n",
+    "processed_dataset = ds['train'].map(process_example)\n",
+    "\n",
+    "# Print a few examples to verify\n",
+    "# for i in range(5):\n",
+    "#     print(f\"Original: {processed_dataset[i]['prompt']}\")\n",
+    "#     print(f\"Processed: {processed_dataset[i]['processed_text']}\")\n",
+    "#     print()\n",
+    "\n",
+    "# Save the processed dataset if needed\n",
+    "# processed_dataset.save_to_disk('path/to/save/processed_dataset')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. \\n\\n Passage: The gatecode is 312. Remember it. 312 is the gatecode. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The gatecode is 312. \\n\\n Passage: The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The vault key is 415. Remember it. 415 is the vault key. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The vault key is 415. \\n \\n Passage:  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is. The pass key is 5269. Remember it. 5269 is the pass key.  yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go.  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the pass key? The pass key is '"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "processed_dataset[3][\"prompt\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Creating parquet from Arrow format: 100%|█████████████████████████████████████████████████████████████████| 13/13 [00:00<00:00, 196.57ba/s]\n",
+      "Uploading the dataset shards: 100%|██████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00,  2.08it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "CommitInfo(commit_url='https://huggingface.co/datasets/nanotron/llama3-1024-passkey-retrieval-eval/commit/8f3b79e9ffb94efbc49d73978ddbc705d6f14bc9', commit_message='Upload dataset', commit_description='', oid='8f3b79e9ffb94efbc49d73978ddbc705d6f14bc9', pr_url=None, pr_revision=None, pr_num=None)"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "processed_dataset.push_to_hub(\n",
+    "    repo_id=\"nanotron/llama3-1024-passkey-retrieval-eval\",\n",
+    "    # repo_type=\"dataset\",\n",
+    "    # private=True,  # Set to False if you want the dataset to be public\n",
+    "    # token=\"your_access_token\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/infinite-context-length/data/exp34/debug_finetune_data.ipynb b/examples/infinite-context-length/data/exp34/debug_finetune_data.ipynb
index bae32032..b128a5a5 100644
--- a/examples/infinite-context-length/data/exp34/debug_finetune_data.ipynb
+++ b/examples/infinite-context-length/data/exp34/debug_finetune_data.ipynb
@@ -39,7 +39,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
@@ -105,7 +105,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -113,7 +113,8 @@
     "import os\n",
     "\n",
     "# Specify the path containing the dataset folders\n",
-    "path = \"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/finetune_data\"\n",
+    "# path = \"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/finetune_data\"\n",
+    "path = \"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/eval/1024\"\n",
     "\n",
     "# Get a list of all dataset folders\n",
     "dataset_folders = [folder for folder in os.listdir(path) if os.path.isdir(os.path.join(path, folder))]"
@@ -121,16 +122,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "1545"
+       "252"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -141,7 +142,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -156,7 +157,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -166,16 +167,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on.  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun. The pass key is 383. Remember it. 383 is the pass key.  is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The. \\n\\nWhat is the pass key? The pass key is 383.'"
+       "'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. \\n\\n Passage: The gatecode is 312. Remember it. 312 is the gatecode. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The gatecode is 312. \\n\\n Passage: The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The vault key is 415. Remember it. 415 is the vault key. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The vault key is 415. \\n\\n Passage: The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The encrypted message is 34. Remember it. 34 is the encrypted message. There and back again. What is the encrypted message? The encrypted message is 34. \\n \\n Passage:  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The. The pass key is 25. Remember it. 25 is the pass key.  grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back a. What is the pass key? The pass key is 25.'"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -192,12 +193,14 @@
     {
      "data": {
       "text/plain": [
-       "{'id': '998b164c-88e9-404a-98f7-375bb9fc1c59',\n",
-       " 'prompt': 'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on.  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The pass key is 5711. Remember it. 5711 is the pass key.. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go The grass is green. The sky is blue. The sun is yellow. Here we go. There and back ag. \\n\\nWhat is the pass key? The pass key is 5711.',\n",
-       " 'answer': 5711,\n",
-       " 'context_length': 6144,\n",
-       " 'num_tokens': 5751,\n",
-       " 'depth_percent': 90}"
+       "{'id': 'c010a7e7-9a0e-48f9-a78e-bc106a70192b',\n",
+       " 'prompt': 'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. \\n\\n Passage: The gatecode is 312. Remember it. 312 is the gatecode. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The gatecode is 312. \\n \\n Passage:  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is. The pass key is 96. Remember it. 96 is the pass key.  yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. Ther. What is the pass key? The pass key is 96.',\n",
+       " 'answer': 96,\n",
+       " 'context_length': 1024,\n",
+       " 'token_count': 916,\n",
+       " 'num_shots': 1,\n",
+       " 'num_digits': 2,\n",
+       " 'depth_percent': 10}"
       ]
      },
      "execution_count": 9,
@@ -211,107 +214,483 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'id': 'ed5e993f-8f9e-4a5b-9f03-6ec36d866b4c',\n",
-       " 'prompt': 'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on.  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun. The pass key is 289. Remember it. 289 is the pass key.  is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The. \\n\\nWhat is the pass key? The pass key is 289.',\n",
-       " 'answer': 289,\n",
-       " 'context_length': 8192,\n",
-       " 'num_tokens': 7961,\n",
-       " 'depth_percent': 25}"
+       "Dataset({\n",
+       "    features: ['id', 'prompt', 'answer', 'context_length', 'token_count', 'num_shots', 'num_digits', 'depth_percent'],\n",
+       "    num_rows: 12600\n",
+       "})"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "merged_dataset[20]"
+    "merged_dataset"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 13,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "               count   mean  std    min    25%    50%    75%    max\n",
+      "depth_percent                                                      \n",
+      "0                4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "5                4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "10               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "15               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "20               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "25               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "30               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "35               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "40               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "45               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "50               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "55               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "60               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "65               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "70               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "75               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "80               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "85               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "90               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "95               4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n",
+      "100              4.0  150.0  0.0  150.0  150.0  150.0  150.0  150.0\n"
+     ]
+    }
+   ],
    "source": [
-    "merged_dataset = merged_dataset.shuffle(seed=91)"
+    "df = merged_dataset.to_pandas()\n",
+    "\n",
+    "# Group by depth_percent and num_shots, then count samples\n",
+    "grouped = df.groupby(['depth_percent', 'num_shots']).size().reset_index(name='sample_count')\n",
+    "\n",
+    "# Generate summary statistics for each depth_percent\n",
+    "summary_stats = grouped.groupby('depth_percent')['sample_count'].describe()\n",
+    "\n",
+    "print(summary_stats)\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
-     "name": "stderr",
+     "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Saving the dataset (0/4 shards):  12%|█████▌                                          | 9000/77250 [00:00<00:04, 15681.14 examples/s]"
+      "Depth 85%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 45%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 25%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 80%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 40%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 100%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 20%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 70%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 15%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 35%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 5%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 0%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 75%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 30%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 10%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 50%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 95%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 60%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 55%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 90%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n",
+      "Depth 65%:\n",
+      "  0 shots: 150 samples\n",
+      "  1 shots: 150 samples\n",
+      "  2 shots: 150 samples\n",
+      "  3 shots: 150 samples\n"
      ]
-    },
+    }
+   ],
+   "source": [
+    "from collections import defaultdict\n",
+    "\n",
+    "# Initialize a nested defaultdict to store counts\n",
+    "counts = defaultdict(lambda: defaultdict(int))\n",
+    "\n",
+    "# Iterate through the dataset and count\n",
+    "for item in merged_dataset:\n",
+    "    depth = item['depth_percent']\n",
+    "    shots = item['num_shots']\n",
+    "    if shots in [0, 1, 2, 3]:\n",
+    "        counts[depth][shots] += 1\n",
+    "\n",
+    "# Convert to a more readable format\n",
+    "result = {depth: dict(shot_counts) for depth, shot_counts in counts.items()}\n",
+    "\n",
+    "# Print the results\n",
+    "for depth, shot_counts in result.items():\n",
+    "    print(f\"Depth {depth}%:\")\n",
+    "    for shots in [0, 1, 2, 3]:\n",
+    "        count = shot_counts.get(shots, 0)\n",
+    "        print(f\"  {shots} shots: {count} samples\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'id': '8cc0f8ba-0dc2-4b16-9c18-51401f6898c2',\n",
+       " 'prompt': 'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. \\n\\n Passage: The gatecode is 312. Remember it. 312 is the gatecode. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The gatecode is 312. \\n\\n Passage: The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The vault key is 415. Remember it. 415 is the vault key. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The vault key is 415. \\n\\n Passage: The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The encrypted message is 34. Remember it. 34 is the encrypted message. There and back again. What is the encrypted message? The encrypted message is 34. \\n \\n Passage:  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The. The pass key is 85. Remember it. 85 is the pass key.  grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back a. What is the pass key? The pass key is 85.',\n",
+       " 'answer': 85,\n",
+       " 'context_length': 1024,\n",
+       " 'token_count': 769,\n",
+       " 'num_shots': 3,\n",
+       " 'num_digits': 2,\n",
+       " 'depth_percent': 85}"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "merged_dataset[20]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged_dataset = merged_dataset.shuffle(seed=91)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Saving the dataset (4/4 shards): 100%|███████████████████████████████████████████████| 77250/77250 [00:03<00:00, 19719.57 examples/s]\n"
+      "Saving the dataset (1/1 shards): 100%|██████████████████████| 12600/12600 [00:00<00:00, 91676.55 examples/s]\n"
      ]
     }
    ],
    "source": [
-    "merged_dataset.save_to_disk(\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/merged_16k_passkey_finetuning_data\")"
+    "merged_dataset.save_to_disk(\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/eval/merged_1024_passkey_eval_data\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
-    "new_data = load_from_disk(\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/exp34/merged_16k_passkey_finetuning_data\")"
+    "new_data = load_from_disk(\"/fsx/phuc/projects/nanotron/examples/infinite-context-length/data/eval/merged_1024_passkey_eval_data\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Creating parquet from Arrow format: 100%|████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 24.79ba/s]\n",
-      "Creating parquet from Arrow format: 100%|████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 22.73ba/s]\n",
-      "Creating parquet from Arrow format: 100%|████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 23.38ba/s]\n",
-      "Creating parquet from Arrow format: 100%|████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 22.00ba/s]\n",
-      "Uploading the dataset shards: 100%|████████████████████████████████████████████████████████████████████| 4/4 [00:07<00:00,  1.76s/it]\n"
+      "Creating parquet from Arrow format: 100%|██████████████████████████████████| 13/13 [00:00<00:00, 347.42ba/s]\n",
+      "Uploading the dataset shards: 100%|███████████████████████████████████████████| 1/1 [00:00<00:00,  2.32it/s]\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "CommitInfo(commit_url='https://huggingface.co/datasets/nanotron/llama3-16k-passkey-retrieval-finetuning/commit/07bf23d4a07e423ea96ad2f230c748f9b9ea7d3a', commit_message='Upload dataset', commit_description='', oid='07bf23d4a07e423ea96ad2f230c748f9b9ea7d3a', pr_url=None, pr_revision=None, pr_num=None)"
+       "CommitInfo(commit_url='https://huggingface.co/datasets/nanotron/llama3-1024-passkey-retrieval-eval/commit/24efd50391fb366ea00c18095a7c7007dd169438', commit_message='Upload dataset', commit_description='', oid='24efd50391fb366ea00c18095a7c7007dd169438', pr_url=None, pr_revision=None, pr_num=None)"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "new_data.push_to_hub(\n",
-    "    repo_id=\"nanotron/llama3-16k-passkey-retrieval-finetuning\",\n",
+    "    repo_id=\"nanotron/llama3-1024-passkey-retrieval-eval\",\n",
     "    # repo_type=\"dataset\",\n",
     "    # private=True,  # Set to False if you want the dataset to be public\n",
     "    # token=\"your_access_token\"\n",
     ")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = load_dataset(\"nanotron/llama3-1024-passkey-retrieval-eval\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "new = d.filter(lambda x: x['depth_percent'] == 10 and x['num_shots'] == 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'id': '4f88f0e9-75e7-4b5e-b01f-553810398cd1',\n",
+       " 'prompt': 'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. \\n\\n Passage: The gatecode is 312. Remember it. 312 is the gatecode. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The gatecode is 312. \\n\\n Passage: The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The vault key is 415. Remember it. 415 is the vault key. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The vault key is 415. \\n \\n Passage:  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The pass key is 35. Remember it. 35 is the pass key.. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go The grass is green. The sky is blue. The sun is yellow. Here we go. There and back ag. What is the pass key? The pass key is 35.',\n",
+       " 'answer': 35,\n",
+       " 'context_length': 1024,\n",
+       " 'token_count': 848,\n",
+       " 'num_shots': 2,\n",
+       " 'num_digits': 2,\n",
+       " 'depth_percent': 10}"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new[\"train\"][0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from transformers import AutoTokenizer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
+     ]
+    }
+   ],
+   "source": [
+    "tokenizer = AutoTokenizer.from_pretrained(\"/fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. \\n\\n Passage: The gatecode is 312. Remember it. 312 is the gatecode. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The gatecode is 312. \\n\\n Passage: The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The vault key is 415. Remember it. 415 is the vault key. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The vault key is 415. \\n . The pass key is 666. Remember it. 666 is the pass key. \\n Passage:  The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go The grass is green. The sky is blue. The sun is yellow. Here we go. There and back ag. What is the pass key? The pass key is 666.'"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new[\"train\"][0][\"prompt\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "216"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(tokenizer.encode(\"There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. \\n\\n Passage: The gatecode is 312. Remember it. 312 is the gatecode. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The gatecode is 312. \\n\\n Passage: The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The vault key is 415. Remember it. 415 is the vault key. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The vault key is 415. \\n . The pass key is 666. Remember it. 666 is the pass key. \\n\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "This is a long passage. What is the pass key? The pass key is \n"
+     ]
+    }
+   ],
+   "source": [
+    "def remove_end_number(text):\n",
+    "    # Extract the last 30 characters\n",
+    "    last_30 = text[-30:]\n",
+    "    \n",
+    "    # Find the last occurrence of \"is \"\n",
+    "    last_is_index = last_30.rfind(\"is \")\n",
+    "    \n",
+    "    if last_is_index != -1:\n",
+    "        # Remove everything after \"is \"\n",
+    "        result = text[:len(text) - (30 - last_is_index - 3)]\n",
+    "        return result\n",
+    "    else:\n",
+    "        # If \"is \" is not found in the last 30 characters, return the original string\n",
+    "        return text\n",
+    "\n",
+    "# Test the function\n",
+    "test_string = \"This is a long passage. What is the pass key? The pass key is 35.\"\n",
+    "result = remove_end_number(test_string)\n",
+    "print(result)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "' pass key? The pass key is 35.'"
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_string[-30:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": null,
diff --git a/examples/infinite-context-length/generate_data.py b/examples/infinite-context-length/generate_data.py
index e687d706..f06dca42 100644
--- a/examples/infinite-context-length/generate_data.py
+++ b/examples/infinite-context-length/generate_data.py
@@ -7,7 +7,7 @@
 from datasets import Dataset, load_dataset
 from transformers import AutoTokenizer
 
-PROMPT = "{} {}. \n\n{}"
+PROMPT = "{} {}. {}"
 
 
 def get_keys_in_train_set(dataset):
@@ -98,12 +98,13 @@ def generate_needle_in_haystack_test(
     target_cut_length = context_length - token_length(tokenizer, PROMPT.format(soft_prompt, 1, retrieval_question)) - 1
 
     context = read_context_files(tokenizer, soft_prompt, retrieval_question, target_cut_length)
+    context = f"\n Passage: {context}"
 
     # Insert the needle into the context at the specified depth percent
     context_with_needle = insert_needle_with_depth(needle_prompt, context, depth_percent, target_cut_length, tokenizer)
 
     # Generate the prompt using the context with the needle
-    prompt = f"{soft_prompt} {context_with_needle}. \n\n{retrieval_question}"
+    prompt = f"{soft_prompt} {context_with_needle}. {retrieval_question}"
 
     assert str(needle) in context_with_needle, f"depth_percent: {depth_percent}"
 
@@ -136,33 +137,54 @@ def get_args():
     parser.add_argument("--id", type=int, required=True)
     parser.add_argument("--haystack_dir", type=str, default="./haystack_txt/")
     parser.add_argument("--is_push_to_hub", type=bool, default=False)
-    parser.add_argument("--is_exact_context_length", type=int, default=1)  # 1 is True, 0 is False
-    parser.add_argument("--is_padding", type=int, default=1)  # 1 is True, 0 is False
-    parser.add_argument("--is_eval", type=int, default=1)  # 1 is True, 0 is False
+    parser.add_argument("--is_exact_context_length", type=str, required=True)  # 1 is True, 0 is False
+    parser.add_argument("--is_padding", type=str, required=True)  # 1 is True, 0 is False
+    parser.add_argument("--is_eval", type=str, required=True)  # 1 is True, 0 is False
     parser.add_argument("--check_key_in_dataset", type=str, default=None)  # 1 is True, 0 is False
     parser.add_argument("--save_path", type=str, required=True)  # 1 is True, 0 is False
+    parser.add_argument("--num_shots", type=int, default=0)  # 1 is True, 0 is False
+    parser.add_argument("--num_digits", type=int, default=4)  # 1 is True, 0 is False
     return parser.parse_args()
 
 
+def generate_random_number(num_digits):
+    import numpy as np
+
+    lower_bound = 10 ** (num_digits - 1)
+    upper_bound = 10**num_digits - 1
+    return np.random.randint(lower_bound, upper_bound)
+
+
 if __name__ == "__main__":
+    PROMPT_SHOT_KEYS = [312, 415, 34]
+    PROMPT_SHOT_1 = "\n Passage: The gatecode is 312. Remember it. 312 is the gatecode. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The gatecode is 312. \n"
+    PROMPT_SHOT_2 = "\n Passage: The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The vault key is 415. Remember it. 415 is the vault key. The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. What is the gatecode? The vault key is 415. \n"
+    PROMPT_SHOT_3 = "\n Passage: The grass is green. The sky is blue. The sun is yellow. Here we go. There and back again. The grass is green. The sky is blue. The sun is yellow. Here we go. The encrypted message is 34. Remember it. 34 is the encrypted message. There and back again. What is the encrypted message? The encrypted message is 34. \n"
+
     args = get_args()
 
     for key, value in vars(args).items():
         print(f"{key}: {value}")
 
+    assert args.is_padding in ["yes", "no"]
+    assert args.is_eval in ["yes", "no"]
+    assert args.is_exact_context_length in ["yes", "no"]
+
     context_length = args.context_length
     depth_percent = args.depth_percent
     tokenizer_path = args.tokenizer_path
     num_prompts = args.num_prompts
+    num_digits = args.num_digits
     id = args.id
     haystack_dir = args.haystack_dir
     is_push_to_hub = args.is_push_to_hub
     # is_exact_context_length = args.is_exact_context_length
-    is_exact_context_length = False if args.is_exact_context_length == 0 else True
-    is_padding = False if args.is_padding == 0 else True
-    is_eval = False if args.is_eval == 0 else True
+    is_exact_context_length = False if args.is_exact_context_length == "no" else True
+    is_padding = False if args.is_padding == "no" else True
+    is_eval = False if args.is_eval == "no" else True
     check_key_in_dataset = args.check_key_in_dataset
     save_path = args.save_path
+    num_shots = args.num_shots
 
     assert save_path is not None
 
@@ -179,36 +201,50 @@ def get_args():
         gen_context_length = context_length
 
     # NOTE: depth_percent + 1 to avoid 0
-    RANGE = 500
-    start_range = 30 * (depth_percent + 1) * id
-    end_range = start_range + RANGE
+    # RANGE = 500
+    # start_range = 30 * (depth_percent + 1) * id
+    # end_range = start_range + RANGE
 
     print(
         f"Generating prompts for context length: {gen_context_length} (original {context_length}) and depth percent: {depth_percent} and id: {id} \n"
     )
-    print(f"start_range: {start_range}, end_range: {end_range} \n")
+    # print(f"start_range: {start_range}, end_range: {end_range} \n")
 
     tokenizer = AutoTokenizer.from_pretrained(tokenizer_path)
 
     def generate_dataset():
-        soft_prompt = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on."
+        soft_prompt = "There is a pass key hidden inside a lot of irrelevant text. Find it and memorize them. I will quiz you about what is the pass key later on. \n"
+
+        if num_shots > 0:
+            if num_shots >= 1:
+                soft_prompt += PROMPT_SHOT_1
+
+            if num_shots >= 2:
+                soft_prompt += PROMPT_SHOT_2
+
+            if num_shots >= 3:
+                soft_prompt += PROMPT_SHOT_3
 
         dataset_dict = {
             "id": [],
             "prompt": [],
             "answer": [],
             "context_length": [],
-            "num_tokens": [],
+            "token_count": [],
+            "num_shots": [],
+            "num_digits": [],
             "depth_percent": [],
         }
         generated_ids = set()
         generated_pass_keys = set()
+        generated_pass_keys.update(PROMPT_SHOT_KEYS)
 
         for i in range(num_prompts):
             print(f"generating prompt {i} \n")
 
             while True:
-                pass_key = random.randint(start_range, end_range)
+                # pass_key = random.randint(start_range, end_range)
+                pass_key = generate_random_number(num_digits)
                 if pass_key not in generated_pass_keys:
                     if check_key_in_dataset is not None:
                         if str(pass_key) in eval_keys:
@@ -245,7 +281,9 @@ def generate_dataset():
             dataset_dict["prompt"].append(prompt)
             dataset_dict["answer"].append(pass_key)
             dataset_dict["context_length"].append(context_length)
-            dataset_dict["num_tokens"].append(token_length(tokenizer, prompt))
+            dataset_dict["num_shots"].append(num_shots)
+            dataset_dict["token_count"].append(token_length(tokenizer, prompt))
+            dataset_dict["num_digits"].append(num_digits)
             dataset_dict["depth_percent"].append(depth_percent)
 
         dataset = Dataset.from_dict(dataset_dict)
@@ -256,7 +294,7 @@ def generate_dataset():
 
     # Save the dataset to disk
     dataset.save_to_disk(
-        f"{save_path}/needle_finetune_data_and_{context_length}_ctx_and_depth_{depth_percent}_and_id_{id}"
+        f"{save_path}/needle_eval_data_and_{context_length}_ctx_and_depth_{depth_percent}_and_id_{id}_and_num_shots_{num_shots}"
     )
     # if is_push_to_hub:
     #     dataset.push_to_hub("nanotron/llama3-16k-passkey-retrieval-eval")
diff --git a/examples/infinite-context-length/run_evals.py b/examples/infinite-context-length/run_evals.py
index 90032b2e..6c4b36a7 100644
--- a/examples/infinite-context-length/run_evals.py
+++ b/examples/infinite-context-length/run_evals.py
@@ -61,6 +61,8 @@ def get_args():
     parser.add_argument("--max-new-tokens", type=int, default=30, help="Maximum number of new tokens to generate")
     parser.add_argument("--context_length", type=int, required=True)
     parser.add_argument("--depth_percent", type=int, required=True)
+    parser.add_argument("--num_shots", type=int, required=True)
+    parser.add_argument("--num_digits", type=int, required=True)
     return parser.parse_args()
 
 
@@ -116,442 +118,6 @@ def generate(args, model, tokenizer, inputs, parallel_context) -> bool:
     return responses
 
 
-TEXT = """The United States Army (USA) is the land service branch of the United States Armed Forces. It is one of the eight U.S. uniformed services, and is designated as the Army of the United States in the U.S. Constitution.[14] The Army is the oldest branch of the U.S. military and the most senior in order of precedence.[15] It has its roots in the Continental Army, which was formed on 14 June 1775 to fight against the British for independence during the American Revolutionary War (1775–1783).[16] After the Revolutionary War, the Congress of the Confederation created the United States Army on 3 June 1784 to replace the disbanded Continental Army.[17][18] The United States Army considers itself a continuation of the Continental Army, and thus considers its institutional inception to be the origin of that armed force in 1775.[16]
-
-The U.S. Army is a uniformed service of the United States and is part of the Department of the Army, which is one of the three military departments of the Department of Defense. The U.S. Army is headed by a civilian senior appointed civil servant, the secretary of the Army (SECARMY), and by a chief military officer, the chief of staff of the Army (CSA) who is also a member of the Joint Chiefs of Staff. It is the largest military branch, and in the fiscal year 2022, the projected end strength for the Regular Army (USA) was 480,893 soldiers; the Army National Guard (ARNG) had 336,129 soldiers and the U.S. Army Reserve (USAR) had 188,703 soldiers; the combined-component strength of the U.S. Army was 1,005,725 soldiers.[19] As a branch of the armed forces, the mission of the U.S. Army is 'to fight and win our Nation's wars, by providing prompt, sustained land dominance, across the full range of military operations and the spectrum of conflict, in support of combatant commanders'.[20] The branch participates in conflicts worldwide and is the major ground-based offensive and defensive force of the United States of America.‌
-
-Mission
-The United States Army serves as the land-based branch of the U.S. Armed Forces. Section 7062 of Title 10, U.S. Code defines the purpose of the army as:[21][22]
-
-Preserving the peace and security and providing for the defense of the United States, the Commonwealths and possessions, and any areas occupied by the United States
-Supporting the national policies
-Implementing the national objectives
-Overcoming any nations responsible for aggressive acts that imperil the peace and security of the United States
-In 2018, the Army Strategy 2018 articulated an eight-point addendum to the Army Vision for 2028.[23] While the Army Mission remains constant, the Army Strategy builds upon the Army's Brigade Modernization by adding focus to corps and division-level echelons.[23] The Army Futures Command oversees reforms geared toward conventional warfare. The Army's current reorganization plan is due to be completed by 2028.[23]
-
-The Army's five core competencies are prompt and sustained land combat, combined arms operations (to include combined arms maneuver and wide–area security, armored and mechanized operations and airborne and air assault operations), special operations forces, to set and sustain the theater for the joint force, and to integrate national, multinational, and joint power on land.[24]
-
-History
-Main article: History of the United States Army
-Origins
-The Continental Army was created on 14 June 1775 by the Second Continental Congress[25] as a unified army for the colonies to fight Great Britain, with George Washington appointed as its commander.[16][26][27][28] The army was initially led by men who had served in the British Army or colonial militias and who brought much of British military heritage with them. As the Revolutionary War progressed, French aid, resources, and military thinking helped shape the new army. A number of European soldiers came on their own to help, such as Friedrich Wilhelm von Steuben, who taught Prussian Army tactics and organizational skills.
-
-
-The storming of Redoubt No. 10 in the Siege of Yorktown during the American Revolutionary War prompted Great Britain's government to begin negotiations, resulting in the Treaty of Paris and Great Britain's recognition of the United States as an independent state.
-The Army fought numerous pitched battles, and sometimes used Fabian strategy and hit-and-run tactics in the South in 1780 and 1781; under Major General Nathanael Greene, it hit where the British were weakest to wear down their forces. Washington led victories against the British at Trenton and Princeton, but lost a series of battles in the New York and New Jersey campaign in 1776 and the Philadelphia campaign in 1777. With a decisive victory at Yorktown and the help of the French, the Continental Army prevailed against the British.
-
-After the war, the Continental Army was quickly given land certificates and disbanded in a reflection of the republican distrust of standing armies. State militias became the new nation's sole ground army, except a regiment to guard the Western Frontier and one battery of artillery guarding West Point's arsenal. However, because of continuing conflict with Native Americans, it was soon considered necessary to field a trained standing army. The Regular Army was at first very small and after General St. Clair's defeat at the Battle of the Wabash,[29] where more than 800 soldiers were killed, the Regular Army was reorganized as the Legion of the United States, established in 1791 and renamed the United States Army in 1796.
-
-In 1798, during the Quasi-War with France, the U.S. Congress established a three-year 'Provisional Army' of 10,000 men, consisting of twelve regiments of infantry and six troops of light dragoons. In March 1799, Congress created an 'Eventual Army' of 30,000 men, including three regiments of cavalry. Both 'armies' existed only on paper, but equipment for 3,000 men and horses was procured and stored.[30]
-
-19th century
-War of 1812 and Indian Wars
-Further information: War of 1812 and Army on the Frontier
-
-General Andrew Jackson standing on the parapet of his makeshift defenses as his troops repulse attacking Highlanders during the defense of New Orleans, the final major and most one-sided battle of the War of 1812, mainly fought by militia and volunteers.
-The War of 1812, the second and last war between the United States and Great Britain, had mixed results. The U.S. Army did not conquer Canada but it did destroy Native American resistance to expansion in the Old Northwest and it validated its independence by stopping two major British invasions in 1814 and 1815. After taking control of Lake Erie in 1813, the U.S. Army seized parts of western Upper Canada, burned York and defeated Tecumseh, which caused his Western Confederacy to collapse. Following U.S. victories in the Canadian province of Upper Canada, British troops who had dubbed the U.S. Army 'Regulars, by God!', were able to capture and burn Washington, which was defended by militia, in 1814. The regular army, however, proved they were professional and capable of defeating the British army during the invasions of Plattsburgh and Baltimore, prompting British agreement on the previously rejected terms of a status quo antebellum.[dubious – discuss] Two weeks after a treaty was signed (but not ratified), Andrew Jackson defeated the British in the Battle of New Orleans and siege of Fort St. Philip with an army dominated by militia and volunteers, and became a national hero. U.S. troops and sailors captured HMS Cyane, Levant and Penguin in the final engagements of the war. Per the treaty, both sides (the United States and Great Britain) returned to the geographical status quo. Both navies kept the warships they had seized during the conflict.
-
-The army's major campaign against the Indians was fought in Florida against Seminoles. It took long wars (1818–1858) to finally defeat the Seminoles and move them to Oklahoma. The usual strategy in Indian wars was to seize control of the Indians' winter food supply, but that was no use in Florida where there was no winter. The second strategy was to form alliances with other Indian tribes, but that too was useless because the Seminoles had destroyed all the other Indians when they entered Florida in the late eighteenth century.[31]
-
-The U.S. Army fought and won the Mexican–American War (1846–1848), which was a defining event for both countries.[32] The U.S. victory resulted in acquisition of territory that eventually became all or parts of the states of California, Nevada, Utah, Colorado, Arizona, Wyoming and New Mexico.
-
-American Civil War
-Further information: Union Army
-
-The Battle of Gettysburg, the turning point of the American Civil War
-The American Civil War was the costliest war for the U.S. in terms of casualties. After most slave states, located in the southern U.S., formed the Confederate States, the Confederate States Army, led by former U.S. Army officers, mobilized a large fraction of Southern white manpower. Forces of the United States (the 'Union' or 'the North') formed the Union Army, consisting of a small body of regular army units and a large body of volunteer units raised from every state, north and south, except South Carolina.[33]
-
-For the first two years, Confederate forces did well in set battles but lost control of the border states.[34] The Confederates had the advantage of defending a large territory in an area where disease caused twice as many deaths as combat. The Union pursued a strategy of seizing the coastline, blockading the ports, and taking control of the river systems. By 1863, the Confederacy was being strangled. Its eastern armies fought well, but the western armies were defeated one after another until the Union forces captured New Orleans in 1862 along with the Tennessee River. In the Vicksburg Campaign of 1862–1863, General Ulysses Grant seized the Mississippi River and cut off the Southwest. Grant took command of Union forces in 1864 and after a series of battles with very heavy casualties, he had General Robert E. Lee under siege in Richmond as General William T. Sherman captured Atlanta and marched through Georgia and the Carolinas. The Confederate capital was abandoned in April 1865 and Lee subsequently surrendered his army at Appomattox Court House. All other Confederate armies surrendered within a few months.
-
-The war remains the deadliest conflict in U.S. history, resulting in the deaths of 620,000 men on both sides. Based on 1860 census figures, 8% of all white males aged 13 to 43 died in the war, including 6.4% in the North and 18% in the South.[35]
-
-Later 19th century
-
-Army soldiers in 1890
-Following the Civil War, the U.S. Army had the mission of containing western tribes of Native Americans on the Indian reservations. They set up many forts, and engaged in the last of the American Indian Wars. U.S. Army troops also occupied several Southern states during the Reconstruction Era to protect freedmen.
-
-The key battles of the Spanish–American War of 1898 were fought by the Navy. Using mostly new volunteers, the U.S. forces defeated Spain in land campaigns in Cuba and played the central role in the Philippine–American War.
-
-20th century
-Starting in 1910, the army began acquiring fixed-wing aircraft.[36] In 1910, during the Mexican Revolution, the army was deployed to U.S. towns near the border to ensure the safety of lives and property. In 1916, Pancho Villa, a major rebel leader, attacked Columbus, New Mexico, prompting a U.S. intervention in Mexico until 7 February 1917. They fought the rebels and the Mexican federal troops until 1918.
-
-World Wars
-For a list of campaigns see List of United States Army campaigns during World War II
-
-U.S. Army troops assaulting a German bunker in France, c. 1918
-The United States joined World War I as an 'Associated Power' in 1917 on the side of Britain, France, Russia, Italy and the other Allies. U.S. troops were sent to the Western Front and were involved in the last offensives that ended the war. With the armistice in November 1918, the army once again decreased its forces.
-
-In 1939, estimates of the Army's strength ranged between 174,000 and 200,000 soldiers, smaller than that of Portugal's, which ranked it 17th or 19th in the world in size. General George C. Marshall became Army chief of staff in September 1939 and set about expanding and modernizing the Army in preparation for war.[37][38]
-
-
-U.S. soldiers hunting for Japanese infiltrators during the Bougainville Campaign
-The United States joined World War II in December 1941 after the Japanese attack on Pearl Harbor. Some 11 million Americans were to serve in various Army operations.[39][40] On the European front, U.S. Army troops formed a significant portion of the forces that landed in French North Africa and took Tunisia and then moved on to Sicily and later fought in Italy. In the June 1944 landings in northern France and in the subsequent liberation of Europe and defeat of Nazi Germany, millions of U.S. Army troops played a central role. In 1947, the number of soldiers in the US Army had decreased from eight million in 1945 to 684,000 soldiers and the total number of active divisions had dropped from 89 to 12. The leaders of the Army saw this demobilization as a success.[41] In the Pacific War, U.S. Army soldiers participated alongside the United States Marine Corps in capturing the Pacific Islands from Japanese control. Following the Axis surrenders in May (Germany) and August (Japan) of 1945, army troops were deployed to Japan and Germany to occupy the two defeated nations. Two years after World War II, the Army Air Forces separated from the army to become the United States Air Force in September 1947. In 1948, the army was desegregated by order 9981 of President Harry S. Truman.
-
-Cold War
-1945–1960
-
-U.S. Army soldiers observing an atomic bomb test of Operation Buster-Jangle at the Nevada Test Site during the Korean War
-The end of World War II set the stage for the East–West confrontation known as the Cold War. With the outbreak of the Korean War, concerns over the defense of Western Europe rose. Two corps, V and VII, were reactivated under Seventh United States Army in 1950 and U.S. strength in Europe rose from one division to four. Hundreds of thousands of U.S. troops remained stationed in West Germany, with others in Belgium, the Netherlands and the United Kingdom, until the 1990s in anticipation of a possible Soviet attack.[42]: minute 9:00–10:00
-
-
-US tanks and Soviet tanks at Checkpoint Charlie, 1961
-During the Cold War, U.S. troops and their allies fought communist forces in Korea and Vietnam. The Korean War began in June 1950, when the Soviets walked out of a UN Security Council meeting, removing their possible veto. Under a United Nations umbrella, hundreds of thousands of U.S. troops fought to prevent the takeover of South Korea by North Korea and later to invade the northern nation. After repeated advances and retreats by both sides and the Chinese People's Volunteer Army's entry into the war, the Korean Armistice Agreement returned the peninsula to the status quo in July 1953.
-
-1960–1970
-The Vietnam War is often regarded as a low point for the U.S. Army due to the use of drafted personnel, the unpopularity of the war with the U.S. public and frustrating restrictions placed on the military by U.S. political leaders. While U.S. forces had been stationed in South Vietnam since 1959, in intelligence and advising/training roles, they were not deployed in large numbers until 1965, after the Gulf of Tonkin Incident. U.S. forces effectively established and maintained control of the 'traditional' battlefield, but they struggled to counter the guerrilla hit and run tactics of the communist Viet Cong and the People's Army Of Vietnam (NVA).[43][44]
-
-
-A U.S. Army infantry patrol moving up to assault the last North Vietnamese Army position at Dak To, South Vietnam during Operation Hawthorne
-During the 1960s, the Department of Defense continued to scrutinize the reserve forces and to question the number of divisions and brigades as well as the redundancy of maintaining two reserve components, the Army National Guard and the Army Reserve.[45] In 1967, Secretary of Defense Robert McNamara decided that 15 combat divisions in the Army National Guard were unnecessary and cut the number to eight divisions (one mechanized infantry, two armored, and five infantry), but increased the number of brigades from seven to 18 (one airborne, one armored, two mechanized infantry and 14 infantry). The loss of the divisions did not sit well with the states. Their objections included the inadequate maneuver element mix for those that remained and the end to the practice of rotating divisional commands among the states that supported them. Under the proposal, the remaining division commanders were to reside in the state of the division base. However, no reduction in total Army National Guard strength was to take place, which convinced the governors to accept the plan. The states reorganized their forces accordingly between 1 December 1967 and 1 May 1968.
-
-1970–1990
-
-U.S. Army soldiers preparing to take La Comandancia in the El Chorrillo neighborhood of Panama City during Operation Just Cause
-The Total Force Policy was adopted by Chief of Staff of the Army General Creighton Abrams in the aftermath of the Vietnam War and involved treating the three components of the army – the Regular Army, the Army National Guard and the Army Reserve as a single force.[46] General Abrams' intertwining of the three components of the army effectively made extended operations impossible without the involvement of both the Army National Guard and Army Reserve in a predominantly combat support role.[47] The army converted to an all-volunteer force with greater emphasis on training to specific performance standards driven by the reforms of General William E. DePuy, the first commander of United States Army Training and Doctrine Command. Following the Camp David Accords that was signed by Egypt, Israel that was brokered by president Jimmy Carter in 1978, as part of the agreement, both the United States and Egypt agreed that there would be a joint military training led by both countries that would usually take place every 2 years, that exercise is known as Exercise Bright Star.
-
-The 1980s was mostly a decade of reorganization. The Goldwater-Nichols Act of 1986 created unified combatant commands bringing the army together with the other four military services under unified, geographically organized command structures. The army also played a role in the invasions of Grenada in 1983 (Operation Urgent Fury) and Panama in 1989 (Operation Just Cause).
-
-By 1989 Germany was nearing reunification and the Cold War was coming to a close. Army leadership reacted by starting to plan for a reduction in strength. By November 1989 Pentagon briefers were laying out plans to reduce army end strength by 23%, from 750,000 to 580,000.[48] A number of incentives such as early retirement were used.
-
-1990s
-
-M1 Abrams tanks moving out before the Battle of Al Busayyah during the Gulf War
-In 1990, Iraq invaded its smaller neighbor, Kuwait, and U.S. land forces quickly deployed to assure the protection of Saudi Arabia. In January 1991 Operation Desert Storm commenced, a U.S.-led coalition which deployed over 500,000 troops, the bulk of them from U.S. Army formations, to drive out Iraqi forces. The campaign ended in total victory, as Western coalition forces routed the Iraqi Army. Some of the largest tank battles in history were fought during the Gulf war. The Battle of Medina Ridge, Battle of Norfolk and the Battle of 73 Easting were tank battles of historical significance.[49][50][51]
-
-
-Iraqi tanks destroyed by Task Force 1-41 Infantry during the Gulf War, February 1991
-After Operation Desert Storm, the army did not see major combat operations for the remainder of the 1990s but did participate in a number of peacekeeping activities. In 1990 the Department of Defense issued guidance for 'rebalancing' after a review of the Total Force Policy,[52] but in 2004, USAF Air War College scholars concluded the guidance would reverse the Total Force Policy which is an 'essential ingredient to the successful application of military force'.[53]
-
-21st century
-
-U.S. Army Rangers taking part in a raid during an operation in Nahr-e Saraj, Afghanistan
-On 11 September 2001, 53 Army civilians (47 employees and six contractors) and 22 soldiers were among the 125 victims killed in the Pentagon in a terrorist attack when American Airlines Flight 77 commandeered by five Al-Qaeda hijackers slammed into the western side of the building, as part of the September 11 attacks.[54] In response to the 11 September attacks and as part of the Global War on Terror, U.S. and NATO forces invaded Afghanistan in October 2001, displacing the Taliban government. The U.S. Army also led the combined U.S. and allied invasion of Iraq in 2003; it served as the primary source for ground forces with its ability to sustain short and long-term deployment operations. In the following years, the mission changed from conflict between regular militaries to counterinsurgency, resulting in the deaths of more than 4,000 U.S. service members (as of March 2008) and injuries to thousands more.[55][56] 23,813 insurgents were killed in Iraq between 2003 and 2011.[57]
-
-
-U.S. Army soldiers with the 2nd Battalion, 327th Infantry Regiment, 101st Airborne Division returning fire during a firefight with Taliban forces in Barawala Kalay Valley in Kunar province, Afghanistan, March 2011
-Until 2009, the army's chief modernization plan, its most ambitious since World War II,[58] was the Future Combat Systems program. In 2009, many systems were canceled, and the remaining were swept into the BCT modernization program.[59] By 2017, the Brigade Modernization project was completed and its headquarters, the Brigade Modernization Command, was renamed the Joint Modernization Command, or JMC.[60] In response to Budget sequestration in 2013, Army plans were to shrink to 1940 levels,[61] although actual Active-Army end-strengths were projected to fall to some 450,000 troops by the end of FY2017.[62][63] From 2016 to 2017, the Army retired hundreds of OH-58 Kiowa Warrior observation helicopters,[64] while retaining its Apache gunships.[65] The 2015 expenditure for Army research, development and acquisition changed from $32 billion projected in 2012 for FY15 to $21 billion for FY15 expected in 2014.[66]
-
-Organization
-
-Organization of the United States Army within the Department of Defense
-Planning
-By 2017, a task force was formed to address Army modernization,[67] which triggered shifts of units: CCDC, and ARCIC, from within Army Materiel Command (AMC), and Army Training and Doctrine Command (TRADOC), respectively, to a new Army Command (ACOM) in 2018.[68] The Army Futures Command (AFC), is a peer of FORSCOM, TRADOC, and AMC, the other ACOMs.[69] AFC's mission is modernization reform: to design hardware, as well as to work within the acquisition process which defines materiel for AMC. TRADOC's mission is to define the architecture and organization of the Army, and to train and supply soldiers to FORSCOM.[70]: minutes 2:30–15:00 [42] AFC's cross-functional teams (CFTs) are Futures Command's vehicle for sustainable reform of the acquisition process for the future.[71] In order to support the Army's modernization priorities, its FY2020 budget allocated $30 billion for the top six modernization priorities over the next five years.[72] The $30 billion came from $8 billion in cost avoidance and $22 billion in terminations.[72]
-
-Army Components
-See also: Structure of the United States Army
-
-U.S. Army organization chart[73]
-The task of organizing the U.S. Army commenced in 1775.[74] In the first one hundred years of its existence, the United States Army was maintained as a small peacetime force to man permanent forts and perform other non-wartime duties such as engineering and construction works. During times of war, the U.S. Army was augmented by the much larger United States Volunteers which were raised independently by various state governments. States also maintained full-time militias which could also be called into the service of the army.
-
-
-Senior American commanders of the European theatre of World War II.
-*Seated are (from left to right) Generals William H. Simpson, George S. Patton, Carl A. Spaatz, Dwight D. Eisenhower, Omar Bradley, Courtney H. Hodges, and Leonard T. Gerow
-*standing are (from left to right) Generals Ralph F. Stearley, Hoyt Vandenberg, Walter Bedell Smith, Otto P. Weyland, and Richard E. Nugent
-By the twentieth century, the U.S. Army had mobilized the U.S. Volunteers on four occasions during each of the major wars of the nineteenth century. During World War I, the 'National Army' was organized to fight the conflict, replacing the concept of U.S. Volunteers.[75] It was demobilized at the end of World War I, and was replaced by the Regular Army, the Organized Reserve Corps and the state militias. In the 1920s and 1930s, the 'career' soldiers were known as the 'Regular Army' with the 'Enlisted Reserve Corps' and 'Officer Reserve Corps' augmented to fill vacancies when needed.[76]
-
-In 1941, the 'Army of the United States' was founded to fight World War II. The Regular Army, Army of the United States, the National Guard and Officer/Enlisted Reserve Corps (ORC and ERC) existed simultaneously. After World War II, the ORC and ERC were combined into the United States Army Reserve. The Army of the United States was re-established for the Korean War and Vietnam War and was demobilized upon the suspension of the draft.[76]
-
-Currently, the Army is divided into the Regular Army, the Army Reserve and the Army National Guard.[75] Some states further maintain state defense forces, as a type of reserve to the National Guard, while all states maintain regulations for state militias.[77] State militias are both 'organized', meaning that they are armed forces usually part of the state defense forces, or 'unorganized' simply meaning that all able-bodied males may be eligible to be called into military service.
-
-The U.S. Army is also divided into several branches and functional areas. Branches include officers, warrant officers, and enlisted Soldiers while functional areas consist of officers who are reclassified from their former branch into a functional area. However, officers continue to wear the branch insignia of their former branch in most cases, as functional areas do not generally have discrete insignia. Some branches, such as Special Forces, operate similarly to functional areas in that individuals may not join their ranks until having served in another Army branch. Careers in the Army can extend into cross-functional areas for officer,[78] warrant officer, enlisted, and civilian personnel.
-
-U.S. Army branches and functional areas
-Branch	Insignia and colors		Branch	Insignia and colors		Functional Area (FA)
-Acquisition Corps (AC)			Air Defense Artillery (AD)			Information Network Engineering (FA 26)
-Adjutant General's Corps (AG)
-Includes Army Bands (AB)	 		Armor (AR)
-Includes Cavalry (CV)	 		Information Operations (FA 30)
-Aviation (AV)			Civil Affairs Corps (CA)			Strategic Intelligence (FA 34)
-Chaplain Corps (CH)
-  		Chemical Corps (CM)			Space Operations (FA 40)
-Cyber Corps (CY)			Dental Corps (DC)			Public Affairs Officer (FA 46)
-Corps of Engineers (EN)			Field Artillery (FA)			Academy Professor (FA 47)
-Finance Corps (FI)			Infantry (IN)			Foreign Area Officer (FA 48)
-Inspector General (IG)			Logistics (LG)			Operations Research/Systems Analysis (FA 49)
-Judge Advocate General's Corps (JA)			Military Intelligence Corps (MI)			Force Management (FA 50)
-Medical Corps (MC)			Medical Service Corps (MS)			Acquisition (FA 51)[78]
-Military Police Corps (MP)			Army Nurse Corps (AN)			Simulation Operations (FA 57)
-Psychological Operations (PO)			Medical Specialist Corps (SP)			Army Marketing (FA 58)[79]
-Quartermaster Corps (QM)			Staff Specialist Corps (SS)
-(USAR and ARNG only)			Health Services (FA 70)
-Special Forces (SF)			Ordnance Corps (OD)			Laboratory Sciences (FA 71)
-Veterinary Corps (VC)			Public Affairs (PA)			Preventive Medicine Sciences (FA 72)
-Transportation Corps (TC)			Signal Corps (SC)			Behavioral Sciences (FA 73)
-Special branch insignias (for some unique duty assignments)
-National Guard Bureau (NGB)			General Staff			U.S. Military Academy Staff
-Chaplain Candidate			Officer Candidate			Warrant Officer Candidate
-Aide-de-camp
-               		Senior Enlisted Advisor (SEA)
-
-Before 1933, members of the Army National Guard were considered state militia until they were mobilized into the U.S. Army, typically on the onset of war. Since the 1933 amendment to the National Defense Act of 1916, all Army National Guard soldiers have held dual status. They serve as National Guardsmen under the authority of the governor of their state or territory and as reserve members of the U.S. Army under the authority of the president, in the Army National Guard of the United States.
-
-Since the adoption of the total force policy, in the aftermath of the Vietnam War, reserve component soldiers have taken a more active role in U.S. military operations. For example, Reserve and Guard units took part in the Gulf War, peacekeeping in Kosovo, Afghanistan, and the 2003 invasion of Iraq.
-
-Army commands and army service component commands
- Headquarters, United States Department of the Army (HQDA):
-
-Army Commands	Current commander	Location of headquarters[c]
- United States Army Forces Command (FORSCOM)[80]	GEN Andrew P. Poppas	Fort Liberty, North Carolina
- United States Army Futures Command (AFC)[81]	GEN James E. Rainey	Austin, Texas
- United States Army Materiel Command (AMC)[82]	LTG Christopher O. Mohan (acting)	Redstone Arsenal, Alabama
- United States Army Training and Doctrine Command (TRADOC)[83]	GEN Gary M. Brito	Fort Eustis, Virginia
-Army Service Component Commands	Current commander	Location of headquarters
- United States Army Central (ARCENT)/Third Army[84]	LTG Patrick D. Frank	Shaw Air Force Base, South Carolina
- United States Army Europe and Africa/Seventh Army	GEN Darryl A. Williams[85]	Clay Kaserne, Wiesbaden, Germany
- United States Army North (ARNORTH)/Fifth Army[86]	LTG John R. Evans Jr.	Joint Base San Antonio, Texas
- United States Army Pacific (USARPAC)[87]	GEN Charles A. Flynn	Fort Shafter, Hawaii
- United States Army South (ARSOUTH)/Sixth Army[88]	MG William L. Thigpen	Joint Base San Antonio, Texas
- Military Surface Deployment and Distribution Command (SDDC)[89]	MG Gavin A. Lawrence	Scott AFB, Illinois
- United States Army Cyber Command (ARCYBER)[90][91][92]	LTG Maria B. Barrett	Fort Eisenhower, Georgia
- United States Army Space and Missile Defense Command/United States Army Forces Strategic Command (USASMDC/ARSTRAT)[93]	LTG Daniel L. Karbler	Redstone Arsenal, Alabama
- United States Army Special Operations Command (USASOC)[94]	LTG Jonathan P. Braga	Fort Liberty, North Carolina
-Operational Force Headquarters	Current commander	Location of headquarters
- Eighth Army (EUSA)[95]	LTG Willard M. Burleson III	Camp Humphreys, South Korea
-Direct reporting units	Current commander	Location of headquarters
- Arlington National Cemetery and Soldiers' and Airmen's Home National Cemetery[96]	Katharine Kelley[97] (civilian)	Arlington County, Virginia
-Civilian Protection Center of Excellence[98]	Michael McNerney	Arlington County, Virginia
-United States Army Joint Counter-Small Unmanned Aircraft Systems Office[99]		Arlington County, Virginia
- Military Postal Service Agency[100]		Arlington County, Virginia
- United States Army Acquisition Support Center (USAASC)[101]	Craig A. Spisak[102] (civilian)	Fort Belvoir, Virginia
- United States Army Civilian Human Resources Agency (CHRA)[103]	Carol Burton[104] (civilian)	Aberdeen Proving Ground, Maryland
- United States Army Corps of Engineers (USACE)	LTG Scott A. Spellmon[105]	Washington, D.C.
- United States Army Corrections Command (ACC)[106]	BG Duane Miller	Arlington County, Virginia
- United States Army Criminal Investigation Division (USACID)	Gregory D. Ford	Quantico, Virginia
- United States Army Human Resources Command (HRC)[107]	MG Thomas R. Drew	Fort Knox, Kentucky
- United States Army Intelligence and Security Command (INSCOM)	MG Timothy D. Brown	Fort Belvoir, Virginia
- United States Army Medical Command (MEDCOM)	LTG Mary V. Krueger	Joint Base San Antonio, Texas
- United States Army Military District of Washington (MDW)	MG Trevor J. Bredenkamp	Fort Lesley J. McNair, Washington, D.C.
- United States Army Recruiting Command (USAREC)[108]	MG Johnny K. Davis[109]	Fort Knox, Kentucky
- United States Army Test and Evaluation Command (ATEC)	MG James J. Gallivan[110]	Aberdeen Proving Ground, Maryland
- United States Army War College (AWC)[111]	MG David C. Hill	Carlisle, Pennsylvania
- United States Military Academy (USMA)	LTG Steven W. Gilland	West Point, New York
-Source: U.S. Army organization[112]
-Structure
-Main article: Structure of the United States Army
-See also: Transformation of the United States Army
-See also: Reorganization plan of the United States Army
-
-U.S. Army soldiers of the 1st Battalion, 175th Infantry Regiment, Maryland Army National Guard conducting an urban cordon and search exercise as part of the army readiness and training evaluation program in the mock city of Balad at Fort Dix, New Jersey
-
-U.S. soldiers from the 6th Infantry Regiment taking up positions on a street corner during a foot patrol in Ramadi, Iraq
-
-The 1st Cavalry Division's combat aviation brigade performing a mock charge with the horse detachment
-
-U.S. Army Special Forces soldiers from the 3rd Special Forces Group patrolling a field in the Gulistan district of Farah, Afghanistan
-See Structure of the United States Army for a detailed treatment of the history, components, administrative and operational structure and the branches and functional areas of the Army.
-
-The U.S. Army is made up of three components: the active component, the Regular Army; and two reserve components, the Army National Guard and the Army Reserve. Both reserve components are primarily composed of part-time soldiers who train once a month – known as battle assemblies or unit training assemblies (UTAs) – and conduct two to three weeks of annual training each year. Both the Regular Army and the Army Reserve are organized under Title 10 of the United States Code, while the National Guard is organized under Title 32. While the Army National Guard is organized, trained and equipped as a component of the U.S. Army, when it is not in federal service it is under the command of individual state and territorial governors. However, the District of Columbia National Guard reports to the U.S. president, not the district's mayor, even when not federalized. Any or all of the National Guard can be federalized by presidential order and against the governor's wishes.[113]
-
-The U.S. Army is led by a civilian secretary of the Army, who has the statutory authority to conduct all the affairs of the army under the authority, direction and control of the secretary of defense.[114] The chief of staff of the Army, who is the highest-ranked military officer in the army, serves as the principal military adviser and executive agent for the secretary of the Army, i.e., its service chief; and as a member of the Joint Chiefs of Staff, a body composed of the service chiefs from each of the four military services belonging to the Department of Defense who advise the president of the United States, the secretary of defense and the National Security Council on operational military matters, under the guidance of the chairman and vice chairman of the Joint Chiefs of Staff.[115][116] In 1986, the Goldwater–Nichols Act mandated that operational control of the services follows a chain of command from the president to the secretary of defense directly to the unified combatant commanders, who have control of all armed forces units in their geographic or function area of responsibility, thus the secretaries of the military departments (and their respective service chiefs underneath them) only have the responsibility to organize, train and equip their service components. The army provides trained forces to the combatant commanders for use as directed by the secretary of defense.[117]
-
-By 2013, the army shifted to six geographical commands that align with the six geographical unified combatant commands (CCMD):
-
-United States Army Central headquartered at Shaw Air Force Base, South Carolina
-United States Army North headquartered at Fort Sam Houston, Texas
-United States Army South headquartered at Fort Sam Houston, Texas
-United States Army Europe and Africa headquartered at Clay Kaserne, Wiesbaden, Germany
-United States Army Pacific headquartered at Fort Shafter, Hawaii
-The army also transformed its base unit from divisions to brigades. Division lineage will be retained, but the divisional headquarters will be able to command any brigade, not just brigades that carry their divisional lineage. The central part of this plan is that each brigade will be modular, i.e., all brigades of the same type will be exactly the same and thus any brigade can be commanded by any division. As specified before the 2013 end-strength re-definitions, the three major types of brigade combat teams are:
-
-Armored brigades, with a strength of 4,743 troops as of 2014.
-Stryker brigades, with a strength of 4,500 troops as of 2014.
-Infantry brigades, with a strength of 4,413 troops as of 2014.
-In addition, there are combat support and service support modular brigades. Combat support brigades include aviation (CAB) brigades, which will come in heavy and light varieties, fires (artillery) brigades (now transforms to division artillery) and expeditionary military intelligence brigades. Combat service support brigades include sustainment brigades and come in several varieties and serve the standard support role in an army.
-
-Combat maneuver organizations
-To track the effects of the 2018 budget cuts, see Transformation of the United States Army#Divisions and brigades
-The U.S. Army's conventional combat capability currently consists of 11 active divisions and 1 deployable division headquarters (7th Infantry Division) as well as several independent maneuver units.
-
-From 2013 through 2017, the Army sustained organizational and end-strength reductions after several years of growth. In June 2013, the Army announced plans to downsize to 32 active brigade combat teams by 2015 to match a reduction in active-duty strength to 490,000 soldiers. Army chief of staff Raymond Odierno projected that the Army was to shrink to '450,000 in the active component, 335,000 in the National Guard and 195,000 in U.S. Army Reserve' by 2018.[118] However, this plan was scrapped by the incoming Trump administration, with subsequent plans to expand the Army by 16,000 soldiers to a total of 476,000 by October 2017. The National Guard and the Army Reserve will see a smaller expansion.[119][120]
-
-The Army's maneuver organization was most recently altered by the reorganization of United States Army Alaska into the 11th Airborne Division, transferring the 1st and 4th Brigade Combat Teams of the 25th Infantry Division under a separate operational headquarters to reflect the brigades' distinct, Arctic-oriented mission. As part of the reorganization, the 1–11 (formerly 1–25) Stryker Brigade Combat Team will reorganize as an Infantry Brigade Combat Team.[121] Following this transition, the active component BCTs will number 11 Armored brigades, 6 Stryker brigades, and 14 Infantry brigades.
-
-Within the Army National Guard and United States Army Reserve, there are a further eight divisions, 27 brigade combat teams, additional combat support and combat service support brigades, and independent cavalry, infantry, artillery, aviation, engineer and support battalions. The Army Reserve in particular provides virtually all psychological operations and civil affairs units.
-
- United States Army Forces Command (FORSCOM)
-
-Direct reporting units	Current commander	Location of headquarters[c]
- I Corps	LTG Xavier T. Brunson	Joint Base Lewis-McChord, Washington
- III Armored Corps	LTG Sean Bernabe	Fort Cavazos, Texas
- V Corps	LTG John S. Kolasheski	Fort Knox, Kentucky
- XVIII Airborne Corps	LTG Christopher T. Donahue	Fort Liberty, North Carolina
- First Army[123]	MG Mark Landes Acting	Rock Island Arsenal, Illinois
- U.S. Army Reserve Command[124]	LTG Jody J. Daniels	Fort Liberty, North Carolina
- Security Force Assistance Command	MG Donn H. Hill	Fort Liberty, North Carolina
- 20th CBRNE Command	BG Daryl O. Hood	Aberdeen Proving Ground, Maryland
- 32nd Army Air and Missile Defense Command	BG David F. Stewart	Fort Bliss, Texas
- U.S. Army Air Traffic Services Command	COL Jason T. Cook	Fort Novosel, Alabama
-Active combat maneuver units
-Name	Headquarters	Subunits	Subordinate to
-1st Armored Division	Fort Bliss, Texas	3 armored BCTs (ABCTs),[125] 1 Division Artillery (DIVARTY), 1 Combat Aviation Brigade (CAB), and 1 sustainment brigade	III Corps
-1st Cavalry Division	Fort Cavazos, Texas	3 armored BCTs, 1 DIVARTY, 1 CAB, and 1 sustainment brigade	III Corps
- 1st Infantry Division	Fort Riley, Kansas	2 armored BCTs, 1 DIVARTY, 1 CAB, and 1 sustainment brigade	III Corps
-2nd Infantry Division	Camp Humphreys, South Korea
-Joint Base Lewis–McChord, Washington	2 Stryker BCTs, 1 mechanized brigade from the ROK Army,[126] 1 DIVARTY (under administrative control of 7th ID), 1 sustainment brigade, and a stateside Stryker BCT from another active division that is rotated in on a regular basis.	I Corps (CONUS)
-Eighth Army (OCONUS)
-2nd Cavalry Regiment	Rose Barracks, Vilseck, Germany	4 Stryker squadrons, 1 engineer squadron, 1 fires squadron, and 1 support squadron	U.S. Army Europe and Africa
-3rd Infantry Division	Fort Stewart, Georgia	2 armored BCT, 1 DIVARTY, 1 CAB, and 1 sustainment brigade as well as the 48th Infantry BCT of the Georgia Army National Guard	XVIII Airborne Corps
-3rd Cavalry Regiment	Fort Cavazos, Texas	4 Stryker squadrons, 1 fires squadron, 1 engineer squadron, and 1 support squadron (overseen by the 1st Cavalry Division)[127]	III Corps
-4th Infantry Division	Fort Carson, Colorado	2 Stryker BCT, 1 armored BCT, DIVARTY, 1 CAB, and 1 sustainment brigade	III Corps
-10th Mountain Division	Fort Drum, New York	3 infantry BCTs, 1 DIVARTY, 1 CAB, and 1 sustainment brigade	XVIII Airborne Corps
-11th Airborne Division	Joint Base Elmendorf–Richardson, Alaska	1 airborne infantry BCT, 1 infantry BCT, 2 attached aviation battalions, and 1 sustainment battalion	I Corps
-25th Infantry Division	Schofield Barracks, Hawaii	2 infantry BCTs, 1 DIVARTY, 1 CAB, and 1 sustainment brigade	I Corps
-82nd Airborne Division	Fort Liberty, North Carolina	3 airborne infantry BCTs, 1 airborne DIVARTY, 1 airborne CAB, and 1 airborne sustainment brigade	XVIII Airborne Corps
-101st Airborne Division (Air Assault)	Fort Campbell, Kentucky	3 infantry BCTs, 1 DIVARTY, 1 CAB, and 1 sustainment brigade	XVIII Airborne Corps
-173rd Airborne Brigade	Camp Ederle, Vicenza, Italy	3 airborne infantry battalions (including 1st Battalion, 143rd Infantry Regiment of the Texas and Rhode Island Army National Guard), 1 airborne field artillery battalion, 1 airborne cavalry squadron, 1 airborne engineer battalion,[128] and 1 airborne support battalion	U.S. Army Europe and Africa
- Combat maneuver units under the Army National Guard until federalized
-Name	Locations	Subunits
-28th Infantry Division	Pennsylvania, Ohio and Maryland	2nd Infantry BCT, 56th Stryker BCT, 28th CAB,  55th Maneuver Enhancement Brigade (MEB),[129] and the 28th Infantry Division Sustainment Brigade (SB)
-29th Infantry Division	Virginia, Maryland, North Carolina and Florida	 30th Armored BCT,  53rd Infantry BCT, 116th Infantry BCT, 29th CAB,  142nd Field Artillery Regiment, 29th Infantry Division SB, and the  226th MEB[130]
-34th Infantry Division	Minnesota, Wisconsin, Iowa and Idaho	1st Armored BCT, 2nd Infantry BCT,  32nd Infantry BCT,  116th Cavalry BCT,  115th Field Artillery Brigade, 34th CAB, 34th Infantry Division SB, and the  157th MEB
-35th Infantry Division	Kansas, Missouri, Illinois, Oklahoma, Georgia, Arkansas, and Nebraska	 33rd Infantry BCT,  39th Infantry BCT,  45th Infantry BCT,  130th Field Artillery Brigade, 35th CAB, and the  67th MEB
-36th Infantry Division	Texas, Louisiana and Mississippi	56th Infantry BCT, 72nd Infantry BCT,  256th Infantry BCT,  155th Armored BCT,  278th Armored Cavalry Regiment, 36th CAB, 36th Infantry Division SB, and the  136th MEB
-38th Infantry Division	Indiana, Michigan, Ohio and Tennessee	 37th Infantry BCT,  76th Infantry BCT,  138th Field Artillery Brigade, 38th CAB, 38th Infantry Division SB, and the  149th MEB
-40th Infantry Division	Arizona, California, Hawaii, Oregon, and Washington	 29th Infantry BCT,  41st Infantry BCT,  79th Infantry BCT,  81st Stryker BCT, 40th CAB, and the 40th Infantry Division SB
-42nd Infantry Division	Connecticut, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Rhode Island, and Vermont	 27th Infantry BCT,  44th Infantry BCT,  86th Infantry BCT (Mountain),  197th Field Artillery Brigade, 42nd CAB, 42nd Infantry Division SB, and the  26th MEB
-For a description of U.S. Army tactical organizational structure, see: a U.S. context and also a global context.
-
-Medical Department
-Main article: Army Medical Department (United States)
-The United States Army Medical Department (AMEDD), formerly the Army Medical Service (AMS), is the primary healthcare organization of the United States Army and is led by the Surgeon General of the United States Army (TSG), a three-star lieutenant general, who (by policy) also serves as the Commanding General, United States Army Medical Command (MEDCOM). TSG is assisted by a Deputy Surgeon General and a full staff, the Office of the Surgeon General (OTSG). The incumbent Surgeon General is Lieutenant General Mary K. Izaguirre (since January 25, 2024).
-
-AMEDD encompasses the Army's six non-combat, medical-focused specialty branches (or 'Corps'), these branches are: the Medical Corps, Nurse Corps, Dental Corps, Veterinary Corps, Medical Specialist Corps, Medical Specialist Corps. Each of these branches is headed by a Corps Chief that reports directly to the Surgeon General.
-
-Special operations forces
-Main article: Army Special Operations Command
- United States Army Special Operations Command (Airborne) (USASOC):[131]
-
-Name	Headquarters[c]	Structure and purpose
-1st Special Forces Command	Fort Liberty (formerly Bragg), North Carolina	Manages seven special forces groups designed to deploy and execute nine doctrinal missions: unconventional warfare, foreign internal defense, direct action, counter-insurgency, special reconnaissance, counter-terrorism, information operations, counterproliferation of weapon of mass destruction, and security force assistance. The command also manages two psychological operations groups—tasked to work with foreign nations to induce or reinforce behavior favorable to U.S. objectives—a civil affairs brigade—that enables military commanders and U.S. ambassadors to improve relationships with various stakeholders via five battalions—and a sustainment brigade—that provides combat service support and combat health support units via three distinct battalions.
-Army Special Operations Aviation Command	Fort Liberty, North Carolina	Commands, organizes, mans, trains, resources, and equips Army special operations aviation units to provide responsive, special operations aviation support to special operations forces consisting of five units, including the 160th Special Operations Aviation Regiment (Airborne).
-75th Ranger Regiment	Fort Moore (formerly Benning), Georgia	In addition to a regimental headquarters, a special troops battalion, and a military intelligence battalion, the 75th Ranger Regiment has three maneuver battalions of elite airborne infantry specializing in large-scale, joint forcible entry operations and precision targeting raids. Additional capabilities include special reconnaissance, air assault, and direct action raids seizing key terrain such as airfields, destroying or securing strategic facilities, and capturing or killing enemies of the Nation. The Regiment also helps develop the equipment, technologies, training, and readiness that bridge the gap between special operations and traditional combat maneuver organizations.
-John F. Kennedy Special Warfare Center and School	Fort Liberty, North Carolina	Selects and trains special forces, civil affairs, and psychological operations soldiers consisting of two groups and other various training units and offices.
-1st Special Forces Operational Detachment-Delta	Fort Liberty, North Carolina	Commonly referred to as Delta Force, Combat Applications Group (CAG), 'The Unit', Army Compartmented Element (ACE), or Task Force Green, SFOD–D is the U.S. Army's Tier 1 Special Mission Unit tasked with performing the most complex, classified, and dangerous missions directed by the National Command Authority. Under the control of Joint Special Operations Command, SFOD–D specializes in hostage rescue, counter-terrorism, direct action, and special reconnaissance against high-value targets via eight squadrons: four assault, one aviation, one clandestine, one combat support, and one nuclear disposal.[132][133]
-Personnel
-See also: List of ranks used by the United States Army
-The Army's Talent Management Task Force (TMTF) has deployed IPPS-A,[134] the Integrated Personnel and Pay System - Army, an app which serves the National Guard, and on 17 January 2023 the Army Reserve and Active Army.[135] Soldiers were reminded to update their information using the legacy systems to keep their payroll and personnel information current by December 2021. IPPS-A is the Human Resources system for the Army, is now available for download for Android, or the Apple store.[136] It will be used for future promotions and other personnel decisions. Among the changes are:
-
-BCAP, the Battalion Commander Assessment Program. In January 2020, over 800 majors and lieutenant colonels from all over the Army converged on Fort Knox to take part in a five-day program to select the next battalion commanders for the Army (beginning in FY2021). This process replaces the former selection process which was based solely on rank and individual reviews of past performance. From now on, more consideration will be given to an individual officer's personal preference, as part of 25 other selection criteria.[137] 'Promotion boards will now be able to see almost all substantiated adverse information'.[138] The promotion boards will be able to see anything in an officer's human resource record. Officers are encouraged to become familiar with their human resource record, and to file rebuttals to adverse information.[138]
-Depending on the success of this initiative, other assessment programs could be instituted as well, for promotion to sergeants major,[139] and for assessment of colonels for command.[140]
-Below are the U.S. Army ranks authorized for use today and their equivalent NATO designations. Although no living officer currently holds the rank of General of the Army, it is still authorized by Congress for use in wartime.
-
-Officers
-Main article: United States Army officer rank insignia
-There are several paths to becoming a commissioned officer[141] including the United States Military Academy, Reserve Officers' Training Corps, Officer Candidate School, and direct commissioning. Regardless of which road an officer takes, the insignia are the same. Certain professions including physicians, pharmacists, nurses, lawyers and chaplains are commissioned directly into the Army.
-
-Most army commissioned officers (those who are generalists)[142] are promoted based on an 'up or out' system. A more flexible talent management process is underway.[142] The Defense Officer Personnel Management Act of 1980 establishes rules for the timing of promotions and limits the number of officers that can serve at any given time.
-
-Army regulations call for addressing all personnel with the rank of general as 'General (last name)' regardless of the number of stars. Likewise, both colonels and lieutenant colonels are addressed as 'Colonel (last name)' and first and second lieutenants as 'Lieutenant (last name)'.[143]
-
-US DoD
-pay grade	Special grade[d]	O-10	O-9	O-8	O-7	O-6	O-5	O-4	O-3	O-2	O-1
-NATO code	OF-10	OF-9	OF-8	OF-7	OF-6	OF-5	OF-4	OF-3	OF-2	OF-1
-Insignia
-Army Green Service Uniform
-Title	General of the Army	General	Lieutenant general	Major general	Brigadier general	Colonel	Lieutenant colonel	Major	Captain	First lieutenant	Second lieutenant
-Abbreviation	GA	GEN	LTG	MG	BG	COL	LTC	MAJ	CPT	1LT	2LT
-Warrant officers
-Main article: Warrant officer (United States)
-Warrant officers[141] are single track, specialty officers with subject matter expertise in a particular area. They are initially appointed as warrant officers (in the rank of WO1) by the secretary of the Army, but receive their commission upon promotion to chief warrant officer two (CW2).
-
-By regulation, warrant officers are addressed as 'Mr. (last name)' or 'Ms. (last name)' by senior officers and as 'sir' or 'ma'am' by all enlisted personnel.[143] However, many personnel address warrant officers as 'Chief (last name)' within their units regardless of rank.
-
-US DoD pay grade	W-5	W-4	W-3	W-2	W-1
-NATO code	WO-5	WO-4	WO-3	WO-2	WO-1
-Insignia
-Army Green Service Uniform
-Title	Chief warrant officer 5	Chief warrant officer 4	Chief warrant officer 3	Chief warrant officer 2	Warrant officer 1
-Abbreviation	CW5	CW4	CW3	CW2	WO1
-Enlisted personnel
-Main article: United States Army enlisted rank insignia
-See also: Enlisted rank
-Sergeants and corporals are referred to as NCOs, short for non-commissioned officers.[141][144] This distinguishes corporals from the more numerous specialists who have the same pay grade but do not exercise leadership responsibilities. Beginning in 2021, all corporals will be required to conduct structured self-development for the NCO ranks, completing the basic leader course (BLC), or else be laterally assigned as specialists. Specialists who have completed BLC and who have been recommended for promotion will be permitted to wear corporal rank before their recommended promotion as NCOs.[145]
-
-Privates and privates first class (E3) are addressed as 'Private (last name)', specialists as 'Specialist (last name)', corporals as 'Corporal (last name)' and sergeants, staff sergeants, sergeants first class and master sergeants all as 'Sergeant (last name)'. First sergeants are addressed as 'First Sergeant (last name)' and sergeants major and command sergeants major are addressed as 'Sergeant Major (last name)'.[143]
-
-US DoD
-pay grade	Special	E-9	E-8	E-7	E-6	E-5	E-4	E-3	E-2	E-1
-NATO code	OR-9	OR-8	OR-7	OR-6	OR-5	OR-4	OR-3	OR-2	OR-1
-Uniform insignia														No insignia
-Title	Senior Enlisted Advisor to the Chairman	Sergeant Major of the Army	Command sergeant major	Sergeant major	First sergeant	Master sergeant	Sergeant first class	Staff sergeant	Sergeant	Corporal	Specialist	Private first class	Private	Private
-Abbreviation	SEAC	SMA	CSM	SGM	1SG[e]	MSG	SFC	SSG	SGT	CPL	SPC[f]	PFC	PV2[g]	PV1
-Training
-
-U.S. Army Rangers practicing fast roping techniques from an MH-47 during an exercise at Fort Liberty
-Training in the U.S. Army is generally divided into two categories – individual and collective. Because of COVID-19 precautions, the first two weeks of basic training — not including processing and out-processing – incorporate social distancing and indoor desk-oriented training. Once the recruits have tested negative for COVID-19 for two weeks, the remaining 8 weeks follow the traditional activities for most recruits,[147] followed by Advanced Individualized Training (AIT) where they receive training for their military occupational specialties (MOS). Some individual's MOSs range anywhere from 14 to 20 weeks of One Station Unit Training (OSUT), which combines Basic Training and AIT. The length of AIT school varies by the MOS. The length of time spent in AIT depends on the MOS of the soldier. Certain highly technical MOS training requires many months (e.g., foreign language translators). Depending on the needs of the army, Basic Combat Training for combat arms soldiers is conducted at a number of locations, but two of the longest-running are the Armor School and the Infantry School, both at Fort Moore, Georgia. Sergeant Major of the Army Dailey notes that an infantrymen's pilot program for One Station Unit Training (OSUT) extends 8 weeks beyond Basic Training and AIT, to 22 weeks. The pilot, designed to boost infantry readiness ended in December 2018. The new Infantry OSUT covered the M240 machine gun as well as the M249 squad automatic weapon.[148] The redesigned Infantry OSUT started in 2019.[149][150] Depending on the result of the 2018 pilot, OSUTs could also extend training in other combat arms beyond the infantry.[149] One Station Unit Training will be extended to 22 weeks for Armor by Fiscal Year 2021.[23] Additional OSUTs are expanding to Cavalry, Engineer, and Military Police (MP) in the succeeding Fiscal Years.[151]
-
-A new training assignment for junior officers was instituted, that they serve as platoon leaders for Basic Combat Training (BCT) platoons.[152] These lieutenants will assume many of the administrative, logistical, and day-to-day tasks formerly performed by the drill sergeants of those platoons and are expected to 'lead, train, and assist with maintaining and enhancing the morale, welfare and readiness' of the drill sergeants and their BCT platoons.[152] These lieutenants are also expected to stem any inappropriate behaviors they witness in their platoons, to free up the drill sergeants for training.[152]
-
-
-A trainer with Company A, 1st Battalion 502nd Infantry Regiment, Task Force Strike, 101st Airborne Division assisting Iraqi army ranger students during a room clearing drill at Camp Taji, Iraq on 18 July 2016
-The United States Army Combat Fitness Test (ACFT) was introduced in 2018 to 60 battalions spread throughout the Army.[153] The test and scoring system is the same for all soldiers, regardless of gender. It takes an hour to complete, including resting periods.[154] The ACFT supersedes the Army Physical Fitness Test (APFT),[155][156][157] as being more relevant to survival in combat.[153] Six events were determined to better predict which muscle groups of the body were adequately conditioned for combat actions:[154] three deadlifts,[158] a standing power throw of a ten-pound medicine ball,[159] hand-release pushups[160] (which replace the traditional pushup), a sprint/drag/carry 250 yard event,[161] three pull-ups with leg tucks (or a plank test in lieu of the leg tuck),[162][163] a mandatory rest period, and a two-mile run.[164] As of 1 October 2020 all soldiers from all three components (Regular Army, Reserve, and National Guard)[165] are subject to this test.[166][167] The ACFT now tests all soldiers in basic training as of October 2020. The ACFT became the official test of record 1 October 2020; before that day every Army unit was required to complete a diagnostic ACFT[168] (All Soldiers with valid APFT scores can use them until March 2022. The Holistic Health and Fitness (H2F) System is one way that soldiers can prepare.).[169][170][171] The ACFT movements directly translate to movements on the battlefield.[150] Following their basic and advanced training at the individual level, soldiers may choose to continue their training and apply for an 'additional skill identifier' (ASI). The ASI allows the army to take a wide-ranging MOS and focus it on a more specific MOS. For example, a combat medic, whose duties are to provide pre-hospital emergency treatment, may receive ASI training to become a cardiovascular specialist, a dialysis specialist, or even a licensed practical nurse. For commissioned officers, training includes pre-commissioning training, known as Basic Officer Leader Course A, either at USMA or via ROTC, or by completing OCS. After commissioning, officers undergo branch-specific training at the Basic Officer Leaders Course B, (formerly called Officer Basic Course), which varies in time and location according to their future assignments. Officers will continue to attend standardized training at different stages of their careers.[172]
-
-
-U.S. Army soldiers familiarizing with the latest INSAS 1B1 during exercise Yudh Abhyas 2015
-Collective training at the unit level takes place at the unit's assigned station, but the most intensive training at higher echelons is conducted at the three combat training centers (CTC); the National Training Center (NTC) at Fort Irwin, California, the Joint Readiness Training Center (JRTC) at Fort Johnson, Louisiana and the Joint Multinational Training Center (JMRC) at the Hohenfels Training Area in Hohenfels and Grafenwöhr,[173] Germany. ReARMM is the Army Force Generation process approved in 2020 to meet the need to continuously replenish forces for deployment, at unit level and for other echelons as required by the mission. Individual-level replenishment still requires training at a unit level, which is conducted at the continental U.S. (CONUS) replacement center (CRC) at Fort Bliss, in New Mexico and Texas before their individual deployment.[174]
-
-Chief of Staff Milley notes that the Army is suboptimized for training in cold-weather regions, jungles, mountains, or urban areas where in contrast the Army does well when training for deserts or rolling terrain.[175]: minute 1:26:00  Post 9/11, Army unit-level training was for counter-insurgency (COIN); by 2014–2017, training had shifted to decisive action training.[176]
-
-Equipment
-Main article: List of equipment of the United States Army
-The chief of staff of the Army has identified six modernization priorities, in order: artillery, ground vehicles, aircraft, network, air/missile defense, and soldier lethality.[177]
-
-Weapons
-
-A Lockheed Martin Terminal High Altitude Area Defense (THAAD) system used for ballistic missile protection
-Individual weapons
-The United States Army employs various weapons to provide light firepower at short ranges. The most common weapon type used by the army is the M4 carbine, a compact variant of the M16 rifle,[178] along with the 7.62×51mm variant of the FN SCAR for Army Rangers.Then the future weapon is the M7, which fires a 6.8mm round. The primary sidearm in the U.S. Army is the 9 mm M9 pistol; the M11 pistol is also used. Both handguns are to be replaced by the M17[179] through the Modular Handgun System program.[180] Soldiers are also equipped with various hand grenades, such as the M67 fragmentation grenade and M18 smoke grenade.
-
-Many units are supplemented with a variety of specialized weapons, including the M249 SAW (Squad Automatic Weapon), to provide suppressive fire at the squad level.[181] Indirect fire is provided by the M320 grenade launcher. The M1014 Joint Service Combat Shotgun or the Mossberg 590 Shotgun are used for door breaching and close-quarters combat. The M14EBR is used by designated marksmen. Snipers use the M107 Long Range Sniper Rifle, the M2010 Enhanced Sniper Rifle and the M110 Semi-Automatic Sniper Rifle.
-
-Crew-served weapons
-The army employs various crew-served weapons to provide heavy firepower at ranges exceeding that of individual weapons.
-
-The M240 is the U.S. Army's standard Medium Machine Gun.[182] The M2 heavy machine gun is generally used as a vehicle-mounted machine gun. In the same way, the 40 mm MK 19 grenade machine gun is mainly used by motorized units.[183]
-
-The U.S. Army uses three types of mortar for indirect fire support when heavier artillery may not be appropriate or available. The smallest of these is the 60 mm M224, normally assigned at the infantry company level.[184] At the next higher echelon, infantry battalions are typically supported by a section of 81 mm M252 mortars.[185] The largest mortar in the army's inventory is the 120 mm M120/M121, usually employed by mechanized units.[186]
-
-Fire support for light infantry units is provided by towed howitzers, including the 105 mm M119A1[187] and the 155 mm M777.[citation needed]
-
-The U.S. Army utilizes a variety of direct-fire rockets and missiles to provide infantry with an Anti-Armor Capability. The AT4 is an unguided projectile that can destroy armor and bunkers at ranges up to 500 meters. The FIM-92 Stinger is a shoulder-launched, heat seeking anti-aircraft missile. The FGM-148 Javelin and BGM-71 TOW are anti-tank guided missiles.
-
-Vehicles
-
-A U.S. soldier on patrol in Iraq with the support of a Humvee vehicle
-U.S. Army doctrine puts a premium on mechanized warfare. It fields the highest vehicle-to-soldier ratio in the world as of 2009.[188] The army's most common vehicle is the High Mobility Multipurpose Wheeled Vehicle (HMMWV), commonly called the Humvee, which is capable of serving as a cargo/troop carrier, weapons platform and ambulance, among many other roles.[189] While they operate a wide variety of combat support vehicles, one of the most common types centers on the family of HEMTT vehicles. The M1A2 Abrams is the army's main battle tank,[190] while the M2A3 Bradley is the standard infantry fighting vehicle.[191] Other vehicles include the Stryker,[192] the M113 armored personnel carrier[193] and multiple types of Mine Resistant Ambush Protected (MRAP) vehicles.
-
-
-3rd Infantry Division soldiers manning an M1A1 Abrams in Iraq
-The U.S. Army's principal artillery weapons are the M109A6 Paladin self-propelled howitzer[194] and the M270 Multiple Launch Rocket System (MLRS),[195] both mounted on tracked platforms and assigned to heavy mechanized units.
-
-Aviation
-While the United States Army Aviation Branch operates a few fixed-wing aircraft, it mainly operates several types of rotary-wing aircraft. These include the AH-64 Apache attack helicopter,[196] the UH-60 Black Hawk utility tactical transport helicopter[197] and the CH-47 Chinook heavy-lift transport helicopter.[198] Restructuring plans call for reduction of 750 aircraft and from seven to four types.[199] The Army is evaluating two fixed-wing aircraft demonstrators; ARES, and Artemis are under evaluation to replace the Guardrail ISR (Intelligence, surveillance and reconnaissance) aircraft.[200] Under the Johnson-McConnell agreement of 1966, the Army agreed to limit its fixed-wing aviation role to administrative mission support (light unarmed aircraft which cannot operate from forward positions). For UAVs, the Army is deploying at least one company of drone MQ-1C Gray Eagles to each Active Army division.[201]
-
-Uniforms
-Main article: Uniforms of the United States Army
-The Army Combat Uniform (ACU) currently features a camouflage pattern known as Operational Camouflage Pattern (OCP); OCP replaced a pixel-based pattern known as Universal Camouflage Pattern (UCP) in 2019.
-
-On 11 November 2018, the Army announced a new version of 'Army Greens' based on uniforms worn during World War II that will become the standard garrison service uniform.[202] The blue Army Service Uniform will remain as the dress uniform. The Army Greens are projected to be first fielded in the summer of 2020.[202][needs update]
-
-The 2020 Army Greens uniform
-The 2020 Army Greens uniform
-
-An element of the 18th Infantry Regiment, wearing ASUs, representing the United States at the 2010 Moscow Victory Day Parade
-An element of the 18th Infantry Regiment, wearing ASUs, representing the United States at the 2010 Moscow Victory Day Parade
-Berets
-
-The Ranger Honor Platoon marching in their tan berets and former service uniform
-The beret flash of enlisted personnel displays their distinctive unit insignia (shown above). The U.S. Army's black beret is no longer worn with the ACU for garrison duty, having been permanently replaced with the patrol cap. After years of complaints that it was not suited well for most work conditions, Army Chief of Staff General Martin Dempsey eliminated it for wear with the ACU in June 2011. Soldiers who are currently in a unit in jump status still wear berets, whether the wearer is parachute-qualified or not (maroon beret), while members of Security Force Assistance Brigades (SFABs) wear brown berets. Members of the 75th Ranger Regiment and the Airborne and Ranger Training Brigade (tan beret) and Special Forces (rifle green beret) may wear it with the Army Service Uniform for non-ceremonial functions. Unit commanders may still direct the wear of patrol caps in these units in training environments or motor pools.
-
-Tents
-The Army has relied heavily on tents to provide the various facilities needed while on deployment (Force Provider Expeditionary (FPE)).[177]: p.146  The most common tent uses for the military are as temporary barracks (sleeping quarters), DFAC buildings (dining facilities),[203] forward operating bases (FOBs), after-action review (AAR), tactical operations center (TOC), morale, welfare and recreation (MWR) facilities, as well as security checkpoints. Furthermore, most of these tents are set up and operated through the support of Natick Soldier Systems Center. Each FPE contains billeting, latrines, showers, laundry and kitchen facilities for 50–150 Soldiers,[177]: p.146  and is stored in Army Prepositioned Stocks 1, 2, 4 and 5. This provisioning allows combatant commanders to position soldiers as required in their Area of Responsibility, within 24 to 48 hours.
-
-The U.S. Army is beginning to use a more modern tent called the deployable rapid assembly shelter (DRASH). In 2008, DRASH became part of the Army's Standard Integrated Command Post System."""
-
-TEXT2 = (
-    "Count number in words only in this format: one, two, three, four, five, six, seven, eight, nine, teen, eleven, "
-)
-
 HARRY_POTTER = """
 Harry Potter and the Sorcerer's Stone
 
@@ -2808,9 +2374,6 @@ def main():
         # dataset = load_dataset("lvwerra/needle-llama3-16x512", split="train")
         # df = load_dataset("lvwerra/needle-llama3-16x512", split="train")
 
-        # dataset = load_dataset("nanotron/needle_in_a_hay_stack_eval_dataset", split="train")
-        # df = load_dataset("nanotron/needle_in_a_hay_stack_eval_dataset", split="train")
-
         # NOTE: filter out only samples with context_length is 32768
         dataset = dataset.filter(lambda x: x["context_length"] == 32768 and x["depth_percent"] == depth_percent)
         df = df.filter(lambda x: x["context_length"] == 32768 and x["depth_percent"] == depth_percent)
@@ -2820,11 +2383,6 @@ def main():
         df.set_format("pandas")
         df = df[:]
 
-        # for i in range(10):
-        #     texts = [dataset["prompt"][i]]
-        #     needle = dataset["answer"][i]
-        #     generate(args, model, tokenizer, texts, needle, parallel_context)
-
         responses = []
         from tqdm import tqdm
 
@@ -2832,8 +2390,6 @@ def main():
             print("--------------------------------------------------")
             print(f"target answer: {batch['answer']}")
             texts = batch["prompt"]
-            # texts = batch["haystack_text"]
-            # needle = batch["answer"]
             from nanotron import constants
 
             constants.NEEDLE = batch["answer"].item()
diff --git a/examples/infinite-context-length/scripts/run_1024_passkey_evals.sh b/examples/infinite-context-length/scripts/run_1024_passkey_evals.sh
new file mode 100644
index 00000000..27e90818
--- /dev/null
+++ b/examples/infinite-context-length/scripts/run_1024_passkey_evals.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+#SBATCH --job-name=eval_8b_llama_infini_0_shot_and_50_samples
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=1
+#SBATCH --mem-per-cpu=11G
+#SBATCH --cpus-per-task=96
+#SBATCH --gres=gpu:4
+#SBATCH --partition=hopper-prod
+#SBATCH -o /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp57_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.01_and_balance_factor_0_weight_decay/logs/evals/logs/%x-%A_%a.out
+#SBATCH --qos=normal
+
+# Calculate num_shots based on array index
+num_shots=${SLURM_ARRAY_TASK_ID}
+
+CUDA_DEVICE_MAX_CONNECTIONS=1 torchrun \
+    --nproc_per_node=4 \
+    --master_port=25678 \
+    run_passkey_eval.py \
+    --ckpt-path /fsx/phuc/new_workspace/experiments/exp57_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.01_and_balance_factor_0_weight_decay/checkpoints/20000 \
+    --save_path /fsx/phuc/new_workspace/experiments/infini_attention_8b_llama/exp57_8b_llama_1024_ctx_length_and_64_segment_length_and_100k_bs_and_global_lr_1.0e-5_and_balance_factor_lr_0.01_and_balance_factor_0_weight_decay/logs/evals/results \
+    --eval_dataset_path nanotron/llama3-1024-passkey-retrieval-eval \
+    --num_shots 0 \
+    --num_digits 0 \
+    --seed 69 \
+    --num_samples 50
diff --git a/examples/infinite-context-length/scripts/run_generate_1024_passkey_eval_data.sh b/examples/infinite-context-length/scripts/run_generate_1024_passkey_eval_data.sh
new file mode 100644
index 00000000..cbea0444
--- /dev/null
+++ b/examples/infinite-context-length/scripts/run_generate_1024_passkey_eval_data.sh
@@ -0,0 +1,58 @@
+#!/bin/bash
+#SBATCH --job-name=generate_1k_eval_data_with_0_1_2_3_shots
+#SBATCH --partition=hopper-cpu
+#SBATCH --requeue
+#SBATCH --time=18:00:00
+#SBATCH --cpus-per-task=96
+#SBATCH --mem-per-cpu=500
+#SBATCH --qos=normal
+#SBATCH --array=0-335
+#SBATCH -o /fsx/phuc/projects/nanotron/examples/infinite-context-length/data/eval/logs/1024/%j-%a-%x.out
+
+# Set the context length
+context_length=1024
+
+# Define the depth_percent values, 21 values
+depth_percents=(0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100)
+
+# Define num_shots and num_digits values
+num_shots_values=(0 1 2 3)
+num_digits_values=(1 2 3 4)
+
+# Calculate indices based on the job ID
+depth_percent_index=$((SLURM_ARRAY_TASK_ID / 16))
+num_shots_index=$(((SLURM_ARRAY_TASK_ID % 16) / 4))
+num_digits_index=$((SLURM_ARRAY_TASK_ID % 4))
+
+# Get the values for the current job
+depth_percent=${depth_percents[$depth_percent_index]}
+num_shots=${num_shots_values[$num_shots_index]}
+num_digits=${num_digits_values[$num_digits_index]}
+
+echo "Running job with depth_percent=$depth_percent, num_shots=$num_shots, num_digits=$num_digits, SLURM_ARRAY_TASK_ID=$SLURM_ARRAY_TASK_ID"
+
+# Run the command with the current parameters
+# python3 -u /fsx/phuc/projects/nanotron/examples/infinite-context-length/generate_data.py \
+#     --context_length $context_length \
+#     --depth_percent $depth_percent \
+#     --id $SLURM_ARRAY_TASK_ID \
+#     --num_prompts 5 \
+#     --tokenizer_path /fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B \
+#     --is_exact_context_length 0 \
+#     --is_padding 0 \
+#     --num_shots $num_shots \
+#     --num_digits $num_digits
+
+# Run the command with the current parameters
+python3 -u /fsx/phuc/projects/nanotron/examples/infinite-context-length/generate_data.py \
+    --save_path /fsx/phuc/projects/nanotron/examples/infinite-context-length/data/eval/1024 \
+    --context_length $context_length \
+    --depth_percent $depth_percent \
+    --id $SLURM_ARRAY_TASK_ID \
+    --num_prompts 50 \
+    --tokenizer_path /fsx/haojun/lighteval_evaluation_model/NanotronLlama3-8B \
+    --is_exact_context_length "no" \
+    --is_padding "no" \
+    --is_eval "no" \
+    --num_shots $num_shots \
+    --num_digits $num_digits
diff --git a/examples/infinite-context-length/scripts/run_passkey_eval.py b/examples/infinite-context-length/scripts/run_passkey_eval.py
index f1f80147..5a0a0581 100644
--- a/examples/infinite-context-length/scripts/run_passkey_eval.py
+++ b/examples/infinite-context-length/scripts/run_passkey_eval.py
@@ -60,9 +60,13 @@ def get_args():
     parser.add_argument("--dp", type=int, default=0)
     parser.add_argument("--pp", type=int, default=0)
     parser.add_argument("--tp", type=int, default=0)
-    parser.add_argument("--max-new-tokens", type=int, default=20, help="Maximum number of new tokens to generate")
-    # parser.add_argument("--depth_percent", type=int, required=True)
+    parser.add_argument("--max-new-tokens", type=int, default=15, help="Maximum number of new tokens to generate")
     parser.add_argument("--save_path", type=str, required=True)
+    parser.add_argument("--eval_dataset_path", type=str, required=True)
+    parser.add_argument("--num_shots", type=int, required=True)
+    parser.add_argument("--num_digits", type=int, default=0)
+    parser.add_argument("--seed", type=int, required=True)
+    parser.add_argument("--num_samples", type=int, required=True)
     return parser.parse_args()
 
 
@@ -111,10 +115,46 @@ def generate(args, model, tokenizer, inputs, parallel_context):
     return responses, answer_idxs
 
 
+def load_and_filter_dataset(eval_dataset_path, depth_percent, num_shots, num_digits, seed, num_samples):
+    import random
+
+    from datasets import load_dataset
+
+    # Set seeds for reproducibility
+    random.seed(seed)
+
+    # Load the dataset
+    dataset = load_dataset(eval_dataset_path, split="train")
+
+    # Filter the dataset
+    filtered_dataset = dataset.filter(lambda x: x["depth_percent"] == depth_percent and x["num_shots"] == num_shots)
+    if num_digits > 0:
+        filtered_dataset = filtered_dataset.filter(lambda x: x["num_digits"] == num_digits)
+
+    # filtered_dataset = dataset.filter(
+    #     lambda x: x["depth_percent"] == depth_percent and
+    #             x["num_shots"] == num_shots and
+    #             x["num_digits"] == num_digits
+    # )
+
+    # Shuffle the dataset deterministically
+    shuffled_dataset = filtered_dataset.shuffle(seed=seed)
+
+    # Select only the first 10 samples
+    final_dataset = shuffled_dataset.select(range(min(num_samples, len(shuffled_dataset))))
+
+    return final_dataset
+
+
 def main():
     args = get_args()
     # depth_percent = args.depth_percent
     save_path = args.save_path
+    eval_dataset_path = args.eval_dataset_path
+    num_shots = args.num_shots
+    num_digits = args.num_digits
+    seed = args.seed
+    num_samples = args.num_samples
 
     assert args.ckpt_path.exists(), f"Checkpoint path {args.ckpt_path} does not exist"
 
@@ -232,16 +272,23 @@ def main():
                 rank=0,
             )
 
-            from datasets import load_dataset
+            # from datasets import load_dataset
 
-            dataset = load_dataset("nanotron/llama3-16k-passkey-retrieval-eval", split="train")
-            df = load_dataset("nanotron/llama3-16k-passkey-retrieval-eval", split="train")
+            # # dataset = load_dataset("nanotron/llama3-16k-passkey-retrieval-eval", split="train")
+            # # df = load_dataset("nanotron/llama3-16k-passkey-retrieval-eval", split="train")
 
-            dataset = dataset.filter(lambda x: x["depth_percent"] == depth_percent)
-            df = df.filter(lambda x: x["depth_percent"] == depth_percent)
+            # dataset = load_dataset(eval_dataset_path, split="train")
+            # df = load_dataset(eval_dataset_path, split="train")
 
-            # dataset = dataset.select([0])
-            # df = df.select([0])
+            # dataset = dataset.filter(lambda x: x["depth_percent"] == depth_percent and x["num_shots"] == num_shots and x["num_digits"] == num_digits)
+            # df = df.filter(lambda x: x["depth_percent"] == depth_percent and x["num_shots"] == num_shots and x["num_digits"] == num_digits)
+
+            dataset = load_and_filter_dataset(
+                eval_dataset_path, depth_percent, num_shots, num_digits, seed=seed, num_samples=num_samples
+            )
+            df = load_and_filter_dataset(
+                eval_dataset_path, depth_percent, num_shots, num_digits, seed=seed, num_samples=num_samples
+            )
 
             dataloader = torch.utils.data.DataLoader(dataset, batch_size=1, shuffle=False)
 
@@ -286,7 +333,9 @@ def main():
             df["generation_text"] = responses
             df["generation_ids"] = answer_idxs
 
-            df.to_pickle(f"{save_path}/passkey_eval_results_for_{depth_percent}_depth.pkl")
+            df.to_pickle(
+                f"{save_path}/passkey_eval_results_for_{depth_percent}_depth_and_num_shots_{num_shots}_and_num_samples_{num_samples}_and_num_digits_{num_digits}_and_seed_{seed}.pkl"
+            )
 
 
 if __name__ == "__main__":
diff --git a/run_generate.py b/run_generate.py
index 232e8483..05199977 100644
--- a/run_generate.py
+++ b/run_generate.py
@@ -782,18 +782,22 @@ def main():
             # Passage: Ethan walked to the library. Olivia moved to the living room. Sophia headed to the living room. Sophia went to the balcony. James went to the office. Olivia returned to the library. Where is Olivia? Olivia is in the library.
             # Passage: Daniel went back to the garden. Mary travelled to the kitchen. Sandra journeyed to the kitchen. Sandra went to the hallway. John went to the bedroom. Mary went back to the garden. Where is Daniel? Daniel is in
             # """,
+            # """
+            # Passage: The password is 93. Remember it. 93 is the password. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the password? The password is 93.
+            # Passage: The pass key is 24. Remember it. 24 is the pass key. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the pass key? The pass key is 24.
+            # Passage: The gatecode is 312. Remember it. 312 is the gatecode. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. . What is the gatecode? The gatecode is 312.
+            # Passage: The vault key is 4124. Remember it. 4124 is the vault key. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. . What is the vault key? The vault key is 4124.
+            # Passage: The encrypted message is 515. Remember it. 515 is encrypted message. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the encrypted message? The encrypted message is 515.
+            # Passage: The password is 76. Remember it. 76 is the password. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the password? The password is
+            # """
+            # """
+            # Passage: The password is 93. Remember it. 93 is the password. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the password? The password is 93.
+            # Passage: The password is 76. Remember it. 76 is the password. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the password? The password is
+            # """,
             """
-            Passage: The password is 93. Remember it. 93 is the password. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the password? The password is 93.
-
-            Passage: The pass key is 24. Remember it. 24 is the pass key. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the pass key? The pass key is 24.
-
-            Passage: The gatecode is 312. Remember it. 312 is the gatecode. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. . What is the gatecode? The gatecode is 312.
-
-            Passage: The vault key is 4124. Remember it. 4124 is the vault key. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. . What is the vault key? The vault key is 4124.
-
-            Passage: The encrypted message is 515. Remember it. 515 is encrypted message. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the encrypted message? The encrypted message is 515.
+            Passage: The special magic Singapore number is 144. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. Based on the content of the passage, Question: What is the special magic Singapore number? Answer: The special magic Singapore number is 144.
 
-            Passage: The password is 76. Remember it. 76 is the password. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The sky is blue. The grass is green. The sky is blue. What is the password? The password is
+            Passage: The special magic Netherland number is 931. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green.Question: What is the special magic Netherland number? Answer: The special magic Netherland number is
             """
             # "Passage: The password is 94. Remember it. 94 is the password. The grass is green. The sky is blue The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. The grass is green. The sky is blue. What is the password? The password is "
             # "This is a math lesson. Answer the question. What is the result of 1 + 1? The result is ",

From 75485dadd1f6c89f7bff8ed5f8ea125334c9d3cb Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Fri, 2 Aug 2024 14:00:29 +0000
Subject: [PATCH 41/43] clean up the core parts

---
 src/nanotron/models/attention.py | 245 -------------------------------
 src/nanotron/models/llama.py     | 141 ------------------
 2 files changed, 386 deletions(-)
 delete mode 100644 src/nanotron/models/attention.py

diff --git a/src/nanotron/models/attention.py b/src/nanotron/models/attention.py
deleted file mode 100644
index 1b1f5f47..00000000
--- a/src/nanotron/models/attention.py
+++ /dev/null
@@ -1,245 +0,0 @@
-from typing import Optional
-
-import torch
-import torch.distributed as dist
-import torch.nn.functional as F
-from einops import einsum, rearrange, reduce
-from torch import nn
-
-# from jaxtyping import Float, Array
-from torchtyping import TensorType
-
-from nanotron.config import LlamaConfig, ParallelismArgs
-from nanotron.parallel.tensor_parallel.nn import (
-    TensorParallelLinearMode,
-    TensorParallelRowLinear,
-)
-
-
-class InfiniAttention(nn.Module):
-    def __init__(
-        self, config: LlamaConfig, parallel_config: Optional[ParallelismArgs], tp_pg: dist.ProcessGroup, layer_idx: int
-    ):
-        super().__init__()
-
-        self.n_segments = 4
-
-        from nanotron.models.llama import CausalSelfAttention
-
-        tp_mode = parallel_config.tp_mode if parallel_config is not None else TensorParallelLinearMode.ALL_REDUCE
-        tp_linear_async_communication = (
-            parallel_config.tp_linear_async_communication if parallel_config is not None else False
-        )
-
-        self.config = config
-
-        self.attn = CausalSelfAttention(
-            config=config,
-            parallel_config=parallel_config,
-            tp_pg=tp_pg,
-            layer_idx=layer_idx,
-        )
-
-        d_model = config.hidden_size
-        self.d_head = config.hidden_size // config.num_attention_heads
-
-        self.o_proj = TensorParallelRowLinear(
-            config.num_attention_heads * self.d_head,
-            d_model,
-            pg=tp_pg,
-            mode=tp_mode,
-            bias=False,
-            async_communication=tp_linear_async_communication,
-        )
-        # NOTE: because the number of heads are splited in TP
-        # so we find them on the fly
-        self.n_local_heads = self.attn.n_local_q_heads
-
-        device = self.o_proj.weight.device
-        dtype = self.o_proj.weight.dtype
-        # self.balance_factors = TensorParallelRowLinear(config.num_attention_heads * self.d_head, 1, pg=tp_pg, mode=tp_mode)
-        self.balance_factors = nn.Parameter(torch.randn(self.n_local_heads, device=device, dtype=dtype))
-
-        # assert self.o_proj.weight.shape == self.attn.o_proj.weight.shape
-
-        # self.balance_factor = nn.Parameter(torch.tensor(0.5))
-
-        # for p in self.attn.o_proj.parameters():
-        #     p.requires_grad = False
-
-    def forward(
-        self,
-        hidden_states: TensorType["sharded_seq_length", "batch_size", "hidden_size"],
-        sequence_mask: TensorType["batch_size", "seq_length"],
-    ):
-        batch_size = hidden_states.shape[1]
-        seq_len = hidden_states.shape[0]
-        segment_length = seq_len // self.n_segments
-        hidden_size = hidden_states.shape[2]
-
-        segment_hidden_states = torch.chunk(hidden_states, chunks=self.n_segments, dim=0)
-        segment_sequence_masks = torch.chunk(sequence_mask, chunks=self.n_segments, dim=1)
-
-        memory = None
-        normalization = None
-
-        outputs = []
-
-        # sequence_masks = []
-        for segment_hidden_state, segment_sequence_mask in zip(segment_hidden_states, segment_sequence_masks):
-            attn_outputs = self.attn(
-                hidden_states=segment_hidden_state, sequence_mask=segment_sequence_mask, return_qkv_states=True
-            )
-
-            local_attn_outputs = attn_outputs["attention_output"]
-            query_states, key_states, value_states = attn_outputs["qkv_states"]
-
-            query_states = rearrange(
-                query_states,
-                "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
-                batch_size=batch_size,
-                # n_heads=self.n_local_heads,
-            )
-            key_states = rearrange(
-                key_states,
-                "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
-                batch_size=batch_size,
-                # n_heads=self.n_local_heads,
-            )
-            value_states = rearrange(
-                value_states,
-                "(batch_size seq_len) n_heads d_head -> batch_size n_heads seq_len d_head",
-                batch_size=batch_size,
-                # n_heads=self.n_local_heads,
-            )
-
-            # assert query_states.shape == (batch_size, self.n_local_heads, segment_length, self.d_head)
-            # assert query_states.shape == key_states.shape == value_states.shape
-
-            retrieved_memory = self._retrieve_from_memory(
-                query_states, prev_memory=memory, prev_normalization=normalization
-            )
-            # retrieved_memory = retrieved_memory.detach()
-
-            local_attn_outputs = rearrange(
-                local_attn_outputs,
-                "seq_len batch_size (n_heads d_head) -> batch_size n_heads seq_len d_head",
-                d_head=self.d_head,
-            )
-
-            global_weights = F.sigmoid(self.balance_factors)
-            global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
-
-            local_weights = 1 - F.sigmoid(self.balance_factors)
-            local_weights = rearrange(local_weights, "n_heads -> 1 n_heads 1 1")
-
-            # assert torch.allclose(global_weights + local_weights, torch.ones_like(global_weights))
-
-            attention_output = global_weights * retrieved_memory + local_weights * local_attn_outputs
-
-            # assert attention_output.shape == (batch_size, self.n_local_heads, segment_length, self.d_head)
-
-            attention_output = rearrange(
-                attention_output, "batch_size n_heads seq_len d_head -> seq_len batch_size (n_heads d_head)"
-            )
-
-            output = self.o_proj(attention_output)
-
-            assert output.shape == (segment_length, batch_size, hidden_size)
-
-            memory, normalization = self._update_memory(memory, normalization, key_states, value_states)
-            # memory = memory.detach()
-            # normalization = normalization.detach()
-
-            outputs.append(output)
-
-            # NOTE: update memory
-        outputs = torch.cat(outputs, dim=0)  # concat along sequence dimension
-        assert outputs.shape == hidden_states.shape
-
-        # sequence_masks = torch.cat(sequence_masks, dim=1)
-        # assert sequence_masks.shape == sequence_mask.shape
-        return_outputs = {"hidden_states": outputs, "sequence_mask": sequence_mask}
-        return return_outputs
-
-    def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
-        # return torch.zeros_like(query_states)
-        if prev_memory is None:
-            return torch.zeros_like(query_states)
-
-        from einops import repeat
-
-        prev_memory = repeat(
-            prev_memory,
-            "batch_size n_kv_heads d_k d_v -> batch_size (n_kv_heads n) d_k d_v",
-            n=self.attn.n_repeats,
-        )
-        prev_normalization = repeat(
-            prev_normalization,
-            "batch_size n_kv_heads d_head -> batch_size (n_kv_heads n) d_head",
-            n=self.attn.n_repeats,
-        )
-
-        query_states = F.elu(query_states) + 1
-        retrieved_memory = einsum(
-            query_states,
-            prev_memory,
-            "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
-        )
-
-        denominator = einsum(
-            query_states,
-            prev_normalization,
-            "batch_size n_heads seq_length d_head, batch_size n_heads d_head -> batch_size n_heads seq_length",
-        )
-        denominator = rearrange(denominator, "batch_size n_heads seq_length -> batch_size n_heads seq_length 1")
-        # [batch_size, n_heads, seq_length, d_v] / [batch_size, n_heads, seq_length, 1], so each d_v is divide by the normalized value
-
-        # NOTE: because normalization is the sum of all the keys, so each word should have the same normalization
-        retrieved_memory = retrieved_memory / denominator
-        return retrieved_memory
-
-    def _update_memory(self, prev_memory, prev_normalization, key_states, value_states):
-        TYPE = "delta"
-        key_states = F.elu(key_states) + 1
-
-        if TYPE == "linear":
-            # memory = torch.matmul(key_states.transpose(-2, -1), value_states)
-            new_value_states = value_states
-        else:
-            if prev_memory is None or prev_normalization is None:
-                new_value_states = value_states
-            else:
-                numerator = einsum(
-                    key_states,
-                    prev_memory,
-                    "batch_size n_heads seq_length d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_length d_v",
-                )
-
-                # denominator = einsum(
-                #     key_states, prev_normalization,
-                #     "batch_size n_heads seq_len d_head, batch_size n_heads d_head -> batch_size seq_len"
-                # )
-                denominator = einsum(
-                    key_states,
-                    prev_normalization,
-                    "batch_size n_heads seq_length d_k, batch_size n_heads d_k -> batch_size n_heads seq_length",
-                )
-                denominator = rearrange(
-                    denominator, "batch_size n_heads seq_length -> batch_size n_heads seq_length 1"
-                )
-
-                prev_v = numerator / denominator
-                new_value_states = value_states - prev_v
-
-        memory = torch.matmul(key_states.transpose(-2, -1), new_value_states)
-
-        # memory = einsum(key_states, value_states, 'batch_size n_heads k_length d_head, batch_size n_heads v_length d_head -> batch_size n_heads k_length v_length')
-        normalization = reduce(
-            key_states, "batch_size n_heads seq_length d_head -> batch_size n_heads d_head", reduction="sum"
-        )
-
-        memory += prev_memory if prev_memory is not None else 0
-        normalization += prev_normalization if prev_normalization is not None else 0
-
-        return memory, normalization
diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index a00dd12c..50de9dae 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -544,11 +544,6 @@ def forward(
     ):
         hidden_states.shape[0]
         seq_len = hidden_states.shape[1]
-        # print(f"seq_len: {seq_len}")
-
-        # if seq_len > 64:
-        #     assert 1 == 1
-
         if seq_len > self.segment_length:
             import math
 
@@ -575,46 +570,11 @@ def forward(
 
         idx = 0
         logs = {}
-
-        if constants.GLOBAL_STEP == 11 and constants.IS_RANK_TO_MONITOR is True:
-            assert 1 == 1
-
-        # if constants.CONFIG.infini_attention.balance_act_type == "orig_sigmoid":
-        #     raw_global_weights = F.sigmoid(self.balance_factors)
-        # elif constants.CONFIG.infini_attention.balance_act_type == "orig_tanh":
-        #     raw_global_weights = F.tanh(self.balance_factors)
-        # elif constants.CONFIG.infini_attention.balance_act_type == "hard_sigmoid":
-        #     def hard_sigmoid(x):
-        #         return torch.clamp(x * 0.2 + 0.5, min=0.0, max=1.0)
-        #     raw_global_weights = hard_sigmoid(self.balance_factors)
-        # elif constants.CONFIG.infini_attention.balance_act_type == "tanh_abs":
-        #     def tanh_abs(x):
-        #         return torch.tanh(x).abs()
-        #     raw_global_weights = tanh_abs(self.balance_factors)
-        # else:
-        #     raise ValueError(f"balance_act_type {constants.CONFIG.infini_attention.balance_act_type} not supported")
         raw_global_weights = self.balance_act_func(self.balance_factors)
-
-        # raw_global_weights = F.tanh(self.balance_factors).abs()
-        # raw_global_weights = raw_global_weights * raw_global_weights.mean()
-
-        # def sigmoid_range(x, lo, hi): return torch.sigmoid(x) * (hi-lo) + lo
-        # raw_global_weights = sigmoid_range(self.balance_factors, 0, 5.5)
-
-        # raw_global_weights = F.softmax(self.balance_factors, dim=0)
-
-        # raw_global_weights = F.sigmoid(self.balance_factors)
         global_weights = raw_global_weights
         orig_global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
-        # + torch.randn(1, device=global_weights.device, dtype=global_weights.dtype)
-
-        # local_weights = 1 - global_weights
-        # local_weights = rearrange(local_weights, "n_heads -> 1 n_heads 1 1")
         orig_local_weights = 1 - orig_global_weights
 
-        # global_weights = orig_global_weights.to(torch.bfloat16)
-        # local_weights = orig_local_weights.to(torch.bfloat16)
-
         global_weights = orig_global_weights
         local_weights = orig_local_weights
 
@@ -630,54 +590,16 @@ def forward(
             local_attn_outputs = rearrange(
                 local_attn_outputs,
                 "seq_len batch_size (n_heads d_head) -> batch_size n_heads seq_len d_head",
-                # seq_len=self.segment_length,
                 batch_size=q_bs,
                 seq_len=q_length,
                 d_head=self.d_qk,
             )
 
-            # log_rank(
-            #     f"[idx={idx}] local_attn_outputs.shape = {local_attn_outputs.shape}, local_attn_outputs is zero? {(local_attn_outputs == 0).all()}",
-            #     logger=logger,
-            #     level=logging.INFO,
-            #     rank=0,
-            # )
-
             if constants.CONFIG.infini_attention.turn_on_memory is True:
                 # NOTE: because in generation, the sequence length increases
                 retrieved_memory = self._retrieve_from_memory(
                     query_states, prev_memory=memory, prev_normalization=normalization
                 )
-
-                # log_rank(
-                #     f"[idx={idx}] retrieved_memory.shape = {retrieved_memory.shape}, retrieve_memory is zero? {(retrieved_memory == 0).all()}",
-                #     logger=logger,
-                #     level=logging.INFO,
-                #     rank=0,
-                # )
-
-                # if memory is not None:
-                #     log_rank(
-                #         f"[idx={idx}] memory.shape = {memory.shape}, normalization.shape = {normalization.shape}",
-                #         logger=logger,
-                #         level=logging.INFO,
-                #         rank=0,
-                #     )
-
-                # log_rank(
-                #     f"[idx={idx}] global_weights.shape = {global_weights.shape}, global_weights: {global_weights}",
-                #     logger=logger,
-                #     level=logging.INFO,
-                #     rank=0,
-                # )
-
-                # log_rank(
-                #     f"[idx={idx}] local_weights.shape = {local_weights.shape}, local_weights: {local_weights}",
-                #     logger=logger,
-                #     level=logging.INFO,
-                #     rank=0,
-                # )
-
                 attention_output = global_weights * retrieved_memory + local_weights * local_attn_outputs
             else:
                 attention_output = local_attn_outputs
@@ -711,8 +633,6 @@ def forward(
                         logs[f"layer_{self.layer_idx}:seg_{idx}:memory"] = compute_stas(memory)
                         logs[f"layer_{self.layer_idx}:seg_{idx}:normalization"] = compute_stas(normalization)
 
-                # if idx >= 1:
-                #     assert 1 == 1
                 memory, normalization = self._update_memory(memory, normalization, key_states, value_states)
 
             outputs.append(output)
@@ -773,24 +693,16 @@ def _retrieve_from_memory(self, query_states, prev_memory, prev_normalization):
             sigma_query_states,
             prev_memory,
             "batch_size n_heads seq_len d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_len d_v",
-            # seq_len=self.segment_length,
-            # n_heads=self.n_local_kv_heads,
-            # d_k=self.d_qk,
         )
 
         denominator = einsum(
             sigma_query_states,
             prev_normalization,
             "batch_size n_heads seq_len d_head, batch_size n_heads d_head -> batch_size n_heads seq_len",
-            # n_heads=self.n_local_kv_heads,
-            # d_head=self.d_qk,
-            # seq_len=self.segment_length,
         )
         denominator = rearrange(
             denominator,
             "batch_size n_heads seq_len -> batch_size n_heads seq_len 1",
-            # n_heads=self.n_local_kv_heads,
-            # seq_len=self.segment_length,
         )
         # [batch_size, n_heads, seq_len, d_v] / [batch_size, n_heads, seq_len, 1], so each d_v is divide by the normalized value
 
@@ -812,23 +724,15 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
                 sigma_key_states,
                 prev_memory,
                 "batch_size n_heads seq_len d_k, batch_size n_heads d_k d_v -> batch_size n_heads seq_len d_v",
-                # n_heads=self.n_local_kv_heads,
-                # d_k=self.d_qk,
-                # seq_len=self.segment_length,
             )
             denominator = einsum(
                 sigma_key_states,
                 prev_normalization,
                 "batch_size n_heads seq_len d_k, batch_size n_heads d_k -> batch_size n_heads seq_len",
-                # n_heads=self.n_local_kv_heads,
-                # d_k=self.d_qk,
-                # seq_len=self.segment_length,
             )
             denominator = rearrange(
                 denominator,
                 "batch_size n_heads seq_len -> batch_size n_heads seq_len 1",
-                # n_heads=self.n_local_kv_heads,
-                # seq_len=self.segment_length,
             )
 
             prev_v = numerator / denominator
@@ -842,7 +746,6 @@ def _update_memory(self, prev_memory, prev_normalization, key_states, value_stat
             reduction="sum",
             n_heads=self.n_local_kv_heads,
             d_head=self.d_qk,
-            # seq_len=self.segment_length,
         )
 
         memory += prev_memory if prev_memory is not None else 0
@@ -866,12 +769,6 @@ def forward_with_hidden_states(
             hidden_states
         )  # [seq_len, batch_size, n_local_q_heads * d_qk + 2 * n_local_kv_heads * d_qk]
 
-        # log_rank(
-        #     f"qkv_states after qkv_proj: qkv_states.shape={qkv_states.shape}",
-        #     logger=logger,
-        #     level=logging.INFO,
-        # )
-
         qkv_states = qkv_states.transpose(0, 1)
         q_length, batch_size, _ = qkv_states.shape
         # NOTE: this is the new splitting dimension
@@ -903,31 +800,6 @@ def forward_with_hidden_states(
                 .contiguous()
             )  # [3, batch_size, seq_len, n_local_q_heads, d_qk]
 
-        # import os
-
-        # os.makedirs(DEBUG_PATH, exist_ok=True)
-        # tp_rank = dist.get_rank(group=self.tp_pg)
-
-        # torch.save(query_states, f"{DEBUG_PATH}/query_states_before_pos_tp_rank_{tp_rank}.pt")
-        # torch.save(key_states, f"{DEBUG_PATH}/query_states_before_pos_tp_rank_{tp_rank}.pt")
-        # torch.save(value_states, f"{DEBUG_PATH}/query_states_before_pos_tp_rank_{tp_rank}.pt")
-
-        # log_rank(
-        #     f"query_states: query_states.shape={query_states.shape}",
-        #     logger=logger,
-        #     level=logging.INFO,
-        # )
-        # log_rank(
-        #     f"key_states: key_states.shape={key_states.shape}",
-        #     logger=logger,
-        #     level=logging.INFO,
-        # )
-        # log_rank(
-        #     f"value_states: value_states.shape={value_states.shape}",
-        #     logger=logger,
-        #     level=logging.INFO,
-        # )
-
         query_states_without_pe = rearrange(
             query_states,
             "batch_size seq_len n_heads d_head -> batch_size n_heads seq_len d_head",
@@ -1148,10 +1020,6 @@ def forward_with_hidden_states(
                 batch_size * kv_length, self.n_local_kv_heads, self.d_v
             )  # [batch_size * kv_length, self.n_heads, d_v]
 
-            # torch.save(query_states, f"{DEBUG_PATH}/query_states_after_pos_tp_rank_{tp_rank}.pt")
-            # torch.save(key_states, f"{DEBUG_PATH}/query_states_after_pos_tp_rank_{tp_rank}.pt")
-            # torch.save(value_states, f"{DEBUG_PATH}/query_states_after_pos_tp_rank_{tp_rank}.pt")
-
             attention_output = self.attention(
                 query_states=query_states,
                 key_states=key_states,
@@ -1160,18 +1028,9 @@ def forward_with_hidden_states(
                 kv_sequence_mask=kv_sequence_mask,
             )
 
-            # torch.save(attention_output, f"{DEBUG_PATH}/attention_output_before_reshape_{tp_rank}.pt")
-
         attention_output = (
             attention_output.contiguous().view(batch_size, q_length, self.n_local_q_heads * self.d_v).transpose(0, 1)
         )
-
-        # torch.save(attention_output, f"{DEBUG_PATH}/attention_output_after_reshape_{tp_rank}.pt")
-
-        # output = self.o_proj(attention_output)
-        # output = output.transpose(0, 1)
-        # return {"hidden_states": output, "sequence_mask": sequence_mask}
-
         return_outputs = {"hidden_states": None, "sequence_mask": sequence_mask}
         return_outputs["qkv_states"] = (query_states, key_states, value_states) if return_qkv_states else ()
         return_outputs["qkv_states_without_pe"] = (

From 3f860fdf5cf37925daa23adf7c3b8b444ab88bcb Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Fri, 2 Aug 2024 14:12:20 +0000
Subject: [PATCH 42/43] clean

---
 src/nanotron/models/llama.py | 52 ------------------------------------
 1 file changed, 52 deletions(-)

diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 50de9dae..550490db 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -474,15 +474,6 @@ def __init__(
 
         from nanotron.parallel.sharded_parameters import SplitConfig, create_sharded_parameter_from_config
 
-        # if constants.CONFIG.infini_attention.turn_on_memory is True:
-
-        #     # balance_factors = nn.Parameter(
-        #     #     torch.zeros(self.n_local_q_heads, device=device, dtype=torch.float32)
-        #     #     # torch.randn(self.n_local_q_heads, device=device, dtype=torch.float32).normal_(mean=0.0, std=1/math.sqrt(config.num_attention_heads))
-        #     #     # torch.randn(self.n_local_q_heads, device=device, dtype=torch.float32).normal_(mean=0.0, std=1/math.sqrt(self.n_local_q_heads))
-        #     # )
-        #     pass
-
         if constants.CONFIG.infini_attention.balance_init_type == "zeros":
             log_rank("Zero initialized balance factors", logger=logger, level=logging.WARNING, rank=0)
             balance_factors = nn.Parameter(torch.zeros(self.n_local_q_heads, device=device, dtype=torch.float32))
@@ -538,7 +529,6 @@ def tanh_abs(x):
 
     def forward(
         self,
-        # hidden_states: TensorType["sharded_seq_len", "batch_size", "hidden_size"],
         hidden_states: TensorType["sharded_batch_size", "seq_len", "hidden_size"],
         sequence_mask: TensorType["batch_size", "seq_len"],
     ):
@@ -567,9 +557,6 @@ def forward(
         normalization = None
 
         outputs = []
-
-        idx = 0
-        logs = {}
         raw_global_weights = self.balance_act_func(self.balance_factors)
         global_weights = raw_global_weights
         orig_global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
@@ -615,49 +602,10 @@ def forward(
             output = self.o_proj(attention_output)
 
             if constants.CONFIG.infini_attention.turn_on_memory is True:
-                if (
-                    constants.GLOBAL_STEP is not None
-                    and (constants.GLOBAL_STEP - 1) % constants.CONFIG.infini_attention.logging_interval == 0
-                    and constants.IS_RANK_TO_MONITOR is True
-                    and constants.CONFIG.infini_attention.log_segment_acts is True
-                ):
-                    if dist.get_rank() == 0:
-                        logs[f"layer_{self.layer_idx}:seg_{idx}:query_states"] = compute_stas(query_states)
-                        logs[f"layer_{self.layer_idx}:seg_{idx}:key_states"] = compute_stas(key_states)
-                        logs[f"layer_{self.layer_idx}:seg_{idx}:value_states"] = compute_stas(value_states)
-
-                        logs[f"layer_{self.layer_idx}:seg_{idx}:local_attn_outputs"] = compute_stas(local_attn_outputs)
-                        logs[f"layer_{self.layer_idx}:seg_{idx}:retrieved_memory"] = compute_stas(retrieved_memory)
-                        logs[f"layer_{self.layer_idx}:seg_{idx}:attention_output"] = compute_stas(attention_output)
-                        logs[f"layer_{self.layer_idx}:seg_{idx}:output"] = compute_stas(output)
-                        logs[f"layer_{self.layer_idx}:seg_{idx}:memory"] = compute_stas(memory)
-                        logs[f"layer_{self.layer_idx}:seg_{idx}:normalization"] = compute_stas(normalization)
-
                 memory, normalization = self._update_memory(memory, normalization, key_states, value_states)
 
             outputs.append(output)
-
-            idx += 1
-
-            # NOTE: update memory
         outputs = torch.cat(outputs, dim=1)  # concat along sequence dimension
-        assert outputs.shape == hidden_states.shape
-
-        if (
-            constants.GLOBAL_STEP is not None
-            and (constants.GLOBAL_STEP - 1) % constants.CONFIG.infini_attention.logging_interval == 0
-        ):
-            if constants.IS_RANK_TO_MONITOR is True:
-                import wandb
-
-                for i in range(raw_global_weights.shape[0]):
-                    logs[f"layer_{self.layer_idx}:global_weights"] = compute_stas(orig_global_weights, log_tensor=True)
-                    logs[f"layer_{self.layer_idx}:local_weights"] = compute_stas(orig_local_weights, log_tensor=True)
-                    logs[f"layer_{self.layer_idx}:global_weights:head_{i}"] = raw_global_weights[i].item()
-                    logs[f"layer_{self.layer_idx}:balance_factors:head_{i}"] = self.balance_factors[i].item()
-
-                logs[f"layer_{self.layer_idx}:outputs"] = compute_stas(outputs)
-                wandb.log({**logs, "iteration_step": constants.GLOBAL_STEP})
 
         return_outputs = {
             "hidden_states": outputs,

From 0d99cfb83fc181e575978a9dc35dc686cdef0dfb Mon Sep 17 00:00:00 2001
From: Phuc Nguyen <b3f0cus@icloud.com>
Date: Fri, 2 Aug 2024 14:21:35 +0000
Subject: [PATCH 43/43] clean

---
 src/nanotron/models/llama.py | 10 +++-------
 1 file changed, 3 insertions(+), 7 deletions(-)

diff --git a/src/nanotron/models/llama.py b/src/nanotron/models/llama.py
index 550490db..0d1f6e59 100644
--- a/src/nanotron/models/llama.py
+++ b/src/nanotron/models/llama.py
@@ -557,13 +557,9 @@ def forward(
         normalization = None
 
         outputs = []
-        raw_global_weights = self.balance_act_func(self.balance_factors)
-        global_weights = raw_global_weights
-        orig_global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
-        orig_local_weights = 1 - orig_global_weights
-
-        global_weights = orig_global_weights
-        local_weights = orig_local_weights
+        global_weights = self.balance_act_func(self.balance_factors)
+        global_weights = rearrange(global_weights, "n_heads -> 1 n_heads 1 1")
+        local_weights = 1 - global_weights
 
         for segment_hidden_state, segment_sequence_mask in zip(segment_hidden_states, segment_sequence_masks):
             attn_outputs = self.forward_with_hidden_states(